Factors Influencing Factors Influencing Precipitation Efficiency (PE)Precipitation Efficiency (PE)

in a Continental Mid-Latitude Location in a Continental Mid-Latitude Location

byby

Mohd Hisham Mohd AnipMohd Hisham Mohd Anip

AdvisorAdvisor

Dr Patrick MarketDr Patrick Market

ContentContent

IntroductionIntroduction Literature reviewLiterature review MethodologyMethodology Results & DiscussionsResults & Discussions ConclusionsConclusions Questions/comments?Questions/comments?

IntroductionIntroduction What is PE?What is PE?

The efficiency of a system in eliminating the The efficiency of a system in eliminating the moisture it ingests from the atmosphere moisture it ingests from the atmosphere (Doswell et al. 1996)(Doswell et al. 1996)

total available moisturetotal available moisture

Braham (1952) – total inflow water vapor into the Braham (1952) – total inflow water vapor into the cloud basecloud base

Ferrier et al. (1996) – total condensation over Ferrier et al. (1996) – total condensation over column of aircolumn of air

moisture available total

ionprecipitat totalPE

Why study the PE?Why study the PE?

Give an indication of how efficient a system is Give an indication of how efficient a system is eliminating the moisture it ingests from the eliminating the moisture it ingests from the atmosphereatmosphere

Heavy rainfall systems are associated with higher Heavy rainfall systems are associated with higher

PE value (Fankhauser 1988, Doswell et al. 1996, PE value (Fankhauser 1988, Doswell et al. 1996, Scofield 2000)Scofield 2000)

Use as a forecasting tool to forecast heavy rainfall Use as a forecasting tool to forecast heavy rainfall & flash flood events& flash flood events

Literature ReviewLiterature Review

First study has been conducted in the early First study has been conducted in the early 1950’s, 1950’s,

- after the Thunderstorm Project- after the Thunderstorm Project

Braham (1952) Braham (1952)

- determined thunderstorm - determined thunderstorm water water budget. budget.

Braham (1952) Mid-latitude thunderstorm Observed 10%

Sellers (1965) Climatological Observed 5-19%

Newton (1966) Mid-latitude squall line Observed 50%

Fankhauser (1966) Mid-latitude thunderstorm Observed 60%

Auer and Marwitz (1968) Mid-latitude hailstorms Observed 21-120%

Chisholm (1968) Mid-latitude thunderstorm Observed 21%

Hartzell (1969) Mid-latitude hailstorm Observed 45%

Chisholm (1970) Mid-latitude squall line Observed ~100%

Marwitz (1972) Mid-latitude hailstorm Observed ~4%

Foote and Fankhauser (1973) Mid-latitude hailstorm Observed 15%

Chalon et al. (1976) Mid-latitude hailstorm Observed 40%

Houze et al. (1976) Mid-latitude frontal system Observed 60-90%

Caracena et al. (1979) Mid-latitude thunderstorm Observed 85%

Gamache and Houze (1983) Tropical MCS Observed ~59%

Heymsfeld and Schotz (1985) Mid-latitude squall line Observed 25-40%

Lipps and Hemler (1986) Tropical convection Modeled ~40%

Fankhauser (1988) Mid-latitude thunderstorms Observed 19-47%

Ryan et al. (1989) Mid-latitude cold front Observed 0%

Chong and Hauser (1989) Tropical squall line Observed 45-57%

McBean and Stewart (1991) Mid-latitude frontal system Observed 70%

Ferrier et al. (1996) Tropical and mid-latitude squall lines

Modeled 24-45%

Rauber et al. (1996) Tropical convection Observed 20-30%

Szeto et al. (1997) High-latitude frontal system Modeled 0-80%

Li et al. (2002) Tropical convection Modeled 20-130%

Market et al. (2003) Mid-Latitude MCS Observed 4-48%

Literature ReviewLiterature Review

Findings from later Findings from later observational studies observational studies revealreveal

i. negative correlationi. negative correlation

between wind shear between wind shear and PE valueand PE value

(Marwitz 1972) (Marwitz 1972)

Literature ReviewLiterature Review

ii. Larger cloud base area and cloud base ii. Larger cloud base area and cloud base mixing ratio, PE, higher cloud base mixing ratio, PE, higher cloud base height, PE height, PE

(Fankhauser 1988)(Fankhauser 1988)

iii. PE instantaneous values vary with the iii. PE instantaneous values vary with the lifetime of a system (Doswell et al. 1996) lifetime of a system (Doswell et al. 1996)

Literature ReviewLiterature Review

(Market et al. 2003)(Market et al. 2003)

iv. Relatively strong negative correlation iv. Relatively strong negative correlation between Convective Inhibition (CIN) and PE between Convective Inhibition (CIN) and PE (Market et al. 2003)(Market et al. 2003)

Literature ReviewLiterature Review

Significant findings from modeling studySignificant findings from modeling study

i. PE in convective system is control by i. PE in convective system is control by vertical orientation of the updrafts (Ferrier vertical orientation of the updrafts (Ferrier et al. 1996)et al. 1996)

ii. PE is higher in a heavy rain regime under ii. PE is higher in a heavy rain regime under warm environmental condition and strong warm environmental condition and strong convection (Li et al. 2002)convection (Li et al. 2002)

Literature ReviewLiterature Review

Objective of this studyObjective of this study

i. Examine i. Examine PE variationPE variation with with seasonsseasons

ii. Examine ii. Examine PE variationPE variation with with cloud cloud typestypes (stratiform vs. convective) (stratiform vs. convective)

iii. To find the relations of environmental iii. To find the relations of environmental factors to PE value, if any, and used them factors to PE value, if any, and used them to support the earlier findings to support the earlier findings

Area of Study - Columbia, MOArea of Study - Columbia, MO

Why choose Columbia?Why choose Columbia?

i.i. Good annual amount of rainfall ~1000mmGood annual amount of rainfall ~1000mm

ii. Sanborn & KCOU Weather Station ii. Sanborn & KCOU Weather Station

iii. SuomiNet systemiii. SuomiNet system

Criteria to select the event from Oct 1Criteria to select the event from Oct 1stst, 2003 to , 2003 to Sept 30Sept 30thth, 2004, 2004

i. Total rainfall > 0.25 in (6.4mm)i. Total rainfall > 0.25 in (6.4mm)

ii. Rainfall was continuously for at least 4hrs.ii. Rainfall was continuously for at least 4hrs.

MethodologyMethodology

Few methods to calculate PE, e.g.,Few methods to calculate PE, e.g.,

SellersSellers Method (1965), P/PW Method (1965), P/PW- a climatological approach- a climatological approach

ScofieldScofield Method (1987), PW X RH Method (1987), PW X RH- RH is a mean value taken between 1000 - RH is a mean value taken between 1000 and 700mb pressure level and 700mb pressure level

Water BudgetWater Budget Method (Braham 1952, Palmén & Method (Braham 1952, Palmén & Newton 1969)Newton 1969)- known as true PE because it takes into - known as true PE because it takes into

account all the moisture in and out of a account all the moisture in and out of a rainfall rainfall systemsystem

Using water budget method by Palmén & Newton Using water budget method by Palmén & Newton (1969) to calculate PE assumed to be in steady (1969) to calculate PE assumed to be in steady state system at a fixed point state system at a fixed point

(A)(A) (B)(B)

P P = total precipitation= total precipitationE E = evaporation = evaporation

(A)(A) = local change in specific humidity tendency= local change in specific humidity tendency(B)(B) = moisture flux divergence= moisture flux divergence

o op

p

p

pqVdp

gdpt

q

gEP .

11

PE CalculationPE CalculationUsed analysis data from Used analysis data from RUC20RUC20 model to model to generate water budget terms generate water budget terms

RUC20RUC20- latest meteorological numerical models, - latest meteorological numerical models, and features 50 layers and 20 km horizontal and features 50 layers and 20 km horizontal resolution that improves the accuracy and resolution that improves the accuracy and timeliness of current weather analyses and short-timeliness of current weather analyses and short-range weather forecasts range weather forecasts

RUC20 output acquired from the Atmospheric RUC20 output acquired from the Atmospheric Radiation Measurement (ARM) of the Department Radiation Measurement (ARM) of the Department of Energy (DOE) of Energy (DOE)

Results and DiscussionsResults and Discussions

31 events have been identified31 events have been identified

PE values range from PE values range from -78% to 236% -78% to 236% were were calculatedcalculated

According to Marwitz (1972), PE value over According to Marwitz (1972), PE value over the lifetime of rainfall system should be the lifetime of rainfall system should be between 0% and 100%, but instantaneous between 0% and 100%, but instantaneous value can vary from 0% to (value can vary from 0% to (DoswellDoswell et al. 1996 et al. 1996))

PE value > 100% (4 cases)PE value > 100% (4 cases)

- because the values were estimated - because the values were estimated toward the end of the system lifetime toward the end of the system lifetime

((Doswell et aDoswell et all. 1996. 1996))

PE value < 0% (1 case)PE value < 0% (1 case)

- because the system was precipitating out - because the system was precipitating out as well as advecting moisture out of the as well as advecting moisture out of the system, experiencing a net loss in moisture system, experiencing a net loss in moisture ingestingest

Results and DiscussionsResults and Discussions

Seasonal variationSeasonal variation

- land heating and cooling has played a major - land heating and cooling has played a major factor for these variations factor for these variations

- higher temperature will result in more - higher temperature will result in more evaporation which produces more moisture evaporation which produces more moisture and rainfall during warmer season and rainfall during warmer season

Month No. of Events Season Average PE (%)

Dec, Jan, Feb 6 Winter 12

Mar, Apr, May 9 Spring 51

Jun, Jul, Aug 8 Summer 69

Sept Oct, Nov 7 Fall 43

Seasonal variationSeasonal variation

- - precipitable water values are typically precipitable water values are typically greater through the warm season and lower greater through the warm season and lower in the cold season (Ross and Elliott 1996) in the cold season (Ross and Elliott 1996)

- PE value is affected by relative humidity - PE value is affected by relative humidity and precipitable water (Doswell et al. 1996)and precipitable water (Doswell et al. 1996)

Month No. of Events Season Average PE (%)

Dec, Jan, Feb 6 Winter 12

Mar, Apr, May 9 Spring 51

Jun, Jul, Aug 8 Summer 69

Sept Oct, Nov 7 Fall 43

Cloud/system typeCloud/system type

-- PE value for convective system is higher PE value for convective system is higher because of the ability of updrafts and because of the ability of updrafts and downdrafts to collect droplets that would downdrafts to collect droplets that would become precipitation (Ferrier et al. 1996 )become precipitation (Ferrier et al. 1996 )

-- Under warm environmental condition and Under warm environmental condition and strong convective system the precipitation strong convective system the precipitation would be more efficient, which produced would be more efficient, which produced higher higher PEPE value (Li et al. 2002) value (Li et al. 2002)

RainfallSystem

No of Events Summer Fall Winter Spring PE average (%)

Convective 19 6 7 1 5 56

Stratiform 11 2 0 5 4 29

Cloud/system typeCloud/system type

-- Stratiform system generally produce little or Stratiform system generally produce little or no precipitation and what little might fall no precipitation and what little might fall consist of minute particles such as drizzle consist of minute particles such as drizzle

-- Convective rainfall accounts for ~70% of the Convective rainfall accounts for ~70% of the total rainfall, because its intensity is so much total rainfall, because its intensity is so much higher (Houze 1997)higher (Houze 1997)

RainfallSystem

No of Events Summer Fall Winter Spring PE average (%)

Convective 19 6 7 1 5 56

Stratiform 11 2 0 5 4 29

Environmental factorsEnvironmental factors

- only involve the convective system (19 events)- only involve the convective system (19 events)- unfortunately no correlations have been found- unfortunately no correlations have been found- proceed with advance analysis by selecting the - proceed with advance analysis by selecting the event that extremely fulfill study assumption & event that extremely fulfill study assumption & have moderate unstable conditionhave moderate unstable condition

- - 6 events 6 events were short listed which shows;were short listed which shows;i. strong inverse correlation (-0.764) i. strong inverse correlation (-0.764)

between PE value and between PE value and environmental environmental wind wind shear (shear (Marwitz 1972Marwitz 1972))

ii. high probability (86%) where PE value is ii. high probability (86%) where PE value is a a function of precipitable water function of precipitable water (Doswell (Doswell et al. 1996)et al. 1996)

Case study ( August 24Case study ( August 24thth, 2004), 2004)

- example of perfect steady-state system passing - example of perfect steady-state system passing through the study areathrough the study area

1500 UTC : Approaching the study area1500 UTC : Approaching the study area

Surface Analysis chart (1500 UTC)Surface Analysis chart (1500 UTC)

500 mb Height & Vorticity chart (1500 UTC)500 mb Height & Vorticity chart (1500 UTC)

Skew-T chart from 1500 UTC RUC20 soundingSkew-T chart from 1500 UTC RUC20 sounding

1800 UTC: Over the study area1800 UTC: Over the study area

2000 UTC: Leaving the study area2000 UTC: Leaving the study area

Facts of the Event:Facts of the Event:

i. 16.76 mm rainfall amount was recorded over study i. 16.76 mm rainfall amount was recorded over study area from 16 to 19 UTC observationarea from 16 to 19 UTC observation

ii. Amount of ii. Amount of precipitableprecipitable water water measure from UMC measure from UMC SuomiNet system drop tremendously as the system SuomiNet system drop tremendously as the system passing trough the study area passing trough the study area

iii. 45% of PE value was calculated with estimation of iii. 45% of PE value was calculated with estimation of 37.61 mm available water between 1000 and 300 37.61 mm available water between 1000 and 300 mb pressure levelmb pressure level

iv. Report from National Climatic Data Centeriv. Report from National Climatic Data Center reveals reveals

that that 13 locations 13 locations in Missouri were experienced in Missouri were experienced significant weather associated with this weather significant weather associated with this weather systemsystem

ConclusionsConclusions PE value is highest during summer, followed by PE value is highest during summer, followed by

spring, fall & winterspring, fall & winter

PE value is higher for convective type system PE value is higher for convective type system than the stratiformthan the stratiform

After advance analysesAfter advance analyses

- There is strong inverse correlation between - There is strong inverse correlation between environmental wind shear and PE value environmental wind shear and PE value

- There is high probability that precipitable water - There is high probability that precipitable water is a function of PE valueis a function of PE value

Case study shows that 45% PE was estimated Case study shows that 45% PE was estimated

for the perfect steady-state convectivefor the perfect steady-state convective

weather system weather system

Questions/Comments??Questions/Comments??

Special Thanks: Dr MarketSpecial Thanks: Dr Market