an overview on convec,on-permi0ng climate modelingindico.ictp.it › event › 8313 › session ›...

An overview on Convec,on-Permi0ng Climate

Modeling

Paolo Stocchi, Erika Coppola Abdus Salam ICTP, Trieste (Italy)

Ninth RegCM Workshop, May-June 2018, ICTP

Convec'onistherisingofplumesofmoistairinresponsetoinstabilityintheatmosphere

In the tropicsmost of the rainfall is convec've,while in themid-la'tudes about 40 per cent ofprecipita'onoccursinareaswithconvec'veinstability

MODELLINGCONVECTION

Convec@ontakesplaceonscaleswhichcannotbesimulatedwithgridspacingsof climate models (RCM > 10 km andGCM > 100 km). It is thereforemodelledinseparateparameteriza'onschemes

Convec@onisthemainprocessofver@calexchangebetweenthelowerandtheuppertroposphere,inpar@cularofwatervapour,heatandchemicalspecies

Parameteriza'on are considerated asa major source for errors andunce r t an t y i n f u tu re c l ima teprojec@ons.

Contribu*onofthedifferentphysicalparametriza*onschemesfortemperatureintheIFS(averagedoverthetropics)

InECMWF’s IntegratedForecas@ngSystem (IFS), convec@onaccountsfor about 50 per cent of the total forecast tendencies above theboundary-layer

blackline:totalmodeltendency

Clouds,Aerosols(Microphysics)

PBL(Turbolence)

Soil-Vegeta'on-AtmosphereCoupling

RCM(>10km)Convec@onparameterized

Interac@onwithotherparameteriza@onschemes:

Radia'on

Weaknessesinconvec@onparameteriza@onschemescanimplyfar-reachingconsequencesthroughnonlineari@es

Definciesindiurnalcycleandinabilitytorepresenthourlyprecipita@onextrems[Daietal.,1999Brockhausetal.,2008]

Tendencyfortoomuchpersistentlightrainandunders@ma@onintensityofheavyrain(Berthouetal.,2018)

Unders@ma@onofhourlyprecipita'onintensi'es[Prainetal,2013]

Coarseresolu@onandConvec@veparameteriza@onleadto:

The grey zone of convection The drive towards higher resolution in global weather models complicates matters a little. “The equations used in convection schemes assume that there is a state of quasi-equilibrium in every grid box, in other words there is an approximate balance between rising and sinking movements of air,” Peter says. This does not hold any more at a grid spacing of 5 km or less. “This is referred to as the grey zone since we don’t yet know how best to represent certain processes at these resolutions. We won’t be able to do this correctly if we just continue as before.” (h]ps://www.ecmwf.int/en/about/media-centre/news/2017/how-model-convec@on-and-its-impact-weather) Theupperboundonthehorizontalgridspacingofconvec@on-permi`ngsimula@onswasinves@gatedbyWeismanetal.[1997]usingidealizedsqualllinesimula@ons.Theirfindingsdemonstratedtheinabilitytorepresentaccuratelynonhydrosta@cdynamicswithhorizontalgridspacingslargerthan4 km.Theconvec@vemassfluxwasoveres@matedoncethisthresholdwasexceededandresultedin“grid-scalestorms.”Thela]eremergeasconvec@veinstabilityisforcedontoanunrealis@callycoarsescale,henceoveres@ma@ngtheconvec@[email protected],CPMat4 kmorcoarsergridspacingsmaynotalwaysyieldimprovementsoverLSMs.Applyingconvec@onparameteriza@onschemesatsuchgridspacingsmayovercometheaforemen@onedissuesofunderresolvedconvec@on[DengandStauffer,2006;Leanetal.,2008;RobertsandLean,2008](Preinetal2014)

CPM(<=4km)

Apromisingremedytotheerror-proneclimatesimula@onsusingconvec@veparameteriza@onsistheuseofconvec@on-permi`ngmodel(CPM)(horizontalgridspacing<4 km)thatoperatesonthekilometerscale..

A t t h e s e s c a l e s , c o n v e c @ o nparameter i za@on schemes mayeventually be switched off as deepconvec@on starts to be resolvedexplicitly

CONVECTIONPERMITTINGMODELING(CPM)

Sincethebeginningofthe21stcentury,advancesinhigh-performancecompu@ngallowedsteadyrefinementofthenumericalgridsofclimatemodelswellbeyond10 km

Sincethebeginningofthe21stcenturymoreandmorestudieshavefocusedonCPMclimatesimula@onsandthereisnowastrongneedtosynthesizethesestudiesandtobuildthefounda@onandcommonbasisforfutureadvancesinclimatemodeling.Furthermore,impactresearchersandstakeholdersshouldbeinformedofwhattoexpectfromCPMclimatesimula@ons.Thisreviewpaperaimstoprovidethiskindofscien@ficbasisbysummarizingtheknowledgeacquireduptonowandbyhighligh'ngexis'ngchallengesandimportantresearchques'onsinthisfield.Inpar@cular,wereviewthefollowing:(1)WhatgridspacingisneededforCPMclimatesimula@ons(sec@on 3)?(2)Whatisthebestdownscalingstrategytoconvec@on-permi`ngscales(sec@on 4)?(3)Whatarethemostimportantmodelcomponentsthatrequirefurtherdevelopment(sec@on 5)?(4)Whatare,intheory,theaddedvaluesofCPMclimatesimula@onscomparedtoLSMsimula@ons(sec@on 6.1)?(5)Whataddedvaluescouldactuallybedemonstratedinprac@calapplica@ons(sec@on 6)?(6)AndwhatcanwelearnfromCPMaboutfutureclimatechangethatisnotassessablefromLSM(sec@on 7)?

Pioneering work toward CPM climate simulations was provided by [Grell et al., 2000] who performed 14 month long simulations with Δx = 1 km and showed drastic changes in the seasonal average precipitation patterns compared to LSM simulations. More recent studies have performed CPM simulations on time scales longer than 1 year to investigate climatological features in CPM simulations [e.g., Brisson et al., 2015; Chan et al., 2013; Ban et al., 2014; Fosser et al., 2014; Kendon et al., 2014; Junk et al., 2014; Tölle et al., 2014; Prein et al., 2013b; Rasmussen et al., 2011; Ikeda et al., 2010; Gensini and Mote, 2014; Chan et al., 2013; Kendon et al., 2012; Knote et al., 2010; Rasmussen et al., 2014, Berthou et al., 2018].

knowledgeacquireduptonow

Studies to date show that convec@on-permi`ng models do not necessarily be]er represent daily meanprecipita@on [e.g., Chan et al. 2013, Berthou et al., 2018 ] but have significantly be]er sub-daily rainfallcharacteris@cswithimprovedrepresenta@onofthe:•  Diurnalcycleoftheamount,intensityandfrequencyofprecipita@on(Banetal.2014,Kenondetal.2012,

Langhansetal.2013,Preinetal.,2013,Fosseretal.,2014,Berthouetal.,2018)•  Thespa'alstructureofrainfallanditsdura'on-intensitycharacteris@cs(Kendonetal,2012,Berthouetal.,

2018)

•  Intensityofhourlyprecip'a'onextremes(Chanetal.2014Banet.al2014Fosseretal.2015)•  Orographicprecipita'on(Liuetal2016)

DIURNAL CYCLE

AllCPMsclimatesimula'onsshowimprovementsintheshape(onsetandpeak)oftheprecipita'ondiurnalcyclecomparedtotheircorrespondingLSMsimula'ons[Banetal.2014,Kenondetal.2012,Langhansetal.2013,Preinetal.,2013,Fosseretal.,2014,Berthouetal.,2018]

[Preinetal.2014]

Switzerland[Banetal.,2014] SouthernUK[Kendonetal.,2012] Switzerland[Langhansetal.,2013]

EasternpartoftheAlps[Preinetal.,2013a] Germany[Fosseretal.,2014].

Domainm

Domains

Domaind Domainm

DomainI Domainj

Domainm:JJAmean1998-2007Domaind:Annualmean1989-2008DomainI:JJA2007-2008Domainj:JJA1968-1999

DIURNAL CYCLE

Berthouetal.2018

AmplitudeandthePhase(hourofthemaximumprecipita@oninlocal@me)ofthemeandiurnalcycleateachgrid-point

Amplitude:CPMsshowstrongeramplitudesinthe2.2kmmodelsoverhighorography(>1500m)comparedtothe12kmmodelsPhase:CPMsshowbeeer'[email protected],thepeakbeingshiqedfromlatemorning-earlyaqernooninparameterisedmodelstomid-lateaqernoonintheconvec@on-permi`ngmodels

UKMO2KmUKMO12Km

ETH2KmETH12Km

OBSAMPLITUDE

UKMO2KmUKMO12Km

ETH2KmETH12Km

OBSPHASE

hoursmm

DIURNAL CYCLE

Berthouetal.2018



UKMO2KmUKMO12Km

ETH2KmETH12Km

OBSAMPLITUDE

UKMO2KmUKMO12Km

ETH2KmETH12Km

OBSPHASE

hoursmm0 2 4 6 8 10 0 4 8 12 16 20 24

DIURNAL CYCLE

Berthouetal.2018



UKMO2KmUKMO12Km

ETH2KmETH12Km

OBSAMPLITUDE

UKMO2KmUKMO12Km

ETH2KmETH12Km

OBSPHASE

hoursmm0 2 4 6 8 10 0 4 8 12 20 2416

The largest differences between LSM and CPM climate simulations occur on short (subdaily) time scale and for summertime high‐precipitation intensities. Heavy hourly precipitation is typically underestimated in LSM, while large improvements were found in CPM climate simulations [Ban et al., 2014; Fosser et al., 2014; Chan et al., 2013, 2014b] (see Figure 9, for an example). Gensini and Mote [2014] (see Table 1, domain c) show that CPM climate simulations can reproduce proxies for hazardous convective weather (tornadoes, thunderstorm, and large hail) in the USA

Extreme Precipitation

Cumulative distributions of (a, b) daily precipitation and (c, d) daily maximum 1 h precipitation as a function of threshold, expressed relative to the total number of days shown in Figures 9a and 9c and relative to the number of wet days shown in Figures 9b and 9d for the data at 24 Swiss stations. The distributions have been calculated for June, July, and August (JJA) in the period 1998–2007 [Ban et al., 2014]. The CPM simulation with Δx = 2 km reproduces the observations very well, while the LSM simulation with Δx = 12 km underestimates the frequency of daily maximum 1 h precipitation. ©2014. American Geophysical Union. All Rights Reserved.

EXTREME PRECIPITATION Extreme Precipitation

Hourly%JJA%extremes%

[Ban et al. 2013]

Daily%JJA%extremes%

CPM&climate&simulaIons&add&value&to&hourly&precipitaIon&extremes&but&not&to&daily&extremes& Presentation

Michel Déqué

Improvementinsimula@ondailyprecipintensityseemtobedependentontheregionandmodelsBanetal.2014,Kenondetal.2012,Langhansetal.2013,Preinetal.,2013,Fosseretal.,2014,Berthouetal.,2018

Berthouetal.2018

Averageofvaluesabovethe99thpercen'leofalldaysinautumn(SON)inmm/dayEXTREMEPRECIPITATION

Mediterranean intense events inautumn at the daily scale are beeerrepesentedby2.2kmmodelsintermsofloca'onandintensity.

shiq in contribu@onof precipita@on from low (<2mm/h) to moderate (2-8 mm/h) and intenseprecipita@on(>8mm/h)inboth2.2Kmmodel

Averageofvaluesabovethe99thpercen@leofalldaysinautumn(SON)inmm/day

EXTREMEPRECIPITATION

Mediterraneanintenseeventsinautumnatthedailyscalearebeeerrepesentedby2.2kmmodelsintermsofloca'onandintensity.,

Berthouetal.2018

UKMO12Km UKMO2Km

ETH2KmETH12Km

OBSmm/day

0 35 90 135

<2mm/h

<8mm/h

>8mm/h


MapoftheThefrac@onalcontribu@ontototalrainfallfromlowintensity(<2mm/h),moderateevents(2-8mm/h)andintenseevents(>8mm/h)

UKMO12Km UKMO2Km ETH2KmETH12Km

0.05 0.15 0.25 0.40 0.60 0.80 1.00

Shiiincontribu'onofprecipita'onfromlow(<2mm/h)tomoderate(2-8mm/h)andintenseprecipita'on(>8mm/h)inboth2.2Kmmodelinboth2.2Kmmodelispresenteverywhereonland

OBS

Low

Moderate

Intensee

<2mm/h

<8mm/h

>8mm/h




0.05 0.15 0.25 0.40 0.60 0.80 1.00

Shiiincontribu'onofprecipita'onfromlow(<2mm/h)tomoderate(2-8mm/h)andintenseprecipita'on(>8mm/h)inboth2.2Kmmodelispresenteverywhereonland

OBS

Low

Moderate

Intensee

<2mm/h

<8mm/h

>8mm/h




0.05 0.15 0.25 0.40 0.60 0.80 1.00

moderate to intensewetspell tend tobeoveres'matedby the2.2kmmodeleven ifThe2.2kmmodelsyieldbeeerresultsfortheseeventsinallcountriesfottheETH2.2andonlyinSwitzerlandforUKMO

OBS

Low

Moderate

Intensee

JJAseasonalmeanprecipita'onfor1997–2001

APan-AfricanConvec'onPermikngClimateSimula'on:Ini@alresults5yrofsimual@ons[Stra]onetal.,2018]

CP4-Africa(4km)substan'allyreducingthedrybiases

CP4Km CP4Km minus OBS

R25Km minus OBS GLOB minus OBS

Contribution of 3h (mm day-1) prec to the daily precipitation rate across the West African monsoon (WAM)

CP4-Africa(4km)compareswellwithobserva'onaldatafromTRMMandCMORPH,andisasignificantimprovementovertheresultswithparameterizedconvec'on(R25-Africa)

JJAseasonalmeanprecipita'onfor1997–2001

APan-AfricanConvec'onPermikngClimateSimula'on:Ini@alresults5yrofsimual@ons[Stra]onetal.,2018]

CP4-Africa(4km)substan'allyreducingthedrybiases

CP4Km CP4Km minus OBS

R25Km minus OBS GLOB minus OBS

The mean diurnal cycle of precipitation for JJA

In all regions (the diurnal cycle of CP4-Africa is improved with a later peak in rainfall

RegCM V4.7.0: Convec,on permi0ng

CASESTUDY1:NortherCaliforniaon16-18February2004(Ralphetal.,2006)

RegCMDomain3km

OBSTRMM/CHIRPS

RegCM3kmWSM5

RegCM3kmNOGHE

Themodelreproduceswelltheprecipita@onfieldandlocaliza@onofthemaximuminpar@cularwithnoghero]omicrophysicsparameteriza@on

Accumulatedprec(mm)


CASESTUDY3:LakeVictoriaon26Nov-1Dec1999(Ralphetal.,2006)

OBSTRMM60hacc.Prec(mm)

RegCM3Km(standardTemp)

RegCM3Km(T°change)


CASESTUDY3:LakeVictoriaon26Nov-1Dec1999(Ralphetal.,2006)

OBSTRMM60hacc.Prec(mm)

RegCM12km

RegCM3Km


CASESTUDY2:GreatPlainson9-11June2010(Higgins,2011)

RegCMDomain3km

OBSNCEPIV

RegCM3kmWSM5

RegCM3kmSUBEX

Themodelreproduceswelltheprecipita@onfieldandlocaliza@onofthemaximuminpar@cularwithWSM5microphysicsparameteriza@on

Accumulatedprec(mm)

SPECIALTHANKSTO:J.AbrahamTorresAlavez

LITERATURE Done, J., Davis, C. A., & Weisman, M. (2004). The next generation of NWP: Explicit forecasts of convection using the Weather Research and Forecasting (WRF) model. Atmospheric Science Letters, 5(6), 110-117. Langhans, W., J. Schmidli, and C. Schär (2012), Bulk convergence of cloud-resolving simulations of moist convection over complex terrain, J. Atmos. Sci., 69(7), 2207–2228. Prein, A. F., Langhans, W., Fosser, G., Ferrone, A., Ban, N., Goergen, K., ... & Brisson, E. (2015). A review on regional convection permitting climate modeling: Demonstrations, prospects, and challenges. Reviews of geophysics, 53(2), 323-361. Lind, P., Lindstedt, D., Kjellström, E., & Jones, C. (2016). Spatial and Temporal Characteristics of Summer Precipitation over Central Europe in a Suite of High-Resolution Climate Models. Journal of Climate, (2016). Brisson, E., Demuzere, M., & van Lipzig, N. P. (2015). Modelling strategies for performing convection-permitting climate simulations. Meteorologische Zeitschrift. Brisson, E., Van Weverberg, K., Demuzere, M., Devis, A., Saeed, S., Stengel, M., & van Lipzig, N. P. (2016). How well can a convection-permitting climate model reproduce decadal statistics of precipitation, temperature and cloud characteristics?. Climate Dynamics, 1-19. Ban, N., Schmidli, J., & Schär, C. (2015). Heavy precipitation in a changing climate: Does short term summer precipitation increase faster?. Geophysical Research Letters, 42(4), 1165-1172. Mahoney, K., Alexander, M. A., Thompson, G., Barsugli, J. J., & Scott, J. D. (2012). Changes in hail and flood risk in high-resolution simulations over Colorado's mountains. Nature Climate Change, 2(2), 125-131. Rasmussen, R., Ikeda, K., Liu, C., Gochis, D., Clark, M., Dai, A., ... & Yates, D. (2014). Climate change impacts on the water balance of the Colorado Headwaters: High-resolution regional climate model simulations. Journal of Hydrometeorology, 15(3), 1091-1116. Berthou S., J. Kendon E., C. Chan Steven, Ban N., Leutwyler D., Schar C., Fosse., G (2018) Pan-European climate convetion permitting scale : a model intercomparison study . Climate Dynammics Stratton A. R., Senior A. C., Vosper B. S. A Pan African Convection-Permitting Regional Climate Simulation with the Met Office Unified Model: CP4-Africa. Journal of Climate, 2018

Ninth RegCM Workshop, May-June 2018, ICTP Trieste (Italy)

an overview on convec,on-permi0ng climate modelingindico.ictp.it › event › 8313 › session ›...

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