1)Projec6onsthatreflectrealitygivenconstraintsofGCMsandoceaniccontext.2)Simulateprecipita6onandothercovariatesresponsetotheanthropogenicforcingsacrossPuertoRico.
**Elicitexpertknowledgetoselectrelevantclimatevariables.
To30-km
To10-km
To2-km
Chosetousedynamicaldownscaling
To30-km
To10-km
To2-km
OURGOAL:2-KMHorizontalResoluWonWithHourlyOutput
UsingmulWpleRCM-GCMcombinaWons
RSM
NHM
WeatherResearchandForecasWngModel(WRF)
RegionalSpectralModel(RSM)andtheNon-HydrostaWcModel(NHM)
RSM
NHM
WeatherResearchandForecasWngModel(WRF)
RegionalSpectralModel(RSM)andtheNon-HydrostaWcModel(NHM)
Collabora6onwithVasuMisraatFSU
SelectGlobalClimateModelstoDownscaleScenarioRCP8.5(HighGHGEmissions)
Historical(1986-2005)andFuture(2041-2060)*indicatescompleted
CNRM-CM5 CCSM4 GFDL-CM5
WRF RSM-NHM
WRF-CCSM4*RSM-NHM-CCSM4*
WRF-CNRM-CM5* RSM-NHM-GFDL-CM5
ExperimentalDesignforRegionalClimateModeling
• THREEGCMs– CCSM4,CNRM5,GFDL-CM3
• TWORCMs– WRF,NHM-RSM
• TWO20yearperiods– 1986-2005(past)– 2040-2060(future)– RCP8.5–highfossilfuelemissionsscenario
42
ManyMorePhysicalVariablesAvailable(andrelaWonshipsbetweenvariablesaremaintained)
• Surface– Rainfall,Temperature,Humidity,winds,soilmoisture/temperature,runoff,evapotranspira6on,pressure
• Abovecanopy– Asabove,plusothers– Mixingheight,ver6calwinds
• Radia6on– Incoming,outgoing,diffuse,net,cloudfrac6on
• Diagnos6cVariables– Heightofcloudbase,– Sta6s6cal:HeatWavedura6on,extremes,percen6les,etc.
ManyMorePhysicalVariablesAvailable
• Surface– Rainfall,Temperature,Humidity,winds,soilmoisture/temperature,runoff,evapotranspira6on,pressure
• Abovecanopy– Asabove,plusothers– Mixingheight,ver6calwinds
• Radia6on– Incoming,outgoing,diffuse,net,cloudfrac6on
• Diagnos6cVariables– Heightofcloudbase,– Sta6s6cal:HeatWavedura6on,extremes,percen6les,etc.
Time,Storage,andProcessingConstraints=>CannotRetainAll
VariablesatAllTimeSteps
2-DayStakeholderworkshophostedbyCLCCinSanJuantorefineclimatemodeloutput
IDEAISTOHAVECLIMATEPROJECTIONSTHATARESPECIFICTOTHEDECISION,BUTALSO
RELEVANTTOOTHERSCIENTIFIC/ECOLOGICALQUESTIONS
HowcouldclimatechangeaffectshadecoffeeproducWon?
Providingpublicgoods
Follow-upworkshopinAugust2016todiscussavailablemodelingoutputs
Providingpublicgoods
Rankclimatevariablesbasedonecologicalsignificance
Usedthisdialoguetohelpretainnecessaryclimatemodeldata
DownscaledClimateVariables
Wereduced~1Petabyteofmodeloutputto<20TBwiththeknowledgeofclimatevariablestoretainfrompriorworkshop
Exceeded1millionCPUhourstoaccomplishthedownscalingforjustoneoftheregionalclimatemodels.
Maximum2-mTemperatureChangeannualaverage
PrecipitaConChangepercentchangefortheannualtotal
ECOREGIONANALYSIS
(Subtropicalwetforest-wetseason)
>1”/hr
Hourlyrainfallbin%difference
ProjectedChangesSoilMoisture
Low-levelCloudFracWon
p(Occupancy | Temperature)
Temperature (°C)
Den
sity
20 22 24 26 28 30
0.00
0.02
0.04
0.06
0.08
0.10
p(Occupancy | Precipitation)
Annual Precip (mm/yr)
Den
sity
0 500 1000 1500 2000
0e+0
01e−0
42e−0
43e−0
44e−0
45e−0
4
p(Occupancy | Dry Seas Soil Moisture)
Soil Moisture (%)
Den
sity
0 20 40 60 80 100
0.00
00.
002
0.00
40.
006
0.00
80.
010
p(Occupancy | Temperature)
Temperature (°C)
Den
sity
20 25 30
0.00
0.05
0.10
0.15
p(Occupancy | Precipitation)
Annual Precip (mm/yr)
Den
sity
−500 0 500 1000 1500 2000 2500
0.00
000.
0002
0.00
040.
0006
0.00
080.
0010
0.00
12
p(Occupancy | Dry Seas Soil Moisture)
Soil Moisture (%)
Den
sity
0.2 0.4 0.6 0.8 1.0
0.0
0.5
1.0
1.5
2.0
2.5
Temperature
Precipita6on
SoilMoisture
00.10.20.30.40.50.60.70.80.91
0 1002003004005006007008009001000
LocalO
ccup
ancy
Prob
ability(P
si)
00.10.20.30.40.50.60.70.80.91
0 1002003004005006007008009001000LocalO
ccup
ancyProab
ility
(Psi)
ElevaWon(m),PrecipitaWon
E.wightmanae
E.brifoni
Whataretheenvironmentallimitsofthesespecies?
Useacous6crecorderstoes6mateoccupancyofthreespeciesacrossenvironmentalgradients
EsWmateoccupancybasedonrecordedcalls
Howcouldthesegradientschangewithclimatechange?
Precipita6on
La6tud
e
Longitude
00.10.20.30.40.50.60.70.80.91
0 100 200 300 400 500 600 700 800 900 1000
LocalO
ccup
ancyProba
bility
(Psi)
00.10.20.30.40.50.60.70.80.91
0 100 200 300 400 500 600 700 800 900 1000LocalO
ccup
ancyProab
ility
(Psi)
ElevaWon(m),PrecipitaWon
E.wightmanae
E.brifoni
NEXTSTEPS
Nextsteps:Exploreresilienceofwindwardslopes
ElYunqueCaribbeanNa6onalRainforest
PotenCaltocoupletoWRF-HydroModel
ElYunqueCaribbeanNa6onalRainforest
Hybriddownscaling
SelectGlobalClimateModelstoDownscaleScenarioRCP8.5(HighGHGEmissions)
Historical(1986-2005)andFuture(2041-2060)*indicatescompleted
CNRM-CM5 CCSM4 GFDL-CM5
WRF RSM-NHM
WRF-CCSM4*RSM-NHM-CCSM4*
WRF-CNRM-CM5* RSM-NHM-GFDL-CM5
GlobalClimateModelstoDownscaleScenarioRCP8.5(HighGHGEmissions)Historical(1986-2005)andFuture(2041-2060)
CNRM-CM5 CCSM4 GFDL-CM5
WRF RSM-NHM
WRF-CCSM4RSM-NHM-CCSM4
WRF-CNRM-CM5 RSM-NHM-GFDL-CM5
ARRM-WRF-CNRM-CM5 ARRM-WRF-CCSM4
Combiningsta6s6calanddynamicaldownscalingapproaches
CCSM4(GCM)
OBS
Combiningsta6s6calanddynamicaldownscalingapproaches
RCM OBS
Combiningsta6s6calanddynamicaldownscalingapproaches
Sta6s6calModel
OBS
Combiningsta6s6calanddynamicaldownscalingapproaches
Hybrid
OBS
Takingoccupancymodelingastepfurther.Isreproduc6onoccurringatoccupiedsites?Aresitesbeingoccupiedbyafewindividualsorby“many”?Plusgene6cworktoestablishpopula6onstructure.
Augment field work with terraria experiments to test eco-physiological limits (w/colleagues at Univ. Puerto Rico)
GeoDataPortal(GDP)
Web-basedaccesstoandprocessingofglobalchangedatatoaddressclimateandlandscapechange
THANKS!QUESTIONS?