Monsoon and its rainfall simulation in climate models - ioc

Monsoon and its rainfall simulation in climate models: a partial review

and some perspectivesLaurent Li ([email protected])

Laboratoire de Météorologie Dynamique (LMD)Institut Pierre-Simon Laplace (IPSL) CNRS/UPMC (Paris VI), Paris, France

Thanks to Dr. T Zhou (LASG/IAP/CAS) for providing useful materials

About LMD:

The LMD is jointly operated by the Ecole NormaleSupérieure , the University Pierre & Marie Curie , the Ecole Polytechnique and the Centre National de la Recherche Scientifique. LMD is implemented at three sites (one in Palaiseau, two in Paris). About 150 people work in LMD, including visiting scholars and Ph.D. students

About IPSL:

IPSL is a confederation of 6 Parisian laboratories (LATMOS, LISA, LMD, LOCEAN, LPMAA, LSCE) with a common scientific objective to study the earth’s environment. There are more than 700 people working in these laboratories of IPSL

MOMSEI summer school – VI, Phuket 2015-10

http://www.lmd.jussieu.fr/~li/Li_for_MOMSEI6_201510.pdf

mailto:[email protected]

Modèles de l'IPSL pour CMIP5:LMDZ-ORCHIDEE-ORCA-LIM-PISCES-INCA-REPROBUS-OASIS

1. Asian summer monsoon as observed2. Simulation of global monsoon in climate models3. Simulation of Asian summer monsoon in climate models4. Investigate regional climate over East China with LMDZ-regional5. Role of the Tibetan Plateau in Asian monsoon6. Perspectives

1. The Asian monsoon is a component of the global monsoonal system: observed mean-state and variability

Prof. Bin WANG (University of Hawaii), in a restaurant, with his team

The annual range (AR):The local summer-minus-winter precipitation. Here, summer means JJA in the NH and DJF in the SH. The global monsoon precipitation domain:Defined by the region in which the AR exceeds 180 mm and the local summer monsoon precipitation exceeds 35% of annual rainfall.

Annual range (a) and annual mean precipitation rate (b). The thick solid lines outline the global monsoon precipitation domain.

Wang and Ding (2006, GRL)

NH monsoon precipitation domain and annual reversal of the winds. Climatological mean JJA minus DJF rainfall (shading) and (A) 925-hPa winds, (B) 200-hPa winds, and (C) vertical wind shear (VWS, 850-hPa minus 200-hPa winds). The monsoon rainfall domain outlined by the green solid lines is defined by the local summer-minus-winter precipitation rate exceeding 2.0 mm/d and the local summer precipitation exceeding 55% of the annual total. The boxed areas in A–C indicate the regions where the 925 (200)-hPa zonal wind index and NHSM circulation (VWS) index are defined

Wang et al. 2012 PNAS

Courtesy Trenberth and Stepaniak (2004)

质量守恒令全球季风不同子系统的变化存在关联Mass conservation is a strong constraint in relating different components of the global monsoon system

(JJA – DJF) Latent heat release (P-E) and water-vapor transport

东亚夏季风是全球季风系统的组成部分

Asian Summer monsoon is part of the global monsoon system(JJA – DJF rainfall rate and 850 hPa wind)

Courtesy T. Zhou (IAP/LASG)

Southwest Vortex

Australian High

Typhoon

Marskerian High

Somali Jet

Forcing of Tibetan Plateau

DD

D

Cold air from mid-and high lat

Meiyu-Front

Southeast Trade Wind

Eastward MJO

Monsoon Trough

Convective Cloud-Cluster

Monsoon Low

NorthwesternPacificSubtropicalHigh

East Asian Summer Monsoon Systems

Schematic of boreal summer (June–September) and winter (December–February) atmospheric conditions in the South Asian monsoon region. Lower panels: orography (>1,000 m, shaded grey); SSTs (shaded yellow/orange); sea-level pressure (blue contours, interval 2 hPa) and lower tropospheric (850 hPa) winds. Upper panels: upper tropospheric (200 hPa) wind vectors and rainfall (shaded blue). The summer diagram shows a line (in red) bounding the northward extent of the monsoon Hadley-type circulation

Turner and Annamalai 2012, Nature Climate Change

The 20 year (1979-1999) climatology of precipitation (mm/d, shading), sea level pressure (hPa, solid line), and 850 hPa winds (m/s) in (a) JJA and (b) DJF using GPCP, ERA40, and HadSLP2. Dotted box indicates the East Asia domain for quantitative evaluations. The contour intervals of SLP are 3 hPa in JJA above 1009 hPa and 5 hPa in DJF.

Boo et al 2011, JGR

Moisture transport patterns averaged for 1990–1999 during (a) Pre-onset of the ASM (the 6th pentad of March-the 3rd pentad of May), and (b) Post-onset of theASM (the 5th pentad of May-the 2nd pentad of July).

Cheng et al. 2012; Ding 2004; Ding et al. 2004

Oceandisaster 7%

Meterorological

disasters71%

Earthquakedisaster 8%

Others 8% Biologicaldisaster 6%

Typhoon 4%Localstrong

convection8%

Low-temperatur

e andfrost

injury 7%

Flood 28%

Drought53%

Meteorological disasters occur frequently with great losses in China

Great influence and heavy losses in meteorological disasters

Drought and flood are the major contributors

0

1000

2000

30004000

5000

6000

7000

8000

1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010

Year

Deat

h to

ll（pe

rson

s)

Death toll

Averaged during 1990-2010

4044 deaths

0

1

2

3

4

5

6

7

8

9

10

0

1000

2000

3000

4000

5000

6000

1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010

Percentage of GDP(%)

Direct economic losses(100 million

RMB

)

年份

DEL by meteorological disasters

Percentage of GDP

2.37% 210.5 billion Yuan

Cheng et al 2010(Chinese Sci Bull)

Wanxiang Cave, China (33°19′ N, 105°00′ E)

EOF1 of normalized annual range anomalies (upper) and the corresponding PC of Annual Range Index (ARI) (lower).

There is an overall weakening of the global land monsoon precipitation in the last 56 years (1948-2003)


Time series of (a) the Northern Hemisphere-averaged June-July-August precipitation, (b) the Southern Hemisphere-averaged December-January-February precipitation, and (c) the global monsoon index(GMI), or the sum of a and b


Variation of the East Asian Summer Monsoon during the second half of the 20th century

East Asian Summer Monsoon has strong variabilities at interannual and decadal scales. Since the 1980s, the monsoon diminished in intensity, creating precipitation anomalies (above-normal in the south and below-normal in the north).

East Asian Summer Monsoon Index

Decadal variation of rainfall

Courtesy Dr. T. Zhou

Global Monsoon Domain

Global Monsoon Index

Weakening of EASM and its linkage to the global monsoon

EASM index

(Zhou et al. 2008, GRL; Zhou et al. 2009, Meteor. Z.)

Long-term variation of the African monsoon

Courtesy of M. Hoerling et al. (2006)

EASM index

Inter-basins water transfer projects: West / Middle /East

Detection and attribution of Monsoon variation?An uncertain issue !

Variability and trends of the NHSM system, and the Hadley and Walker circulation. Time series of boreal summer (MJJAS) mean indices representing (A) NHSM precipitation intensity (mm/d) averaged over the entire NH monsoon rainfall domain; (B) NHSM circulation intensity measured by the vertical shear of zonal wind (850 hPa minus 200 hPa) averaged over 0°–20°N, 120°W–120°E, (r=0.85); (C) Hadley circulation intensity measured by the maximum absolute value of the cross-equatorial, zonal mean meridional mass stream function(1010 kg·s−1); and (D) Walker circulation intensity measured by the low-level zonal winds at 850 hPa averaged over the equatorial Pacific (10°S–10°N,140°E–120°W). The red dashed lines in each panel denote the linear trends.


Climate anomalies associated with the NHSM circulation index. Regressed 2-m air temperature anomalies over land and SST anomalies over ocean (shading: °C), sea-level pressure anomalies (contours: Pa) and 850-hPa wind anomalies (vector) with respect to the NHSM circulation (VWS) index for the period of 1979–2010. Wind vectors are significant at 95% confidence level by the Student t test. The blue lines outline the eastern Pacific triangle and western Pacific K-shape regions where the mega-ENSO index is defined. The HadISST and ERAI reanalysis data were used


Normalized NHSM circulation index in relation to the mega-ENSO, AMO, and hemispheric thermal contrast (HTC). (A) normalized mega-ENSO index (r =

0.77). (B) (B) Normalized AMO index, (r =

0.44). (C) (C) Normalized HTC index

measured by the 2-m air temperature averaged over the NH (0–60°N) minus that over the SH (0–60°S), (r = 0.63).

The thick black lines in each panel denote 3-y running means of NHSM circulation index. The merged ERA-40 (1958–1978) and ERAI (1979–2011) reanalysis datasets were used.


2. Numerical simulation of the global monsoon

A physical knowledge more than a century old:

First direct application ?Lewis Fry Richardson (1922)

Henri Navier (1785-1836) George Gabriel Stokes (1819 – 1903) Navier-Stokes equations (1845):

L.F. Richardson’s view of numerical weather prediction (1920s) (painting: François Schuiten, 2000)

Numerical modelling

Physics of a GCM

Evolution of climate models(1990)

(1996)

(2001)

(2007)

Courtesy IPCC

Model Institute/Country Atmosphere Resolution (number of grids) Group

INM-CM3.0 2 INM/Russia 5.0°×4.0°L21 (3240) LOW

GISS-ER 2 GISS/USA 5.0°×4.0°L20 (3312) LOW

CGCM3.1(T47) 1,2 CCCma/Canada 3.75°×~3.75°L31 (4608) LOW

ECHO-G 2 MIUB/Germany 3.75°×~3.75°L19 (4608) LOW

IPSL-CM4 1,2 IPSL/France 3.75°×~2.5°L19 (6912) MED

FGOALS-g1.0 1 IAP/China 2.8125°×~3.0°L26 (7680) MED

CNRM-CM3 2 CNRM/France 2.8125°×~2.8125°L45(8192) MED

BCCR-BCM2.0 1 BCCR/Norway 2.8125°×~2.8125°L31(8192) MED

MIROC3.2(medres) 1,2 CCSR/Japan 2.8125°×~2.8125°L20(8192) MED

MRI-CGCM2.3.2 1,2 MRI/Japan 2.8125°×2.8125°L30 (8192) MED

GFDL-CM2.0 1,2 GFDL/USA 2.5°×2.0°L24 (12960) MED

GFDL-CM2.1 1,2 GFDL/USA 2.5°×~2.0°L24 (12960) MED

CSIRO-MK3.0 2 CSIRO/Australia 1.875°×~1.875°L18 (18432) HIGH

ECHAM5 1 MPI/Germany 1.875°×~1.875°L31(18432) HIGH

CCSM3 1 NCAR/USA 1.40625°×~1.40625°L26(32768) HIGH

MIROC3.2(hires) 1,2 CCSR/Japan 1.125°×~1.125°L56 (51200) HIGH

Used models (CMIP3 C20C simulations)

Kim et al. 2008 J. Climate

Climatological annual mean precipitation (mm day−1). PCCs (pattern correlation coefficients) between the observations and the group ensemble means are shown at the upper-right corner of each figure

Annual mean precipitation biases (mm day−1)

Kim et al., 2008 JCL

Climatological annual precipitation range (shading; mm day−1) and monsoon domains (contours).


Spatial pattern of the EOF1 mode of the normalized annual precipitation range over the observed global land monsoon domain and its corresponding principal component

Kim et al. 2008 J. Climate

Time series of the NHMI (mm day−1). Time series of the GOMI (mm day−1).


Primary Science Questions1. What are the relative contributions of internal processes and external forcing that are driving the 20th century historical evolution of global monsoons?2. To what extent and how does the atmopshere-ocean interaction contribute to the interannual variability and predictability?3. What are the effects of Eurasian orography, in particular the Himalaya/Tibetan Plateau, on the regional/global monsoons?4. How well can developing high-resolution models and improving model dynamics and physics help to reliably simulate monsoon precipitation and it variability and change?

Global Monsoons Modelling Intercomparison Project (GMMIP) for CMIP6http://www.lasg.ac.cn/gmmip/

Co-Chairs• Tianjun Zhou, Institute of Atmospheric Physics, CAS, China• Andy Turner, University of Reading, UK • James Kinter, COLA, George Mason University, USA

priority EXP name integration short description and purpose model type

Tier-1 AMIP20C 1870-2013 Extended AMIP run. Observed SST AGCM

Tier-2 HIST-IPO 1870-2013

Pacemaker 20th century historical run. Observational historical SST is restored in the tropical lobe of the IPO domain (20°S-20°N, 175°E-75°W).

CGCM with SST restored to model climatology plus observed historical SST anomaly in IPO domain

Tier-2 HIST-AMO 1870-2013

Pacemaker 20th century historical run. Observational historical SST is restored in the AMO domain (0-70°N, 70°W-0°).

CGCM with SST restored to model climatology plus observed historical SST anomaly in AMO domain

Tier-3 DTIP 1979-2013 Topography of TP is reduced to 500m. AGCM

Tier-3 DTIP-DSH 1979-2013

Surface sensible heat released at the elevation above 500m over the TIP is not allowed to heat the atmosphere.

AGCM

Tier-3 DHLD 1979-2013Topography in Africa, Americas and Asia is reduced to a certain height (500m).

AGCM

GMMIP-proposed experiments

3. How is the Asian monsoon simulated in coupled climate models ?

CMIP3 models. Climatological distribution of JJA mean precipitation (shaded: mm/day) and 850-hPa wind (vectors: m/s)

Song and Zhou 2014, J Cli

CMIP5 models. Climatological distribution of JJA mean precipitation (shaded: mm/day) and 850-hPa wind (vectors: m/s)

Song and Zhou 2014, J Cli

Leading MV-EOF patterns and corresponding PC of SLP (shaded) and 850 hPa winds (vectors) in (left) ERA-40 and (right) MME. MME is constructed by using 35 realizations from 17 CMIP5 models.

Song et al. 2014, GRL

Linear trends of SLP (shaded; hPa/(44 year) ) and 850hPa winds (vectors; ms-1 /(44 year)) in JJA during 1958–2001. (a) Observations (SLP and 850 hPa winds from ERA-40), (b) all-forcing run, (c) anthropogenic-forcing run, (d) GHG-forcing run, (e) natural-forcing run, and (f) aerosol-forcing run from MME. The green box in a and b is northern China (32°N–42°N, 105°E–122°E). The dotted areas indicate that the precipitation trends are statistically significant at the 10% level. The MME is constructed by using 35 realizations from17 CMIP5 models.


Linear trends for SAT trends (K/(44 year)). (a) The observation is from GISTEMP. (a and b) The black boxes are eastern China (28°N–38°N, 105°E–122°E). The domain average has been subtracted and shown in the right corner. The MME is constructed by using 35 realizations from 17 CMIP5 models.


(a) Scatterplot of the linear trends of SAT (K/(44 year)) averaged over eastern China (28°N–38°N, 105°E–122°E) and SLP (hPa/(44 year)) averaged over northern China (32°N–42°N, 105°E–122°E) in JJA during 1958–2001. The dots indicate 17 models in different forcing runs identified by different colors. The lines indicate the best linear fit lines between SAT and SLP. The fitting coefficients are given in the brackets. (b) Linear trends of SAT averaged over eastern China (28°N–38°N, 105°E–122°E) in the observation, all-forcing run, anthropogenic forcing run, GHG-forcing run, aerosol-forcing run, and natural-forcing run of MME (the SAT averaged over the EASM region (0°N–50°N, 90°E–160°E) have been subtracted). The MME is constructed by using 35 realizations from 17 CMIP5 models.


1) Mean Squared Error (MSE)

Model evaluation metrics

A model field identical to observation has a M1 value of 1, and the closer of M1 value to 1, the greater skill in simulating the spatial climatologies.

2) Interannual variability

Symmetric variability statistic (M2): M2 is equal to 0 when the two fields are identical, and the closer M2 to 0, the greater skill is

Chen, Weilin, Zhihong Jiang, Laurent Li, 2011: Probabilistic Projections of Climate Change over China under the SRES A1B Scenario Using 28 AOGCMs. J. Climate, 24, 4741–4756.

ING

V_EC

HAM

4

CSIR

O_M

K3.5

UKM

O_H

ADCM

3

MM

E

HadG

EM2-

AO

CSIR

O_M

K3.0

GFD

L-CM

2.1

NCAR

_CCS

M3.

0

MIR

OC3

. 2 (h

i)

MIU

B_EC

HO_G

ING

V C-

ESM

CGCM

3.1

(T63

)

MIR

OC3

.2 (m

ed)

ECHA

M5_

C

ECHA

M5/

MPI

-OM

GFD

L-CM

2.0

CGCM

3.1(

T47)

IPSL

_CM

4_V2

UKM

O_H

ADG

EM1

HadC

M3C

MRI

_CG

CM2.

3.2

IPSL

_CM

4

INM

CM3.

0

BCCR

_BCM

2.0

CNRM

_CM

3

NCAR

_PCM

1

FGO

ALS-

G1.

0

CNRM

-CM

3.3

GIS

S-EH --

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Smal

l erro

r

Tas Pr

Tas

Better performance-2.5

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0Pr

Model skill score M1


MM

E

ING

V_EC

HAM

4

MRI

_CG

CM2.

3.2

UKM

O_H

ADCM

3

MIR

OC3

. 2(m

ed)

MIR

OC3

. 2(h

i)

NCAR

_CCS

M3.

0

CGCM

3.1(

T63)

CSIR

O_M

K 3.

5

GFD

L-CM

2.0

IPSL

_CM

4

MIU

B_EC

HO_G

CSIR

O_M

K3.0

HadC

M3C

ECHA

M5/

MPI

-OM

CGCM

3.1

(T47

)

GFD

L-CM

2.1

UKM

O_H

ADG

EM1

ipsl_

cm4_

V2

ECHA

M5_

C

ING

V C-

ESM

NCAR

_PCM

1

FGO

ALS-

G1.

0

HadG

EM2-

AO

INM

CM3.

0

CNRM

_CM

3

BCCR

_BCM

2.0

GIS

S-EH

CNRM

-CM

3.3

0

1

2

3

4

Smal

l erro

r

Tas Pr

Better performance

Tas

-2

-1

0

1

2

3

4

5

6

7

8

9

10Pr

Model skill score M2


Boo et al 2011, JGR

Boo et al 2011, JGR

Taylor diagrams of the AMIP climatology over East Asia (100°–145°E, 20°–50°N) for the 20 year period (1979-1989)

(a) temperature(black), precipitation(red),and SLP (blue)

(b) 200 hPa U (black), 850 hPaV (red), and 500 hPa Z (blue).

JJA

DJF

Figure 2 Time series of mean summer (June–September) precipitation averaged over land points within 60–90° E, 7–27° N in the historical (20c3m; 1861–1999) and SRES A1B (2000–2100) future projection CMIP3 experiments. Four models are depicted; the black curve shows their ensemble mean. Observations from the AIR index are also shown for the 1871–2008 period as a proxy for South Asia rainfall. All curves are first normalized by their mean and standard deviation measured over 1961–1999 and are passed through an 11-year moving window. The faint black curve shows the observations without this smoothing. The inset compares the AIR with area-mean averages over the same domain as above from 1951–2004 IMD daily gridded data and 1901–2009 monthly gridded CRU data. The values listed in the legend are for June–September mean rainfall and interannual standard deviation, in mm. Obs, observations.


Figure 3 Precipitation response to doubling of carbon dioxide concentrations. Mean summer (June–September) precipitation projections in the 1% per year increasing carbon dioxide experiment (1pctto2x) of the CMIP3 multimodel database after doubling of carbon dioxide concentrations relative to control conditions. a, Mean across 20 models. b, A subset of four of these models judged to reasonably simulate the monsoon seasonal cycle, interannualvariability and the teleconnection between monsoon rainfall and ENSO. Models were first bilinearly interpolated onto a common 5° grid to compute ensemble means. Stippling in a indicates where more than two-thirds of the models agree on the sign of change.


Figure 4 Normalized probability of occurrences (number of occurrences divided by the total number of years) of interannual variability of South Asian monsoon rainfall from four CMIP3 models. Pre-industrial PDF (solid line) and future climate (1% per year increase in carbon dioxide experiments, 1pctto2x) PDF (dashed line) are shown. The future variations are scaled by the pre-industrial control interannual standard deviations (std) whose values (in mm) are also shown. The differences in the shape of the PDFs have been tested for significance based on a Kolmogorov–Smirnov test. Although all models suggest a reduction in the occurrence of normal monsoon years (± one standard deviation in monsoon rainfall) the changes in the tails are significant in only one model, mri_cgcm2_3_21 (d).


4. Using LMDZ to investigate climate change over East China

Two French zoomed climate models

LMDZ-Mediterranean(IPSL, Paris)

Arpege-Mediterranean(Météo-France, Toulouse)

𝜕𝜕𝑋𝑋𝜕𝜕𝑡𝑡 = 𝑀𝑀 𝑋𝑋 +

𝑋𝑋𝑎𝑎 − 𝑋𝑋𝛕𝛕

Real orography

• LMDZregional is a global GCM with a zoom over Southeast China. Local resolution: 50 km.• It is run as a regional climate model, with nudging conditions (every 6 hours) from a global

model (LMDZ-g, ERA40, IPCC, etc.) at low resolution outside the zoom. The model is free to have its own behaviours inside the zoom.

• It is possible to do two-way nesting with LMDZ-global

Comparison of climatological rainfall (mm/day) DJF/MAM/JJA/SONObservation

LMDZ-ERA40

Precipitation anomaly (110-120E / 27-33N). With 10-point running mean

Observation

LMDZ-era40

Three flooding summer seasons in China: rainfall anomaly

1991 1994 1998

Obs

LMDZ

Added values of LMDZ-regional: extremes

Spectral distribution of rainfall in southeast China, comparison between the observation, LMDZ/CTRL, LMDZ/CTRL2, and a few other coarse-resolution global models. Added values of high-resolution models can be clearly identified.

Chen et al. 2011, JCL

Annual-mean rainfall (mm/d) (top), and its future variation (bottom: 2050-2000)

LMDZ-global LMDZ-regional LMDZ-sn

Variations (2050 minus 2000) of seasonal-mean precipitation (mm/d)

LMDZ-global (top); LMDZ-regional (bottom)

Spring Summer Autumn Winter

FGOALS-g2

MPI-ESM-MR

IPSL-CM5A-MR CNRM-CM5

BCC-CSM-1-1-M

LMDZ-regional

Mosaic representation of models resolution in five GCMs and in LMDZ-regional

FGOALS-g2

MPI-ESM-MR

IPSL-CM5A-MR CNRM-CM5

BCC-CSM-1-1-M

LMDZ-regional

Changes (2071/2100 – 1971/2000, RCP8.5) in surface air temperature (°C)in global models (upper panels) and regional models (lower panels)

Changes (2071/2100 – 1971/2000, RCP8.5) in rainfall rate(mm/day)in global models (upper panels) and regional models (lower panels)

5. Role of the Tibetan Plateau: mechanical versus sensible-heating effects ?

Boos W, and Z Kuang, 2010: Dominant control of the South Asian monsoon by orographic insulation versus plateau heating, Nature, 463, 218-223.

Wu et al., 2012: Thermal Controls on the Asian Summer Monsoon. Sci. Rep. 2, 404; DOI:10.1038/srep00404 (2012)

The Tibetan plateau is generally believed to emit energy into the atmosphere in the form of dry heat and water vapour, serving as a heat source that drives the South Asian summer monsoon. Observations of the present climate, however, do not clearly establish the Tibetan plateau as the dominant thermal forcing in the region: peak upper-tropospheric temperatures during boreal summer are located over continental India, south of the plateau. Although Tibetan plateau heating locally enhances rainfall along its southern edge in an atmospheric model, the large-scale South Asian summer monsoon circulation is otherwise unaffected by removal of the plateau, provided that the narrow orography of the Himalayas and adjacent mountain ranges is preserved. Additional observational and model results suggest that these mountains produce a strong monsoon by insulating warm, moist air over continental India from the cold and dry extratropics.

Figure 1 Observational estimates of June-August thermodynamic structure, precipitation and wind. a , Satellite-based (AIRS) estimate of mass-weighted vertical mean temperature for 175-450 hPa. b, ERA40 equivalent potential temperature on a terrain-following model level about 20 hPa above the surface. c, TRMM precipitation rate (colourshading) and ERA40 850 hPa winds (vectors). In all panels, grey lines denote coasts and thick black contours surround surface pressures lower than 900 hPa and 700 hPa. The contour interval is 1 K in a, 2 K in b and 2 mm d-1 in c.

Figure 2 Thermodynamic structure from balloon soundings for June-August. a , Equivalent potential temperature within 25 hPa of the surface at radiosonde sites over and around the Tibetan plateau. Black squares and circles mark the stations used to produce the vertical profiles for India and Tibet, respectively, shown in b and c. b, Daily mean profiles oftemperature, averaged over Indian stations with the warmest upper-tropospheric temperature (solid red line) and Tibetan plateau stations with sufficient upper-level data (solid blue line). Dashed lines are dry adiabats from the lowest sounding level up to the lifted condensation level, and moist pseudoadiabats thereafter. Convective available potential energy (CAPE) for each sounding is displayed, with the two values for India corresponding to calculations performed using reversible and pseudoadiabatic ascent. c, Mean temperature difference between the Indian and Tibetan plateau sites, with positive values denoting air that is warmer over Indian sites. The black line denotes values at 00:00 utc (5:30 am India local time) and the magenta line at 12:00 utc (5:30 pm India local time). Boos and Kuang 2010, Nature

Figure 3 Thermodynamic structure, precipitation and wind from the atmospheric model. All panels are for June-August and as in Fig. 1 but for the model run with a, standard topography, b, no elevated topography, and c, surface elevations north of the Himalayas set to zero.

Boos and Kuang 2010, Nature

Figure 4 Results from model runs with modified topography and surface albedo. Shading shows precipitation and arrows show 850 hPa horizontal wind, both as anomalies relative to the control run with standard topography and albedo. a, Run with no elevated topography but standard surface albedo (that is, the same run shown in Fig. 3b). b, Run with standard topography but with the Tibetan plateau assigned a surface shortwave albedo of unity. The thick black contour surrounds regions where the surface albedo was modified.

Boos and Kuang 2010, Nature

In contrast to its effects on South Asian summer climate, the Tibetan plateau may be very important for East Asian climate. It is likely that the mechanical effects of plateau orography set the position of the jet stream and the dynamics of low-level flow that advect moisture into East Asia. Such effects may be tied to jet stream and frontal dynamics that are extratropical in nature, rather than the tropical Hadley circulation dynamics thought relevant for the South Asian summer monsoon

Schematic diagram showing the mechanisms by which the atmosphere responds to the Tibetan Plateau warming, in particular the remote impact of TP warming on East Asian summer monsoon rainfall through two Rossby wavetrains. The letters A and C denote anticyclonic and cyclonic circulation centers, respectively.

Wang et al 2008 GRL

Temporal evolution of (top) Ta, (upper middle) Ts, (lower middle) V0, and (bottom) SH over the CE-TP. The units of Ta and Ts are °C, V0, m/s, and SH, W/m2. Curves with open circles are 71-station averaged, and curves with closed circles are 37-station averaged.

Duan and Wu 2009 JC

SCIENTIFIC REPORTS | 11 May 2012 | 2 : 404 | DOI: 10.1038/srep00404

The Asian summer monsoon affects more than sixty percent of the world’s population. Various mechanisms have been suggested to understand the dominant factors for its generation and strength. Here we use observation data and numerical experiments to demonstrates that the Asian summer monsoon systems are controlled mainly by thermal forcing whereas large-scale orographically mechanical forcing is not essential: the South Asian monsoon south of 20N by land–sea thermal contrast, its northern part by the thermal forcing of the Iranian Plateau, and the East Asian monsoon and the eastern part of the South Asian monsoon by the thermal forcing of the Tibetan Plateau.

Wu et al., 2012, Scientific Reports

Figure 1 Impacts of land–sea thermal contrast. Summer precipitation rate (color shading, unitmm d–1) and 850 hPawinds (vectors) for a, the control experiment CON;b, observations averaged over the period 1979–2009; c, experiment NMT inwhich the global surface elevations are set to zero; and d, experiment L_S in which only the elevations of the Iranian Plateau (IP) and the Tibetan Plateau (TP) are set to zero. Thick contours indicate elevations higher than 1,500 m and 3,000 m.

Figure 2 Impacts of mountain mechanical forcing. Summer precipitation rate and 850 hPa winds for a, the difference (DIFF) between the CON and L_S experiments, indicating the compensating rainfall and circulation required to make up the total monsoon; b, experiment IPTP_Min which the IP and TP mechanical forcing exists; c, experiment IP_M inwhich the IP mechanical forcing exists; and d, experiment TP_M in which the TP mechanical forcing exists.


Figure 3 Impacts of mountain thermal forcing on the Asian summer monsoon, showing the summer precipitation rate (color shading, unit mm d–1) and 850 hPawinds (vectors) generated due to the elevated surface sensible heating of a, the Iranian Plateau (IP_SH); b, the Tibetan Plateau (TP_SH);c, the IP and TP (IPTP_SH). Thick red contours surrounding red-hatched regions indicate elevations higher than 1,500 m and 3,000 m.

Figure 2a


Figure 4 Relative contributions of the climbing and deflecting effects of mountains.

Summer precipitation rate (color shading, unit mm/d) and streamlines at the sigma=0.89 level for a, the CON experiment; b, the IPTP_M experiment; c, the HIM experiment; d, the HIM_M experiment.

Dashed contours surround elevationshigher than 1,500 m and 3,000 m, with red and black colors respectively indicating with and without surface sensible heating of the mountains. Dark blue open arrows denote the main atmospheric flows impinging onthe TP, either climbing up the plateau (a and c) or moving around the plateau, parallel to orographic contours (b and d).


Figure 5 Structure of the South Asian summer monsoon, showing 80°E–90°E longitudinally averaged vertical–meridional cross-sections of pressure vertical velocity (contour interval, 2x10–2 Pa s–1) for experiments

a, CON; and b, IPTP_M.


Figure 6 Schematic diagram showing the gross structure of the South Asian summer monsoon. For the southern branch, water vapor along the conveyer belt is lifted up due mainly to land–sea (L_S) thermal contrast in the tropics; for the northern branch the water vapor is drawn away from the conveyer belt northward toward the foothills and slopes of the TP, and is uplifted to produce heavy precipitation that is controlled mainly by IPTP-SHAP; the rest of the water vapor is transported northeastward to sustain the East Asian summer monsoon, which is controlled by the land–sea thermal contrast as well as thermal forcing of the TP.Wu et al., 2012, Scientific Reports

6. Perspectives:

- Climate downscaling and upscaling: scale interaction- Inter-disciplinary studies and Multi-model approach

Global

Regional

buffer zone

buffer zone

Schematic of the quadruple coupling: M4

Global O-A coupled model: LMDZ-global / ORCA2Regional O-A coupled model: LMDZ-regional / MED8

Two atmospheric models are coupled through buffer zonesTwo oceanic models are also coupled through buffer zones

Numerical models (in IPSL) for Mediterranean climate studies

1. Asian summer monsoon as observed2. Simulation of global monsoon in climate models3. Simulation of Asian summer monsoon in climate models4. Investigate regional climate over East China with LMDZ-regional5. Role of the Tibetan Plateau in the Asian monsoon6. Perspectives

Monsoon and its rainfall simulation in climate models: a partial review and some perspectives

Laurent Li ([email protected])Laboratoire de Météorologie Dynamique (LMD)

Institut Pierre-Simon Laplace (IPSL) CNRS/UPMC (Paris VI), Paris, France

mailto:[email protected]

Documents

Monsoon and its rainfall simulation in climate models - ioc