**elicit expert knowledge to select relevant climate...

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?