Extreme Precipitation by High Extreme Precipitation by High Resolution RegCM3Resolution RegCM3

Over East Asia

Jing ZHENG , Zhenghui Xie Jing ZHENG , Zhenghui Xie Institute of Atmospheric Physics (IAP),CAS, ChinaInstitute of Atmospheric Physics (IAP),CAS, China

Xunqiang Bi Xunqiang Bi the Abdus Salam International Centre for Theretical Physics (ICTP), the Abdus Salam International Centre for Theretical Physics (ICTP),

ItalyItaly

Outline

IntroductionIntroductionModel & Exp.Model & Exp.Results Results DiscussionDiscussion

Outline

IntroductionIntroductionModel & Exp.Model & Exp.Results Results DiscussionDiscussion

Giorgi & Bi, 2000:Giorgi & Bi, 2000:

The The internal model variabilityinternal model variability exhibits a pronounced exhibits a pronounced summer maximum. summer maximum.

It significantly influences the It significantly influences the day-to-day model day-to-day model solution, especially for summer precipitationsolution, especially for summer precipitation..

Also affected by the model internal variability was the Also affected by the model internal variability was the frequency of occurrence of heavy daily precipitationfrequency of occurrence of heavy daily precipitation events.events.

A regional climate model simulation is characterized A regional climate model simulation is characterized by an intrinsic level of internal variability which can by an intrinsic level of internal variability which can be excited by any type of perturbation and is be excited by any type of perturbation and is regulated by synoptic conditions, season, model regulated by synoptic conditions, season, model domain, region of application, and specific simulation domain, region of application, and specific simulation period.period.

Giorgi & Bi, 2000:Giorgi & Bi, 2000:

The internal model variability exhibits a pronounced The internal model variability exhibits a pronounced summer maximum. summer maximum.

It significantly influences the day-to-day model It significantly influences the day-to-day model solution, especially for summer precipitation.solution, especially for summer precipitation.

Also affected by the model internal variability was the Also affected by the model internal variability was the frequency of occurrence of heavy daily precipitation frequency of occurrence of heavy daily precipitation events.events.

A regional climate model simulation is characterized A regional climate model simulation is characterized by an intrinsic level of internal variability which can by an intrinsic level of internal variability which can be excited by any type of perturbation and is be excited by any type of perturbation and is regulated by regulated by synoptic conditionssynoptic conditions, , seasonseason, , model model domaindomain, , region of applicationregion of application, and , and specific simulation specific simulation periodperiod..

Resolution?Resolution? Model? Its internal model variability?Model? Its internal model variability?

the extreme precipitation,Yangzi and Huaihe Valley summer, 1998 the extreme precipitation,Yangzi and Huaihe Valley summer, 1998 compared to compared to 60km resolution60km resolution & & observational dataobservational data..the results indicated that the results indicated that high resolution can give more details high resolution can give more details about the region of the extreme precipitationabout the region of the extreme precipitation. . Additionally, Additionally, the maximum of the extreme precipitation were the maximum of the extreme precipitation were differentdifferent by the two simulations of different resolutions. by the two simulations of different resolutions.Difficulties in simulating precipitation, esp. extreme prec.Difficulties in simulating precipitation, esp. extreme prec.

20km resolution of RegCM3 20km resolution of RegCM3

Outline

IntroductionIntroductionModel & Exp.Model & Exp.Results Results DiscussionDiscussion

Summary of RegCM3 Core

Dynamics:Dynamics:MM5 Hydrostatic (Grell et al

1994)Radiation:Radiation:

CCM3 (Kiehl 1996)Large-Scale Clouds & Large-Scale Clouds &

Precipitaion:Precipitaion:SUBEX (Pal et al 2000)

Cumulus convection:Cumulus convection:Anthes-Kuo (1977)Grell (1993)Emanuel (1991)

Boundary Layer:Boundary Layer:Holtslag (1990)

Tracers/Aerosols/dust:Tracers/Aerosols/dust:Qian et al (2001); Solmon et

al (2005); Zakey et al. (2006)

Land Surface:Land Surface:BATS (Dickinson et al 1993)SUB-BATS (Giorgi et al 2003)

Ocean FluxesOcean FluxesBATS (Dickinson et al 1993)Zeng et al (1998)

ComputationsComputationsParallel Code (Bi, Gao, Yeh)Multiple PlatformsMore User-Friendly Code

(Pal et al 2006; Since Giorgi et al 1993ab)

ICTP…ICTP…

Experiment Design Region – East China

Period – 1998. Jun. ~ Aug. (June: Spinup time)

Resolution – 2.5o60km20km (80*100, (32N,112E)(80*100, (32N,112E))

ICBC Experiment ERA40.vs.NNRP2

Cumulus Scheme Experiment (ERA40)

Domain Size experiment (NNRP2, icup=4)

Buffer zone experiment (ERA40, icup=4)

 

6060kmkm2020kmkm

ICBC -- ERA40 .vs. NNRP2ICBC -- ERA40 .vs. NNRP2ERA40ERA40 NNRP2NNRP2 ??

Outline

IntroductionIntroductionModel & Exp.Model & Exp.ResultsResultsDiscussionDiscussion

Time Series for Precipitation

NNRP2 vs ERA40 NNRP2 vs ERA40 (icup=4)(icup=4) 60km 60km 20km 20km ERA40ERA40(icup=1,2,4)(icup=1,2,4)60km60km20km20km 4 observational stations: 4 observational stations: Wuhan, Wuhan, Hefei, Hefei, Nanjing, Nanjing, ShanghaiShanghai

ERA[i1]ERA[i2]ERA[i4]NNRP[i4]EnsembleObs.

ERA[i1]ERA[i2]ERA[i4]NNRP[i4]EnsembleObs.

ERA[i1]ERA[i2]ERA[i4]NNRP[i4]EnsembleObs.

ERA[i1]ERA[i2]ERA[i4]NNRP[i4]EnsembleObs.

Domain Size Experiment (NNRP2,i4)

LargeLargeSmallSmallObsObs

Buffer Zone Experiment (ERA40,i4)

BZ12BZ12BZ18BZ18★★ ObsObs

GPCPGPCPRegCM3RegCM3 CMAPCMAPCRUCRU

Met. stationsMet. stationsSpatial pattern

Spatial pattern

ERA40_i4ERA40_i4 NNRP2_i4NNRP2_i4 NNRP2_SNNRP2_SERA40_BZERA40_BZ

tpr .vs. prcv July1998

Spatial pattern

ERA40_i4ERA40_i4 NNRP2_i4NNRP2_i4 NNRP2_SNNRP2_SERA40_BZERA40_BZ

tpr .vs. prcv Aug1998

Outline

IntroductionIntroductionModel & Exp.Model & Exp.Results Results DiscussionDiscussion

Preliminary conclusion & Discussion

simulations were simulations were differentdifferent by different resolutions/ domain by different resolutions/ domain sizes/ cumulus schemes/ forcing fields.sizes/ cumulus schemes/ forcing fields.

Resolution: higher resolution can give more details about the region Resolution: higher resolution can give more details about the region of the extreme precipitation.of the extreme precipitation.

Domain: it depends, but smaller seems much higher peaks.Domain: it depends, but smaller seems much higher peaks. Cumulus schemes:Cumulus schemes: MIT-Emanuel seems better here. MIT-Emanuel seems better here. Forcing fields: ERA40Forcing fields: ERA40 southward rain band [vs. NNRP2 ] southward rain band [vs. NNRP2 ] DifficultiesDifficulties in simulating precipitation, esp. extreme prec. in simulating precipitation, esp. extreme prec. Resolution & Precipitation?Resolution & Precipitation? Cumulus scheme? Domain size? Forcing fields?Cumulus scheme? Domain size? Forcing fields? Internal model variability?Internal model variability? Land Component of the Model? More accurate physical Land Component of the Model? More accurate physical

process?process?

A CASE STUDY ----A CASE STUDY ----

Thanks for Your Thanks for Your Attention!Attention!