BAY of Bengal Cyclones

National Conference

Bay of Bengal Tropical Cyclone Experiments

(BOBTEX

1

Cyclone Warning Division

India Meteorological DepartmentMausam Bhawan, Lodi Road

New Delhi

Extended Abstract

National Conference

on


(BOBTEX-2011)

New Delhi 1-2 November 2011


Meteorological DepartmentMausam Bhawan, Lodi Road

New Delhi-110003 (India)

Extended Abstracts

Ministry of Earth Sciences


Meteorological Department

New Delhi

1-2 November 2011


India Meteorological Department

Mausam Bhawan, Lodi Road

New Delhi-110003

Extended Abstracts

National Conference

on


(BOBTEX-2011)

Forward

During the past few years, huge technological advancements have been achieved elsewhere in the world to observe the inner core of the cyclone through aircraft probing. Accordingly, Ministry of Earth Sciences conceived a programme in 2008 for aircraft probing of tropical cyclones over the Bay of Bengal which resulted in the commencement of Forecast Demonstration Project (FDP) in 2008 with Multi-institutional mechanism and IMD as nodal agency. FDP programme is aimed to demonstrate the ability of various NWP models to assess the genesis, intensification and movement of cyclones over the north Indian Ocean with enhanced observations over the data sparse region and to incorporate modifications into the models which could be specific to the Bay of Bengal. The lessons learnt during the pre-pilot and pilot phases of FDP campaign helped in improved monitoring and prediction of cyclonic disturbances during 2008-2010. During the Final Phase of the FDP programme (15 Oct.-30 Nov., 2012) India is planning to take up aircraft probing of cyclones over the Bay of Bengal with hiring of aircraft and drop sonde experiments. Considering all these, a two days National Conference on Bay of Bengal Tropical Cyclone Experiments (BOBTEX-2011) is organised in New Delhi during 01-02 November 2011. There are valuable research papers dealing with various aspects of cyclones over the Bay of Bengal, especially in relation to FDP from leading experts of both research and operational meteorological environments. It is intended that the conference will be a first step towards an ongoing focus on impact of surface-upper air and space based observations in operational cyclone forecasting and NWP modelling in the north Indian Ocean. I am glad to inform that a volume of Extended Abstract of the research papers of the national conference, BOBTEX-2011 is brought out which will be very helpful as guidance material for further research on cyclone and planning of future FDP campaigns. I thank Cyclone Warning Division of IMD, New Delhi, for organising BOBTEX-2011. My special thanks are due to Dr. M Mohapatra and Dr Naresh Kumar for bringing out this Extended Abstract of the Proceedings of the conference. I also thank Prof. T.N. Krishnamurti for agreeing to deliver the keynote address; Prof. S.K. Dube, Prof. U. C. Mohanty, Mr R.C. Bhatia and Mr. S. Raghavan for agreeing to deliver the lead talks; Prof. J. Shukla for agreeing to chair the Panel discussion and concluding session of the conference and Mr D.R. Sikka for reviewing the extended abstracts of the proceedings. IMD, New Delhi Ajit Tyagi 01. November 2011 Director General of Meteorology

Contents

Page Synoptic and Climatological Aspects

1. Outcome and challenges of the Forecast Demonstration Project 1

on Landfalling Cyclones over the Bay of Bengal.

Ajit Tyagi, M. Mohapatra, D.R. Sikka* and B. K. Bandyopadhyay

2. Utility of Tropical Cyclone Module for monitoring and 8

prediction of cyclonic disturbances over the North Indian Ocean.

M Mohapatra, Naresh Kumar and B. K. Bandyopadhyay

3. Climatology and intensification of Bay of Bengal Cyclonic storms 10

K.Seetharam

4. Study of wind shear, squall lines and cloud top temperatures in

association with Tropical cyclone 13

Charan Singh

5. Performance of modified CLIPER model for tropical cyclone track

prediction over the north Indian Ocean 16

R. P. Sharma, M. Mohapatra and B. K. Bandyopadhyay

6. Possible causes for absence of cyclogenesis over the Bay of

Bengal during October-November 2009 19

S. Adhikary and M. Mohapatra

7. WARD Cyclone – A Case Study 21

S.R. Ramanan, K.V. Balasubramanian and M.Veerakumar

8. Upper Ocean Observations during the passage of cyclone JAL-2010 26

Anitha Gera, M Ravichandran and A. K. Mitra

9. Salient features of JAL Cyclone of November 2010 – A case Study 27

D. C. Gupta

10. Characteristics of VLF atmospherics during tropical cyclone ‘AILA’

and several other thunderstorms over North-East India 30

Rakesh Roy, Abhijit Choudhury, Anirban Guha and Barin Kumar De

11. The Role of India Meteorological Department Telecommunication

Infrastructure on Forecast Demonstration Project (FDP) program of Tropical

Cyclones over Bay of Bengal 31

Sankar Nath

12. Evaluation of Cone of Uncertainty in Tropical Cyclone Track Forecast

over north Indian Ocean Issued by India Meteorological Department 32

D. P. Nayak and M. Mohapatra

Satellite and Radar Applications in Cyclone Monitoring

13. Observational aspects including DWR for cyclone monitoring 35

S. Raghavan

14. Observations of Cyclones from Space-Based Platforms: Current Status

and future Prospects 36

R.C. Bhatia

15. Early Detection of Global Tropical Cyclogenesis using OSCAT Data 37

C. M. Kishtawal and Neeru Jaiswal

16. Objective Detection of Center of Tropical Cyclone in Remotely Sensed 38

Infrared Images

Neeru Jaiswal, C. M. Kishtawal, P. K. Pal

17. Analysis of tropical cyclones by using microwave imageries of other 39

polar orbiting satellites over Indian region

Suman Goyal and A. K. Sharma

18. Estimation of intensity of tropical cyclone over Bay of Bengal 40

using Microwave imagery

T. N .Jha, M Mohapatra and B .K .Bandyopadhyay

19. Making a complete picture – radar composite 43

B. Arul Malar Kannan, Suresh Chand and S.K. Kundu

20. Study of Tropical Cyclone AILA using Doppler Weather Radar data 44

D. Pradhan

Heavy Rainfall, Gale Wind and Storm Surge

21. Storm surge and coastal inundation 46

S. K. Dube

22. Numerical modeling of Tide-Surge interaction in the Bay of Bengal 49

Jismy Poulose

23. Outlook of tide and storm induced current off Gopalpur coast 50

Susant Kumar Misra, P. Chandramohan, A. S. N Murty, J. K. Panigrahi,

R. Mahadevan, M. M. Mahanty and J. K. Sahu

24. Estimation of pressure drop within the tropical cyclone and height 51

of associated storm surge using Doppler velocity data

D.Pradhan, Anasuya Mitra

25. Tropical Cyclones Wind Radii prediction over North Indian ocean 53

M. Mohapatra and Monica Sharma

26. Drop size distribution Characteristics of cyclone and convective precipitation 57

observed over Semi-arid-zone in India

S.Balaji Kumar, S.B.Surendra Prasad, U.V. Murali Krishan

and K.Krishna Reddy

27. Changes in extreme daily rainfall associated with cyclonic disturbances 58

over Andaman & Nicobar Islands in a warming climate

Naresh Kumar, M. Mohapatra, A. K. Jaswal and B. P. Yadav

28. Monitoring Formation and Movement of the Depression of

16-23 June 2011 using DWR, Satellite Products and Synergy and Utility of

Implimenting a Real time Nowcasting in IMD for filling the forecasting Gap 60

Rajendra Kumar Jenamani

29. Forecasting of rainfall from landfalling cyclone using satellite derived

rain rate data: A case Study for cyclone ‘Aila’ 62

Habibur Rahaman Biswas and P.K.Kundu

30. Unprecedented flood in river Mahanadi in Orissa in September, 2008

and its impact on economic development 63

S.C.Sahu and S.K.Dastidar

31. Deep Depression without Heavy Rainfall 64

Bikram Singh, R.C. Vashisth, B.P. Yadav and Charan Singh

32. Lessons from IRENE 65

S. Raghavan

NWP Applications in Cyclone Prediction

33. NWP models applications in Tropical Cyclone Predictions

over the Bay of Bengal 66

U. C. Mohanty*, Krishna K Osuri and S. Pattanayak

34. IMD’s recent initiatives for improved Tropical Cyclone track and intensity

forecast over Indian region using Hurricane WRF Model 69

Y.V. Rama Rao, T.S.V. Vijay Kumar, Zhan Zhang, K. Naga Ratna,

A.K. Das, D.R. Pattanaik, S.K. Roy Bhowmik and Ajit Tyagi

35. Impact of cyclone bogusing and regional assimilation on tropical

cyclone track and intensity predictions 70

Manjusha Chourasia, R. G. Ashrit, John P George

36. Numerical Simulation of Tropical Cyclones in Bay of Bengal 71

R. D. Kanase and P. S. Salvekar

37. Tropical Cyclone Genesis Potential Parameter (GPP) and it’s application

over the North Indian Sea 74

S. D. Kotal and S. K. Bhattacharya

38. Track Prediction of North Indian Ocean Tropical Cyclones using ARW model 75

Krishna K. Osuri, U. C. Mohanty, A. Routray and M. Mohapatra

39. On the Implementation and the ability of the Ensemble Prediction System

for tropical cyclone track and strike probability for North Indian Ocean 76

K. Naga Ratna

40. Ocean atmospheric coupled model to estimate energy and path of

cyclone near the coast 77

Ramkrishna Datta

41. Track, intensity and few dynamical aspects of ‘AILA’ as simulated by

operational NWP model of the IAF 79

Wg Cdr TP Srivastava and Wg Cdr Anil Devrani

42. Analysis of Barotrophic Energetics of Tropical Cyclone Khai-Muk 85

S.Balachandran

43. Performance evaluation of spectrum of cyclones over North Indian Ocean

using RAMS model 86

Ancy Thomas, Basanta kumar Samala and Akshara Kaginalkar

44. An Observational and Modeling Study of the Tropical Cyclone PHET 87

Jagabandhu Panda, R. K. Giri and Harvir Singh

45. Large-Scale Characteristics of Rapidly Intensifying Tropical Cyclones

over the Bay of Bengal and a Rapid Intensification (RI) Index 89

S. D. Kotal and S. K. Roy Bhowmik

46. Development of the Lagrangian Advection model for prediction of tropical

cyclone track over the Indian Ocean 90

Sanjeev Kumar Singh, C. M. Kishtawal, Neeru Jaiswal, and P. K. Pal

47. Extended Range Forecast of Tropical Cyclone Genesis Based on Coupled

Model Outputs 92

D. R. Pattanaik, M. Mohapatra, Y. V. Rama Rao and Ajit Tyagi

48. Impact of Resolution and Data Assimilation on the prediction of the

cyclone “JAL” over Bay of Bengal using WRF (NMM) and grid

point statistical interpolation scheme 95

K. Naga Ratna

49. Study of JAL cyclone track using WRF cumulus parameter schemes 96

M. Venkatrami Reddy, S. Balaji Kumar, S. B. Surendra Prasad

and K. Krishna Reddy

50. Impact of data assimilation system for simulation of tropical cyclones

over Bay of Bengal with WRF-NMM modeling system 97

Sujata Pattanayak and U C Mohanty

BOBTEX-2011

Cyclone Warning Division, India Meteorological Department, New Delhi 1

Outcomes and Challenges of Forecast Demonstration Project (FDP) on Landfalling Cyclones

over the Bay of Bengal

Ajit Tyagi, M. Mohapatra, D.R. Sikka* and B. K. Bandyopadhyay


Mausam Bhavan, Lodi Road, New Delhi-110003

*40, Mausam Vihar, New Delhi-110051

1. Introduction During the past few years huge technological advancements have been achieved elsewhere

in the world to observe the inner core of the cyclone. Accordingly a programme has been evolved

for improvement in prediction of track and intensity of tropical cyclones over the Bay of Bengal

resulting in planning of the Forecast Demonstration Project (FDP). FDP programme is aimed to

demonstrate the ability of various NWP models to assess the genesis, intensification and movement

of cyclones over the north Indian ocean with enhanced observations over the data sparse region and

to incorporate modification into the models which could be specific to the Bay of Bengal based on

the in-situ measurements and following the actual track through Satellite and Radar observations.

FDP Programme is scheduled to be implemented in three phases, viz., (i) Pre- pilot phase (15 Oct-

30 Nov. 2008, 2009, (ii) Pilot phase (15 Oct-30 Nov. 2010 and 2011) and (iii) Final phase (15 Oct-

30 Nov. 2012). India is planning to take up aircraft probing of cyclones over the Bay of Bengal

during 15 Oct.-30 Nov., 2012 with hiring of aircraft and dropsonde experiments.

To accomplish the above objective, the initiative was carried out with following priorities.

(i) Observational upgradation

(ii) Modernisation of cyclone analysis and prediction system

(iii) Cyclone analysis and forecasting procedure.

(iv) Warning products generation, presentation & dissemination,

(v) Confidence building measures and capacity building

2. Implementation of FDP during 2008-2010 Various strategies were adopted for improvement of observation, analysis and prediction of

cyclone. Several national institutions participated for joint observational, communicational & NWP

activities during the pre-pilot and pilot phases of FDP campaign during 2008-10. There were 23

days of intense observation period (IOP) in association with cyclonic disturbances (CDs) during

2008 and 2010. and no IOP during 2009, as there was no CD during FDP period over the Bay of

Bengal.

Enhanced observations during Intense IOP helped in improved monitoring and prediction of

CDs. The additional data was collected from Sagar Kanya cruise, enhanced AWS network of the

coast, high wind speed recorders (HWSRs), Doppler Weather Radars (DWRs), five activated buoy

observations from the Bay of Bengal, Oceansat-II observations and microwave imagery products.

The comparison of observational systems before and after FDP indicates a significant improvement

in terms of Radar, AWS, high wind speed recorders over the region (Table 1). It has resulted in

reduction in landfall point location error from 55 km to 25 km (Mohapatra et al, 2011)

Table 1. Observatory network by end of 2007 and 2010

Observational system Network by end of 2007 Network by end of 2010

Surface synoptic observatory network 559 559

Pilot balloon observatory network 62 62

Radiosonde/Radiowind network 35 39

Buoy network 6 12

AWS network 125 524

HWSR - 12

DWR 5 12

BOBTEX-2011


To ensure the availability of the data and forecast products from various national and

international sources at Cyclone Warning Division, IMD, New Delhi, an institutional mechanism

was developed in consultation with all the stake holders. A standard operation procedure (SOP) has

been prepared for monitoring and prediction of cyclonic disturbances and issue of warning. It

includes the road map and check lists for this purpose.

The tropical cyclone analysis, prediction and decision-making process was made by blending

scientifically based conceptual models, dynamical & statistical models, meteorological datasets,

technology and expertise. Conventional observational network, automatic weather stations (AWS),

buoy & ship observations, cyclone detection radars and satellites were used for this purpose. A new

weather analysis and forecasting system in a digital environment was used to plot and analyse

different weather parameters, satellite, Radar and numerical weather prediction (NWP) model

products. An integrated fully automated forecasting environment facility was thus set up for this

purpose. The manual synoptic weather forecasting was replaced by hybrid systems in which

synoptic method could be overlaid on NWP models supported by modern graphical and GIS

applications to produce

• high quality analyses

• Ensemble of forecasts from NWP models at different scales - global, regional and

mesoscale

• Prediction of intensity and track of tropical cyclone and storm surge

• Specialized warning information to various sectors including Govt. and non-Govt. agencies,

The Tropical Cyclone Module installed in this forecasting system has the facilities to serve

the above purpose. The automation of the process has increased the efficiency of system, visibility

of IMD and utility of warning products. The products before and after initiative are shown in Fig.1.

The improvement in monitoring and forecasting tools and techniques are shown in Table 2.

Fig.1. Comparison of weather analysis products before and after the initiative

3. Outcome of FDP-2008-2010 Salient features of achievements are described below.

(a). Cyclone track and intensity forecast : For comparison, the 24 hr track forecast errors and the skill scores during 2003 and 2010 are

shown in Fig.2 (RSMC, New Delhi, 2009, 2010, 2011. The figures clearly indicate the gradual

improvement in the cyclone forecast by IMD, as the error has decreased and the skill has increased.

The average landfall error was less than the long period average error for the landfalling cyclones

over the north Indian Ocean. It is also very much comparable to the forecast errors over other

Ocean basins including north Atlantic and Pacific Ocean basins. Considering, the intensity forecast,

the average 24 hrs wind forecast error has been about 10 knots (Table 3) for these cyclones.

(ii) After initiative(Isobaric analysis at mean sea

level during cyclone, Phet at 00 UTC of 03 June

2010)

(i) Before initiative

(Isobaric analysis at mean sea level)

BOBTEX-2011


Table 2. Comparative analysis of tools and techniques by the end of 2007 and 2010.

Parameters Tools/technique by end of 2007 Additional tools/technique by

end of 2010

Genesis Synoptic, satellite (visible & IR imagery),

NWP analysis (T254), coarser resolution

ECMWF, UKMO, NCEP, Quikscat, Ascat,

AMV

Microwave imagery,

Oceansat-II

Location

monitoring

Ship, Buoy, limited AWS, Quikscat, Ascat,

AMV

Enhanced AWS network,

GPSsonde, buoy, Oceansat-II

Intensity

monitoring

Satellite (Visible and infrared imagery), Radar,

Quikscat, Ascat, AMV

Microwave imagery,

enhanced DWR network,

buoy network, Oceansat-II

Genesis forecast Synoptic, satellite, radar Microwave imagery,

Dynamical statistical model

Track forecast Synoptic, satellite, radar, CLIPER, Limited

NWP guidance (Coarser ECMWF, UKMET,

NCMRWF (T80), LAM, MM5, QLM),

High resolution ECMWF,

IMD GFS(382),Experimental

(T574), NCEP GFS, ARPS

(Meteo-France), NCMRWF,

MME, Experimental HWRF,

WRF (ARW), WRF (NMM),

modified CLIPER, ISRO GA

technique

Strike

probability

- Strike probability based on

EPS and super EPS

Intensity

forecast

- Dynamical statistical model

Rapid

intensification

- Dynamical statistical model

Comparing the landfall forecast errors, the 24 hour mean error has been significantly less

during last three years (2008-2010). It is about 100 km against the long period average error of

about 150 Km(Fig. 3).

24 hr Track Forecast Error (km)

203

165

142

181

131110

136127

0

50

100

150

200

250

2003 2004 2005 2006 2007 2008 2009 2010

Year

Err

or

(km

)

24 hr track Forecast Error (km)

Linear (24 hr track Forecast Error (km))

3 per. Mov. Avg. (24 hr track Forecast Error (km))

Fig.2 (a). 24 hr cyclone track forecast errors of IMD during 2003-2010.

BOBTEX-2011


24 hr Forecast Track Skill Score (%)

6.3

29.5

18.621.9

13

24.1

53

13

y = 1.8357x + 14.164

R2 = 0.0983

0

10

20

30

40

50

60

2003 2004 2005 2006 2007 2008 2009 2010

Year

Skill S

co

re (%

)

24 hr Track Forecast Skill Score

Linear (24 hr Track Forecast Skill Score)

3 per. Mov. Avg. (24 hr Track Forecast Skill Score)

Fig.2.(b): 24 hr cyclone track forecast skill scores of IMD during 2003-2010.

Fig. 3. Landfall forecasterrors of IMD during 2003-2010

Table 3. Official average intensity forecast error of 2010

Lead Period

(hrs)

Intensity Error (knots) No. of

Observation verified Average Absolute Average RMS

12 1.0 8.1 11.3 55

24 4.5 12.2 16.4 49

36 8.7 15.3 20.4 37

48 13.4 16.5 21.9 29

60 19.6 20.9 26.8 23

72 21.0 21.0 28.3 19

The performance of NWP models have increased along with the introduction of NWP

platforms like IMD GFS, WRF, HWRF and ensemble prediction system (EPS) The mean track

forecast errors of NWP models during 2010 are given in Table 4. The performance of multi-model

ensemble (MME) prediction is reasonably good. The 48 hours track forecast errors by MME

technique of IMD is about 200 km.

24 hr Landfall forecast errors (km) during 2003-2010

0

100

200

300

400

500

600

2003 2004 2005 2006 2007 2008 2009 2010

Year

Err

or

(km

)

24 hr forecast error Linear (24 hr forecast error)

12 hr Landfall forecast errors (km) during 2003-2010

0

50

100

150

200

250

300

350

2003 2004 2005 2006 2007 2008 2009 2010

Year

Err

or

(km

)

12 hr forecast error Linear (12 hr forecast error)

BOBTEX-2011


Table 4. Mean Track forecast errors of NWP models for cyclones during 2010

(b) Cyclone Warning Services The format and content of bulletins have been changed significantly as shown in Table 5.

These improvements have contributed to effective management of cyclone by disaster managers.

The time of issue and frequency of bulletins have been standardized. The frequency of

bulletin has also been increased along with the increase in number of users. The lead time of the

forecast has been increased upto 72 hrs. The design of the bulletin has been revised with inclusion

of prognostic and diagnostic features, observed and forecast track and intensity in Tabular form and

storm surge guidance for all member countries of WMO/ESCAP Panel. The observed and

forecast track and intensity of the cyclone were updated in cyclone page of IMD website time to

time, based on the tropical cyclone advisory bulletin issued by Cyclone Warning Division of IMD,

New Delhi. The cone of uncertainty in the forecast has been introduced with effect from the

cyclone, ‘WARD’ during December, 2009. It is helpful to the decision makers as it indicates the

standard forecast errors in the forecast for different periods like 12, 24, 36, 48, 60 and 72 hrs. The

improvement in delivery services of cyclone warning after the intiative as compared to prior to

initiative are shown in the Table 6.

Table 5. Comparison of cyclone warning products and bulletins before and after the initiative

SN Parameters Bulletin issued before

initiative

Bulletin issued after

initiative(2010)

1 Date and time of issue of bulletin Date only Both date and time

2 Current location, intensity Yes Yes

3 Past movement Yes Yes

4 Forecast validity period Upto 24 hrs Upto 72 hrs(+6, +12, +18, +124,

+36, +48, +60 and +72 hrs)

5 Quality of forecast track and

intensity

(Qualitative) Quantitative.

6 Landfall point and time Qualitative Quantitative with lati/long of

landfall and time

7 Prognostic and diagnostic features Nil Detailed features are explained

in the Technical bulletin.

08 Graphical presentation of

observed and forecast track

No Yes

9 Adverse weather (Heavy rain,

Gale wind and storm surge)

Storm surge for Indian

coast only

For coasts of all member

countries of WMO/ESCAP

Panel

10 Advice and action suggested Yes Yes, but more specific

AVERAGE 12 hours 24 hours 36 hours 48 hours 60 hours 72 hours

ECMWF 54 71 102 170 202 246

NCEP-GFS 158 178 177 236 253 334

JMA 195 96 176 203 232 268

IMD-MM5 118 141 241 350 363 356

IMD-QLM 103 144 167 181 256 311

IMD-MME 72 104 140 205 190 244

IMD-T382 94 124 164 212 246 290

IMD-WRF-VAR 155 137 236 253 234 265

BOBTEX-2011


Table 6. Beneficiaries feedback of cyclone warning services before and after initiative

SN Parameters Beneficiaries feedback

before initiative

Beneficiaries feedback after initiative

(e.g. 2010)

1 Number of deaths Higher Less

2 Loss due to evacuation of

people due to uncertainty in

forecast

Higher Less

3 Quality of warning

presentation

Poor Good

3 Appreciation by disaster

management agencies

Limited Appreciation by central & state Govt

agencies, and neighbouring countries

4 Number of warnees Less, e.g. six in 2003-

04 at national level

More, e.g. Fifteen in 2009-10 at

national level

5 Number of visitors to

cyclone page of IMD’s

website

Less (No counter) Significantly higher. Number of

visitor during last cyclone, PHET

(June 2010) : 40, 000 (Approx)

(c). Loss of lives due to cyclones The loss lives due to cyclone has reduced significantly due to many factors including

improvement in early warning system of cyclone. Characteristics of two similar severe cyclones

crossing Andhra Pradesh coast near Machhilipatnam in 2003 and 2010 are shown hear as example

to compare the loss of human lives.

Cyclone period : 17-21 May 2010 11-16 December 2003

Cyclone category Severe cyclone Severe cyclone

Point of landfall South of Machhilipatnam South of Machhilipatnam

Maximum wind at landfall 100 kmph 100 kmph

Landfall forecast error 24 hr lead time 55 km 257 km

48 hr lead time 115 km No forecast issued

72 hr lead time 207 No forecast issued

Loss of human lives 06 81

4. Challenges of FDP

With repeated attempt, the aircraft probing of TCs could not be possible till now. It is major

challenge for FDP-2012. The FDP on landfalling TCs over the Bay of Bengal with aircraft

probiong facility will help us in minimising the error in monitoring and hence prediction of tropical

cyclone track and intensity forecasts (Martin and Gray 1993). In addition, this project will help in

the following.

(a) Validation of Dvorak technique over the NIO

(b) Validation of pressure–wind relationship in TCs over the NIO

(c) Understanding and prediction of structure of TCs over the NIO.

(d) Development/validation of wind conversion factor for converting 3-minute average wind to 1-

minute average wind (used in Dvorak’s technique) and 10-min average wind (as required for

preparation of standardised international best tracks archives)

(e) Reanalysis of best tracks with modified pressure–wind relationship, wind adjustment and

modified Dvorak classification of intensity

(f) Improvement/validation of performance of numerical weather prediction models

BOBTEX-2011


The other major challenges include (i) assimilation of regional data and development of

suitable global and regional models for cyclone prediction with suitable modification of model

physics, resolution and initial and boundary conditions (ii) development of ensemble prediction

system based on IMD GFS and WRF models.

5. Conclusions The FDP on landfalling cyclones over the Bay of Bengal has helped in improvement of

monitoring, forecasting and warning of cyclones over the north Indian Ocean. The observational

network, tools and technologies, especially the NWP models have improved significantly during

2008-2010. As a result, the 24 hr forecast track error has reduced from 163km during 2003-2007 to

141 km during 2008-2010. However, the main challenge of the FDP is still to be realised with the

introduction of aircraft probing of cyclones and dropsonde experiments.

References

Martin JD, Gray WM (1993) Tropical cyclone observation and forecasting with and without

aircraft

reconnaissance. Weather Forecast 8:519–532

Mohapatra, M., B. K. Bandyopadhyay, Ajit Tyagi, 2011, Best track parameters of tropical cyclones

over the North Indian Ocean: a review, Natural Hazards, DOI 10.1007/s11069-011-9935-0.

RSMC, New Delhi (2009) Report on cyclonic disturbances over the North Indian Ocean during

2008. IMD, New Delhi





BOBTEX-2011


Utility of Tropical Cyclone Module for monitoring and prediction of cyclonic disturbances

over the North Indian Ocean

M Mohapatra, Naresh Kumar and B. K. Bandyopadhyay



1. Introduction The tropical cyclone (TC) forecast & warning operations and decision-making process

should be made by blending scientifically based conceptual models, meteorological datasets,

technology and expertise (IMD, 2003). The tropical cyclone module (TCM) available in synergie

system since the end of 2009 provides a digitized platform for the above purpose As adverse

weather warning depends on the track forecast, this TCM helps in accurate prediction of adverse

weather and hence effective management of TC. This TCM is helpful in improving (i) cyclone

analysis and forecasting procedure and (ii) warning products generation, presentation &

dissemination. All these aspects are presented and analysed herewith.

2. cyclone analysis and forecasting procedure A new weather analysis and forecasting system in a digital environment has been established

at National Weather Forecasting Centre, New Delhi to plot and analyse different weather

parameters, satellite, Radar and numerical weather prediction (NWP) model products. An

integrated fully automated forecasting environment facility is thus available for this purpose. The

manual synoptic weather forecasting has been replaced by hybrid systems in which synoptic

method could be overlaid on NWP models supported by modern graphical and GIS applications to

produce

• high quality analyses

• Ensemble of forecasts from NWP models at different scales - global, regional and

mesoscale

• Prediction of intensity and track of tropical cyclone

• Specialized warning information to various sectors

Fig.1. Strategy adopted for cyclone analysis and forecasting The major highlights of the strategies followed for monitoring and prediction of cyclone are

shown in the Figure 1. The TCM installed in this forecasting system has the following facilities.

• Analysis of all synoptic, satellite and NWP model products for genesis, intensity and track

monitoring and prediction

• Preparation of past and forecast tracks upto 120 hrs

• Depiction of uncertainty in track forecast

Action Synopic

Users*

End

forecast

Initial conditions

(Observations)

Synoptic

Satellite

Forecaster

NWP

Model

Numerical

forecasts

Runs of different

Models,

Consecutive runs

from the same

model,

Ensemble runs

("choosing the

best member") *Central / State Govt/ Media/ Public

BOBTEX-2011


• Structure forecasting (Forecast of wind in different sectors of cyclone)

However all the data are not still available in TCM through synergie system. For better

monitoring and prediction, addition help is taken of ftp and websites to collect and analyse:

• Radar data and products from IMD’s radar network and neighbouring countries

• Satellite imageries and products from IMD and international centres

• Data, analysis and forecast products from various national and international centres

Fig.2. Utility of Modernised cyclone analysis and forecasting system using TCM Averag e time (minutes ) c ons umed by R S MC , New D elhi

to is s ue the warning bulletin

189180

152 155

y = -13x + 201.5

R2 = 0.84

0

20

40

60

80

100

120

140

160

180

200

2007 2008 2009 2010

Y ear

Tim

e (

Min

ute

s)

Fig.3. Average time consumed by RSMC, New Delhi to issue cyclone warning bulletin since

last three hourly synoptic observations To ensure the availability of the data and forecast products from various national and

international sources at Cyclone Warning Division, IMD, New Delhi, an institutional mechanism

was developed in consultation with all the stake holders. A standard operation procedure (SOP) has

been prepared for monitoring and prediction of cyclonic disturbances and issue of warning. It

includes the road map and check lists for this purpose.

3. Warning products generation, presentation & dissemination Various steps were taken by the nominee to improve product generation, presentation and

dissemination, which could enhance the users’ response for effective cyclone disaster management.

A few highlights of the initiative are discussed herewith. A few examples of products generated

using TCM are shown in Fig. 2.The time of issue and frequency of bulletins have been

standardized. The frequency of bulletin has also been increased with reduction in time required for

issue of bulletin as shown in Fig.3. The design of the bulletin has been revised with inclusion of

prognostic and diagnostic features, observed and forecast track and intensity and adverse weather in

graphical form.

4. Conclusions The TCM is a very good tool for monitoring and prediction of cyclonic disturbances and

associated adverse weather. However, it needs to be used in conjunction with other data,

information and products available from national and international centres.

References : IMD, 2003, Cyclone Manual, India Meteorological Department, Mausam Bhavan, Lodi Road, New

Delhi

Display of wind radii envelop

Display of wind radii envelop

Comparison of various

model predictions

BOBTEX-2011


Climatology and intensification of Bay of Bengal Cyclonic storms

K.Seetharam

Meteorological Centre, Hyderabad

It has long been hypothesized the large scale atmospheric forcings for enhanced convection,

warmer sea surface temperatures, low level voriticity and windshear and availability of mid-

tropospheric humidity are favourable for cyclogenesis and intensification over Bay of Bengal

tropical storms. The cyclonic storms and severe cyclonic storms data sets for a period of 120 years

1891-2010 formed over Bay of Bengal were collected from the e-atlas of India Meteorological

Department. It is seen from the data sets that during the period 1891-2010 506 cyclonic storms

were formed over Bay of Bengal (on an average 8) and 221 of them intensified in to the Severe

Cyclonic storm stage (44%) with an average of 4. Overall, on an average 50% of the cyclonic

storms formed over Bay of Bengal intensified in to Severe Cyclonic Storms. The trend was little

erratic prior to 60s but there is a continuous and systematic decrease in the cyclonic storms over

Bay of Bengal from 60s onward up to 2000 and started again rising in 2001-2010. Examination of

the plots of data sets showed overall decreasing trend in the total number of cyclonic storms and

overall increasing trend in the total number of severe cyclonic storms when fitted with linear trend.

When a 6th

degree polynomial trend was fitted to the data sets with forward forecast for next 5

years, the trends were alternating with different periods in case of both cyclonic storms and severe

cyclonic storms but the forecast showed increasing trend in both cyclonic storms and severe

cyclonic storms beyond 2010. Further the data sets have been divided in to two epochs. The epoch I

is the period 1891-1950 and epoch II is the period 1951-2010. Comparison of epoch I and epoch II

showed that the total number of cyclonic storms formed in the Bay of Bengal was 284 out of which

94 intensified up to the stage of Severe Cyclonic storms (33%) in the epoch I and total number of

cyclonic storms formed in the Bay of Bengal was 221 out which 127 intensified up to the stage of

Severe Cyclonic storms (57%) in epoch II. The intensification of the systems is stronger during the

epoch II than the epoch I even though there is a decrease in the total number of cyclonic storms

over Bay of Bengal from epoch I to epoch II. Moreover, further examination of the data sets on the

decadal scale showed that 35 cyclonic storms formed in the Bay of Bengal during the decade 1981-

1990 out of which 22 (63%) intensified in to Severe Cyclonic Storms and during the decade 2001-

2010 32 cyclonic storms formed in the Bay of Bengal out of which only 11 (34%) intensified in to

Severe Cyclonic Storms. In this paper the environmental conditions like SSTs and Relative

Humidity during the two contrasting decades 1981-1990 & 2001-2010 were compared. The sea

surface temperatures (SSTs) taken are the extended Kaplan SSTs taken for decades 1981-1990 &

2001-2010 from the NCEP/NCAR reanalysis data sets. The study indicated the unusual warming in

the West Central Bay and East Central Bay is leading to the intensification of cyclonic storms over

Bay of Bengal. The Relative Humidity is also taken from NCEP/NCAR reanalysis. The study of

the humidity pattern between 1000 hPa and 500 hPa levels indicated low humidity in lower levels

and higher humidity during the period 1981-1990 in comparison with the period 2001-2010 with

negative N-S gradient in both levels.

Fig. 1 Decade wise Cyclonic Storms/Severe Cyclonic Storms over Bay of Bengal (1891-2010)

with linear trends fitted

BOBTEX-2011


Fig.2. Year-wise Cyclonic Storms and Severe Cyclonic Storms over Bay of Bengal (1891-

2010) fitted with 6th

degree polynomial trend

Fig. 3. Year-wise Cyclonic Storms and Severe Cyclonic Storms over Bay of Bengal (1891-

2010) fitted with linear trend

References Briegel, Lisa M., William M. Frank, 1997: Large-Scale Influences on Tropical Cyclogenesis in the

Western North Pacific”, Monthly Weather Review, 125, pp 1397–1413.

Joseph P.V. and Prince K. Xavier., (1999), “Monsoon Rainfall and Frequencies of Monsoon

Depressions and Tropical Cyclones of recent 100 years and an outlook for the first decades

of the 21st century., Meteorology beyond-2000, Proceedings of National Symposium

Tropmet-99., 16-19 Feb 1999, Editors A.K. Bhatnagar et al., Indian Meteorological Society,

Chennai Chapter., 364-371.

Kalnay, E. and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project Bulletin of

American Meteorological Society, Vol. 77, No. 3, pp 437-471.

BOBTEX-2011


Ramesh Kumar M.R & Sankar S, 2010, “Impact of global warming on cyclonic storms over north

Indian Ocean”, Indian Journal of Marine Sciences Vol. 39(4), pp. 516-520

Seetharam,K, 2004,”Statistics of cyclonic disturbances in the North Indian Ocean”, Mausam, 55

No.4, pp 698-704.

Sikka, D.R, 1977,”Some aspects of life history structure and movement of monsoon depressions”,

Pure and Applied Geophysics, 115, pp1501-1529.

Sujata Mandke K and Usha Bhide V, 2003,”A study of storm frequency over Bay of

Bengal”,Journal of Indian Geophysical Union, Vol.7, No.2, pp 53-58

Fig.. 4 Year wise Cyclonic storms and Severe Cyclonic Storms (2001-2010)

BOBTEX-2011


Study of wind shear, squall lines and cloud top temperatures in association with

Tropical cyclone

Charan Singh


Mausam Bhavan Lodi Road, New Delhi-110003

1. Introduction In Tropical cyclone (TC) is a most disastrous weather phenomena, it causes huge damage to

the life and property all around the world. To understand its dynamics mainly inner core and effects

of surrounding environment mechanism is very essential. In north Indian Ocean (NIO), this

becomes very important as some TCs cause huge amount of rainfall, but in some cases very less

rainfall is observed. These are described as moist and dry air environment tropical cyclones. Orissa

super TC & Nargis are the examples of moist air environment and Ogni & Sidar are the dry air

environment TCs. Vertical Wind Shear (VWS) play an

important role in genesis, intensification and weakening of

TCs as at the time of genesis and strengthening phase, it

enhances the mixing of moist air in vertical column and on

weakening phase it enhances dry air mixing which causes

rapid weakening of the system. Squall lines form ahead of the

TCs due to increase in instability and transport of energy

from the TCs. Squall lines along with rainband clouds

associated with TCs are the main causes of rain and

thunderstorms. TCs, which made landfall over Indian coasts,

the associated rainfall is mainly confined to the right

forward sector followed by left forward sector, it also

depends upon the season and depth convection. TCs

formed just before or after of the southwest monsoon,

generally cause more rainfall than other TCs. Also, TCs

associated with Cloud Top Temperature (CCT) ≤ -600C

cause very heavy rainfall (15-25 cm in 24 hours) over the

respective area. It is observed that the rainfall also

depends on the speed of TCs as slow moving TCs cause

much more rainfall rather than fast moving TCs.

2. Role of Vertical Wind Shear, Vertical Wind Shear (VWS) of horizontal winds is

generally considered as a resultant vector wind between 200

and 850 hPa level. The main function of the wind shear is to

sustain the cloud clusters in a vertical form. When a cloud

clusters develops over the sea surface due to higher Sea

Surface Temperature (SST) or Ocean Heat Contents (OHC),

which depends on the vertical profile of the sea, the sea

surface transmits the energy to the air parcels, where

atmosphere is already unstable. Initially air parcel lifts to the

free level convection then moist air mixing starts and system

starts grow. In the presence of the sufficient OHC, it

continues to strengthen [Fig. 1] (RSMC, New Delhi report, 2002) and the height of the cloud

increases with decrease in the VWS and start mixing of moist air. As VWS starts increase (≤ 12

kts), the dry air mixing increases and upper parts of TCs also start drifting along strong upper air

winds [Fig.2] (RSMC, New Delhi report, 2007). As a result TCs start losing its intensity.

BOBTEX-2011


3. Role of squall lines and rainbands: Squall lines are a kind of linear organization

meso-scale convective systems, which cause torrential

rainfall and thunderstorms. They may appear ahead of

landfalling TCs in general. The criteria to define squall

line is similar to Parker and Johns’s (2000). The region

exceeding 40 dBz reflectivity must extend longer than

100 km for at least 2-3 hours and convection of this

region is organized in linear or quasi linear shape with

an apparent common leading edge. The squall lines

sometimes are seen separated from the rainbands of

TCs [Fig. 3] (RSMC, New Delhi report, 2001). The

analysis of radar images show an apparent moisture

increase towards the formation position of the squall

line obviously due to the transportation of moisture

through the outer flow of the approaching TCs. In

general landfalling TCs cause squall lines in its front

quadrants.

4. Cloud top temperature: In TCs, maximum rainfall occur in the area of

maximum convection zone (Corbosiero, K. L.,

and J. Molinari, 2002). According to

(Raghavan, 1991). The maximum low level

convergence appears to occur in the right sector,

which contributes to this maximum in the right

rear sector and the formation of convective

‘streamer’ bands in the rear. To assess the

strength of convection, CTT from infra-red

satellite imagery is used as the proxy. Colder

CCT of convective clouds suggests that the

vertical extent of the cloud is more. Therefore, CTT is used as a measure of convection strength.

Isotherm analysis of CTT reveals that for most of the cases, convection generally tends to be

enhanced over the region to the right of the track. In general, about 70% convection is to the right

of track [Fig. 4 &5], which is well in agreement with the distribution of rainfall. In most of the

cases, intense to very intense convection is observed in the inner core of the TCs during the landfall

processes. The asymmetries in convection are also observed. It is due to unequal VWS in vertical

levels (Corbosiero, K. L., and J. Molinari, 2002). Very severe cyclonic storm over Bay of Bengal

during October 15-19, 1999 moved in a north-northeasterly direction before landfall near Gopalpur

(Orissa) in the early morning of 18 October, 1999. Satellite imagery received at 0230 hours IST of

18 October [Fig. 5] shows dense cloud mass with CTT -80- to -400C, spread over about 350 kms

diameter elongated along the track [Fig.4] of the TC. Study reveals that the maximum rainfall has

occurred within 150 kms radius from the landfall point and it was located on both sides along the

track. It is clear in this case that the maximum rainfall occurred over the area which lay under the

most convective cloud cover. The right first quadrant in this case also got good amount of rainfall

that ranged between 25-30 cm and it further extends beyond 300 kms of diameter. Fig. 6 shows that

the 24 hours accumulated rainfall is, to a certain extent inversely proportional to the speed of

movement of TCs with the best fit for speed range 4-10 knots. The maximum rainfall from a

landfalling TCs moving with speed in the range 4-10 knots can be estimated

by 905.64)(3429.5)( +−= speedXextremeR , with a standard deviation of 8.9 mm which is quite

BOBTEX-2011


large. Large standard deviation arises due to smaller data set used in the study. Thus assessing

extreme rainfall amount in ranges will give a better result rather than quantifying it with a single

number. Studies by (Singh and Bandyopadhyay, 2007) suggest that most of the TCs over NIO

basins move with a transitional speed between 4-12 knots. Therefore, the above emperical relation

could be used as a first guess by the operational forecasters to assess the extreme rainfall that could

occur in association with landfalling TCs.

5. Conclusion: Understanding of TCs inner core structure and effects of surrounding environment

mechanism is very essential to forecast the intensity and movement of TCs. In general, moist air

environment TCs cause more rainfall and bigger in size in comparison to dry air environment TCs.

Wind shear play an important role in genesis, intensification and weakening of TCs. At the time of

strengthening, the wind shear is generally ≤ 12 kts and at weakening stage it is generally ≥ 13 kts.

However, it is very difficult to fix the criteria of threshold value of VWS. Squall lines along with

rainbands clouds associated with TCs are the main causes of rain and thunderstorms. For TCs,

which made landfall over Indian coasts, the associated rainfall is mainly confined to the right

forward sector followed by left forward sector, and also depends upon the season and CCTs.

During landfall process, the CCT ≤ -600C cause very heavy rainfall (15-25 cm in 24 hours) over the

respective area. It is observed that the rainfall also depends on the speed of TCs as slow moving

TCs cause much more rainfall than fast moving TCs. Understanding the dynamics of the TCs and

the surrounding environment is still needed for prediction of location specific extremely heavy

rainfall.

References: Corbosiero, K.L., and J. Molinari, 2002: The effect of vertical wind shear on the distribution of

convection in tropical cyclones. Mon.Wea.Rev. 130, 2110-2123.

India Meteorological Department: Forecasting manual IV-23 weather radar as an aid to forecasting

1991 by S Raghavan.

Parker, M.D.and R.H.Johnson, 2000: Organizational models of mid-latitude meso-scale convective

systems. Mon.Wea.Rev.128, 3413-3436.

RSMC, New Delhi report, 2007, 2008 and 2001: A report on cyclonic disturbances over north

Indian ocean during 2007. Published by IMD, New Delhi.

Singh, C., and Bandyopadhyay, B.K. 2004: Behaviour of tropical cyclones along the east coast of

India prior to landfall. Mausam, 58, 2, pp 273-279.

BOBTEX-2011


Performance of modified CLIPER model for tropical cyclone track prediction

over the north Indian Ocean

R. P. Sharma, M. Mohapatra and B. K. Bandyopadhyay



E-Mail : [email protected]

1. Introduction India Meteorological Department (IMD) is the nodal agency for prediction of cyclonic

disturbances over the north Indian Ocean. The cyclone forecasts have improved steadily in the

recent decade (RSMC, New Delhi, 2011) due to improvement in monitoring and forecasting

technique, analysis tools and knowledge and human expertise. However, the very basic climatology

and persistence (CLIPER) models for the prediction of TC motion still have a number of

applications in a forecast office and continue to be developed. Some of these applications, not all of

which refer directly to the forecast process, are to 1) provide a convenient frame of reference upon

which the performance of more sophisticated models can be assessed, 2) enable the assessment of

‘‘forecast difficulty,’’ 3) provide a convenient way to generate bogus TC tracks, 4) provide a ‘‘first

guess’’ forecast, and 5) provide a reasonable forecast in portions of basins where deviations from

climatology and persistence are small (Pike and Neumann, 1987, Bessafi et al, 2002). Over the

north Indian Ocean, the CLIPER model was first developed by Sikka and Suryanarayana (1968) for

forecasting the movement of tropical storm for 24 hr period. Neumann and Mandal (1978)

developed a modified CLIPER model based on data of 1282 storms during 1877-1974 including

depressions to forecast the track upto 72 hrs in the interval of 12 hrs. However, there has been

significant improvement in monitoring technique leading to error in estimation of location and

intensity errors in recent decades (Mohapatra et al, 2011). Hence, it is felt that the existing CLIPER

model should be modified with inclusion of cyclone data set upto recent years for better reference

model. In this study, we present the characteristics of modified CLIPER model and its performance

with respect to cyclones during forecast demonstration project (FDP) period (2008-10).

2. Characteristics of modified CLIPER The modified CLIPER model is based on the data set of all the cyclones and depressions during

1891-2009 over the north Indian Ocean based on cyclone e-Atlas published by IMD (2008). It

includes the same parameters as predictors which was used by Neumann and Mandal (1987). It

uses the regression equation based on primary predictors to forecast the track upto 72 hrs in the

interval of 12 hrs. The predictors include the current and previous 12-hr position, the day of the

year, and the intensity of the system (depression/cyclone). The initial motion of the storm

(persistence) is the most important predictor for this model.

3. Performance of modified CLIPER model over the north Indian Ocean (NIO) The performance of the modified CLIPER has been evaluated by calculating the track

forecast errors of old and modified CLIPER models with respect to six hourly (00, 06, 12 and 18

UTC) best track data of tropical cyclones (TC) over the north Indian Ocean in post monsoon season

(October to December) during recent three years (2008-2010). This period is considered as

maximum data were collected during this period under forecast demonstration project (FDP) on

landfalling cyclones over the Bay of Bengal. For this purpose, the best track data have been

collected from the reports on cyclonic disturbances over the north Indian Ocean published by

RSMC, New Delhi (2009, 2010, 2011). There were six cyclones during this period as mentioned in

Table 1. The results are presented and discussed in the following sections.

BOBTEX-2011


Table 1. Details of TCs considered under the study

S.N. TC Period

1 Cyclonic storm, RASHMI 26-28 October 2008

2 Cyclonic storm, KHAI MUK 11-13 November 2008

3 Cyclonic storm, NISHA 26-28 November 2008

4 Cyclonic storm, WARD 10-15 December 2009

5 Very severe cyclonic storm, GIRI 20-23 October 2010

6 Severe cyclonic storm, JAL 4-8 November 2010

3.1. Track error of modified CLIPER model The mean track errors of the modified CLIPER model based on the data of six TCs under

consideration are presented in Table 2. It is observed that the track error increases with increase in

forecast time period. The mean 12, 24, 36, 48, 60 and 72 hr track forecast errors are 97, 180, 256,

363, 461 and 540 respectively. Compared to 68, 150, 216, 292, 361, 392 km found in earlier study

of Mandal and Neumann (1978) based on data of 1877-1974and 62, 147, 240, 338, 431, 517 km by

Bessafi et al (2002) based on data of 1988-1997 for the year as a whole including storm and

depression. The results indicate that the forecast difficulty level is higher during the post monsoon

season. It may be due to the typical tracks of the systems including northeastwards and

southwestward recurvature in case of TC GIRI and WARD respectively.

Table 2. Track forecast error based on modified CLIPER Model

Lead time(hrs) Error (Km) No. of cases

12 97 49

24 180 37

36 256 25

48 363 16

60 461 10

72 540 8

The modified CLIPER model has helped to provide better guidance also in respect of larger

spatial coverage and larger lead period compared to older model. To illustrate this fact, the number

of additional cases of forecasts for which guidance is available from the modified CLIPER model is

shown in Table 3. It is due to improvement in climatological database.

Table 3. No. of additional forecasts available from modified CLIPER Model due to

improvement in climatological database.

Lead time(hrs) No. of cases

12 8

24 10

36 4

48 2

60 3

72 3

4. Conclusions: The modified CLIPER model provides better spatial and temporal prediction coverage. It

could provide prediction for more lead period and more geographical area due to increase in

climatological database. It needs to be further validated for entire north Indian Ocean and during

the entire satellite era since 1960 to analyse its efficiency over the region.

BOBTEX-2011


References Bessafi, M., A. Lasserre-Bigorry, C. J. Neumann, F. Pignolet-Tardan, D. Payet, and M. Lee-Ching-

Ken, 2002, Statistical Prediction of Tropical Cyclone Motion: An Analog–CLIPER

Approach, Weather and Forecasting, 17, 821-831.

Neumann, C. J., and G. S. Mandal, 1978: Statistical prediction of tropical storm motion over the

Bay of Bengal and Arabian Sea. Indian J. Meteor. Hydrol. Geophys., 29, 487–500.

Pike, A. C., and C. J. Neumann, 1987: The variation of track forecast difficulty among tropical

cyclone basins. Wea. Forecasting, 2, 237–241.

Mohapatra, M., Bandyopadhyay, B.K. and Tyagi, Ajit, 2011, Best track parameters of tropical

cyclones over the North Indian Ocean: a review, Natural Hazards, DOI/10.1007/s11069-011-

9935-0

Sikka, D. R., and Suryanarayana, R., 1968, India Met. Dep., Sci. Rep., 76, 268pp

RSMC, New Delhi, 2009, Reports on Cyclonic disturbances over the north Indian Ocean during

2008, published by IMD, New Delhi.





BOBTEX-2011


Possible causes for absence of cyclogenesis over the Bay of Bengal

during October-November 2009

S. ADHIKARY1 AND M. MOHAPATRA

2

India Meteorological Department,

Mausam Bhawan, Lodi Road, New Delhi – 110 003 Email: [email protected]

1 and [email protected]

2

1. Introduction: India has a coastline of about 7,516 km of which 5,400 km is along mainland. The entire

coast is affected by cyclones with varying frequency and intensity. Though only about five

cyclones develop over north Indian Ocean during a year out of 80 cyclones developing over the

globe, more than 75% of the human deaths occur over the north Indian Ocean rim countries due to

the cyclones. Thus the disaster managers and planners need the prediction of cyclogenesis well in

advance. Tourism, insurance and re-insurance companies also make use of seasonal forecasts in

their policy decision.

To predict cyclogenesis, at first detailed understanding about causes of formation and

absence of cyclone is required. There are many case studies regarding causes of cyclone but few

case studies about absence of cyclone. The Madden-Julian oscillation (MJO) can be considered as

one of the factors for occurrence or absence of cyclone. As all cyclonic disturbances (CDs) are

initially formed from these convective cloud clusters (Kalsi, 2002), the modulation of activity

during MJO passage is likely to be an important factor to cyclogenesis. However, the effect of the

MJO on the dynamical parameters may also have an important role to play.

There are very few cases in the recorded history of CD over the north Indian Ocean (NIO) when

there has been no CD over the Bay of Bengal during October to November. There have been five

such years, viz. 1895, 1911, 1920, 1957 and 2009 during 1891 - 2010. However out of the five

years, 2009 is the only year in the satellite era when data on sea areas are most reliable (Mohapatra,

et al 2011). Considering this, a case study has been taken to explain the possible causes of absence

cyclogenesis in the Bay of Bengal during October – November 2009.

2. Data and methodology: In this case study, we have tried to find out whether only MJO is responsible for the absence

of cyclone during October – November 2009 or some other dynamical parameters are also

responsible. In our study, we have taken MJO data from the Centre for Australian Weather and

Climate Research, Australia (http://www.cawcr.gov.au). The NCEP/NCAR reanalysis (Kistler et al,

2001) is utilized dynamical parameters. The reanalysis product provides global data on a 2.50

latitude and 2.50 longitude grid for a large number of dynamical and thermo dynamical parameters

including zonal and meridional wind, mean sea level pressure (MSLP), geopotential height, sea

surface temperature (SST) etc. The reanalysis products are a combination of assimilated

observations along with model derived approximations. The region of study has been taken as 500

E to 1200 E and equator to 40

0N, which is reasonably large to take into account the physical

relationship between the cyclogenesis and the large scale field parameters.

The statistics of cyclonic disturbances over the Bay of Bengal during October - November

have been taken from the best track data set published as Cyclone E-Atlas by IMD.

3. Result and discussion: Analyzing the MJO index (Wheeler and Hendon, 2004), the MJO was in the phase 4 and 5

during 1 – 10 October and it continued to be in phase 8 and 1 which are not favourable for

cyclogenesis over the NIO (Mohapatra and Adhikary, 2011). Though the phase was favourable

during 1 – 10 Oct., the amplitude was less which did not support intensification (Fig. 1). During

November, the MJO index lay over phase 3, 4 and 5 during 7th

to 23rd

November. Among those

days, during 7-12 November there was higher amplitude resulting development of cyclone, Phyan

BOBTEX-2011


over Arabian Sea and no development of cyclogenesis in the Bay of Bengal.

Besides MJO, all the Gray parameters (Gray, 1968) for cyclogenesis have been analysed to

find out the possible causes for the absence of CD during October to November 2009. The middle

layer relative humidity (RH) was not favourable as it was significantly below normal. Geo potential

height anomaly and OLR anomaly were positive over the BoB indicating suppressed convection.

During this period SST was near normal. Also there was dominating mid latitude westerlies

penetrating into Indian region leading to reverse pressure gradient with low over Tibetan region and

high over south BoB in October and November 2009.

4. Conclusion: The MJO is not the only determining factor for the occurrence / non-occurrence of CDs

over the BoB. However its interaction with the dynamical and thermo dynamical features plays an

important role in cyclogenesis over the BoB.

References: Kalsi, S. R., 2002, Use of satellite imagery in tropical cyclone intensity analysis and forecasting,

Meteorological Monograph, Cyclone Warning Division, No. 1/2002, IMD, New Delhi – 110

003.

Kistler, R. et al, 2001, The NCEP/NCAR 50 years reanalysis: Monthly means CD-ROM and

documentation, Bulletin, American Meteorological Society, 82, 247 – 267.

Mohapatra, M. and Adhikary, S., Modulation of cyclonic disturbances over the north Indian Ocean

by Madden - Julian oscillation, MAUSAM, 62, 3 (July 2011), 375-390.

Mohapatra, M., Bandyopadhyay, B. K., Tyagi, Ajit., 2011, Best track parameters of tropical

cyclones over the North Indian Ocean: a review", Natural Hazards, DOI 10.1007/s11069-

011-9935-0

Wheeler, Matthew C. and Hendon, Harry H., 2004, “An all-season real-time multivariate MJO

Index: Development of an index for monitoring and prediction”, Mon. Wea. Rev., 132, 1917-

1932.

Fig. 1: The amplitude and phase of MJO index (Wheeler and Hendon, 2004) during Oct. –

Nov. 2009.

BOBTEX-2011


WARD Cyclone – A Case Study

S.R. Ramanan, K.V. Balasubramanian and M.Veerakumar

Regional Meteorological Centre, Chennai

Introduction

A cyclonic storm (CS) WARD (10-15 December, 2009) developed over southwest Bay of

Bengal (BOB) and crossed northeast Sri Lanka coast, close to south of Trincomalee as a deep

depression (DD) between 0800 and 0900 UTC of 14th

December, 2009. It weakened into a

wellmarked low pressure area (WML) over north Sri Lanka at 0300 UTC of 15th

December, 2009.

It then emerged into Gulf of Mannar and became insignificant on 16th

December. Cyclone WARD

followed a rare track, as it moved initially in a northerly direction (Fig.: 1) and moved in a

westsouthwesterly direction across Sri Lanka. It was a slow moving system, as it travelled at the

average rate of 200 km per day (8 km per hour). Before landfall it weakened into a depression. In

this study various features of WARD cyclone is discussed.

Muthuchami and Sridharan (2008) have studied the intensification and movement of CS in

BOB during post-monsoon season. Krishna Rao (1997) has described the synoptic methods of

forecasting tropical cyclones (TC). Desai and Walkar have observed that a CS recurve to the north

and to the northeast when there is a passage of middle and upper troposheric westerly trough.

Occurrence of higher preceipitable water content, higher air temperature at 300 hPa level and

higher upward vertical velocity in lower levels may be indicative of future movement of a CS

(Rameshchand and Mohapatra – 2007). Raj et. al. (2007) considered that the SCS of BOB during

post monsoon season are characterised by the presence of low OLR in the west/northwest and

front/left front sector. Research over the past four decades has established that environmental forces

at large radii have a significant impact on tropical cyclone intensification. It has also been

established that environmental vertical wind shear has a detrimental effect on TC strength. This fact

has been confirmed in recent studies. While small amounts of vertical shear have been seen as

beneficial to TC development shears above 8-12m/s have proven deleterious to TC intensity and

structure. {Levi Thatcher and Zhaoxia Pu (2011)}. Lei Yang et. al. (2011) considered that the West

Pacific Subtropical High of winter-time may be a critical modulator of TC tracks in north Indian

ocean region, specifically during post-winter-monsoon period. Moreover, such a strong weather

system is associated with Northeast Trade Wind and East Asia Winter Monsoon. How westward

this system extends is predictable when information on whether TC in BOB moves westward is

available. However this mechanism and causal relationship between the West Pacific Subtropical

High as well as possible modulated systems will have to be investigated in the future.

Earlier to WARD cyclone of 2009 there is only one CS during 28th

November to 7th

December 1996 which had unusual movement (Fig. 2). This system made first loop over central

BOB near longitude 87.00 E on the night of 30

th November, 1996 and later had a second loop near

the coast of Andhra Pradesh during the night of 4th

December, 1996. Thus, the system created a

unique history in its movement over the BOB. There is no parallel example in the past when a

cyclone executed two loops in the BOB. The very rare southward movement of a tropical cyclone

has been captured well by the altostratus warming from 0758UTC/3rd

December 1996 (Suresh,

2005). WARD cyclone is another such CS which initially moved northwards, then west-

southwestwards and thus followed a rare track.

BOBTEX-2011


Results and discussion

Genesis Convective cloud clusters were seen over the south east BOB during first week of

December, 2009 in association with an active Inter-Tropical Convergence Zone (ITCZ). This

developed into a WML over southwest and adjoining south east Bay on 10th

morning {Fig. 3(a)}. It

concentrated into a depression at 0900 UTC of 10th

near 6.50

N/85.00

E.

Intensification and movement It further intensified into a deep depression (DD) near 7.0

0 N/84.0

0 E at 0000 UTC of 11

th

December {Fig. 3(b)}. While moving northward, it intensified into a CS WARD at 0900 UTC of

the same day near 8.50 N/84.5

0 E. It continued as a CS and moved slowly northward till 0600 UTC

of 12th

December {Fig. 3(c)}. It then moved west-south westwards and weakened into a DD over

south west BOB at 1800 UTC of 12th

near 9.50 N/83.5

0 E. Continuing to move in a west-south

westerly direction, it crossed northeast Sri Lanka coast close to the south of Trincomalee between

0800 and 0900 UTC of 14th

as a DD. It weakened further into a depression over north Sri Lanka

close to Trincomalee at 0900 UTC of 14th

and into a WML over Sri Lanka at 0300 UTC of 15th

December. It emerged into the Gulf of Mannar as a LOPAR at 1200 UTC of the same day and

became less marked at 0900 UTC of 16th

December. The track of the system is shown in Fig. 1.

The storm was tracked mostly on the basis of satellite imageries {(Fig 3 (a) to (g)}.

Environmental features The environmental features like sea surface temperature, vertical wind shear of horizontal

wind, mid-tropospheric humidity, low level convergence, upper level divergence were favourable

for cyclogenesis over the southwest and adjoining southeast Bay of Bengal during the first week of

December. The sea surface temperature was about 28-30 deg. C over this region. The vertical wind

shear of horizontal wind was low to moderate (10-15 knots) throughout the life period of the

system except 12th December evening when the wind shear became moderate to high (20-30 knots)

{Fig. 6 (a) and (b)}. It led to the weakening of the system over the sea. However, from 13th

onwards, the wind shear became low to moderate again favouring intensification of the system.

Though, the system did not intensify further due to its interaction with land surface, as it lay close

to Sri Lanka, it could maintain its intensity of deep depression due to favourable vertical wind shear

{Fig. 6 (a) and (b)} and high ocean thermal energy.

The system was close to the upper tropospheric ridge in association with the upper

tropospheric anti-cyclonic circulation throughout the life period of cyclone leading to slow

movement of the system. It was more dominant in the initial phase leading to near northerly

movement of the system till 12th December morning. However, the system lay to the south of a

well defined mid-tropospheric anti-cyclonic circulation, which guided the system to move in a

southwesterly direction from 12th

December onwards {Fig. 5 (a) and 5(b)}. As the system came

closer to Sri Lanka coast, the upper tropospheric flow also supported the system to move in a west

southwesterly direction.

Realised weather The system was away from the Tamil Nadu coast for most part of its life cycle. When the

system weakened in to a Low pressures area and emerged into a Gulf Mannar as a trough it gave

rainfall in Tamil Nadu on 15th

and 16th

December, 2009. Past studies have indicated that whenever

a trough of low lies over Gulf of Mannar with upper air wind favourable up to even one Km is

sufficient enough to generate wide spread rainfall over coastal area leading to active/vigorous

monsoon over coastal Tamil Nadu.

BOBTEX-2011


Fig. 1: Track of WARD cyclone

(source: IMD)

Fig. 2: Track of CS – TC08B –

28th

November 1996 to 7th

December 1996 with unsual

southwestward movement.

(a) 10.12.2009 0600 UTC

- Cluster of clouds in

association with ITCZ

forming a WML

(b) 11.12.2009 0600 UTC

DD 8.0/84.5

(c) 12.12.2009 0600 UTC -

CS 10.0/84.5 – tightly

curved banding wrapping

into the center.

(d) 13.12.2009 0600 UTC - S-

ly/SWly movement DD

9.0/83.0

(e) 14.12.2009 0600 UTC

Just before crossing. DD

8.5/81.5

(f) 15.12.2009 0600UTC

Weakened into a WML

over Sri Lanka

(g) 16.12.2009 0600UTC

LOPAR over Gulf of Mannar

BOBTEX-2011


Fig. 3 : Sattellite imageries of WARD Cyclone (source; Dundee – www.dundee.ac.uk)

(a) 12.12.2009 0000 UTC

10.0/84.5 – CS with wind

speed 35 kts.

(b) 12.12.2009 1200 UTC -

10.0/83.5 –convection being

sheaed to east of the storm

centre

(c) 13.12.2009 – 0600 UTC –

9.0/83.0 – DD - wind speed

20 kts -

(d) 13.12.2009 – 1800 UTC –

9.0/82.5 – DD-interaction

with land area

(e) 14.12.2009 - 0000 UTC (f) 14.12.2009 – 1200 UTC

(g) 15.12.2009 – 0000 UTC Fig. 4 (a) to (g): Satellite derived winds showing low level

winds. The low level circulation is strong initially with

stronger wind speeds and reducing when WARD started

interacting with the land mass of Sri Lanka . source ;

RAMMB – rammb.cira.colostate.edu

BOBTEX-2011


Fig. 5 (a) and (b): Mass weighted deep layer

mean wind in two layers (a) 200 to 850 hPa and

(b) 500 to 850 hPa from the balanced 3-D wind

field derived from the AMSU temperature

retrievals. The area averaging is in an area

contained within 0 to 600 km from the centre of

the CS.

Fig. 6 (a) and (b): Area averaged vertical wind

shear in two layers (a) 200 to 850 hPa and (b)

500 to 850 hPa from the balanced 3-D wind

field derived from the AMSU temperature

retrievals. The area averaging is in an area

contained within 0 to 600 km from the centre of

the CS.

Conclusions

CS WARD initially moved in a northerly direction but later moved in a est and

southwesterly direction since it was close to upper tropospheric ridge till 12th

December 2009

morning. Due the same reason it moved very slowly too. Later it moved west and southwestwards

because the upper tropospheric flow supported the system to move in that direction. The vertical

wind shear became moderate on 12th

and due to this the system weakened into a DD.

Reference: 1. Desai. D.S., and Walkar.B.D., Recurving cyclonic storms during 1870-74, Mausam, 48, 3

(July, 1997) 421-28.

2. Krishna Rao. A.V.R., Tropical cyclones – synoptic methods of forecasting, Mausam, 48, 2

(April, 1997), 239-256.

3. Lei Yang et. al., ‘Recent Hurricane Research - Climate, Dynamics, and Societal Impacts’, p-

227-246, Edited by: Anthony Lupo, Published by InTech, April 2011.

4. Levi Thatcher and Zhaoxia Pu, ‘Recent Hurricane Research - Climate, Dynamics, and

Societal Impacts’, p-270-286, Edited by: Anthony Lupo, Published by InTech, April 2011.

5. Muthuchami.A and Sridharan.S.,Intensification and movement of cyclonic storms in Bay of

Bengal during post monsoon season, Mausam, 59, 1 (January, 2008), 51-68.

6. Rameshchand and Mohapatra, Diagnostic study of re-curving cyclone – ‘Mala’ over Bay of

Bengal, Mausam, 61, 1 (January 2010), 11-18.

7. Raj et. al., Severe cyclonic storm of North Indian Ocean, Mausam, 58, 4 (October 2007),

481-500.

8. Suresh.R, ‘Foreshadowing the tracks of tropical depressions and cyclonic storms and

understanding their thermo dynamical structure over Bay of Bengal and Arabian sea using

TOVS and ATOVS data’, ITSC XIV Proceedings, Beijing, China, 25-31 May 2005,

published by Cooperative Institute for Meteorological Satellite Studies · Space Science

and Engineering Center / University of Wisconsin-Madison,

http://cimss.ssec.wisc.edu/itwg/itsc/itsc14/proceedings/A43.

BOBTEX-2011


Upper Ocean Observations during the passage of cyclone JAL-2010

Anitha Gera1, Ravichandran M

2 and Mitra A. K

1,

1National Centre for Medium Range Weather Forecast

2Indian National Centre for Ocean Information Services

Severe Cyclonic Storm Jal which developed from a low pressure system occurred in the

Bay of Bengal during 4-8th

Nov 2010. The estimated lowest central pressure was 988hpa. The

cyclone passed very near to a buoy located at 8 N 85.5E. The buoy recorded upper ocean and met

observations during the passage of JAL. These observations are of much value especially in the

context of the scanty observations under such severe weather events. These observations therefore

analysed to enhance our understanding of the air sea interaction processes and the oceans role

during the passage of a cyclone. In addition there are a few Argo floats which recorded the upper

ocean temperature and salinity profiles of the upper ocean near to the track of the JAL-2010.The

evolution of the mixed layer temperature, salinity and currents are examined as the cylone traversed

along its path. Relevant satellite data are also used to complement these in-situ observations.

BOBTEX-2011


Salient features of JAL Cyclone of November 2010 – A case Study

D. C. GUPTA

Meteorological Office, Port Blair, India

Email: [email protected] Abstract:

A severe cyclonic storm “JAL” (04- 08 Nov. 2010) developed over the Bay of Bengal from

the remnant of a depression which moved from northwest Pacific Ocean to the Bay of Bengal

across southern Thailand. It moved west-northwestwards and intensified upto severe cyclonic storm

on 6th

November, 2010. However due to lower ocean thermal energy and moderate to high vertical

wind shear, the severe cyclonic storm, JAL weakened gradually into a deep depression and crossed

North Tamil Nadu – South Andhra Pradesh coast, close to North of Chennai near 13.30 N and 80.3

0

E around 1600 UTC of 07th

November 2010.

The unique features associated with system was that it weakened into a deep depression

over Bay of Bengal before landfall. The convective clouds were sheared to the west to a large

extent on the date of landfall, 7th November 2010. As result of this more rainfall occurred over the

interior parts of South India than over coastal regions.

2. Introduction:

The low pressure system over Indian region are classified on the basis of the maximum

sustained winds speed associated with the system and the pressure deficit/ number of closed isobars

associated with the system. The pressure criteria are used, when the system is over land and wind

criteria is used, when the system is over the sea. The system is called as low if there is one closed

isobar in the interval of 2 hPa. It is called depression, if there are two closed isobars, a deep

depression, if there are three closed isobars and cyclonic storm if there are four or more closed

isobars. Considering wind criteria, the system with wind speed of 17-27 knots is called as

depression, the system with wind speed 28-33 knots is called as deep depression, the system with

wind speed 34-63 knots is called cyclonic storm, a severe cyclonic storm if the wind speed is 64-

119 knots and a super cyclonic storm if the wind speed is 120 knots or more. Based on the above

criteria, a severe cyclonic storm formed over Bay of Bengal and crossed over North Tamil

Nadu/south Andhra Pradesh coast and gave copious amount of rainfall over southern peninsula of

India and caused damage of lives & property.

3. Life history (Genesis, intensification/ movement and dissipation) of JAL cyclone:

3.1 Genesis of JAL cyclone: A depression formed over the West Pacific Ocean on31st Oct.2010 in association with an

active Inter –Tropical Convergence Zone (ITCZ). It moved west north-westwards across Southern

Thailand and emerged as a low pressure area over the South Andaman sea on 2nd

November.

Animated imageries indicated merging of mesoscale convective clusters along with increase in

deep convection from 3rd

to 4th

November, 2010. As result of further improvement in convecting

band, the well marked low pressure area continued to move west- northwestwards and concentrated

into a depression at 0000 UTC of 04th

November over Southeast Bay of Bengal near Lat. 8.00

N

and 92.00 E. the track of the system is shown in fig.1.

3.2 Intensification and movement of JAL cyclone: The system intensified into a Deep Depression in the early morning of 5

th November and

into a cyclonic storm ‘JAL’ at 0600 UTC of the same day with centre near lat. 9.00

N and long.

87.50

E about 900 km east-southeast of Chennai. The cyclonic storm ‘JAL’ over southeast Bay of

Bengal continued to move west-northwestwards and intensified further into severe cyclonic storm

in the early morning of 6th

November, 2010. However as the severe cyclonic storm, JAL moved to

southwest Bay of Bengal closer to coast.

3.3 Dissipation of JAL cyclone:

BOBTEX-2011


It entered into a region of lower ocean thermal energy and moderate to high vertical wind

shear in association with the strong easterlies in the upper tropospheric level. The high wind shear

led to westward shearing of the convective clouds from the system centre and Lower Ocean thermal

energy led to unsustainability of convection over the region. Due to these two factors, the severe

cyclonic storm ,JAL weakened into a cyclonic storm at 0600 UTC of 7th

November2010 over

southwest Bay of Bengal with centre near lat.12.50N and long.82.5

0E, about 250 km east-southeast

of Chennai. It weakened further into a deep depression and crossed North Tamil Nadu –South

Andhra Pradesh coast, close to north of Chennai near 13.30N and 80.3

0 E around 1600 UTC of 07

th

November2010. It continued to move west –northwestwards and further weakened into a

depression at 0300 UTC and into a well marked low pressure area over Rayalaseema and adjoining

south interior Karnataka at 0600 UTC of 8th

November2010. The weakening of the system before

landfall could be attributed to lower ocean heat content, though SST was higher than threshold

value.

It emerged into the east central Arabian Sea on 9th

Nov and then moved initially

northwestwards towards Saurashtra &Kutch and adjoining Pakistan coast during 9-11 November. It

then moved northeastwards across Saurashtra & Kutch and adjoining Pakistan coast and became

less marked on 12th

November, 2010. The satellite imageries of the system are shown in fig.2.

4.0 Realized weather and associated damage:

(a) Rainfall: Rainfall occurred at most places with heavy to very heavy rainfall at a few places over North Tamil

Nadu, Pudducherry, coastal Andhra Pradesh, Rayalseema, south interior Karnataka and coastal

Karnataka.

(b) Wind: Squally winds with maximum wind speed reaching upto 60 kmph has been reported from different

observatory stations of IMD along North Tamil Nadu –south Andhra Pradesh coast. Ennore Port of

Tamil Nadu reported 33knots (61kmph) in the forenoon of 7th

Nov. 2010. The wind speed

decreased at the time of landfall, as the system weakened gradually and crossed as a deep

depression.

(c) Damage: Andhra Pradesh: Eleven people died in Andhra Pradesh , hundreds of houses were damaged and

standing crops over about 15000 hectares were destroyed. A loss of about 83 crores was estimated.

Tamil Nadu:

Five persons lost their lives about 100 pucca/kutcha houses were either fully or partially damaged.

Many boats were damaged and some were missing due to floods. Rail, road and air transport were

affected due to heavy rain. Sea water inundated in low lying areas.

5.0 Conclusions: (a) The severe cyclonic storm JAL weakened into a deep depression over southwest Bay of Bengal

before landfall.

(b) the high wind shear led to westward shearing of the convective clouds from the centre of the

system.

(c) the copious amount of rainfall occurred over interior part of southern Peninsula than its coastal

area.

Reference:

IMD, 2011, RSMC, Report on,”Cyclonic disturbances over North Indian ocean during 2010”.

BOBTEX-2011


BOBTEX-2011


Characteristics of VLF atmospherics during tropical cyclone ‘AILA’ and several other

thunderstorms over North-East India

Rakesh Roy , Abhijit Choudhury, Anirban Guha and Barin Kumar De

Department of Physics, Tripura Central University, Suryamaninagar-799022, Tripura

E-mail: [email protected]

Lightning discharges radiate most of the electromagnetic energy in the very low frequency

(VLF, 3-30 kHz) and extremely low frequency (ELF, 3 Hz-3 kHz) bands. The exact electrical

processes inside thunderclouds are not yet exactly understood. It is difficult to accurately construct

an empirical model to explain the spectral character of radiated electromagnetic energy from

electrified thundercloud. To understand the physical mechanism precisely, more in situ

experimental data are required.

In the present work, we analyzed the data of VLF atmospherics at four discrete frequencies

received at the Department of Physics, Tripura University during the period from April-October,

2009. We selected temporal data from 76 active thunder-active days over North-East India for the

present investigation. Results show a total of nine different types of characteristic features in the

variation of atmospherics especially during the monsoon period. They are named as Gradual Fall

Gradual Rise (GFGR), Gradual Rise Sudden Fall (GRSF), Gradual Rise Gradual Fall (GRGF),

Gradual Fall Sudden Rise (GFSR), Sudden Rise Gradual Fall (SRGF), Sudden Rise Sudden Fall

(SRSF), Sudden Fall Sudden Rise (SFSR), Sudden Fall Gradual Rise (SFGR) and Spiky. During

the monsoon thunder active days, among all the patterns, GRGF occurred in most of the cases at all

frequencies with an average occurrence number of 37 at each frequency. During our observational

period, the severe tropical cyclonic storm “AILA” (RSMC Designation BOB02, JTWC Designation

02B) occurred over the Bay of Bengal during 23-26 May 2009. Among several characteristic

features during normal monsoon period, SRSF dominated the atmospherics on the 25th

May, 2009

with an average occurrence of 86 numbers in each frequency during the period, when the cyclone

struck the coastal areas of the Bay of Bengal. The VLF atmospherics at different frequencies for

25th

May, 2009 have also been analyzed statistically. The rise rate and fall rate of the atmospherics

for all the patterns are also analyzed for both for the monsoon days and the cyclone active day and

comparative study is performed. The possible interpretation of the observed variations in

atmospherics is explained on the basis of the dynamic electrical activity that occurs inside the

thunder-cloud during cyclonic activity. It appears from the analysis that VLF atmospherics

recorded in North-East India can be used as an efficient remote sensing tool to investigate the

electrical activity of severe thunderstorms and cyclones over Bay of Bengal.

BOBTEX-2011


The Role of Meteorological Department Telecommunication Infrastructure on Forecast Demonstration Project (FDP) program over Bay of Bengal.

Sankar Nath


Mausam Bhavan, Lodi Road, New Delhi 110003, India

The high speed secured communication link to exchange data and warning information is

needed as the Forecast Demonstration Project (FDP) program is aimed to demonstrate the ability

of various NWP models to assess the genesis, intensification and movement of cyclones over the

North Indian ocean with enhanced observations over the data sparse region and to incorporate

modification into the models which could be specific to the Bay of Bengal based on the in-situ

measurements and following the actual track through Satellite and Radar observations. The Main

objective of Telecommunication in IMD is to provide Meteorological data and processed

information to forecasters and users in quickest time to meet their time bound operational

requirements. Over the time advancements in technologies have always been adopted in IMD.

Low speed (up to 300 bps) point t o point teleprinter links were replaced by medium speed (2.5

Kbps) point to point x.25 links and then point to point lease line TCP/IP high speed (64 Kbps)

links were introduced and now high speed (256 Kbps to 2 Mbps) any to any MPLS VPN links

and high speed internet connectivity have been implemented. VPN links provide secure very fast

communication links therefore requirement of transfer of large volume of ASCII and binary data

in short time is possible with it. More over data is simultaneously accessible at many locations

therefore it has overcome the problem of dependency of one center on other center for data

requirements. All AMSS centres, RMCs, MCs, Radar and RS/RW stations have been provided

with VPN links with speeds varying between 256 Kbps to 2 Mbps and speeds can further be

increased depending upon data flow requirements. A central element in a high technology

Meteorological communication environment -TRANSMET AMSS is receive, check and forward

automatically, the meteorological data and products according to the WMO standards.

TRANSMET interconnects our Meteorological sub-systems procured under modernization

project of IMD including High Performance Computer System (HPCs) to run the numerous

numerical weather prediction model installed at NWP section; share in real time our data and

product internally and from/to the meteorological world. It has the audio-visual warning system

for warning message reception and send the whole message to predefined users through e-mail

when a message with particular header is received. It also has the ability to retrieve message from

E-mail and submit that message to GTS.Warning messages can be diverted to predefined FAX

and Mobile numbers through SMS. It can exchange satellite, RADAR, model etc. data file to

predefined users as soon as those are received through FTP.

The data in various research groups under FDP program were exchange through the FTP

server installed at Regional Telecom Hub (RTH) New Delhi as well as through Email-

Group .This FTP server is accessible through high speed internet connectivity. The exchange of

warning message to IMD’s and disaster management group of different state through SMS were

demonstrated through Transmet AMSS.The information of FDP program is also displayed in

IMD website http://www.imd.gov.in.It is clear from the above discussion that the Meteorological

communication has a vital role for data and processed information to forecasters and users in

quickest time to meet their time bound operational requirements as well as conduct any research

program.

BOBTEX-2011


Evaluation Of Cone Of Uncertainty in Tropical Cyclone Track Forecast over north Indian

Ocean Issued by India Meteorological Department

D. P. Nayak and M. Mohapatra




1. Introduction The "cone of uncertainty"-also known colloquially as the "cone of death," "cone of

probability," and "cone of error"-represents the forecasted track of the center of a tropical cyclone

(TC) and the likely error in the forecast track based on predictive skill of past years as well as

numerous additional details about the TC. The India Meteorological Department (IMD) introduced

the cone of uncertainty (COU) in TC track forecast in December 2009 with effect from TC, WARD

over the Bay of Bengal. Comparing the other Ocean basins, the National Hurricane Centre (NHC),

USA introduced the COU in 2002. Prior to this, IMD issued quantitatively the 24 hr forecast track

and intensity in the interval of 06 hrs in 2003. In 2008, IMD extended this track and intensity

forecast upto 72 hrs (every 6 hrs upto 24 hrs and every 12 hrs subsequently upto 72 hrs). Though

there was no COU prior to WARD cyclone, IMD used to mention the probable area of landfall, by

indicating the likely landfall area between two coastal stations (say, the cyclone is likely to cross

Andhya Pradesh coast between Machilipatnam and Nellore). Hear an attempt is made to evaluate

the COU issued in the graphics by IMD during 2010.

2. Data and Methodology The COU represents the probable position of a TC’s circulation center, and is made by

drawing a set of circles centered at each forecast point—06, 12, 18, 24, 36, 48, and 72 hours for a

three-day forecast. The radius of each circle is equal to the average official track forecast errors of

20(35), 40(75), 60(115) and 80(150) nautical miles (km) based on data of 2003-2008 (Table-1). As

the official track forecast beyond 24 hrs period was not issued by IMD, the radius of circle is taken

as 110(200), 135(250), 165(300) and 190(350) nautical miles(km) based on average errors of quasi-

lagrangian model (QLM) of IMD used for track forecasting during 1999-2008. The cone is then

constructed by drawing a tangent line that connects the outside boundary of all the circles. Over the

Atlantic and Pacific Oceans, the COU is drawn by considering the official average track forecast

errors during past five years. The COU includes several elements, viz: the forecast track line, the

“cone” symbolising the averaged forecast error, landfall area, and background elements, such as the

legend, scale, and underlying map. An example is shown in Fig.1. The frequency of official track

forecast error for five cyclones (Laila, Phet, Bandu, Giri and Jal) during 2010 (RSMC, New Delhi,

2011) lying within and outside COU for all forecast periods has been calculated and analysed.

3. Results and discussion. The statistics of track forecast errors lying between and out side the COU are given in

Table2. It is found that the frequency of errors lying outside the COU increases with increase in

lead period of the forecast. The observed tracks of the TCs are thus expected to lie within 55-75

percent of time. It is in agreement with those over other Ocean basin. The entire track of the TC is

expected to remain within the COU roughly 60-70% of the time over the north Atlantic Ocean and

Pacific Oceans (NHC, 2008). Further, it is found that the frequency of observed track lying outside

the COU is higher in case of recurving TCs. The frequency of such cases was maximum in case of

PHET, which had a rarest of rare track (RSMC, New Delhi, 2011)

BOBTEX-2011


Fig.1. A typical example of observed and Forecast track of depression which later on became

the severe cyclonic storm Jal

Table 1. Radius of the circle based on standard error used to construct COU.

Forecast period (hrs) Standard error (kms)

12 75

24 150

36 200

48 250

60 300

72 350

Table 2. Statistics of official six hourly track forecast error lying within and outside the COU.

Forecast

Period

(hrs)

No. of track forecast

error within COU

No. of track forecast

error outside COU

Total No. of

Forecast

12 37(66) 19(34) 56(100)

24 29(62) 18(38) 47(100)

36 27(75) 9(25) 36(100)

48 17(61) 11(39) 28(100)

60 13(59) 9(41) 22(100)

72 11(55) 9(45) 20(100)

All periods 134(56) 75(44) 209(100)

Figures inside the parentheses are the percentage frequencies.

BOBTEX-2011


4. Conclusions

There have been impressive strides in both forecast accuracy and lead time in recent years.

The COU represents the state of the art in forecast products. The frequency of errors lying outside

the COU increases with increase in lead period of the forecast. The observed track of the TCs are

thus expected to lie within 55-75 percent of time. The image has been widely adopted and

disseminated to the public by the media, in part because it is a graphic and thus telegenic (Lundgren

and McMakin 1998). Yet the COU is a complicated figure, containing multiple messages,

presented by multiple graphical elements. Hence there is a need for conducting a survey to evaluate

the users response to this graphical product, as it is done in other basins. (Broad etal, 2007)

References :

Kenneth Broad, Anthony Leiserowitz, Jessica Weinkle, And Marissa Steketee, Bams, 2007,

Misinterpretations of the “Cone of Uncertainty” in Florida during the 2004 Hurricane

Season, BAMS, May 2007, 1-17

Lundgren, R. E., and A. H. McMakin, 1998: Risk Communication: A Handbook for

Communicating Environmental, Safety and Health Risks. Batetelle Press, 473 pp

NHC, USA, 2008, "Definition of the NHC Track Forecast Cone". National Oceanic and

Atmospheric Administration. http://www.nhc.noaa.gov/aboutcone.shtml.

RSMC, New Delhi, 2011, Report On Cyclonic Disturbances Over The North Indian Ocean During

2010, IMD, New Delhi,

BOBTEX-2011


Observational Aspects including DWR for Cyclone Monitoring

S. Raghavan

G1, Prathyeka Apts., New No 12, Old no. 7, 1st Trust Link St., Mandaiveli, Chennai- 600028

Email: [email protected]

The long time dream of routine aircraft reconnaissance of Tropical Cyclones (TCs)

affecting the Indian coasts appears close to realisation. This should enable better understanding of

TCs and, more importantly, more effective forecasts and warnings. Aircraft observations over the

Atlantic and Pacific have over the years contributed the most to our knowledge of TC structure and

behaviour. In situ instrumentation, dropsondes and (Doppler and perhaps Polarimetric) Radar

(helical scan and configurations like pseudo-dual Doppler) need to be deployed on board.

Processing software is quite complex and needs to be robust.

Aircraft reconnaissance is taxing in terms of resources and needs to be fully exploited. The

possibility of mounting an instruments package when required and releasing the aircraft for other

uses at other times needs to be explored. At the surface, traditionally we were dependent on hourly

observations from manned coastal observatories and erratic reports from ships. The establishment

of Automatic Weather Stations (AWS) over land and data buoys over the ocean in the last few

years is a great step forward. AWS’s have helped in determining landfall in recent TCs.

The geostationary satellites have been our mainstay in detecting systems at sea and

estimating their intensity for nearly three decades. Polar orbiting data have been in use from earlier

times though continuous coverage is not there. ISRO’s Oceansat scatterometer data have been very

useful in the case of the recent hurricane IRENE in the USA. The recent launching of Megha-

Tropiques may be of great help. The Tropical Rainfall Measuring Mission (TRMM) satellite data

have been widely used and we may look forward to the Global Precipitation Mission (GPM) too.

In India, ground-based Radar has contributed greatly to improved forecast of TCs over the

past 40 years. We had only non-Doppler analogue radars in the last century but we could improve

TC position determination, track extrapolation and mapping of rainfall distribution significantly.

We learnt a great deal about cyclone structure and behaviour in well-developed as well as weak

systems. We also developed the concept of Radius of Maximum Reflectivity and used it to provide

inputs for storm surge forecasting. With the introduction of Doppler radars in the last 10 years we

are able to get the wind field at close range and hopefully determine maximum winds in TCs close

to the coast. IMD is expanding the Doppler radar network and is likely to induct polarimetric

radars. We are organising networking of radars but more needs to be done. There are various

processing techniques using radar data e.g. the Velocity Track Display. The assimilation of radar

reflectivity factor and Doppler velocity in numerical models has been shown to improve TC

intensity and structure analyses and forecasts significantly. A team at Florida State Unviersity has

developed a rain rate initialization for numerical models that utilize radar resolution rains. We need

to adopt all such techniques.

Besides the expanded ground-based radar network of IMD the deployment of (fully) mobile

radars during TC situations is highly desirable. Clear air ST radars/wind profilers located not far

from the coast have a great potential in the matter of understanding of structure of landfalling

cyclones. There are prospects of establishment of more profilers in the near future. None of these

observational platforms can be viewed in isolation. The real time integration of ground-based,

aircraft-based and satellite data into NWP models needs to be pursued keeping in view the

importance of human judgment. Now several organisations have observational facilities as well as

capability to run models. It is necessary that all concerned organisations collaborate effectively on

a day-to-day basis and share their facilities, data and products. A note of caution is necessary.

Despite the existence of all these facilities and more in the US there has been criticism that the

forecast of intensity change has not been good in the case of Hurricane IRENE which hit the US

east coast in August. This has implications for the continued support we can get from government

for efforts such as BOBTEX to improve our understanding and forecast of tropical cyclones and for

the creation of expensive facilities.

BOBTEX-2011


Observations of Cyclones from Space-Based Platforms: Current Status and future Prospects

R.C. Bhatia

Retired ADGM, India Meteorological Department, New Delhi.

Capabilities of meteorological satellites to provide vital observations on Tropical Cyclones

are well known since more than last four decades, Most important are the frequent pictures of earth

cloud cover in the visible, infrared and water vapour channels obtained from Geostationary

meteorological satellites together with the capability of generating a number of quantitative

products from these data. R&D efforts of last several years at the Cooperative Institute for

Meteorological Satellite Studies, Wisconsin have culminated into development of Advance

Dvorak's technique (ADT) for automated analysis of Tropical Cyclones. This technique is currently

operational for North Atlantic and Caribbean Oceans. It is also being used on Experimental basis in

Satellite Division of IMD. Experience of last two years or so in IMD has shown that while

conventional Dvorak Technique works well for cyclones over the Indian seas, current experience of

using ADT over Indian seas does not permit its use on operational basis over our region. More

studies are needed to understand the observed variations between results of ADT and conventional

Dvorak Technique.

R&D efforts of several years at UW-CIMSS have also resulted in the improvements of

quantitative products derived from imagery data. These products have certainly improved the

analysis of Tropical Cyclones and have provided useful information on predicting the future

intensity/ movement of Tropical Cyclones. Quality of currently operational quantitative products

derived from data of Indian satellites is limited by the coarser resolution of the imaging instruments

in use at present on satellites of INSAT/ KALPANA series. With the availability of high quality of

data from the new satellite of INSAT series ( INSAT-3D ) from next year (2012 ) there is a very

good possibility of making further major improvements in the quality of derived products which

will help in better analysis of Tropical Cyclones. Data obtained from the Microwave based

instruments onboard current satellites of Polar orbiting series also complement the conventional

observations based on visible, infrared and water vapour channels. Particularly, the warm core

anomaly observed in the upper troposphere environment of the Tropical Cyclone is very useful as it

is related to the Intensity of the cyclone. Recently launched Megha-Tropique satellite will provide

this data which will improve cyclone analysis over Indian seas. Recently started 3 new METOPS

receiving stations in India will also provide useful products based on microwave data over Indian

regions.

BOBTEX-2011


Early Detection of Global Tropical Cyclogenesis using OSCAT Data

C. M. Kishtawal and Neeru Jaiswal

Atmospheric Sciences Division, Atmospheric & Oceanic Sciences Group

Space Applications Centre (ISRO), Ahmedabad-380015, India

Email: [email protected], [email protected]

In the present work, a technique has been developed to predict the global tropical

cyclogenesis. The technique is based on the premise that there is some similarity between the low

level wind circulations of the systems that turn in to tropical cyclones at later stage. This similarity

of wind patterns has been measured quantitatively by computing the “matching index” between the

given wind pattern and the wind speed signatures of developing systems, available from past

observations. For this purpose a database has been formed that contains the low level wind patterns

of the early stages of the systems of that turn into tropical cyclones. The QuikScat derived wind

data of the period 2000-09 have been used to form a database. The India’s polar orbiting satellite

Oceansat-2 was launched by Indian Space Research Organisation (ISRO) on 23rd

September, 2009

for applications pertaining to ocean studies and meteorology. The OSCAT derived wind fields have

been used to predict the genesis of tropical cyclone (TC) formed all over the globe during the year

2011. In the present work, the tropical cyclogenesis of ten cyclones formed in the year 2011 in the

North Atlantic Ocean (viz., Arlene, Bret, Emily, Harvey, Irene, Katia, Lee, Maria, Nate and

Ophelia), ten cyclones formed in East Pacific and five cyclones formed in the West Pacific have

been discussed. The mean prediction lead time of the technique was found as 70 hours.

Keywords Cyclogenesis, OSCAT, QuikScat, tropical cyclone, scatterometer, vector block matching.

BOBTEX-2011


Objective Detection of Center of Tropical Cyclone in Remotely Sensed Infrared Images

Neeru Jaiswal, C. M. Kishtawal, P. K. Pal



Email: [email protected], [email protected], [email protected]

In the present work, an objective technique has been presented to fix the center position of

TC in the satellite generated infrared images. The basis of the technique is to determine the point

around which the fluxes of the gradient vectors of brightness temperature (BT) are converging.

First, the variance of brightness temperature at each pixel from its neighboring pixels is computed

and then the flux of the gradient of variance values is computed. Next, a line parallel to the

gradient vector at each pixel is drawn across the image, and the locations where these lines intersect

each other are stored in a density matrix. The score values accumulated in the density matrix are

averaged and location with the highest score is identified. This indicates the location where many

lines intercept that indicates a common point that the corresponding gradients are directed toward

(or away from). This position is considered to be the probable center location of the cyclone. This

location is further corrected by matching the BT distribution around a close neighborhood (11x11

pixel) to the 2D Gaussian distribution. The location where the best match is found is fixed as the

center of tropical cyclone. The technique has been tested over the Kalpana Satellite generated

(approximately 900) IR images of the cyclones that formed during the period 2009-10. The

technique has been used in fully automated mode for the five cyclones viz., Phyan, ward, Laila,

Phet, and Jal. The half hourly sequential IR images during the life period of each cyclone is

analysed and the center position is determined. The track of cyclone obtained by the automatically

determined center position is compared with the the observed track obtained from Cooperative

Institute of Meteorological Satellite Studies (CIMSS).

Key words: tropical cyclones, cyclone center, geostationary satellite, Kalpana satellite, infrared

image, gradient vectors, image variance, flux.

BOBTEX-2011


Analysis of Tropical Cyclones by Using Microwave Imageries of other Polar Orbiting

Satellites over Indian Region

Suman Goyal and A. K. Sharma India Meteorological Department


Since 1982 after the launch of first Geostationary satellite by India, center and intensity of

tropical cyclones is estimated in Sat. Met. Div. by using Visible & IR imageries and applying

Dvorak’s technique operationally which have proven to be invaluable in forecast applications. But

now with the advance of satellite techniques and availability of microwave imageries operationally

from satellites NOAA, DMSP, Metops, AQUA, TERRA etc. These imageries were utilized to

analyse T.C’s, LAILA, PHET, GIRI and JAL by using the same technique. Eye appearance and

accuracy in center determination of cyclone is found to be better in microwave imageries as

compared to IR/Visible images of INSAT. Intercomparison of the intensity and center as measured

by INSAT Visible / IR imageries was also done with other agencies like SSD NOAA, JTWC and

CIMSS Wisconsin.

BOBTEX-2011


Estimation of intensity of tropical cyclone over Bay of Bengal using Microwave imagery

T. N. Jha, M. Mohapatra and B. K. Bandyopadhyay


Mausam Bhawan, Lodi Road, New Delhi -110003.


1. Introduction: Genesis, intensification and movement of Tropical cyclone (TC) storms over north Indian

ocean are mainly monitored by Infrared (IR) and visible cloud imageries as surface data over

ocean are scanty. Dvorak’s technique (1975) is used to determine genesis and intensity of TCs

which is absolutely based on IR and visible cloud imageries taken by geostationary satellites. The

technique is imprecise as high degree of skill is required to recognise cloud features and patterns

as well as images are of low resolution. Further this technique has limitation at night due to

unavailability of visible imageries. Forecasters essentially require maximum wind speed to issue

disastrous warning likely to hit coastal areas. Microwave is powerful electromagnetic radiation for

atmospheric sounding which is unaffected by clouds as well as transparent to dense cloud mass

due to high weighting function of microwave frequencies in middle atmospheric region. With

higher resolution microwave imageries abundantly available from polar orbiting satellites and are

very useful to monitor genesis and intensity cyclones through measurement of brightness

temperature from various layer of TC. However its application over north Indian ocean has been

limited as it has been operationally applied since 2010 only . Therefore objective of this paper is to

examine Advance Microwave Sensor Suite(AMSU) imageries particularly in frequencies range at

37, 85 and 91 GHz and to establish a relationship between brightness temperature and average

wind speed over Bay of Bengal during cyclonic disturbances formed during Forecast

Demonstration Project (FDP) campaign of 2008 -10 .

2. Data and Methodology: The data of central location, central pressure , Maximum Sustained Wind (MSW) and

Brightness temperature in respect of five cyclones formed over Bay of Bengal during FDP in

2008 - 2010 , viz., “Rashmi”, “Khai muk “, “Nisha” , “Jal” and “ Giri “ have been retrieved

from website of U S Navy TC page (www.nrlmry.navy..mil/) which are observed by various polar

satellites. Best track data have also been obtained from annual report published by Regional

Specialized Meteorological Centre(RSMC) New Delhi ,2009 and 2011. Parameters based on

microwave imageries are interpolated every 6 hourly interval using central differencing scheme in

order to match the data with best track .The MSW based on best track and microwave observations

are compared and analysed . Similarly brightness temperature at centre of the disturbances has been

extracted using the imageries to establish its relation with MSW. Out of the five TCs, three could

attain the intensity of cyclonic storm ( Rashmi, Nisha, Khai muk) , one severe cyclonic storm (

JAL) and one very severe cyclonic storm ( Giri) . Details of classification of cyclones over Indian

seas are given in cyclone manual published by I.M.D (2003). Cyclonic storm “Khai muk “ and

severe cyclonic storm “ Jal ” weakened into deep depression before land fall over south Andhra

Pradesh coast near Kavali and north Tamil Nadu coast north of Chennai respectively .Very severe

cyclonic storm “ Giri “ rapidly intensified over east central Bay of Bengal and crossed Myanmar

coast near Sittewe. The mean surface wind speed in respect of the cyclonic disturbances ( category

wise) corresponding to brightness temperature 230, 240, 250, 260 and 270 Kelvin has been

analysed over Bay of Bengal .

3. Results and discussion: 37, 85 and 91 GHz frequencies based coordinates of system , wind speed and brightness

temperature for each pass of satellites have been scrutinized and found that 37GHz brightness

temperature imageries do not reflect location specific thermal structure distinctly . The location of

centre based on microwave observations 85 and 91 GHz differs from that of best track by about 20

BOBTEX-2011


Km (Table-1). The lowest mean track difference of 18 Km is found in respect of very severe

cyclonic storm and highest 25 Km in respect of depression.

Table-1. Mean location error of best track compared to Microwave ( in Km)

Cyclonic disturbances Mean Error

Depression 25

Cyclonic storm 22

Severe cyclonic storm 21

Very Severe Cyclonic storm 18

Table -2. Mean MSW (Knots) based on best track and Microwave products.

Cyclonic disturbances Microwave based

on MSW

Best track

based MSW

Error(Microwave -

best track)

Depression 35 27 8

Cyclonic storm 46 40 6

Severe cyclonic storm 67 56 11

Very Severe cyclonic Storm storm 116 88 28

Microwave observations generally overestimate MSW compared to best track wind in

respect of all the five cases irrespective of degree of intensity of cyclonic disturbance and

overestimation vary in the range 5 - 35 Knots . Table-2 shows MSW of depression, cyclonic

storm, Severe cyclonic storm and Very Severe cyclonic storm as per best track. The lowest error of

8 Knots is found in case of depression and the highest of 28 knots in respect of very severe

cyclonic storm.

Brightness temperatures vary in the range of 230 – 270 Kelvin over Bay of Bengal. Fig .1

shows that MSW abruptly increases when central brightness temperature rises to 260-270 Kelvin

at pressure level 250 hPa in order to enhance low level convection leading to intensification of

depression/ cyclone into severe cyclonic storms over Bay of Bengal.

Fig.1. Relation between the brightness temperature and maximum sustained wind speed of

TCs

BOBTEX-2011


4. Conclusions:

Following salient of feature of cyclonic disturbances may be drawn from the study.

• The microwave imageries at the frequencies 85 and 91GHz are found to be useful for

monitoring prediction of genesis and intensity of TC over Bay of Bengal.

• Mean difference in location of TC based on best track and microwave is found to be about

22 Km .It decreases with increase in intensity of system.

• Microwave overestimates MSW by about 11 – 28 knots in respect of severe and very severe

TCs and 6- 8 knot only in case of depression and marginal TCs.

• Brightness temperature in the ranges 230 -250 Kelvin is favourable for genesis of TC over

Bay of Bengal and 260- 270 Kelvin is favourable for intensification of TC into severe TC.

The microwave based brightness temperature does provide lead time to predict

intensification of TC into severe TC.

References:

Cecil, D. J and Zipser, E.J, 1999, ”Relationship between tropical cyclone intensity and satellite

based indicators of inner core convection- 85GHz ice scattering signature and lightening

”,Mon .Wea .Rev, 103 -123.

Dvorak, V. F., 1975, “ Tropical cyclone intensity analysis and forecasting from satellite imagery “.

Mon. Wea. Rev., 103, 420-430.

India Meteorological Department, 2003, ”Cyclone Manual”,

Kidder,S.Q. 1979, “ Determination of tropical cyclone surface pressure and winds from satellite

microwave data”. Technical No. 307.

India Meteorological Department, 2009, “ RSMC annual report” of 2008”,

India Meteorological Department, 2011, “ RSMC annual report” of 2011”,

BOBTEX-2011


Making Complete Picture – Radar Composite

B. Arul Malar Kannan#, Suresh Chand,and S.K. Kundu


Lodi Road, New Delhi, 110003

#[email protected]

IMD under its modernization has undertaken installation of state of art Doppler weather

radars, these 12 numbers of S-Band Single Polarization radars and the 2 numbers of Dual

polarization radars have high end signal processing receivers with a provision of modifying

inclusive of the processing technique, spurious data filtering, smoothening etc. This customization

during data collection enhances the data quality enabling for its immediate use with less further

processing and quality control.

The paper describes the unified IMD radar network conceived and used in creating specific

products such as Radar Satellite overlay and an operational National Radar Composite achieved by

India Meteorological Department in the recent years.

The main points deliberated in the paper includes

1. Networking concepts and the one in place at IMD

2. Creating a common scan strategy between IMD radars

3. With differing radar processing technologies, way to bring into a common platform.

4. Conversion of radar data from individual proprietary format (Rainbow, BEL, IRIS) to a

unified format for use in custom software in creating a composite.

5. Admissible tolerance time limit, elevation angels limit etc between referred radars.

6. Data sets at overlapping region, various techniques and the one being used

7. Choosing an appropriate map projection for the composite

8. Various useful composite products that can be used

9. Automated product generation and animation in real-time for end-users (WEB-update).

10. Integrating echoes on other regions not covered by Radar from INdian SATellite (INSAT)

HDF5 Asia region data sets.

11. Necessity of a composite for cyclone analysis.

12. Future developments and plans.

BOBTEX-2011


Study of Tropical Cyclone AILA using Doppler Weather Radar Data

D. Pradhan

Doppler Weather Radar, Kolkata

A severe cyclonic storm (AILA) formed in the Bay of Bengal during 22-25 May 2009 and

hit the southern coastal region of Kolkata at 0630 UTC. The system further moved northerly as

severe cyclonic storm and crossed Kolkata on 25th

May 2009 during 1000 -1300 UTC. Cyclonic

storm moved slightly northwestwards and then towards north of Kolkata. Doppler weather radar

installed at Kolkata monitored the movement of the cyclonic storm during 0000-1800 UTC of 25th

May 2011 till it weakened as a depression and predicted the track at least 12 hours in advance. As

estimated from velocity images (PPI_V & VVP_2) maximum wind speed associated with the

cyclone was of the order of 75 knots (130 km/h) at an altitude of 0.9 km whereas the max wind at

0.3 km (almost surface wind) of the order of 60 knots at 0635 UTC. It was analyzed from the DWR

reflectivity & velocity images that AILA was a wide core system with no eye formation having two

spiral bands. The maximum vertical extent of the system as measured by DWR was 9 km (where

radar reflectivity reduced to 20 dBz) and average speed of movement before the landfall was 22

km/h. Heavy rain occurred at Kolkata and surroundings since 0600 UTC till 1400 UTC of 25th

May. Other features of this cyclone have been analyzed using DWR velocity data. This is also

established that VVP_2 product is a very good indicator of the arrival/crossing of the system over

the station. The study has been found very suitable for the researchers in understanding the

structure of the cyclone.

Max_Z Pictures of AILA on 25

th May 2009

BOBTEX-2011


PPI_V Pictures of AILA on 25

th May 2009

VVP-2 Pictures of AILA on 25

th May 2009

BOBTEX-2011


STORM SURGE AND COASTAL INUNDATION

S. K. Dube

Indian Institute of Technology, Hauz Khas, New Delhi 110016

([email protected])

Abstract: The destruction due to storm surge flooding is a serious concern along the coastal regions of the

countries around the Bay of Bengal. About 300,000 lives were lost in one of the most severe

cyclones that hit Bangladesh (then East Pakistan) in November 1970. More recently the Nargis

cyclone of May 2008 killed about 140,000 people in Myanmar as well as caused enormous

property damage. Thus, provision of precise prediction and warning of storm surges is of great

interest in the region. The main objective of the present paper is to highlight the recent developments

in storm surge prediction in the Bay of Bengal and also the future plan to enhance storm surge

forecasting capability in the region.

1. Introduction Storm surges are an extremely serious hazard along the east coast of India, Bangladesh,

Myanmar, and Sri Lanka. Although Sri Lanka is affected only occasionally by the storm surge,

however tropical cyclones of November 1964, November 1978 and cyclone of November 1992 have

caused extensive loss of life and property damage in the region. Storm surges affect Myanmar to a

much less extent in comparison with Bangladesh and India. Notable storm surges, which have affected

Myanmar, have been during May 1967, 1968, 1970, 1975, 1982, 1992, 1994, 2008 and 2010; of which

the 1982, 1994, and 2008 (Nargis) caused the heaviest loss of life and damage. Nargis generated storm

surge in excess of 4 m near Ayeyarwady deltaic region. The entire deltaic coast of Myanmar was

flooded with surges ranging from 1.5 - 4.5m.

A detailed review of the problem of storm surges in the Bay of Bengal is given by Ali (1979),

Rao (1982), Murty (1984), Murty et al. (1986), Gönnert et al. (2001), Dube et al. (1997) etc. Although

the frequency of tropical cyclones in the Bay of Bengal is not high compared to northwest Pacific, the

coastal regions of India, Bangladesh and Myanmar suffer most in terms of loss of life and property

damage. The main factors contributing to disastrous surges in the head Bay of Bengal may be

summarized as (Ali, 1979): (a) shallow coastal water, (b) convergence of the bay, (c) high

astronomical tides, (d) thickly populated low-lying islands, (e) favorable cyclone track, and (f)

innumerable number of inlets including world's largest river system (Ganga-Brahmaputra-Meghna).

The purpose of the present paper is to give a review of recent developments in predicting the storm

surges and associated coastal flooding in the Bay of Bengal.

2. Operational storm surge predictions system for the Bay of Bengal In India, the study of numerical storm surge prediction was pioneered by Das (1972).

Subsequently several workers attempted the prediction of storm surges in the Bay of Bengal

(Ghosh, 1977; Johns and Ali, 1980; Johns et al., 1981). Dube et al. (1994), developed a real-time

storm surge prediction system for the coastal regions of India, Bangladesh, Myanmar, and Sri

Lanka. IIT model can be run in a few minutes on a PC in an operational office. One of the

significant features of this storm surge predication system is its ability to investigate multiple

forecast scenarios to be made in real time. This has an added advantage because the meteorological

input needed for surge prediction can be periodically updated with the latest observations and

forecast (data assimilation) from National Weather Services.

Under the auspices of Tropical Cyclone Programme of the World Meteorological

Organization (WMO) the technology (IIT Model) has been transferred to the National

Meteorological and Hydrological Services of the region. Present IIT model predicts only residual

storm surge at the coast line (i.e., water level over and above normal astronomical tides). With the

advantage of simplicity in operation, this model has been used to produce and disseminate timely

warnings to serve public safety. From cyclone season of 2009, Regional Specialized

Meteorological Centre (RSMC) New Delhi is using IIT Model for providing ‘storm surge

BOBTEX-2011


Pegu●

guidance’ to the countries of the region.

3. Validation of Models The reliability of IIT models have been tested using data from several severe cyclones,

which struck the coastal regions of the countries in the Bay of Bengal during last 50 years. The

following sections describe result of numerical experiments carried out to simulate the surges

generated by 2008 Nargis cyclones. The model computed surges is in good agreement with the

available observational estimates.

Fig. 1: Simulated peak surge (m) for 2008 Nargis cyclone (Dube et al., 2009)

Figure 1 depicts the Time history of the movement of Nargis and model computed surge

contours along the coast of Myanmar. The Storm surge model is integrated with a pressure drop of 65

hPa and radius of maximum winds of 25 km obtained from India Meteorological Department. It may

be seen that a maximum surge of 4.5 m is occurred close to the landfall point. The Deltaic region of

Ayeyarwady is affected by surges between 2.5 - 4 m. The Myanmar coast from Pyapon to Yangon is

flooded with a surge of more than 2m. The computed surge values at Pegu and Moulmein are 2.5 m

and 1.5 m respectively. During this cyclone the surge of the order of 4 m was reported by the

Department of Meteorology and Hydrology, Yangon. This is in good agreement with our simulated

sea level elevations.

4. Future Plan to Enhance Storm Surge Forecasting Capabilities for North Indian Ocean While the storm surge prediction for India in particular, and for the North Indian Ocean

region in general, is generally satisfactory, improvements are needed both in storm surge model as

well as meso-scale NWP model to further enhance storm surge forecasting capability in the region.

Keeping this in view IOC-UNESCO/JCOMM organized two Advisory Workshops

(http://www.jcomm.info/SSindia) at Indian Institute of Technology Delhi, during 14-17 July 2009

and 11-15 February 2010, where the international experts on storm surges have worked with the

regional modelling experts to review the current status/performance of an operational storm surge

forecasting model (IIT-D Model) for the North Indian Ocean region and addressed requirements for

upgrading and improving model performance. Workshops also discussed initiatives of the India

Meteorological Department and other Indian national agencies to improve infrastructure required

BOBTEX-2011


for improved prediction of cyclone and associated surges (IOC-UNESCO, 2009 and IOC-UNESCO,

2011). This is a line of activities following the recommendations made at the 1st JCOMM

Scientific and Technical Symposium on Storm Surges (2-6 October 2007, Seoul,

Korea: http://www.surgesymposium.org). This activity is designed and conducted under the

framework of the UNESCO project on “Enhancing regional capabilities for Coastal Hazards

Forecasting and Data Portal Systems”.

REFERENCES Ali, A., 1979: Storm surges in the Bay of Bengal and some related problems, Ph.D. Thesis, University

of Reading, England, 227 pp

Das, P. K., 1972: A prediction model for storm surges in the Bay of Bengal, Nature 239: 211-213

Das, P. K., M. C. Sinha, and V. Balasubramanyam, 1974: Storm surges in the Bay of Bengal. Quart. J.

Roy. Met. Soc. 100:437-449

Dube, S. K., P. C. Sinha, A. D. Rao, and P. Chittibabu, 1994: A real time storm surge prediction

system: An Application to east coast of India, Proc. Indian Natn. Sci. Acad. 60, 157-170

Dube, S. K., A. D. Rao, P. C. Sinha, T. S. Murty, and N. Bahulayan, 1997: Storm surge in the Bay of

Bengal and Arabian Sea: The problem and its Prediction. Mausam 48:283-304

Dube, S. K., Indu Jain, A. D. Rao and T. S. Murty, 2009: Storm surge modeling for the Bay of

Bengal and Arabian Sea, Natural Hazards, 51, 3-27.

Ghosh, S. K., 1977: Prediction of storm surges on the east coast of India. Ind. J. Meteo. Geophys,

28:157-168.

Gönnert, G., S. K. Dube, T. Murty, and W. Siefert, 2001: Global storm surges: theory,

observations and applications. Die Kueste 623 pp

IOC-UNESCO, 2009: Advisory workshop on enhancing forecasting capabilities for North Indian

Ocean storm surges, 14-17 July 2009, IOC Workshop Report no. 223, Paris, UNESCO, 37

pp.

IOC-UNESCO, 2011: Advisory workshop on enhancing forecasting capabilities for North Indian

Ocean storm surges, 11-15 February 2011, IOC Workshop Report no. 239, Paris, UNESCO,

41 pp.

Johns, B., and A. Ali, 1980: The numerical modelling of storm surges in the Bay of Bengal. Quart. J.

Roy. Met. Soc. 106:1-8.

Johns, B., S. K. Dube, U. C. Mohanty, and P. C. Sinha 1981: Numerical simulation of the surge

generated by the 1977 Andhra Cyclone. Quart. J. Roy. Met. Soc. 107:915-934.

Murty, T. S., 1984: Storm Surges: Meteorological Ocean Tides, Department of Fisheries and Oceans,

Ottawa, Canada.

Murty, T. S., and R. F. Henry, 1983: Tides in the Bay of Bengal. Journal of Geophysical Research

88(c-10):6069-6076.

Murty, T. S., R. A. Flather, and R. F. Henry, 1986: The storm surge problem in the Bay of Bengal.

Prog. Oceanog. 16:195-233.

Rao, A. D., 1982: Numerical storm surge prediction in India. Ph.D. thesis, IIT Delhi, New Delhi, 211

pp.

BOBTEX-2011


Numerical modeling of Tide-Surge interaction in the Bay of Bengal

Jismy Poulose

Centre for Atmospheric Sciences

Indian Institute of Technology, New Delhi 110016

([email protected])

Bay of Bengal is one of the most vulnerable area of Indian Ocean to the storm surges which

is associated with tropical cyclones. Shallow nature of Bay of Bengal and high tidal range are the

major reasons for the inundation due to storm surge. Nature of tidal phase at the time of land

crossing of cyclone is important to predict the total water level and inundation along the affected

coastal area. Surge amplitude and arrival time of peak surge can be affected by the tide (Johns et al,

1985 and Sinha et al, 2008). The objective of the paper is to study the non- linear interaction of tide

with the surge for cyclone GIRI using IIT-Delhi numerical storm surge model. Tidal solution

generated using open boundary radiation condition is the initial condition for this vertically

integrated shallow water model. Experiments are done to study the tide-surge interaction at the time

of high tide and peak surge. Figure 1 shows that the surge height at the place of landfall varies

according the tidal phase. A positive interaction occurred at the time of peak surge.

Fig. 1. Tide-surge interaction at the place of landfall during severe cyclone GIRI

References:

Johns, B., Rao, A. D., Dube, S. K. and Sinha, P. C. (1985) Numerical Modelling of tide-surge

interaction in the Bay of Bengal. Phil. Trans. R. Soc. Lond. A313, 507-535

Sinha P. C., Indu, J., Bhardwaj, N., Rao A. D., and Dube, S. K. (2008) Numerical modelling of

tide-surge interaction along Orissa coast of India. Natural Haza

BOBTEX-2011


Outlook of tide and Storm Induced Current Off Gopalpur Coast

Susant Kumar Misra*, P. Chandramohan*, A. S. N Murty**, J. K. Panigrahi**,

R. Mahadevan*, M. M. Mahanty*** and J. K. Sahu****

* INDOMER Coastal Hydraulics(P) Ltd, 63 Gandhi Road, Alwar Thirunagar, Chennai

** Department of Marine Sciences, Berhampur University, Berhampur – 760 007

*** NIOT, Ministry of earth sciences, NIOT Campus, Chennai

**** Costal Marine Construction & Engineering Limited, Mira Road (E), Maharashtra


In the recent past, there has been increased involvement in the Exclusive Economic Zone

(EEZ) and International waters for exploration and exploitation of living and nonliving ocean

resources. The coastal regions are vulnerable to seaborne events and have significant impact on the

socio-economic condition of the coastal community. The increasing trend in investments towards

myriad coastal infrastructure causes the situation alarming. The new CRZ notification of 2011

seems to be an imperative step of government of India in this context. Coastal Regulation Zone

forms taking into consideration of the tidal line and is silent on the natural hazards and associated

water level rise. In this context, the current study on tide and storm induced current supplements the

knowledge on coastal water level at Gopalpur. This paper presents the analysis of the tide and

storm induced current.

Attempts were made to study the tide and storm induced current along the Gopalpur coastal

region by using the MIKE 21 Hydrodynamic module of DHI Software. The study area experiences

semi diurnal tide with an average spring and neap tidal range of about 1.0 m and 0.4 m respectively.

The average spring tidal range is about 2.39 m and neap tidal range is 0.85 m (Chandramohan et al

1994; Mohanty et al 2010; Mishra et al 2011). While the simulated tide induced current magnitudes

were observed to be around 0.213 m/s for all the periods of the constituents, the order of magnitude

of M2 and S2 tidal constituents (0.099 m/s and 0.034 m/s) observed to be reducing. Similarly, the

directions of tide induced currents during the flood and the ebb phases of tides were observed to

remain almost same. The variation of measured current speeds lay between 0.02 and 0.40 m/s and

the direction predominantly remained within the sector of South - West. For the Hydrodynamic

module, the authors used the parameters of 1977 Andhra cyclone which were obtained from

“Cyclone e Atlas of IMD” and Ghosh (1981). The present simulation shows that the storm induced

currents are approximately 0.80 m/s. The present estimation of the height of storm surge also agrees

well with the estimations of other authors (Subbaramaya et al 1979; Johns et al 1981; Ghosh 1981

and Murty 1984).

Keywords: Tide, Storm induced current, cyclone tracks & parameters, MIKE 21 Hydrodynamic

module &, Toolbox, Gopalpur coast.

BOBTEX-2011


Estimation of pressure drop within the tropical cyclone and height of associated storm surge

using Doppler velocity data

D.Pradhan1, Anasuya Mitra

2

1. Doppler Weather Radar, India Meteorological Department, 13th floor New Secretariat

Building, K.S. Roy Road, Kolkata-700001, mail:- [email protected]

2. Junior Research Fellow, India meteorological Department, Mausam Bhawan, New Delhi-

110003, mail: [email protected]

Strong winds and high storm surge are the critical factors associated to Tropical cyclones in

the Bay of Bengal (India).The exact prediction of landfall location, time, wind velocity and

expected storm surge may save thousands of human lives. The large pressure drop within the eye

and the storm surge height are functions of maximum velocity in the eye wall region. These factors

are basic indicators of severity of a cyclone.

A study of five tropical cyclones during post-monsoon seasons in the Bay of Bengal (Fig 1 -

6) has been conducted using Doppler Weather radar radial velocity data to estimate the pressure

drop in the eye of the cyclone and the height of storm surge. Existing empirical relation between

maximum velocity and central pressure drop (Vmax=K√P-Pc) has been modified in terms of radial

velocity measured by the Doppler radar. At present the value of K=14.2 is being used in the above

relation by IMD but a new value of K=13.637 has been found by the authors in this study. The

storm surge height is also calculated for these cyclones using an empirical relation suggested by

SAARC Meteorological Research Centre, Dhacca (Bangladesh) and is found that the values are

very close to the actual occurrence as reported by media and measured by meteorological agencies.

Fig.1. Severe Cyclone (Nov 12, 2002- 0700 UTC) Fig. 2. OGNI (Oct 29, 2006- 0218 UTC)

The study concludes that apart from intensity of a cyclone in terms of eye diameter, radar

reflectivity (precipitation contents and estimated rainfall) and wind speed, central pressure drop and

storm surge height may also be estimated with a very high accuracy using radial velocity data from

Doppler weather radar in the range of 250 km. So far no such study has been carried out in India

for measurement of central pressure drop and storm surge height using DWR data in the Bay of

Bengal coast, present study may be useful in getting estimates for central pressure drop, intensity of

the cyclone and expected storm surge height and additionally may be used for the validation of the

parameters derived from the satellite. The study may also be applied for the validation of the model

output related to the prediction of track and landfall of a tropical cyclone in the Bay of Bengal.

BOBTEX-2011


Fig. 3. SIDR (Nov 15, 2007- 1140 UTC) Fig.4.PCAPPI_V of SIDR at 2 km

(15Nov 2007-1140 UTC)

Fig. 5--RASHMI (Oct 26, 2008 -0644 UTC) Fig.6-- AILA (May 25, 2009-0644 UTC)

Key Words:-Tropical Cyclone, Storm Surge, Bay of Bengal, Central Pressure drop, Eye wall,

Radial velocity, Doppler weather radar.

BOBTEX-2011


Tropical Cyclones Wind Radii prediction over North Indian Ocean

M. Mohapatra and Monica Sharma




1. Introduction: India Meteorological Department (IMD) is the nodal agency for Tropical Cyclones (TC)

monitoring and prediction over the North Indian Ocean. The TC forecast issued by Cyclone

Warning Division of IMD, New Delhi contains forecasts of TC wind field for 3 days in the interval

of 12 hr period. This forecast is issued four times a day based on 00, 06, 12, 18 UTC observations.

The Cyclone Warning Division of IMD introduced the monitoring and forecasting of TC wind radii

during TC, Giri over the Bay of Bengal in October, 2010. The characteristic features of this

forecast, the methodology adopted to generate the forecast and the limitations and future scope are

presented and discussed herewith.

2. Characteristic features of TC wind radii monitoring and prediction: The TC wind radii forecasts are generated in terms of the radii of 34kts, 50kts and 64kts

(1kt = 0.52 ms-1

or 1.85 kmph) winds in four geographical quadrants around the tropical cyclone

(thereafter referred to individually as R34, R50 and R64 for 34kts, 50kts and 64kts wind thresholds

respectively or collectively as wind radii in units of nautical miles (1nm=1.85km)). These wind

radii represent the maximum radial extent of winds reaching 34kts, 50kts and 64kts in each

quadrant. A theoretical description of the concept is shown in Fig.1. The wind radii forecasts are

issued over the sea area only as per the requirement of the users. The thresholds of 34kts, 50kts and

64kts are chosen as the wind of 34kts corresponds to gale wind threshold, the threshold of 50kts

wind is the requirement of mariners and the threshold of 64kts corresponds to wind with hurricane

force.

Fig.1. Radii of surface wind thresholds used by IMD for TC forecasting

3. Methodology adopted for TC wind radii monitoring and prediction: The initial estimation and forecast of the wind radii of TC is rather subjective and strongly

dependent on the data availability, climatology and analysis methods. The subjectivity and reliance

on climatology is amplified in North Indian Ocean in the absence of aircraft observations.

28 kt

34 kt

50 kt

64 kt

Northeast Northwest

Southwest Southeast

BOBTEX-2011


However, recently with the advent of easily accessible remote sensing derived surface and near

surface winds (e.g. Ocean Sat., Special Sensor Microwave Imager (SSMI), low level atmospheric

motion vectors and Advanced Microwave Sounder Unit (AMSU) retrival methods) and advances in

real time data analysis capabilities, IMD introduced TC wind radii monitoring and prediction

product in Oct.,2010. The initial wind radii estimates have become less subjective due to the tools

and products mentioned above. An example of the wind radii forecast issued during TC, Giri (20-

23 October, 2010) is shown in Fig.2.

Fig.2. A typical graphical presentation of cyclone wind forecast during cyclone, GIRI

While better initial estimates of R34, R50 and R64 are becoming available, forecasting these wind

radii remains a difficult task. It is mainly because of the fact that we do not have any objective wind

radii forecast methods and current Numerical Weather Prediction (NWP) models fail to produce

forecasts that are better than climatology (Knaff et al, 2006, Knabb et al, 2006). The road map

followed for monitoring and forecasting of wind radii is given below.

3.1. Roadmap for wind radii monitoring and forecasting over north Indian ocean

(i) Date and time of initial condition

(ii) Official location and Intensity (T/ C.I. No., maximum wind and centre position

(iii) Initial TC wind radii

a. Wind radii based on Oceansat wind

b. SSMI based wind radii

c. Wind radii based on lower level atmospheric motion vectors

d. Wind radii by AMSU retrieval method

e. Wind radii based on global and regional NWP model analyses

f. Wind radii based on DWR wind retrieval

g. Official TC wind radii based on S.N. (a-e).

(iv) Forecast TC wind radii

a. Official forecast of TC intensity and track upto 72 hrs.

BOBTEX-2011


b. Persistence forecast based on initial wind radii and past 12 hrs trend.

c. Climatology of TC corresponding to initial condition (i.e. with respect to

location and intensity of TC)

d. Climatological forecast of TC wind radii based on the climatological data base

e. NWP Model forecasts of 10 metre wind radii

• Select the model most appropriate to initial condition

• Compose the wind field distribution to the actual wind

• Calculate the wind radii in four quadrants for the threshold of 34kts, 50kts and

64kts surface wind

f. Official TC wind radii forecast in four quadrants for the threshold of 34kts, 50kts and

64kts based on S.N. (a-e)

A few remotely sensed products for monitoring of TC wind radii are shown in Fig.3.

4. Limitations and future Scope: Wind radii forecasts are somewhat dependent on track and very sensitive to the initial

vortex initialisation in NWP models and intensity forecasts. Over the past several years, there have

been large improvements in track skill ( RSMC, New Delhi, 2011) and modest improvements in the

intensity skill like other Ocean basins. However, it is still important to note that the intensity and

track errors at 24 hrs (say) are still of the order of 15kts and 130 km (RSMC, New Delhi, 2011)

respectively. These errors, particularly the intensity errors negatively affect wind radii forecasts.

The poor intensity forecast is particularly pronounced when intensity forecast fail to or falsely

forecast winds that exceed the 34kts, 50kts and 64kts thresholds. In the absence of a reliable NWP

model, a common approach is to aid and assess the forecast products with a statistical model that

employs a combination of persistence of the initial conditions and trends of initial conditions along

with climatology. Hence, an attempt is being made to develop a climatology and persistence

(CLIPER) model for TC wind radii forecast over the North Indian Ocean like those over north

Atlantic and Pacific Ocean (Knaff et al, 2007). This will provide basic guidance which will be

always available to the forecaster and serve as a reference forecast for verifying other techniques.

5. References:

Knabb R., E. Rappaport, M. Mainelli, J. Franklin, C. Lauer and A. Krautkramer, cited 2006: Progress

toward operational implementation of tropical cyclone wind probability products

(http//www.ofcm.gov/ihc06/Presentations, knabb.ppt#492,31,Slide31)

Knaff, C.P. Guard, J.P.Kossin, T.P. Marchok, T. Smith, and N.Surgi, 2006: Operational guidance

and skill in forecasting tropical cyclone structure change. Workshop Topic Reports of the

Sixth WMO International Workshop on Tropical Cyclones, Tropical Meteorology Research

Programme Rep. 72, 29 pp.(http://www.wmo.ch/web/arep/arep-home.html.)

Knaff John A., Charles R. Sampson, Mark DeMaria, Timothy P. Marchok, James M Gross and

Colin J. McAdie, 2007, Statistical tropical Cyclone wind radii prediction using Climatology

and Persistence, weather and Forecasting, 22, 781-791



BOBTEX-2011


Fig.3. Lower level atmospheric motion vectors and surface wind derived from

atmosphericTMI, AMSRE and SSMI around 0000 UTC of 22 October 2010 in

connection with cyclone, GIRI.

(a) (b)

(d) (c)

BOBTEX-2011


Drop size distribution Characteristics of cyclone and convective precipitation observed over

Semi-arid-zone in India

S.Balaji Kumar, S.B.Surendra Prasad, U.V. Murali Krishan and K.Krishna Reddy

Semi-arid-zonal Atmospheric Research Centre (SARC),

Yogi Vemana University, Kadapa

[email protected];

The tropical cyclones (TC) are destructive weather storms characterized by a large low

pressure system originate over oceans and move to the coastal areas-bringing large scale

destruction by violent winds and very heavy rainfall. The TCs formed over Bay of Bengal (BoB)

mostly causes severe damage to the life and economy to coastal regions of Tamil Nadu, Andhra

Pradesh and parts of Kerala. Normally, the coastline districts of AP are affected by cyclones and

floods, whereas during the passage of JAL cyclone, Rayalaseema a semi-aird-region (particularly

Kadapa district), the western and northern parts of Andhra Pradesh also experienced heavy

precipitation. For the present study the micro physical variation of the tropical cyclone, JAL

during 4-7 Nov. 2010 in the BoB is carried out. To understand the effect of cyclone, we carried

out an experiment using cyclonic and non-cyclonic precipitation influence a set of ground based

instruments like Automatic Weather Station, Mini Boundary Layer Mast, Micro Rain Radar, laser

based parsivel Disdrometer and also GPS satellite.

JAL cyclonic storm is formed on 4th

November 2010 at 12:30 IST at 90N and 88.90

0E with

a wind speed of 35 kt. The storm gets intensified with 45 kt wind speed on 5th

November at 00 IST

and located at 9.300N and 88.60

0E. The same pattern continued on 00:30 IST and 06:30 IST.

Further the storm moved towards 9.800N and 86.40

0E on 5

th November at12:30 IST with a wind

speed of 55 kt. On 6th

November, the storm wind speed increased and named as cyclone-1 at

10.500N & 85.70

0E and also more or less same magnitude of wind pattern continued from 00:30

IST to 12:30 IST. After that, the wind speed decreased. On 7th

November at 06:30 IST and 12:30

IST the JAL Cyclone wind speeds were 50 and 35 kt, respectively. On 8th

November the JAL

cyclone is declared as tropical depression with wind speed of 25 kt. Our observational analysis on

characteristic variation of raindrop size distribution (RSD) shows distinctly different DSD

variations during cyclonic and non-cyclonic precipitation. The increase of non cyclonic rain rates

arises from the increases of both drop concentration and drop diameter while the increase of the

rain rate in the cyclonic precipitation is mainly due to the increase of median and large drop

concentration. In the cyclonic precipitation the maximum rain drop diameter does not exceeds 4

mm even at higher rain rate but for non cyclonic precipitation rain drop diameter exceeds 4 mm for

higher rain rates. The higher rain rate with large diameter is due to the local convection and

surrounding environmental atmospheric conditions, where as the cyclonic precipitation with less

than 4 mm diameter observed at Kadapa is due to stratified moisture flow movement from BoB.

BOBTEX-2011


Changes in Extreme Daily Rainfall associated with Cyclonic Disturbances over Andaman &

Nicobar Islands in a Warming Climate

Naresh Kumar, M. Mohapatra, A. K. Jaswal and B. P. Yadav

¹India Meteorological Department, Lodi Road, New Delhi-110003

²India Meteorological Department, Pune - 411 005


The studies related to the variation in extreme weather like heavy rainfall are very important

as these events has major impacts on environment and cause considerable damage throughout the

world each year. Manton et al. (2001) studied the trends in extreme daily rainfall and temperature

in southeast Asia and the south Pacific and found decline trend in the frequency of extreme rainfall

at most of the places. Likely cause of extreme weather may be due to increased warming.

According to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change

(IPCC. 2007), the rate of increase of the global average surface temperature is 0.074°C ±.018°C

over the past 100 yr (1906–2005). Extreme weather events are very much important to coastal areas

also. According to Firing et al. (2004), Islands communities are perhaps at the most risk for climate

change events. Andaman & Nicobar Islands is situated in tropical warm pool region and is a

hazardous area influenced by tropical cyclone formation. The studies related to tropical warm pool

regions are very limited. But there are few studies related to Pacific warm pool region. Kruk (2008)

found decreasing trend in heavy rainfall events across Hawaiian Islands and Alaska. He attributed

decrease in heavy events across Hawaiian Islands may be due to possible poleward shift in the

observed Pacific storm track as found by Yin (2005).

Therefore objective of this paper is to examine the frequency of heavy rainfall events (>64.5

mm in past 24 hours) over the region and its linkage with cyclonic disturbance (CDs) over the

region. For this purpose, heavy rainfall data of all the observatories located in Andaman & Nicobar

Islands for their common period between 1961-2000 has considered. The frequency of the CDs

over Andaman & Nicobar Islands are also computed for the period 1961-2000 from IMD (2008).

The average annual frequency of CDs affects Andaman & Nicobar Islands is 2 out of 9 CDs over

the Bay of Bengal during 1961-2000. The monthly percentage of CDs for the period 1961- 2000

over Andaman & Nicobar Islands is shown in Figure 1.

Fig.1. Frequency of CDs over Andaman & Nicobar Islands

There are two peaks in CDs frequency over the region; one is in month of May and another

in month of November. These peaks over the region are mainly due to passes of Inter Tropical

Convergence Zone crosses twice in a year (May and October-November).

In heavy rainfall events, there is decreasing trend in annual as well as all seasonal basis over the

BOBTEX-2011


region. In yearly basis, around 9% reduction in frequency of heavy rainfall from mean yearly

rainfall based on 1961- 2000 data is found. In seasonal basis, there is around 35% reduction in

frequency of pre-monsoon heavy events and 25% reduction in frequency of post-monsoon heavy

events from their respective seasonal mean from 1961-2000.

In CDs events, a significant (confidence level >95%) decreasing trend is found for yearly

frequency between 1961-2000. In percentage wise, it is around 50% of its average annual CDs

between 1961-2000. In season wise, there is around 40% reduction in pre-monsoon season and

around 35% reduction in post-monsoon season from their respective seasonal mean from 1961-

2000. This implies, this reduction in heavy events over Andaman & Nicobar Islands may be

attributed to the strong negative trend in CDs over the area between 1961-2000. Similar trend in

heavy events are also found in west Pacific warm pool region (Kruk, 2008). This also indicate the

reduction in heavy events over the tropical warm pool region.

References: Firing, Y. and M. A. Merrifield (2004), “ Extreme sea level events at Hawaii: influence of

mesoscale eddies”, Geophys. Res. Lett., 31, L24306 doi: 10.1029/2004GRL021539.

IMD-Cyclone e-Atlas (2008) Tracks of cyclones and depressions in Bay of Bengal and the Arabian

Sea 1891-2007.

Kruk MC (2008). Evaluating the impacts of climate change on rainfall extremes for Hawaii and

coastal Alaska. 24th Conference on Severe Local Storms, American Meteorological Society.

Manton, MJ, PM Della-Marta, MR Haylock, KJ Hennessy, N Nicholls, LE Chambers, DA Collins,

G Daw, A Finet, D Gunawan, K Inape, H Isobe, TS Kestin, P Lefale, CH Leyu, T Lwin, L

Maitrepierre, N Ouprasitwong, CM Page, J Pahalad, N Plummer, MJ Salinger, R Suppiah, VL

Tran, B Trewin, I Tibig, and D, Yee (2001) Trends in extreme daily rainfall and temperature in

southeast Asia and the South Pacific: 1916-1998, Int. J. of Climatol, 21, 269-284.

Yin JH (2005) A consistent poleward shift of the storm tracks in simulations of 21st century

climate, Geophys. Res. Lett., 32, L18701, doi:10.1029/2005GL023684.

BOBTEX-2011


Monitoring Formation and Movement of the Depression of 16-23 June 2011 using

DWR, Satellite Products and Synergy and Utility of Implimenting a Real time Nowcasting in

IMD for filling the forecasting Gap

Rajendra Kumar Jenamani

Meteorological Watch Office, IMD,

New ATS Building (Room No.-211, 2nd

Floor),

IGI Airport, New Delhi-110037

[email protected]/[email protected]

Various types of weather systems with different spatial and temporal scales are observed during the

summer monsoon. These systems play very dominant role in the behaviour of monsoon circulation and

accompanying rainfall over India. The weather systems observed during Indian summer monsoon can be

basically divided into two parts; (i) synoptic disturbances of transient characteristics and (ii) semi-permanent

systems of quasi-permanent characteristics. Synoptic weather systems during Indian summer monsoon

consist of monsoon disturbances, off-shore trough/vortex along west coast of India, mid-tropospheric

cyclones, cyclonic circulations and western disturbances. Amongest all the monsoonal weather systems,

monsoon depressions are recognized as the main rainfall-producing synoptic weather systems over India.

These are nothing but intese low-pressure areas at the surface with associated upper air cyclonic circulations.

Normally, most of these are formed over the head Bay off Orissa-West Bengal coast and move in a west-

north-westerly direction along the monsoon trough. These disturbances produce cupious rainfall while

moving through central India.

In pre-eighties(Rao, 1976), importance had been given to the structure and associated rainfall

distribution of monsoon depressions and it’s statistical studies, while most of the studies in recent years are

related to its formation, mechanism and mathematical modeling(Jenamani 2001, Jenamani and Dash 2004

and see ref 4-11). Monsoon disturbances formed during June & September are associated with the onset and

withdrawal phases of the monsoon. Four depressions formed during just ended monsoon season of 2011 as

against the normal of 4-6 monsoon depressions per season (June - September). Out of these, two Depressions

(that formed on 11th June over Arabian Sea & the other during 22nd -23rd, July over Land) had a short life

span. The Depression formed during 16th -23rd, June intensified into a DD. Its subsequent west

northwestward movement was responsible for the advance of the monsoon over the most parts of the

country. The fourth Depression formed towards the end of the season (22nd – 23rd, Sept.) weakened before

moving towards northeast. In the present study, attempts has been made to document how well DWR and

Satellite at real time has been able to detect the Formation and Movement of the Monsoon Depression

formed during 16-23 June 2011 using DWR, Satellite Products and Synergy Analysis workstations in view

of the system was having longer life period and moved along the monsoon trough zone, establishing the

through and bringing the monsoon rain/onset to over major part of eastern, central and Northern parts of

India. We have also used various real time forecast issued by NWFC for finding whether heavy/very heavy

rainfall realized along its path were captured by 24 hours and 48 hours forecast updated at 6-hours to find

their accuracies and inherent problems which limits such forecast accuracies.. Present analysis shows being

the depression forming on the onset phase of monsoon there were quick organization and re-organization of

intense convective cloud systems associated with this depression at various phases of its movement due to

which convention forecast updated at 6-hours have been found to be have limited accuracies. During when

depression was moving across West Bengal, DWR shows reflective in Max Z reaching as high as 54dbz on

morning of 17 June when the system was near Kolkota. When, the system was monitored at 24X7, using

various observing and analysis systems system such as DWR’s 10-minute products, 30-minute Satellite data

at real time, with 3-hourly analysis of various other data e.g. AWS, synop etc by Synergy, it shows such new

technology based monitoring system now have attended full potential of implementing Operational

Nowcasting in IMD which will fill the forecasting Gap arising because of inherent limitation of present

forecast system to capture such high variability at 0-6 hour time scale and district-wise heavy rainfall

warnings.

BOBTEX-2011


References

H.R.Hatwar, Rajendra Kumar Jenamani, S.R.Kalsi and S.K.Subramanian, 2005, “Synoptic

Weather Conditions during ARMEX”, Mausam, 56, 7-18.

Jenamani Rajendra Kumar and Dash, S. K., 2005, “A Study on the Role of Synoptic and Semi-

permanent Features of Indian Summer Monsoon on it’s Rainfall Variations during Different

Phases of El-Nino” Mausam,, 56, 4, 825-840

Jenamani Rajendra Kumar, 2004, “Distinct synoptic patterns associated with pre-break onset phase

and revival of normal monsoon phase”, Mausam, 55 , 591-598

Jenamani Rajendra Kumar, 2007, “Does Break Monsoon always mean Subdued Rainfall over

India? -An analysis of Role of Off-Shore Trough in this aspect”, Mausam, 58, 572-579

Jenamani Rajendra Kumar, Dash, S. K. and V. Thapliyal, 2004. “Decadal and epochal variation of

frequency and duration of monsoon disturbances and their secular relationships with rainfall

over India”, Mausam., 55, 3, 397-408.

Jenamani Rajendra Kumar, H. R. Hatwar, S.R.Kalsi and S.K.Subramanian, 2007, “Another

Deficient monsoon 2004-A comparison with drought year 2002 and possible causes”,

Mausam, 58, 161-176

Jenamani, R. K. and Bhan, S. C., 2008, “Exceptional rainfall event of 26th

July, 2005 over

Mumbai- Radar Echoes and Rainfall”, Mausam, 59, 3, 366-376

Jenamani, Rajendra Kumar, 2001, "Mathematical modelling of weather systems during Indian

summer monsoon", Ph. D. Dissertation, Utkal University, Bhubaneswar.

Rao, Y. P., 1976 "Southwest Monsoon” Met. Monograph, India Meteorological Department,

Synoptic Meteorology, No. 1 /1976.

S. K. Dash, R. K. Jenamani and S. Sudhansu, 2004, “Decreasing frequency of monsoon

depressions over Indian region and associated parameters”, Current Science, 86, 10, 1404-

1411.

S. R. Kalsi, R. K. Jenamani, H. R. Hatwar and, 2006, “Meteorological features associated with

severe drought 2002 ” Mausam, 57, 3, 459-474

BOBTEX-2011


Forecasting of rainfall from landfalling cyclone using satellite derived rain rate data: A case

Study for cyclone ‘Aila’

Habibur Rahaman Biswas and P.K.Kundu*

Regional Meteorological Centre, Kolkata

*Jadavpur University, Kolkata


An important major threat to life and property of east coast of India including West Bengal

Coast is very heavy rainfall from landfalling tropical cyclones originated over Bay of Bengal.

Forecasting magnitude of rainfall from landfalling tropical cyclone is very difficult job. With the

advent of weather satellites, no tropical cyclone anywhere over the globe goes undetected or evades

the eyes of meteorologists. Satellite derived rain rates through cloud area of tropical cyclone can be

used to forecast potential tropical cyclone rainfall accumulations. In the present study, estimation of

24 hours rainfall over Coastal stations before landfall of tropical Cyclone ‘Aila’ has been analysed

using tropical rainfall measuring mission(TRMM) satellite rain rates data and observed storm track

of Aila. Magnitude of estimated rainfalls for the case of cyclone ‘Aila’ nearly match with observed

rainfall over coastal stations. Study explores the feasibility of forecast for 24 hours rainfall from

landfalling cyclone over Bay Bengal using satellite estimate rain rate and storm forecast track.

BOBTEX-2011


Unprecedented flood in river Mahanadi in Orissa in September, 2008 and its impact on

economic development

S.C.Sahu and S.K.Dastidar

Meteorological Centre, Bhubaneswar

[email protected]

State of Orissa is prone to Meteorological hazards such as heat wave, tropical cyclone and

flood. Flood in every year cause damage to kharif crops mainly paddy besides loss of lives and

properties. Northern part of Bay of Bengal is prone to cyclone genesis-that is sea surface

temperature and other meteorological conditions are favourable for formation of low pressure and

its intensification particularly during the monsoon season. The circulation pattern is such that they

move in north-west or north-north-west or west-north-west direction . Orissa coast is directly under

the track of these moving monsoon depressions or deep depressions. Out of seven low pressures

formed over Bay of Bengal during monsoon period of 2008, three systems intensified into

depression and one among them further intensified into deep depression on 16th

September,2008.

Deep depression on 16th

Sept.2008 crossed Orissa coast near Chandbali causing heavy rainfall in

catchment areas of Mahanadi. It caused massive flood surpassing earlier records of flood in

1834,1955 and 1982, 15.81 lakh cusec water were released on 20-9-2008 at Munduli near Cuttack.

19 districts are affected due to inundation of flood water by breaching of 477 embankments and

2895 road breaches. Due to this flood, 4,78,854 hectares of crop area damaged and 40,95,547

numbers of people are affected.

Floods in last 30 years in Mahanadi river has been analysed and rainfall data of rain gauge

stations in Mahanadi catchment are taken for calculation of area-depth relation for large storms.

One day average rainfall on 17th

September,2008 are recorded in districts of Jajpur (211.8 mm) ,

Bhadrak (201.4 mm) , Cuttack ( 136.7 mm) , Kendrapara (205.3 mm) , Bargarh (71.2 mm) , Puri

(52.7 mm) , Khurda (63.1 mm) , Kalahandi (135.2 mm) , Bolangir ( 131.4 mm) , Sonepur ( 131.0

mm) , Kandhamal (177.0 mm) and Boudh ( 60.0 mm) . These districts are in the catchment areas of

Mahanadi. To mitigate the suffering of people during flood , food droppings were made for more

than a week in affected areas and on precautionary measure before occurrence of flood, 3,91,907

numbers of people were evacuated to safer places.

After crossing the coast, the depression maintained its intensity over land for another 12

hours which caused heavy rainfall in interior districts of Orissa and also in Upper Mahanadi

catchment areas in the state of Chattisgarh. Attempt has also been made to study the synoptic

situation of the system for causing such copious rainfall. When deep depression moved to land,

mainly development of cumulonimbus cloud and thundery shower occurred behind the trough line.

Low level convergence behind the trough and divergence ahead of the trough are agreeing to

equation for the conservation of potential vorticity.

(f + ξ )/ ∆p = К

Where f= Coriolis parameter, ξ = Relative vorticity ( cyclonic +ve) and

∆p = Depth of air column

Air overtaking trough line is moving both upwards ( f increasing ) and towards a zone of

cyclonic curvature ( ξ increasing), so ∆p must increase to keep left hand side of equation remain

constant. This vertical expansion of the air column necessitates horizontal contraction

(convergence). Conversely, there is divergence in the air moving southward ahead of the trough

and curving anticyclonically.

Analysis of OLR and SST will also be done for occurrence of heavy rainfall for this deep

depression.

BOBTEX-2011


Deep Depression without Heavy Rainfall

Bikram Singh, R.C. Vashisth, B.P. Yadav and Charan Singh



A depression formed over Bay of Bengal at 0000 UTC of 19

th October 2011. It rapidly

intensified into a deep depression at 0300 UTC of the same day and crossed Bangladesh-Myanmar

coast south of Cox’s Bazaar (Bangladesh) as deep depression by following north-easterly track with

high speed of movement. The uniqueness of the system was that no heavy rainfall occurred and the

movement was faster than the average while it was near the centre of the anti-cyclone. The main

reason for fast movement seems to be the shearing influence due to southward shifting of Sub-

tropical Westerly Jet (STWJ) and the dry cold environment was not conducive for heavy

precipitation. The detail features, causes of fast movement and no heavy rainfall associated with

the system are analysed and discussed in this paper.

BOBTEX-2011


Lessons from IRENE…

S. Raghavan

G1, Prathyeka Apts., New No 12, Old no. 7, 1st Trust Link St., Mandaiveli, Chennai- 600028


The long time dream of routine aircraft reconnaissance of Tropical Cyclones (TCs)

affecting the Indian Coast appears close to realisation. This should enable better understanding of

TCs and, more importantly, more effective warnings. Aircraft reconnaissance is taxing in terms of

resources and needs to be fully exploited. The possibility of mounting an instruments package when

required and releasing the aircraft for other uses at other times needs to be explored. Airborne

Doppler Radar needs to be deployed as it is the device which has led to most of the knowledge of

cyclone structure. Besides its recognised uses, radar can contribute inputs to storm surge

forecasting.

The real time integration of ground-based, aircraft-based and satellite data into NWP

models needs to be pursued keeping in view the importance of human judgment.

The reason for the present title is the context of the Hurricane IRENE in the US. Many

comments have been made that the intensity forecast was not good and that the weakening close to

the coast produced an anticlimax and perhaps over-warning. The criticism of over-warning does

not seem justified. Intensity forecast is particularly difficult. The double eyewall feature seen on

radar which is being commented upon is an indicator of a severe TC but not a reliable predictor of

intensity change. The Oceansat scatterometer data have been very useful in the case of IRENE.

The user is interested not in the phenomenon but its IMPACT. Operationally therefore it is

important to put out warnings with graphics indicating the various possible scenarios and

explaining the uncertainties, while keeping close liaison with disaster managers. This is being

effectively done in the US where weather telecasters are qualified meteorologists. In India we often

give a “deterministic” type of forecast and keep changing it in the light of observations without

explaining the background to the public. While this may be justified scientifically it projects a poor

image of the Meteorological Service with a loss of credibility. It may be better to give a

probabilistic forecast explaining the uncertainties and taking recipients into confidence.

It is also necessary to create greater awareness of the importance of pro-active preparedness

among administrators and ensure more funding for that rather than just for relief measures after the

event.

BOBTEX-2011


NWP models applications in Tropical Cyclone Predictions over the Bay of Bengal

U. C. Mohanty*, Krishna K Osuri and S. Pattanayak

Indian Institute of Technology Delhi, Hauz Khas – 110016, New Delhi, India

* [email protected]

In recent days, Weather Research and Forecasting (WRF) model, the state-of-the-art

mesoscale model, is used worldwide, both in research and operational environments, for the

simulation of high impact extreme weather events such as tropical cyclones (TCs), heavy rainfall

events, and severe thunderstorms. In respect of TC prediction, a number of studies demonstrate

high degree of performance of WRF modeling system over different global cyclone basins. In the

present study, we provided a detailed evaluation of model performance of WRF model for the

simulation of TCs over the Bay of Bengal (BoB).

First, relative performance of widely well known Mesoscale Model version 5 (MM5) and

the Advanced Research WRF (ARW) model are evaluated which clearly indicate that the ARW

model could provide better track and intensity prediction of BoB cyclones compared to that of the

MM5. The improvement with ARW is not noticeable up to 48 hours and after that the improvement

is significant (Figure 1). The mean track error is reduced to almost half with ARW model

compared to that of the MM5 model. There is considerable improvement of about 8%, 5%, 5% and

73% in intensity prediction at 12, 24, 48 and 72 hour forecast respectively, over that of the MM5

model (Pattanayak and Mohanty, 2008). The performance of Hurricane WRF (HWRF) is also

studied for one severe cyclone “Mala” and reveals that the improvement in intensity is significant

compared to the improvement in track prediction. The track forecast error for the cyclone Mala

varies from 180 to 300 km from 24 to 72 hour forecast (Pattanayak et al, 2011).

The operational utility of the HWRF needs high computation requirements. However, a

detailed evaluation of real time predictions of the ARW model for North Indian Ocean (NIO)

cyclones is analyzed and can be found at Osuri et al. (2011a). Before going for real time prediction

of BoB TCs, the ARW model is customized to the same domain by simulating number of cyclones

with different physical parameterization schemes (Osuri et al., 2011d). The 12 TCs of the BoB

during 2007–2010 are predicted in real time at different times and have a total of 71 forecast cases.

The mean track forecast error from the ARW model varies from 170 km to 350 km for 24 to 72

hour forecast length. The mean landfall errors are in the range of 60 to 140 km in 24 to 72 hour

prior to observed landfall time. From the systematic errors, it may be noted that, the ARW model

has right side (eastward) bias and slower (southward) bias for all forecast intervals.

A number of experiments are conducted to assess the impact of assimilation of different

sources of data on initialization and forecast of the ARW model for the simulation of TCs over the

BoB and Arabian Sea. The inclusion of QSCAT and SSMI satellite-derived winds, through a 3-

dimensional variational (3DVAR) data assimilation system into the ARW model initial condition,

improves the initial position in 11 cases out of 13 by 34% (Osuri et al., 2011b). From Figure 3, the

24-, 48-, 72- and 96-hour mean track forecast improves by 28%, 15%, 41% and 47%, respectively,

based on 13 cases (of Narigs with 5 cases, Gonu with 4 cases, Sidr with 2 cases, and KhaiMuk with

2 cases). The landfall prediction is significantly improved in 11 cases by about 37%. Further, the

intensity prediction also improves by 10–20%. Kinematic and thermodynamic structures of TCs are

also better explained, as it could simulate heat and momentum exchange between sea surface and

upper air. Due to better simulation of structure, intensity and track, the 24-hour accumulated

rainfall intensity and distribution are also well predicted with the assimilation of satellite-derived

winds (Osuri et al. 2011b).

Further, the impact of Global Telecommunication system (GTS) data and the Doppler

Weather Radar (DWR) data on simulation of TCs are also examined. Assimilation of the DWR

data significantly improves track and intensity. The mean radial wind error is reduced from 2.59 m

s-1

(FNL analyses) to 1.67 m s-1

in the DWR analysis. The DWR experiments show better temporal

BOBTEX-2011


evolution of intensity with better simulation of surface latent heat flux, relative vorticity at 850 hPa,

and inner core structure of TCs. The improved upper-level divergence and steering flow helps for

better track prediction in the DWR experiments with a large gain in skill, particularly at longer

forecast intervals. Figure 4 indicates that the mean track errors (of all 16 cases) are less for the

DWR experiment tracks and varies from 50 to 250 km from the 12 hr forecast to the 72 hour

forecast. The track errors in case of GTS experiment ranges up to 400 km while in the CNTL, the

errors are even higher and up to 500 km. The gain in skill of the DWR data ranges from 33% to

74% from the 12 to 72 hour forecast. Out of 16 cases, CNTL and GTS could predict the landfall in

8 and 10 cases, while, the DWR experiment succeeds in 14 cases with minimum errors. The

landfall time errors are also reduced in the DWR experiments in most of the cases as compared to

those of others. The mean landfall error of CNTL (8 cases), GTS (10 cases), and DWR (14 cases) is

78, 64, and 66 km respectively. Considering the same 8 cases as that of the CNTL experiment, the

mean errors are 68 and 42 km for the GTS and DWR experiments, respectively. The model-

simulated reflectivity at landfall and the 24-hour accumulated rainfall are also well simulated in the

DWR experiments as compared to CNTL and GTS experiments.

Conclusions: In view of the above results, the following broad conclusions can be drawn:

The WRF modeling system performs better in real-time predictions of the Bay of Bengal

tropical cyclones compared to the MM5 system. HWRF model also provides better track and

intensity prediction of TCs over the BoB. However, the model performance is significantly

improved with data assimilation using additional high density remote sensing data such as satellite

derived winds and DWR radial wind and reflectivity products. Therefore, the high resolution

mesoscale models can provide a good guidance for the track, intensity and landfall prediction of the

Bay of Bengal TCs to the operational forecasters.

References: Krishna K. Osuri, U. C. Mohanty, A. Routray and M. Mohapatra, 2011a: Mean track errors of

Landfalling tropical cyclones of 2007-09 over Indian seas as evident from WRF-ARW

modeling system, Submitted to Atmospheric Research (Under review).

Krishna K. Osuri, U.C. Mohanty, A. Routray and M. Mohapatra, 2011b: Impact of Satellite

Derived Wind Data Assimilation on track, intensity and structure of tropical cyclones over

North Indian Ocean, International Journal of Remote Sensing, 1 – 26,

DOI:10.1080/01431161.2011.596849.

Figure 1: Mean track errors of TCs over the BoB from ARW-

WRF and MM5 model

BOBTEX-2011


Krishna K. Osuri, U. C. Mohanty, D. Niyogi, A. Routray, and D. V. Bhaskar Rao, 2011c, Improved

Prediction of Bay of Bengal Tropical cyclones through Assimilation of Doppler Weather Radar

Observations, Submitted to JGR (Under review).

Krishna K. Osuri, U. C. Mohanty, A. Routray, Makarand A. Kulkarni and M. Mohapatra, 2011d:

Sensitivity of physical parameterization schemes of WRF model for the simulation of Indian

seas tropical cyclones, Natural Hazards, DOI 10.1007/s11069-011-9862-0

Pattanayak S, Mohanty UC (2008) A comparative study on performance of MM5 and WRF models

in simulation of tropical cyclones over Indian seas. Current Science, 95(7):923–936.

Sujata Pattanayak, U. C. Mohanty, and S. G. Gopalakrishnan, 2011: Simulation of very severe

cyclone Mala over Bay of Bengal with HWRF modeling system, Natural Hazards, vol. 52, DOI

10.1007/s11069-011-9863-z.

Mean track forecast errors for BoB cyclones

-8

23

40

48 51 51

0

100

200

300

400

500

600

700

800

12 24 36 48 60 72

Forecast Length (hour)

Po

sitio

n E

rro

rs (km

)

-20

-10

0

10

20

30

40

50

60

Gain

in

Skil

l (%

)

ARW-WRF

Persistence

Gain in Skill (%)

Figure 2: Mean (of 71 cases) track errors of BoB cyclones from the real time

predictions of ARW-WRF model. The gain in skill (%) of the model

with respect to persistence track is also shown in line graph.

Figure 3: Mean vector displacement errors (VDEs in km) in 12-hr interval for CNTL

and 3DVAR experiments (a) Nargis (mean of 5 cases), (b) Gonu (mean of 4

cases), (c) Sidr (mean of 2 cases) and (d) KhaiMuk (mean of 2 cases).

12

0

18

1

17

2

22

1 24

4 26

7

26

2

15

5

11

5 12

7 15

1

14

5

13

1

11

2

10

3

11

3

0

50

100

150

200

250

300

12 24 36 48 60 72 84 96

(b) TC Gonu

90

21

3

25

2

30

0

16

6

11

2

22

4

14

1

78

20

8

21

4

15

1

11

0

17

7

60

14

3

0

50

100

150

200

250

300

350

6 12 18 24 30 36 42 48

(d) TC KhaiMuk

13

8 19

5 23

0

30

6 37

8

58

6

60

9

12

9

89

94

56

0

50

7

34

6

28

7

13

0

11

9

0

100

200

300

400

500

600

700

6 12 18 24 30 36 42 48

(c) TC Sidr

Me

an

VD

Es

(km

)

86

17

7

27

5 31

8 37

3

46

5

58

9

13

5

98

86

33

5

26

7

22

0

18

5

18

1

11

0

0

100

200

300

400

500

600

700

12 24 36 48 60 72 84 96

(a) TC Nargis

Me

an

VD

Es

(km

)

BOBTEX-2011


IMD’s recent initiatives for improved Tropical Cyclone track and intensity forecast over

Indian region using Hurricane WRF Model

Y.V. Rama Rao1, T.S.V. Vijay Kumar

2, Zhan Zhang

2, K. Naga Ratna

1, A.K. Das

1, D.R.

Pattanaik1, S.K. Roy Bhowmik

1 and Ajit Tyagi

1

1India Meteorological Department, New Delhi

2Environmental Modelling Centre (EMC), NCEP, USA

During the last 15 years, IMD running various numerical models for Tropical Cyclone track

prediction such as Limited Area Model (LAM), Quasi-Lagrangian Model (QLM) for operational

numerical guidence. With the operationalisation of High Power Computing System (HPCS) for

numerical modelling at IMD, New Delhi, IMD started high-resolution Global model (35 km

horizontal resolution) for medium range and WRF model for short range track and intensity

forecast. Recently under Indo-US joint collaborative program, IMD adapted HWRF model for

Tropical Cyclone track and intensity forecast for North Indian Ocean (NIO) region for its

operational requirements.

The Weather Research and Forecast (WRF) system for hurricane prediction (HWRFTM

) is

operational at National Centre for Environmental Prediction (NCEP), USA since 2007, providing

deterministic forecast guidance to the National Hurricane Center (NHC) for the Atlantic and North

Eastern Pacific basins. This advanced hurricane prediction system was developed at Environmental

Modelling Centre (EMC), NCEP to address the Nation's next generation hurricane forecast

problems. The HWRFTM

is a high resolution coupled air-sea-land prediction model with a movable

nested grid and advanced physics for high resolution. This model is currently coupled to the

Princeton Ocean Model (POM) in the Atlantic basin. The HWRFTM

has the capability to address

hurricane structure and rainfall forecast problems in addition to advancing wave and storm surge

forecasts. Continued advancements in track and intensity prediction are important focus areas of

this prediction system.

The basic version of the model HWRFV (3.2+) which was operational at EMC, NCEP was

ported on IMD IBM P-6/575 machine with nested domain of 27 km and 9 km horizontal resolution

and 42 vertical levels with outer domain covering the area of 800x80

0 and inner domain 6

0x6

0 with

centre of the system adjusted to the centre of the observed cyclonic storm. The outer domain covers

most of the North Indian Ocean including the Arabian Sea and Bay of Bengal and the inner domain

mainly covering the cyclonic vortex with moving along the movement of the system. The model

has special features such as vortex initialization, coupled with Ocean model to take into account the

changes in SST during the model integration, tracker and diagnostic software to provide the graphic

and text information on track and intensity prediction for real-time operational requirement.

As part of model validation, case studies were undertaken to test the ability of the model for Indian

Seas for Very Severe Cyclonic Storm ‘GIRI’ formed during 20-23 October 2010 and Severe

Cyclonic Storm ‘JAL’ formed during 4 to 7 November 2010 over the Bay of Bengal. The model

was integrated for 5-days forecast with basic input from GFS spectral fields using Gridpoint

Statistical Interpolation (GSI) assimilation system. Also the six hourly cycling of the HWRF model

was tested to run the model in cycling mode. In this run only the atmospheric model (HWRF) was

tested. The Ocean Model (POM-TC) and Ocean coupler requires the customization of Ocean

Model for Indian Seas. In this regards, IMD is expecting to work in collaboration with INCOIS,

Hyderabad which is running the Ocean Models (POM)/Hybrid co-ordinate ocean model (HYCOM)

to support in porting the Ocean Model with Indian Ocean climatology and real time data of SST

over Indian Seas.

The detailed model configuration and validation results along with the limitations and future

plans will be discussed.

BOBTEX-2011


Impact of cyclone bogusing and regional assimilation on tropical cyclone track and intensity

predictions.

Manjusha Chourasia, R. G. Ashrit, John P George

National Centre for Medium Range Weather Forecasting (NCMRWF),

Ministry for Earth Sciences, A-50, Institutional Area, Phase-II

Sector-62, NOIDA, U.P., Pin : 201 309

Email : [email protected]

An attempt is made to assess the impact of tropical cyclone bogusing in WRF assimilation

and forecast system for cyclone track and intensity prediction in short range forecast. Three

tropical cyclones formed in the year 2010 are chosen as study cases; namely 'LAILA' (Bay of

Bengal), 'GIRI' (Bay of Bengal) and 'PHET' (Arabian Sea),.The operational NCMRWF T382L64

analysis and forecasts are used to provide initial conditions for WRF model. The WRF model is

integrated upto 72 hr for producing the cyclone track and intensity forecast. In the tropical cyclone

bogusing scheme used in this study, the existing cyclone vortex in the initial condition is removed,

and an artificial cyclone vortex is ingested at observed location by supplying observed data of

tropical cyclone centre along with intensity and radius of maximum wind. Four sets of model

experiments were carried out: (1) The control experiment (CNTL); Cold start run with interpolated

global T382L64 model analysis initial condition without performing any bogusing or assimilation.

(2) The assimilation experiment (VAR); Initial condition is prepared by regional assimilation

system (WRF 3DVAR) without cyclone bogusing.(3) The cyclone bogusing experiment (BOG);

Model is run with T382L64 global model interpolated output initialized with bogusing without

assimilation. (4) In the forth experiment,(BOGVAR); the initial condition of the model is prepared

with both cyclone bogusing followed with WRF data assimilation .

The impact is demonstrated in terms of track error, central pressure, maximum sustained

wind speed etc. Results indicate a remarkable impact of cyclone bogusing on the initial condition.

All three cyclones can be located in the initial conditions (00 Z) of bogus (BOG and BOGVAR)

experiments which were otherwise absent in no-bogus (VAR and CNTL) experiments. The track

prediction is considerably improved in terms of direction of movement as well as cyclone location

and is close to observations in the BOGVAR experiments.

LAILA

0

100

200

300

400

500

600

700

800

900

0 6 12 18 24 30 36 42 48 54 60 66 72

Forecast time, hr

Tra

ck e

rro

r, k

m

BOGVAR

VAR

Fig.1. Tropical Cyclone 'LAILA' comparison of track errors for 'BOGVAR' and 'VAR'

experiments Results with bogus followed by assimilation has given significant reductions in track errors.

Figure 1. Shows comparison between BOGVAR and VAR experiments track errors during

forecast hours for tropical cyclone 'LAILA'. Here it is evident that bogusing (BOGVAR) has

improved track predictions by reducing track errors. The maximum reduction in track error is 76.81

% in 'LAILA', 87.30 % in 'GIRI' and 51.55 % in 'PHET' respectively in BOGVAR experiment in

comparison to VAR experiment. Maximum sustained wind speed and minimum central pressure

are more close to observations in BOGVAR in comparison to VAR for tropical cyclones 'LAILA'

and 'GIRI'. Whereas in case of 'PHET' the trend in pressure drop and increase in wind speed did not

show significant improvement.

BOBTEX-2011


Numerical Simulation of Tropical Cyclones in Bay of Bengal

R. D. Kanase and P. S. Salvekar

Indian Institute of Tropical Meteorology, Pune-411008, India

[email protected] and [email protected]

In last decade total 29 cyclones were formed in BoB, 9 in pre-monsoon and 20 in post

monsoon. Out of which 7 cyclones were VSCS and 6 cyclones were SCS. It is desirable to have

accurate prediction of the track & landfall for effective implementation of the disaster management.

For this purpose meso-scale numerical models based on well defined dynamical and physical

processes can be used.

In this study, simulation of four cases of sever cyclonic storms [Laila (17-21 May 2010),

Aila(23-26 May 2009), Jal (4-8 Nov. 2010) and SCS (11-16 Dec. 2003)]is carried out using

Mesoscale Model WRF(Skamarock et.al. 2005-WRF Version 3, NCAR Technical Note) and

NCEP FNL reanalysis data with the combination of Cumulus scheme-BMJ, Planetary Boundary

Layer scheme-YSU and Microphysics scheme such as WSM-6 class microphysics. Three two way

interactive nested domains [60km, 20km and 6.6km ] and observed low pressure as the initial state,

model integration is performed to evaluate prediction of track and intensity in terms of Central Sea

Level Pressure (CSLP) & Maximum surface wind speed (MSW) of the storm. The errors in track

prediction are calculated in terms of vector displacement errors compared to the observed (IMD)

track of the storms.

Results

1. Pre-monsoon cyclones: Laila (17-21 May 2010) - A depression formed on 17

th May in BoB, moving in the northwest

direction, intensified into a SCS at 09:19-05-2010, crossed AP Coast near Bapatla between 1100-

1200 UTC of 20th

May 2010.Track of Laila cyclone is well simulated by WRF model (fig.1a) with

minimum/maximum track error is about 40km/160km (fig.1b).

Aila (23-26 May 2009) - A depression formed over BoB on 23rd

May 2009 moved in

northward direction, intensified into a SCS at 06:25-05-2009. It crossed West Bengal coast close to

east of Sagar Island between 0800 &0900UTC of 25th

May 2009. Track & intensity of Aila are very

well simulated. The track error ranges from 12 to 84 km (fig. 2a, 2b) upto 72 hrs of

integration and thereafter continuously increases.

2. Post-monsoon cyclones: Jal (4-8Nov. 2010)- A depression formed over BOB on 00UTC of 4

th Nov. 2010, moved in

north-west direction and intensified into SCS at 21:05-11-2010. It crossed north Tamilnadu & south

AP coast close to north Chennai around 16:07-11-2010. Initially upto 42hrs of integration, the track

error is around 30km, then it is upto 200km, till 96hrs.(fig. 3a1-3b).

SCS (11-16Dec. 2003) - A depression is formed over the southeast BoB on 12:11-12-2003,

moved in north-west direction and intensified into SCS at 12:14-12-2003 and crossed the coast near

Machilipatnam around mid-night on 15-12-2003. Upto 75hrs of integration the track error is

within 100km and afterwards it increases continuously (fig.3a2-3b).

BOBTEX-2011


Conclusions

These results clearly demonstrate that the WRF with model configuration CPs-BMJ, PBLs-

YSU, MPs-WSM6 is suitable for track prediction of severe cyclonic storms. Intensity of Aila is

very well simulated as compared with IMD whereas for other three cyclones intensity is over

estimated.

BOBTEX-2011


Laila Aila Jal SCS-

03

I

M

D

CSLP(hP

a)

986 968 988 990

MSW

(m/s)

29 31 31 29

W

R

F

CSLP(hP

a)

972 962 978 976

MSW

(m/s)

45 36 46 44

Table: Intensity of cyclones

BOBTEX-2011


Tropical Cyclone Genesis Potential Parameter (GPP) and it’s application

over the North Indian Sea

S. D. Kotal and S. K. Bhattacharya

NWP Division,




An analysis of tropical cyclone genesis potential parameter (GPP) for the North Indian Sea

is carried out. The genesis potential parameter developed by Kotal et al. (2009) is computed based

on the product of four variables, namely: vorticity at 850 hPa, middle tropospheric relative

humidity, middle tropospheric instability and the inverse of vertical wind shear at all grid points

over the area. The GPP at a grid point is considered under the conditions that all the variables

vorticity, middle tropospheric relative humidity, middle tropospheric instability and the vertical

wind shear are greater than zero and it is taken as zero when any one of these variables is less or

equal to zero. The variables are computed using the European Centre for Medium Range Weather

Forecasts (ECMWF) model data. Forecast of the genesis parameter up to seven days is also

generated on real time using the ECMWF model output. Higher value of the GPP over a region

indicates higher potential of genesis over the region. Region with GPP value equal or greater than

30 is found to be high potential zone for cyclogenesis. The analysis of the parameter and its

effectiveness during cyclonic disturbances in 2010 affirm its usefulness as a predictive signal (4-5

days in advance) for cyclogenesis over the north Indian Sea.

Key Words: Tropical cyclone, Genesis potential parameter, Vorticity, Moisture variable,

instability and vertical wind shear.

BOBTEX-2011


Track Prediction of North Indian Ocean Tropical Cyclones using ARW model

Krishna K. Osuri1*

, U. C. Mohanty1, A. Routray

2 and M. Mohapatra

3

1C A S, I I T, Hauz Khas, New Delhi – 110016

2 NCMRWF, Noida-201307

3 India Meteorological Department, Lodi Road, New Delhi.

* [email protected]

A detailed evaluation of performance and systematic bias of Advanced Research Weather

Research and Forecasting (ARW) model in predicting the movement of tropical cyclones (TCs)

over the North Indian Ocean (NIO) is undertaken in the present study. There were 16 TCs formed

over the NIO during 2007–2010. These TCs are initialized at different times and have a total of 97

cases. Based on location of genesis, the TCs have been divided into the Arabian Sea (AS) and the

Bay of Bengal (BoB) cyclones. The BoB TCs have been further, divided into recurving, northward

moving, and westward moving TCs. In addition to usual forecast errors, systematic bias in zonal

and meridional direction, cross-track (CT) and along-track (AT) error components relative to

persistence track are also calculated to analyze the gain in skill of model forecast.

The overall skill of ARW model increases with forecast length in track prediction compared

to persistence track. The mean track error varies from 130 km to 350 km from 12 to 72 hour

forecast and the mean landfall position errors are 120, 90 and 52 km for 72, 48 and 24 hour forecast

for the NIO cyclone. The mean time errors (standard deviation) are -7 (15), -3 (13) and -5 (6) hours

for 72, 48 and 24 hour forecast. The mean initial vortex position errors are 78, 71, 68 and 88 km for

northeast/east recurving, northward moving, westward moving systems of the BoB and AS systems

respectively. ARW model exhibits negative skill for short-term (12 hour) forecast for all categories

of systems. The model has a tendency to over-predict east-ward movement of the TCs over the

NIO. ARW forecasts are in general slower as compared to actual speed of the systems and hence

behind to the observed position for all the forecast lengths. As a result, model yields delayed

landfall. Further, as the mean CT errors are less compared to AT errors i.e., ARW model errors are

elliptical in nature with its major axis along the track. As the CT error components are smaller, the

landfall position error is comparatively smaller. Further analysis indicates that the model shows

better performance for post-monsoon cyclones. The track prediction of severe cyclones is better as

compared to weak cyclones over the NIO.

Key words: North Indian Ocean, Landfalling tropical cyclones, Track errors, ARW model

BOBTEX-2011


On the Implementation and the ability of the Ensemble Prediction System for tropical

cyclone track and strike probability for North Indian Ocean

K. Naga Ratna

India Meteorological Department, Lodi Road, New Delhi -110 003.


Implementation of Ensemble Prediction System (EPS) over North Indian Ocean and the

ability to predict the probability that a tropical cyclone will fall within a certain area is evaluated.

The software provided by the TIGGE, has been generalised and implemented for North Indian

Ocean (NIO) to produce Ensemble and Deterministic forecasts for the tropical cyclones and also

Strike Probability along the Indian coast and neighbouring countries.

Ensemble forecasts issued by the European Centre for Medium-Range Weather Forecasts

(ECMWF), National Center for Environmental Prediction (NCEP) and the Met Office (UKMET)

were evaluated for the cyclones JAL, LAILA, PHET and GIRI that formed during 2010, over North

Indian Ocean. The ECMWF model with horizontal resolution of 45km and vertical resolution of

62 levels produces forecast data twice a day for 50 member ensembles; while the UKMO model

having horizontal resolution of 90km and 38 vertical levels has data frequency 2 times a day for 24

member ensembles; NCEP model discretized with resolution of approximately 90km in horizontal

and 28 levels in vertical sends data four times daily for 20 members are available. In the North

Indian Ocean, the ensemble mean of ECMWF, UKMO, NCEP and ECMWF+UKMO+NCEP

(ALL) tracks and intensity are comparable in skill. It is revealed that the strike probability circles

of the ECMWF ensemble could capture the best track with a skill of 70% for 24-48 hours forecasts

and were over dispersive beyond 48hours. UKMET ensemble yielded improvements in the short

range. NCEP ensemble forecasts revealed that the tracks forecasts are better in the short range, the

tracks are found to be deviated more after 48 hours. Further evaluations were done for the track

forecasts and intensity forecasts for all the three model ensembles. The ability has been evaluated

interms of track and intensity for the ensemble means of the three models and for all 10 member, 20

member and 30 member means. The evaluation the EPS thus done will be presented.

BOBTEX-2011


Ocean Atmospheric Coupled Model to Estimate Energy and Path of Cyclone

near the Coast

Ramkrishna Datta

Regional Meteorological Centre,

Alipore, Kolkata


The tropical atmospheric phenomena like Cyclone, Typhoon, Hurricane etc. cause a violent

massive disturbance . The ‘EYE’ region of such phenomena can be regarded on the basis of

abstract idea of fluid dynamics . The said EYE can be imagined as the combination of fluid

dynamical sourceof strength +m and fluid dynamical sink of strength –m at a small distance apart.

. So the EYE can be assumed to constitute a fluid dynamical two dimensional doublet of finite

strength µ. This is here the object doublet. Now the seashore can be regarded as the real line x in

the two dimensional complex plane where as y is the imaginary axis lying on the sea

perpendicular to x . It is assumed that there are no flows of fluid across the real line x (seashore ).

Then the said object doublet can be placed on the sea at a perpendicular distance a from the real

line x in the complex plain (z=x+iy) making an angle 180 degree with the real axis x. Therefore the

image doublet will be at just opposite side of the real line x .

Here the fluid can be regarded as non viscous, incompressible fluid and it is moving with certain

velocity U at infinity in the direction of x axis. The motion of the fluid is wholly two dimensional

in the complex plane z . Now the complex potential w on the whole system which consists of

object doublet, image doublet and the stream velocity U parallel to x axis is given by

w = + - Uz (1)

or � � = q = � U + � (2)

To determine the pressure at any point on the wall we use the Bernoulli’s equation

+ q² = C (constant) (3)

We get

+ m

Y-a

xis

Seashore as the axis of X

+ m

- m

- m

a

U

BOBTEX-2011


= using P = π, q = U when z = ∞

For any point on the sea shore z = x

= (2µ (a²-x²) + U(a²+x²)² ) (4)

=0 gives x=0 , ±a√3

We see that When x= ±a√3

> 0 if µ > 4a²U (5)

And < 0 if µ < 4a²U (6)

Equations (5)and (6) describe analytically the strength of the tropical systems.

If µ > 4a²U . Pressure minimum at x= ±a√3 on the sea shore. Such system coupled with sea

shore minima strike the shore vigorously. This explain Orissa super cyclone 1999.

If µ < 4a²U we get sea shore maximum at x= ±a√3 . Such system coupled with zonal stream

moves towards right in the Bay of Bengal and gulf of Mexico. Eventually which explain

analytically that the cyclones of the Bay of Bengal are stronger than that of at Atlantic ocean. The

same observation had been written by Sir John Eliot, the first director general of observatory of

India Meteorological Department in 1889.

Key words :- Fluid dynamical Source, Sink, Object doublet, image doublet and complex potential.

BOBTEX-2011


Track, Intensity and few Dynamical Aspects of ‘Aila’ as Simulated by Operational NWP

Model of the IAF

Wg Cdr TP Srivastava1 and Wg Cdr Anil Devrani

2

1Met Faculty, Air Force Administrative College, Red Fields, Coimbatore.

2Air Force Centre For Numerical Weather Prediction, Subroto Park, New Delhi.

[email protected]

1. Introduction Operational NWP Model of the IAF uses ARW core of WRF (Version 3.1.1) in a two way

nested configuration at resolutions of 18 and 6 km as per the domains and schemes shown in Fig.1.

Initial and boundary conditions of 0000 UTC and 1200 UTC from NCEP GFS are used for model

integration of 75 hours. The products of these two operational runs are made available to the field

forecasters daily by 1600h and 0400h.

2. History of ‘AILA’ Under the influence of an upper air cyclonic circulation, a low pressure area formed over

the southeast Bay of Bengal on 22nd May morning. It subsequently concentrated into a depression

and lay centered at 1130 hours IST of 23 May 09 near 16.5º N/88.0º E about 600 km south of Sagar

Island. The depression moved northwards, intensified into a deep depression and lay centred at

0830 hours IST of 24 May 09 near 18.0ºN/ 88.5ºE. It further intensified into a cyclonic storm

‘AILA’ at 1730 hours IST of 24th May and lay centred near 18.5ºN/ 88.5ºE. It continued to move

northwards and intensified into a severe cyclonic storm at 1130 hours IST of 25 May 09 and lay

centred over northwest Bay of Bengal near 21.5ºN / 88.0ºE close to Sagar Island. The system

crossed West Bengal coast close to the east of Sagar Island between 1330 to 1430 hours IST as a

severe cyclonic storm with wind speed of 100 to 110 kmph. The lowest estimated central pressure

was about 967 hPa at the time of landfall. After the landfall, the system continued to move in a

northerly direction, gradually weakened into a cyclonic storm and lay centred at 2030 hours IST of

25 May 09 over Gangetic West Bengal, close to Kolkata. It continued its northerly movement,

weakened into a deep depression and lay centred at 0830 hours IST of 26 May 09 over Sub-

Himalayan west Bengal & Sikkim, close to Malda. It weakened into a depression and lay centred at

1130 hours IST of 26 May 09 over the same region close to Bagdogra. By 1430 hours IST of 26

May 09, it weakened further and was seen as a well marked low pressure area over Sub-Himalayan

West Bengal and became less marked by 27 May 09.

3. Prediction by IAF Model To understand the efficacy of the IAF model towards enhancing advance warning of the

impending adverse weather, track, intensity, few dynamical products, 3 hourly rainfall pattern and

composite radar reflectivity generated in the finer nested domain of 6km by using the 0000UTC

initial conditions of 23 May 09 (D-2) and 24 May 09 (D-1), valid for the period from 24 May 09 /

0600 UTC to 26 May 09 / 0600 UTC, have been discussed in the study.

(a) Predicted Track and Intensity of ‘AILA’. Formation and intensification of the system

was captured reasonably well on D-2. As shown in the Fig.2 (a&b), a general northerly track

was predicted by the initial conditions of D-2 and D-1. Deviations in prediction from the

observed track were more from the initial conditions of D-2 than that of D-1. Landfall was

predicted 187km East at three hours later in comparison to the actual location and time on D-2.

D-1 had relatively better prediction as the error reduced to nil though the landfall time was three

hours early. The isobaric patterns confirmed well with the actual pattern throughout the

predicted period but the forecast values of central pressure were 18 – 20 hPa higher, more so

when the system intensified into a severe cyclonic storm.

BOBTEX-2011


(b) Vorticity at 850 hPa and Divergence at 200 hPa. After the onset of South West Monsoon

over Andaman Sea and adjoining south Bay of Bengal by 20th May 2009, increase in the

southerly surge resulted in increase in relative vorticity over the South East Bay of Bengal. It

led to the formation of a low pressure area over the region on 22 May 09. Due to presence of

high magnitude of the low level relative vorticity that was commensurate with the values of

upper level divergence around the centre of the system, intensification of the system continued.

By 1730 hours IST of 24th May it intensified into a cyclonic storm ‘AILA’ and lay centred at

18.50oN / 88.50

oE. Juxtaposition of higher values of low level convergence and upper level

divergence maintained the strength of the system before it started weakening after 0000 UTC of

26 May 09. The predictions of Vorticity at 850 hPa and Divergence at 200 hPa on D-2 were

relatively lower as the model did not intensify the system into a severe cyclonic storm and it

weakened the system into a deep depression much before the predicted land fall. However,

these values were more realistically predicted by the model on D-1.

(c) Vertical Velocity at 500 hPa. Low level convergence if overlaid by upper level divergence

will lead to higher positive values of upward vertical velocity at the level of no-divergence

(LND). Over the Indian region 500hPa is the representative of the LND. Higher positive values

of the vertical velocity at 500hPa predicted by the model, match well with the convective cloud

patterns as shown by the imageries of Kalpana-I, of similar times.

(d) Moisture Convergence at 850 hPa. Moisture advection is horizontal transport of moisture,

which plays a very important role in the development of precipitation. If little moisture is

available, it is unlikely that precipitation will occur. However, if any system is supplied with an

abundance of moisture, there is an increased likelihood that heavy precipitation will be realized.

The maximum moisture convergence as predicted on D-2 and D-1 match well with the areas of

precipitation. Three hourly rainfall patterns as shown by the TRMM 3B42 V6 match well with

the areas of high magnitude of moisture convergence. This rich moisture supply was enough for

showers and thunderstorms to develop as indicated by the radar echoes of Kolkata DWR of

similar times. It is to be noted that the precipitation was located in the region where the

strongest moisture convergence was predicted.

(e) Total Cloud Cover. This product is still in experimental mode. Modifications have been

done for the display of predicted clouds by suppressing or enhancing the values of low, medium

and high clouds to get the best possible realistic picture by comparing it with the Kalpana – I

image of the same time, in the hind cast mode. To make the product more meaningful 6 hourly

predicted rainfall patterns has been superimposed over the predicted total cloud cover. In the

case discussed here, this product matched well with the corresponding actual Kalpana-I IR

images of the similar times. Vertical Velocity at 500hPa, Moisture Convergence at 850hPa,

Total Cloud Cover with 6hourly precipitation predicted for 25 May 09 / 0600 UTC along with

IR imagery of Kalpana-I and 6 hourly rainfall given by TRMM 3B46 V6 valid for 25 May 09 /

0600UTC are shown in Fig. 3(a–h).

(f) Hourly Rainfall Pattern. TRMM 3B42V6 products were used for qualitative validation of

the model predicted rainfall. The three hourly pattern of rainfall predicted by the model on D-2

and D-1 matched reasonably well with the satellite derived rainfall patterns shown by TRMM

product. The model over-predicted the rainfall to a certain degree in comparison to the rainfall

shown by TRMM 3B42V6. A snapshot of comparison of 3 hourly rainfall at 0600UTC on 25

May 09 are shown in Fig. 4(a-c)

(g) Maximum Radar Reflectivity. Maximum Radar Reflectivity was also simulated

reasonably well. The predicted patterns of D-2 and D-1 matched well with the actual Maximum

Reflectivity shown by the DWR of Kolkata. Comparison of this product was done both with

BOBTEX-2011


and without cumulus parameterisation scheme in the nested domain of 6km. It was seen that the

patterns produced without employing cumulus parameterisation scheme were more realistic.

The same is shown for 0600 UTC on 25 May 09 in Fig. 5(a-e).

4. Conclusion Predictions pertaining to track, intensity and rainfall etc. of ’AILA’ from the finer domain

of 6 km of the Operational NWP Model of the IAF had provided sufficient warning time to the

users in the affected areas. The forecasts of D-1 were relatively better and more realistic in

comparison to the one generated on D-2, with advance warning of more than 20hours and 40hours

for its landfall, respectively. As demonstrated by the model generated patterns of maximum radar

reflectivity, cumulus parameterisation in the finer domain of 6km can be avoided to improve the

forecast and economise the computational cost.

Fig.1:IAF Model : WRF Version 3.1.1 (ARW)

Resolution : 18 Km, 6 Km (Double Nested) Physics

Options : Thompson, Thompson Cumulus Schemes :

Grell, Grell PBL : MYJ TKE, YSU

Fig.2(a): Track & Intensity : Initial Condition of

23 May 09/0000UTC

Fig2(b): Track & Intensity : Initial

Condition of 24 May 09/0000UTC

BOBTEX-2011


PREDICTIONS BASED ON INITIAL CONDITIONS OF 23 MAY 09 / 00Z

Fig.3(a):Vertical

Velocity at 500hPa

valid for 25 May

09 / 0600UTC:

Fig.3(b):Moisture

Convergence at 850 hPa

valid for 25 May 09 /

0600UTC:

Fig.3(c):Total Cloud

Cover & 6hrly Pptn


0600UTC:

Fig.3(d): TRMM 3B42V6

6h Rainfall for

0600Z / 25May09

PREDICTIONS BASED ON INITIAL CONDITIONS OF 24 MAY 09 / 00Z

Fig.3(e):Vertical

Velocity at 500hPa

valid for 25 May

09 / 0600UTC:

Fig.3(f):Moisture

Convergence at 850 hPa


0600UTC:

Fig.3(g):Total Cloud

Cover & 6hrly Pptn


0600UTC:

Fig.3(h):Kalpana-I, IR

Image valid at 25 May 09 /

0600UTC:

Fig.4(a): TRMM 3B42V6 3h Rainfall

for 0600Z / 25May09

BOBTEX-2011


Fig.4(b): Model Predicted 3h Rainfall

0600Z / 25May09

IC:23May09 / 0000UTC

Fig.4(c): Model Predicted 3h Rainfall

0600Z / 25May09


Fig.5(a): Max Reflectivity by Kolkata

DWR at

0614Z / 25May09

Fig.5(b): Model Predicted

Max Reflectivity 0600Z /

25May09

IC:23May09 / 0000UTC (with

CP)

Fig.5(c): Model Predicted


25May09


(with CP)

BOBTEX-2011


Fig.5(d): Model Predicted

Max

Reflectivity 0600Z /

25May09


(without CP)

Fig.5(e): Model Predicted


25May09


(without CP)

BOBTEX-2011


Analysis of Barotrophic Energetics of Tropical Cyclone Khai-muk

S.Balachandran


Regional Meteorological Centre, Chennai

email ID: [email protected]

Tropical cyclones (TC) are intense atmospheric vortices characterized by extreme winds,

torrential rain, and destructive storm surges. When a major hurricane makes landfall one or more of

these processes can cause immense property damage and loss of life. Considerable progress has

been made in recent decades unlocking the physical and dynamical mechanisms by which

hurricanes form, and by which they change their structure and intensity. Climatologically, about

80% of all the tropical cyclones on the globe form near or within the ITCZ . This motivates

searching for mechanisms that favor tropical cyclogenesis within the context of ITCZ dynamics.

Studying dynamical mechanisms of perturbation growth in tropical cyclones is important from a

perspective of designing ensemble prediction system and adaptive observations for tropical

cyclones. It is widely accepted that sea surface temperatures (SSTs) and vertical shear are primary

factors controlling the genesis and development of tropical cyclones (TCs).

In the present study, the barotrophic energy conversion processes associated with TC Khai-

muk which formed over the North Indian Ocean and affected the eastern coastal region of southern

peninsular India during 13-16 November 2008 are studied.The special feature of this TC was that it

did not retain its TC intensity for even a day. It intensified into a Cyclonic Storm (CS) at 12 UTC

of 14th

but weakened into Deep Depression (DD) by 15th

/06 UTC over the sea itself and crossed

coast as a DD. The analysis of the instability of the background flow along with change of eddy

kinetic energy and barotropic conversion are presented during life cycle of TC Khai-muk are

presented. .

BOBTEX-2011


Performance evaluation of spectrum of cyclones over North Indian Ocean

using RAMS model

Ancy Thomas, Basanta kumar Samala and Akshara Kaginalkar

*Centre for Development of Advanced Computing,

Pune Unversity Campus, Pune - 411007, India

In the present study, the performance of non-hydrostatic Regional Atmospheric Model

(RAMS) model in simulating the tropical cyclones of different intensities, formed during pre and

post monsoon are analyzed. The cyclones Orissa, Sidr, Mala, h04B, 01A, and Agni occured over

North Indian Ocean are studied. This study reveals the ability of model in down-scaling the

cyclone track simulation, cyclone intensity in terms of lowest sea level pressure, winds at 850 hpa

and 200 hpa and thermodynamical features associated with the development of cyclones such as

vertical wind shear, mid tropospheric humidity and sea surface temperature. It is found that the

model could simulate the track of all cyclones reasonably well except for h04B. The track error

increases with the simulation time. The model overestimates the lowest mean sea level pressure in

comparison with observations. Model is able to represent the low level circulation and upper air

divergence of wind during all the cyclone cases . The model simulations are in agreement with the

criteria of low vertical wind shear required for the cyclogenesis and relative humidity above 60% at

700 hpa and 500 hpa satisfies the condition of high moisture required for the deep convection

during the intensification of cyclones.

BOBTEX-2011


An observational and modeling study of the tropical cyclone Phet.

2Jagabandhu Panda*,

1R. K. Giri** and

1, 3Harvir Singh***

1Satellite Meteorology Division, India Meteorological Department, New Delhi, India

2School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore 3HCL Info-systems, National Centre for Medium Range Weather Forecasting (NCMRWF),

NOIDA, U. P., India

*[email protected], ** [email protected], ***[email protected]

The accuracy of numerical weather prediction (NWP) depends on the quality of forecast

model and initial conditions. In this study, recent and advanced Weather Research and Forecasting

(WRF) mesoscale modeling system (ARW core) is used with a combination of Yonsei University

PBL scheme, Dudhia short wave scheme, RRTM long wave scheme WSM 3-class microphysics

and unified Noah land-surface model in order to study the characteristic features of the tropical

cyclone PHET that occurred over the Arabian sea (in 2010) and affected the coastal areas of several

countries. A comprehensive sensitivity analysis is carried out with respect to various cumulus

convective parameterizations including Grell-Devenyi ensemble scheme, Kain-Fritsch scheme,

Betts-Miller-Janjic scheme and Grell-3D scheme for the prediction of track and intensity of the

cyclonic storm PHET. The initial and boundary conditions for the simulations are derived from

global operational analysis and forecast products of the National Center for Environmental

Prediction-Global Forecast System (NCEP-GFS) available at 1olon/lat resolution in these model

simulations. However, the model initial conditions are further modified using KALPANA-1

atmospheric motion vectors and OCEANSAT-2 surface winds through a three dimensional

variational technique within ARW modeling system (WRF-3DVAR). The simulated results of

extreme weather parameters including the rainfall, wind field, track and intensity of the cyclone are

critically analysed comparing with those observed/predicted by India Meteorological Department

(IMD), New Delhi. Further, the model simulated results are qualitatively examined alongside the

satellite observations from METEOSAT, MODIS and KALPANA-1 in order to understand the

model performance as when compared to the observations. Several parameters derived from

satellite observations are also analysed including outgoing long-wave radiation (OLR), quantitative

precipitation estimate (QPE; rainfall), sea surface temperature (SST), relative vorticity, upper

tropospheric humidity (UTH) and the track of the cyclone (figure shown below) in order to

understand the genesis of the storm. The observational analysis reveals relatively higher values of

SST (~26.5oC), relative vorticity and UTH (90-100%) during the life span of PHET. A higher

negative correlation (~ -0.96) between the OLR and QPE corresponds to the observed maximum

value of QPE when there is minimum OLR and the cyclone reaches its maximum intensity after a

day of attending this state. The model also simulated the extreme weather parameters reasonably

well and the performance is slightly improved further through the satellite data assimilation using

surface winds and atmospheric motion vectors.

BOBTEX-2011


Figure: Track of cyclone PHET

BOBTEX-2011


Large-Scale Characteristics of Rapidly Intensifying Tropical Cyclones over the Bay of Bengal

and a Rapid Intensification (RI) Index

S. D. Kotal and S. K. Roy Bhowmik

India Meteorological Department, NWP Division, New Delhi-110003


A rapid intensification index (RII) is developed for tropical cyclones over the Bay of

Bengal. The RII uses large-scale characteristics of tropical cyclones to estimate the probability of

rapid intensification (RI) over the subsequent 24-h. The RI is defined as an increase of intensity 30

kt (15.4 ms-1

) during 24-h, which represents approximately the 93rd percentile of 24-h intensity

changes of tropical cyclones that developed over the Bay of Bengal during 1981-2010. It is found

that 32% of all very severe cyclonic storms (VSCS) and all super cyclonic storms (SUCS)

underwent RI phase at least once during their lifetime. No cyclonic storm (CS) and severe cyclonic

storm (SCS) underwent RI phase. Various large-scale variables associated with the RI cases are

compared to those of non-RI cases. These comparisons show that the RI cases generally occur at

higher latitude and are intensifying at a faster rate during the previous 12-h than the non-RI cases.

The statistical analysis also shows that the RI cases are embedded in regions where the upper-level

divergence, lower-level relative vorticity and relative humidity are more and vertical winds shear is

weak. Finally, the initial wind speed of RI cases is higher and tends to move with a faster

translational speed than the non-RI cases. The RII technique is developed by combining threshold

(index) values of the eight variables for which statistically significant differences are found between

the RI and non-RI cases. The probability of RI is found to be increases from 0% to 100% when the

total number of indices satisfied increases from zero to eight.

Key words: Tropical cyclone, Rapid intensification, Probability, Vorticity, Divergence, Vertical

wind shear, Bay of Bengal.

BOBTEX-2011


Development of the Lagrangian Advection model for prediction of tropical cyclone track over

the Indian Ocean

Sanjeev Kumar Singh, C. M. Kishtawal, Neeru Jaiswal, and P. K. Pal




A new model has been developed for track prediction of Indian Ocean cyclones. The Model

utilizes environmental steering flow using the forecasts from a high resolution global model and the

effect due to earth’s rotation (the Beta-effect) to determine the future movement of cyclone. The

model is based on the dynamical frame work and the time for running is very less. A new approach

based on vertical profile of potential vorticity (PV) is used to determine the weights for different

vertical levels for computation of mean steering flow. The effect of environmental flow over the

cyclone track is also examined by removing the existing cyclonic feature from the mean wind

fields. For this, a new approach based on vortex pattern matching has been used to identify the

cyclone vortex and to remove it from mean wind fields.

The data used in the present work for the computation of cyclone trajectories are the high

resolution 0.5°×0.5° forecasted atmospheric wind fields and temperature from Global Forecast

System (GFS), which is the global NWP computer model run by NOAA. The wind fields and

temperature are taken for the North Indian Ocean domain at every 6-hour interval of 26 pressure

levels (10 mb-1000 mb) for 0 to 72 hours forecast. The Joint Typhoon Warning Center (JTWC)

best track analysis data has been used for defining the initial position of cyclonic vortex.

The present Lagrangian Advection model has been used to forecast the 6-hourly track of six

tropical cyclones (viz., Nargis, Khai-Muk, Aila, Phyan, Laila and Jal) which were formed in the

North Indian basin during the period 2008 to 2010. The maximum PV based approach has been

used for determining the optimal steering levels which is adapted from the study by Hoover and

Morgan (2006). The important step in this model is to form a synthetic cyclone (Jaiswal and

Kishtawal, 2011) which was used to remove the cyclonic features from the environmental flow.

The forecast errors for all the cyclone cases have been computed with respect to JTWC analysis

best track.

To limit the size of the presentation, the forecasted tracks of one of the above cyclones,

“Nargis”, are shown in Fig.1 (a-f) respectively. The predicted mean track errors of the Lagrangian

Advection model w.r.t. JTWC analysis best track for six cyclones for 12-72 hours are shown in

Fig.2.

References: Hoover, B.T. and Morgan, M.C. (2006) Effects of cumulus parameterization on tropical cyclone

potential vorticity structure and steering flow. Preprints of the 27th AMS Conference on

Hurricanes and Tropical Meteorology, April 23-28, 2006. Monterey, CA, paper 8B.5.

Jaiswal, Neeru and Kishtawal, C.M. (2011) Prediction of tropical cyclogenesis using scatterometer

data. TGRS, 2153862.

BOBTEX-2011


Fig.2: Mean track error of the all six cyclones

Fig.1: Six forecasts ((a) 72 hours prediction from 28-Apr-00Z, (b) 72 hours prediction from 29-Apr-00Z, (c) 72 hours

prediction from 30-Apr-00Z, (d) 60 hours prediction from 01-May-00Z, (e) 36 hours prediction from 02-May-00Z

and (f) 12 hours prediction from 03-May-00Z) generated for NARGIS Cyclone by the Lagrangian Advection model.

a: 72-H Forecast from 28-Apr-00Z b: 72-H Forecast from 29-Apr-00Z c: 72-H Forecast from 30-Apr-00Z

e: 36-H Forecast from 02-May-00Z

d: 60-H Forecast from 01-May-00Z f: 12-H Forecast from 03-May-00Z

BOBTEX-2011


Extended Range Forecast of Tropical Cyclone Genesis Based on Coupled Model Outputs

D. R. Pattanaik*, M. Mohapatra, Y. V. Rama Rao and Ajit Tyagi

India Meteorological Department, New Delhi

Email-* [email protected]/[email protected]

Over the North Indian Ocean the months of October-November are known to produce

cyclones of severe intensity in the Bay of Bengal, which cause damages to life and property over

many countries surrounding the Bay of Bengal. The strong winds, heavy rains and large storm

surges associated with tropical cyclones are the factors that eventually lead to loss of life and

property. Rains (sometimes even more than 30 cm/24 hrs) associated with cyclones are another

source of damage.

There are two cyclones formed during the post monsoon season of 2010 (Fig. 1). The first

one “Giri” initially seen as a low pressure area on 19th October over the east central Bay of Bengal

and neighbourhood, intensified into a tropical cyclone at 0600 UTC of 21st and became a very

severe cyclonic storm (VSCS) at 0300 UTC of 22nd, which crossed the Myanmar coast on 22nd.

The second cyclonic storm of the season “Jal” formed in the Bay of Bengal was first observed as a

low pressure area over the south Andaman Sea and neighbourhood on 2nd November, which

intensified into severe cyclonic storm (SCS) at 2100 UTC of 5th. It crossed north Tamil Nadu-

south Andhra Pradesh coasts, close to north of Chennai between 1700 & 1800 hrs UTC of 7th

November and caused lot of damage in Tamilnadu and south Andhra Pradesh coast associated with

not only strong wind but also due to heavy rainfall associated with the cyclone.

With the improvement in numerical model and use of wide ranges of non conventional data

in the assimilation system of the model there has been considerable improvement in the forecast

skill of tropical cyclones particularly in the short range up to 72 hr. However, the forecasting of

genesis of tropical cyclone and associated rainfall in the extended range time scale (about 10 days

to 2 weeks in advance) is very useful in many respects. In the present study an attempt is made to

forecast the genesis of tropical cyclone and also the associated rainfall activity in the extended

range time scale over the north Indian Ocean for the cyclones “Giri” and “Jal” using the multi-

model ensemble techniques.

The multi-model extended range forecasts are prepared based on the coupled model outputs

from ECMWF and NECP. The outputs from these two models are used and the multi-model

ensemble forecasts are generated on every Friday with forecast anomaly for week 1 (Monday to

Sunday) and week 2 (subsequent Monday to Sunday). The low level relative vorticity, low level

convergence, wind shear and the rainfall forecasts are analysed to consider the genesis of tropical

cyclones. The operational forecast for days 05-11 of weekly mean wind from NCEP CFS and

ECMWF coupled models based on 14th

Oct, 2010 initial condition (Figs. 2a & 2b) indicates

cyclonic circulation at low level over the central Bay of Bengal during the period from 18-24

October associated with the severe cyclone “Giri”. The centre of cyclonic circulation in case of

CFS forecast is (Fig. 2a) closer to observed location of the system when compared with the

ECMWF forecast (Fig. 2b). The genesis of the cyclone “Jal” was very much captured in both the

coupled models even in the forecast valid for 12-18 days based on the initial condition of 21

October, 2010 as indicated by cyclonic circulation over the Tamil Nadu coast during 01-07

November (Fig. 3a & 3b). The MME forecast valid for 01-07 November based on 28 Oct and 21

Oct initial conditions (with forecast period of days 05-11 and days 12-18 respectively) also clearly

indicated large positive rainfall anomalies over the Tamil Nadu coast and adjoining coastal Andhra

Pradesh region (Fig. 3c & 3d) like that of observed rainfall anomalies.

Thus, the extended range forecast indicates very well the genesis and also the associated

BOBTEX-2011


rainfall distribution due to the tropical cyclones of post monsoon season of 2010. The other

dynamical parameters like the low-level vorticity, wind shear, humidity etc are also analysed in the

model forecast fields to understand the genesis of both the severe cyclones “Giri” and “Jal”.

.

Fig. 1 : Cyclonic disturbances of post monsoon season from October-December, 2010. The

dark black lines indicate two severe cyclones “Jal” and “Giri”.

Fig. 2 : Forecast 850 hPa weekly mean wind during the cyclone “Giri” valid for days 05-11

(18-24 Oct 2010) based on initial condition 14 Oct. (a) based on NCEP CFS and (b)

based on ECMWF coupled models.

(a) NCEP CFS 850 hPa forecast mean wind (kts)

Day 12-18 based on 21 Oct, valid for 01-07 Nov 2010

(b) ECMWF 850 hPa forecast mean wind (kts)

Day 12-18 based on 21 Oct, valid for 01-07 Nov 2010

(b) ECMWF 850 hPa forecast mean wind (kts)

Day 05-11 based on 14 Oct, valid for 18-24 Oct 2010

(a) NCEP CFS 850 hPa forecast mean wind (kts)

Day 05-11 based on 14 Oct, valid for 18-24 Oct 2010

BOBTEX-2011


Fig. 3 : Forecast 850 hPa weekly mean wind during the cyclone “Jal” valid for days 12-18

(01-07 Nov 2010) based on initial condition 28 Oct from (a) based on NCEP CFS and

(b) based on ECMWF coupled models. The corresponding MME forecast rainfall

anomalies valid for 01-07 Nov, based on (c) 28 Oct and (d) based on 21 Oct initial

conditions.

(c) MME forecast rainfall anomaly (mm/day)

Valid for days 05-11 (01-07 Nov, 2011), IC=28 Oct

(d) MME forecast rainfall anomaly (mm/day)

Valid for days 12-18 (01-07 Nov, 2011), IC=21 Oct

BOBTEX-2011


Impact of Resolution and Data Assimilation on the prediction of the cyclone “JAL” over Bay

of Bengal using WRF(NMM) and grid point statistical interpolation scheme.

K. Naga Ratna


Lodi Road, New Delhi – 110 003.


In this study, performance of WRF (NMM) model and the regional Grid-point Statistical

Interpolation(GSI) data assimilation scheme used to simulate the cyclone “JAL” that formed over

Bay of Bengal during postmonsoon season 2010, has been evaluated. A severe cyclonic storm,

JAL (4-8 November 2010) developed over the Bay of Bengal from the remnants of a depression

which moved from northwest Pacific Ocean to the Bay of Bengal across southern Thailand. It

moved westnorthwestwards and intensified upto severe cyclonic storm on 6 November. However

as the severe cyclonic storm, JAL moved to the southwest Bay of Bengal closer to India coast and

weakened gradually into a deep depression and crossed north Tamilnadu – south Andhra Pradesh

coast on 7 November.

WRF(NMM) version 3.2 model was integrated with regional GSI data assimilation scheme

for 72 hours from 4 -7 November 2010 at 9km and 3km horizontal resolutions and 38 levels in

vertical. The model could capture the direction of the movement and the landfall of JAL cyclone

which was predicted 48 hours before real-time with landfall forecast error of 56km and time error

of 2 hours delay. The impact of the conventional datasets, as AWS along the east coast, Ship data

of SagarKanya data during its cruise over the Bay of Bengal for the cyclone period, SagarPurvi and

SagarPaschimi stationed near the coast have been assimilated. The impact of the datasets for the

simulations of the cyclone JAL and performance of the model has been evaluated. The cyclone

track and intensity were evaluated for both the horizontal resolutions 9km and 3km. The track

performance with 9km yielded improvement with optimized track error of 50km during 24 to 48

hour period. The intensity of the cyclone as simulated with the 3km resolution model is more

compared to the 9km resolution. Performance parameters thus computed for the validation exercise

are (a) Direct Position Errors (b) Zonal (latitudinal biases DY) (c) Meridional biases (longitudinal

biases DX) and evaluated against the CLIPER model.

In Extension to above study, Hurricane Weather Research Forecast Model (HWRF) adapted

from NCEP, USA has been implemented at India Meteorological Department, New Delhi. WRF

(NMM) being the base of the HWRF model, has the similar data assimilation, regional data

assimilation system. The data assimilated in WRF (NMM) and regional GSI system for the

cyclone JAL has been used on experimental basis for case study in data assimilation with HWRF

model. The experiments done for the cyclone JAL with data assimilation using HWRF model are

compared with above WRF (NMM) model results.

BOBTEX-2011


Study of Jal Cyclone Track Using WRF Cumulus Parameter Schemes

M. Venkatrami Reddy, S. Balaji Kumar, S. B. Surendra Prasad and K. Krishna Reddy

Semi-arid-zonal Atmospheric Research Centre (SARC)

Department of Physics, Yogi Vemana University, Kadapa, Andhra Pradesh

[email protected]

Tropical cyclones that form over the Bay of Bengal and Arabian Sea during pre-monsoon

(April-May), early monsoon (June), late and post monsoon (September-November) cause

vulnerable damage to lives and property over the coastal regions of India with strong winds,

heavy rain and tidal wave. Though the general behavior of the movement of the tropical cyclones

(TC) is known, it is desirable to have timely and reasonably accurate prediction of the tracks and

their intensities. The numerical models based on fundamental dynamics and well-defined physical

processes provide a useful tool for understanding and predicting tropical Cyclones. For accurate

forecast of TC, it is essential that numerical models must incorporate realistic representation of

important physical and dynamical processes as they play crucial role in determining genesis,

intensification and movement. In the present study, numerical simulation experiments on severe

cyclone "JAL" is formed. For “JAL” track prediction, a fully compressible, non-hydrostatic

Advanced Research Weather Research and Forecasting (ARW-WRF) model with Arakawa C-grid

is used. The advanced research WRF model was run at grid spacing of 27 km, 9 km and 3 km. The

cyclone track study is done with National Center for environmental prediction (NCEP), final

analysis fields (NCEP FNL) or the reanalysis data with 1.0 x 1.0 degree grid resolution used as

initial and lateral boundary conditions for the WRF model. In the JAL cyclone track prediction,

WRF modeling was performed by changing cumulus schemes such as Kain Fritsch (KF), Betts-

Miller-Janjic (BMJ), Grell-Devenyi (GD) and New Grell (NG) without changing microphysical

properties, PBL, and Radiation Schemes. The track observed with Kain Fritsch (KF) scheme is

well compared temporally and spatially with Indian Meteorological Department(IMD) observed

track and the remaining Betts-Miller-Janjic (BMJ), Grell-Devenyi (GD) and New Grell (NG)

schemes too suitable with IMD observed track only spatially. The cyclone centre pressure,

maximum cyclone surface wind speed obtained from the model are well compared with the IMD

data. The variation of pressure, temperature and humidity parameters from the Automatic Weather

Station at Yogi Vemana University, kadapa (14.47°N; 78.82°E), a semi arid region of India, during

the cyclone landfall was analyzed and compared with the modeled parameters. The results are in

reasonable in good agreement.

BOBTEX-2011


Impact of data assimilation system for simulation of tropical cyclones over Bay of Bengal with

WRF-NMM modeling system

Sujata Pattanayak and U C Mohanty

Centre for Atmospheric Sciences,

Indian Institute of Technology, Delhi

Hauz Khas, New Delhi-110016

In recent years the need for higher quality and more versatile data assimilation techniques

has becomes widely accepted. Additional demands on data assimilation techniques have resulted

due to several different reasons. First, the increased density, frequency and quality of data network

with increased observing systems (land as well as remote sensing platforms) needs the

improvement in data assimilation systems. Second, the quality and quantity of numerical weather

prediction (NWP) models necessitate appropriate and more realistic representation of initial state of

the atmosphere using better data assimilation techniques.

The study represents the impact of observational datasets for simulation of tropical cyclones

over Bay of Bengal with Non-hydrostatic Mesoscale Model (NMM) core of Weather Research and

Forecasting (WRF) system. Though WRF 3-dimensional variational data assimilation system

(WRF-Var) provides improved initial conditions to Advanced Research WRF (ARW), a unified

WRF-Var utility has been developed to be used by the WRF-NMM core, as well. The upgraded

code has been successfully tested and implemented to simulate three recent very severe cyclonic

storms i.e. the pre-monsoon cyclones Nargis (27 April to 03 May, 2008) & Aila (23 to 26 May,

2009) and the post-monsoon cyclone Jal (04 to 07 November, 2010) developed over Bay of

Bengal. A total of 24 cases (8 different initial conditions for Nargis starting from 28April 2008; 7

different initial conditions for Aila starting from 22 May 2009; 9 different initial conditions for Jal

starting from 03 November 2010) at every 00 and 12 hr are selected for an enhanced assessment on

the performance of the WRF-NMM modeling system. For this purpose, two sets of numerical

experiments are carried out with the meso-scale model WRF-NMM. In the first experiment, i.e. in

the control simulation (CNTL), the model has been integrated up to 96 hours in a single domain

with the horizontal resolution of 9 km along with 51 levels up to a height of 30 km in the vertical

for all the cases. The initial and lateral boundary conditions to a limited area model are usually

provided from the large scale analysis and forecasts available at different NWP centers in the

world. The NCEP Global Forecast System (GFS) analyses and forecasts (1º x 1º horizontal

resolution) are used to provide the initial and lateral boundary conditions respectively.

Again, in order to improve the initial analysis fields for the model integration, an attempt

has been made to initialize WRF-NMM model with WRF-VAR system. Hence, in the second

experiment, i.e. in the data assimilation (DA), the impact of the observational data sets has been

investigated by incorporating the available conventional and non-conventional data sets over Indian

region. Hence, for all the above mentioned cases (Nargis, Aila and Jal), the model is integrated with

corresponding different initial conditions each, as described above with the improved initial

conditions through WRF-Var system.

The improvement in model integration is verified statistically and analytically. The vector

displacement errors (VDEs) in track forecast are calculated with respect to the observed track

provided by the India Meteorological Department (IMD). The mean improvements in VDEs of

33%, 15%, 10%, 14% and 15% are seen (Fig 1) at 00hr, 24hr, 48hr, 72hr and 96hr respectively in

track prediction with the DA experiments than the control simulations. Improvements in model

performance are also noticed in respect of the intensity prediction. The analysis on the

observational datasets such as (a) zonal wind (m/s), (b) meridional wind (m/s), (c) temperature (°K)

and (d) specific humidity (kg/kg) clearly indicate the improvement in model initial condition with

assimilation. In case of Nargis, the root mean square errors (RMSE) for different variables with and

BOBTEX-2011


without assimilation indicate the improvement of 50% with the assimilation technique. It may also

be noted that, the buoy and ship data does not show significant improvement like any other

datasets. It may be due to the scarcity in the data coverage and constrained to only surface data. In

case of Aila, RMSE reduces significantly (more than 300%) with AIREP (aircraft temperature and

winds) observations at the initial time. It may also be noticed that, the buoy and ship data

significantly improve the initial condition to the model integration. In case of Jal, significant

improvement is noticed in zonal and meridional wind components with AIREP and buoy datasets.

Further, the structure of the above mentioned cyclones has been investigated. For this purpose, few

diagnostics such as east-west cross section of horizontal wind (m/s), vertical velocity (m/s),

vorticity (x10-5

s-1

) and moisture convergence etc. representing the structure of the cyclones also

shows the improvement in DA experiments than that of control simulations.

Keywords: WRF-NMM, WRF-Var, Tropical cyclone, Track, Vector Displacement Error, Structure

0

50

100

150

200

250

300

350

400

00hr 12hr 24hr 36hr 48hr 60hr 72hr 84hr 96hr

CNTL

DA

Mean vector displacement errors (km)

Fig 1 Mean vector displacement errors from all the 24 cases with

both CNTL and DA experiments

Documents

BAY of Bengal Cyclones