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
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
hoursmm0 2 4 6 8 10 0 4 8 12 16 20 24
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
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¬&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
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
EXTREMEPRECIPITATION
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
EXTREMEPRECIPITATION
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)inboth2.2Kmmodelispresenteverywhereonland
OBS
Low
Moderate
Intensee
<2mm/h
<8mm/h
>8mm/h
EXTREMEPRECIPITATION
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
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)
RegCM V4.7.0: Convec,on permi0ng
CASESTUDY3:LakeVictoriaon26Nov-1Dec1999(Ralphetal.,2006)
OBSTRMM60hacc.Prec(mm)
RegCM3Km(standardTemp)
RegCM3Km(T°change)
RegCM V4.7.0: Convec,on permi0ng
CASESTUDY3:LakeVictoriaon26Nov-1Dec1999(Ralphetal.,2006)
OBSTRMM60hacc.Prec(mm)
RegCM12km
RegCM3Km
RegCM V4.7.0: Convec,on permi0ng
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)