science and applications traceability matrix · 2) to what extent do clouds and precipitation...

A-CCPAerosols and Clouds-Convection-Precipitation Study

Science and Applications Traceability Matrix

PublicReleaseA19February2019

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A-CCP SATM Navigation Map

Goal1-CloudFeedbacks

Goal2-StormDynamics

Goal3-FallingSnowOverarchingA-

CCPGoal

O5Geophys.Vars.

O2Geophys.Vars.

O3Geophys.Vars.

O8Geophys.Vars.

O9Geophys.Vars.

O6Geophys.Vars.

O4Geophys.Vars.

O7Geophys.Vars.

O10Geophys.Vars.

ClickonBlueLinesorText

Linksto:❑ GeophysicalVariableTables❑ EnabledApplicationTables❑ DecadalSurveyTables❑ Acronyms

WorkinProgress

O1-Observables

O5-Observables

O2-Observables

O3-Observables

O4-Observables

O6-Observables

O7-Observables

O8-Observables

O9-Observables

O10-Observables

Goal4-AerosolProcesses

Goal5-AerosolRad.Forcing

Objective5–AerosolRedistribution

Objective1–LowClouds

Objective2–HighClouds

Objective3–ConvectiveStorms

Objective8–AbsorbingAerosols

Objective9–AerosolDirectEffect

Objective6–AerosolAttribution

Objective4–FallingSnowProcesses

Objective7–AirQuality

Objective10–AerosolIndirectEffect

O1Geophys.Vars.

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Overarching GoalOverarchingA-CCPGoal A+CC

PA CCP

2017DSMostImportantVeryImportant

Goals

Understandtheprocessingofwaterandaerosolthroughtheatmosphereanddevelopthe

societalapplicationsenabledfromthisunderstanding.

C-2a,C-2g,W-1a,W-2a

G1CloudFeedbacks

Reducetheuncertaintyinlow-andhigh-cloudclimatefeedbacksbyadvancingourabilitytopredictthepropertiesoflowandhighclouds.

C-2g,C-5c,H-1b,W-1a,W-2a,W-4a

G2StormDynamics

Improveourphysicalunderstandingandmodelrepresentationsofcloud,precipitationanddynamicalprocesseswithinstorms.

H-1b,H-1c,W-1a,S-4a

G3FallingSnow

Toadvanceunderstandingofitsroleincryospheric-climatefeedbacks,quantifytherateoffallingsnow,particularlyatmiddletohighlatitudes.

W-1a,W-5a,C-5a

G4AerosolProcesses

Reduceuncertaintyinkeyprocessesthatlinkaerosolstoweather,climateandairqualityrelatedimpacts.

D

C-2h,C-5c G5AerosolRadiativeForcing

ReducetheuncertaintyinDirect(D)andIndirect(I)aerosol-relatedradiativeforcingoftheclimatesystem.I

Goalonlyfullyrealizableviacombinedmission. AorCCPmakesmeaningfulcontributiontogoal

�3

Goal 1: Cloud FeedbacksA+CCP

A CCP Goal OverarchingScienceQuestions Objectives

G1CloudFeedbacks

Reducetheuncertaintyinlow-andhigh-cloudclimatefeedbacksbyadvancingourabilitytopredictthepropertiesoflowandhighclouds

1)Towhatextentcanthepropertiesoflowcloudsbedeterminedbyenvironmentalfactors?

2)2)Howdothepropertiesandformationofhighcloudsrelateto(i)deepconvectionand(ii)large-scaleenvironmentalfactors?

O1LowClouds

Minimum:Determinethesensitivityofboundarylayerbulkcloudphysicalandradiativepropertiestolarge-scaleandlocalenvironmentalfactorsincludingthermodynamicanddynamicproperties.

Enhanced:AddstoMinimumcloudmicrophysicalpropertiesandenhancedbulkcloudproperties.O2HighClouds

Minimum:1) Relatetheverticalstructure,horizontalextent,icewaterpath,and

radiativepropertiesofconvectivelygeneratedhighcloudstoconvectiveverticaltransport

2) Relatetheverticalstructure,horizontalextent,icewaterpath,andradiativepropertiesoflargescalehighcloudstoenvironmentalfactors.

Enhanced:AddstoMinimummicrophysicalpropertiesoficeclouds.

�4

Goal 2: Storm DynamicsA+CCP

A CCP Goal OverarchingScienceQuestion Objectives

G2StormDynamics


Howdodifferentconvectivestormsystemscontributetotheverticalmixingandtransportsofheat,water,andotherconstituentswithintheatmosphereandhowdothesetransportsrelatetothecloudandprecipitationpropertiesofstorms?

O3ConvectiveStorms

Minimum:Relateverticalmotionwithinconvectivestormsanditscloud-andprecipitation-structurestoa)stormlifecycle,b)localenvironmentthermodynamicandkinematicfactorssuchastemperature,humidity,andverticalwindshear,c)ambientaerosols,andd)surfaceproperties.

Enhanced:Relateverticalmotionwithinconvectivestormsandotherstormtypesandtheircloud-andprecipitation-structurestoa)latentheatingprofiles,b)stormlifecycle,c)localenvironmentthermodynamicandkinematicfactorssuchastemperature,humidity,andverticalwindshear,d)ambientaerosols,ande)surfaceproperties.

�5

Goal 3: Falling SnowA+CCP


G3FallingSnow


1) Whatlarge-andmesoscalefactorsdeterminethearealextentandintensityofsnowfall.

2)2) Towhatextentdocloudsand

precipitationinfluencethesurfacemassandenergybalancesatEarth’sicecoveredsurface?

O4FallingSnowProcesses

Minimum:Detectandquantifyverticalprofilesoffallingsnowrateandrelatethesetocloudphysicalproperties,meteorologicalforcingandregime,orography,andlandsurfaceproperties.

Enhanced:EnhancementofMinimumwithanadditionalfocusonthesurfaceenergybalanceparticularlyathigherlatitudes.

�6

Goal 4: Aerosol ProcessesA+CCP

A CCP Goal OverarchingScience

Questions Objectives

G4AerosolProcesses


1)1) Whatarethemajor

anthropogenicandnaturalsourcesofaerosolandhowdotheyvaryspatiallyandtemporally?

2)2) Whatarethefactors

thatrelateAODtosurfacePMconcentrations?

3)3) Towhatextentdoes

long-rangetransportofsmoke,dust,andotherparticulatesimpactregionalnear-surfaceairquality?

O5AerosolRedistribution

Minimum:Characterizetheremovalandredistributionofaerosolsbycloudsandlightprecipitation(<2mm/hr).

Enhanced:Characterizetheremovalandredistributionofaerosolsbycloudsandheavyprecipitation(>2mm/hr).

O6AerosolAttributionMinimum:Determineaerosolspeciationtoquantifythecontributionsofdifferentaerosoltypestoobservedaerosolpropertiesandimproveemissionestimatesofthedifferentaerosolsources.

Enhanced:Characterizechangesinaerosolamountsandpropertiesoverspaceandtimeintermsof3Dtransportandspatiallyresolvedemissionsources.

O7AirQuality

Minimum:Enhanceunderstandingoftheprocessescontrollingboundarylayerandnearsurfacespeciatedextinctionasmeanstoconstrainairqualitypredictionsandestimatesofhumanhealthimpacts.

Enhanced:DeterminethespatialandtemporalvariationsinboundarylayerandnearsurfacespeciatedPMconcentrationsasmeanstoconstrainairqualitypredictionsandestimatesofhumanhealthimpacts. �7

Goal 5: Aerosol Rad. ForcingA+CCP


G5AerosolRadiativeForcing

ReducetheuncertaintyinDirect(D)andIndirect(I)aerosol-relatedradiativeforcingoftheclimatesystem.

1) WhatistheroleofabsorbingaerosolsintheEarth’sradiationbudget?

2)2) Howdochangesin

anthropogenicaerosolsaffectEarth’sradiationbudgetandoffsetthewarmingduetogreenhousegases?

3)3) Underwhatconditionsdo

aerosolsimpactthealbedoorcoverageofshallowclouds?

O8AbsorbingAerosolsMinimum:QuantifytheimpactofabsorbingaerosolontheEarth’sradiativebalanceatTOAandsurface,andonatmosphericstability.Enhanced:Quantifytheimpactofabsorbingaerosolsonverticallyresolvedradiativeheatingrates.

O9AerosolDirectEffectMinimum:Reduceuncertaintiesinestimatesofglobalmeanclearandall-skyshortwavedirectradiativeeffects(DRE)to±1.2W/m2atTOAand±0.6W/m2atsurfacewithcommensurateimprovementsinregionalestimatesofDREandanthropogenicaerosolradiativeforcing.Enhanced:Quantifyverticallyresolvedaerosolradiativeforcings.

O10AerosolIndirectEffectMinimum:Provideprocesslevelconstraintsonaerosol-warmcloudinteractionsasameanstoconstrainestimatesofaerosolindirectradiativeforcings.Enhanced:Provideprocesslevelconstraintsonaerosol-coldcloudinteractionsasameanstoconstrainestimatesofaerosolindirectradiativeforcing.

�8

Obj 1: Low CloudsA CC

P

ODO

POR PEA# GeophysicalVariables Qualifiers

Minimum

√ S (√) 1 Cloudliquidwaterpath

√ S (√) 1,2,7,9 Cloudopticaldepth

√ S (√) 1,2,7,9,15 Clouddropleteffectiveradius

√ √ S (√) 1,2,7,9,15,16

Cloudtopphase

√ √ (√) 1,2,7,9,15,16

Cloudtopheight

√ S (√) 1,2,7,9,15 Arealcloudfraction

√ (√) Precipitationphase

√ (√) 1,15,16 Precipitationrateprofile <2mm/hr

√ (√) PBLheight

√ Synopticscalemotion

√ Environmentalthermodynamicprofiles

√ (√) Cloudalbedo Derived

Enhanced(=Minimum+)

√ 1,2 Clouddropletconcentration Layer

√ √ 1,2,7,9, Cloudbaseheight

√ (√) 1 Totalwaterpath

√ 1, Volumetriccloudfraction

√ 1,2,7 Diurnallyresolvedcloudcover

S (√) Surfaceturbulentfluxes(landandocean)

A+CCP

A CCP Objectives

O1LowClouds

Minimum:Determinethesensitivityofboundarylayerbulkcloudphysicalandradiativepropertiestolarge-scaleandlocalenvironmentalfactorsincludingthermodynamicanddynamicproperties.

Enhanced:AddstoMinimumcloudmicrophysicalpropertiesandenhancedbulkcloudproperties.

�9

A+CCPPotentialEnabledApplications

PEA1Weather,agriculture,energyandairqualitymodeling(NWPcenters,USDA,IBM,AFWA,PrivateCompanies)

PEA2Issuingalertsoffog/vog(airqualityandweathercommunities)PEA7Cloudevolutionforaviationandweatherprediction(FAA,DoD,DoE,NOAA)PEA9Icingandvisibilityhazardsforaviationindustry(FAA,AFWA,Airlines,NOAA)PEA15Stormwarningsforlightningandseverestormdevelopment(AFWA,NWS,

andNWPmodelingcommunities)PEA16Forecastingsnowandmixedprecipitationevents(NWPmodeling

communities,privateweathercompanies)

Legend:√Neededtomeetobjective,(√)FromPoRbutinsufficienttomeetobjective,SComplimentaryobservationfromSBG,MComplimentaryobservationfromMC

Obj 2: High CloudsA+CCP

ACCP Objectives

O2HighClouds

Minimum:1) Relatetheverticalstructure,horizontal

extent,icewaterpath,andradiativepropertiesofconvectivelygeneratedhighcloudstoconvectiveverticaltransport

2) Relatetheverticalstructure,horizontalextent,icewaterpath,andradiativepropertiesoflargescalehighcloudstoenvironmentalfactors.

Enhanced:AddstoThresholdmicrophysicalpropertiesoficeclouds.

A CCP

ODO


Minimum

√ √ S (√) Icewaterpath

√ √ S (√) 9,10,15 Cloudopticaldepth

√ √ 9,10,15 Cloudbaseheight

√ √ (√) 9,10,15 Cloudtopheight

√ (√) 9,10,15 Cloudtoptemperature

√ 9,10,15 Cloudarealextent

√ 10 Diurnallyresolvedcloudcoverandcloudtopheight

√ 10,15Verticalairvelocity Above5km,>2

m/s

√ √ 9,10,15 Cloudverticalstructure

√ 9,10,15 Meltinglayerdetection(baseandtopheight)

√ 15 Cloudlifecyclecategories


√ Cloudradiativeeffects,SWLW

√ 10,15 Environmentalthermodynamicprofiles

Enhanced(=Minimum+)

√ √ 9,10,15 Icecrystalnumberconcentration Layer

√ √ S 9,10,15 Bulkcrystalsize,includingeffectiveradius

√ √ 9,10,15 Convectivecloudcover

√ (√) 9,10,15 Cloudverticalstructure Inconvection

√ √ Verticalprofileofradiativeheating

�10


PEA9Icingandvisibilityhazardsforaviationindustry(FAA,AFWA,Airlines,NOAA)

PEA10Characterizationofhaileventsanddamage(NWPcommunities,reinsurance,andagriculturalcommunities)

PEA15Stormwarningsforlightningandseverestormdevelopment(AFWA,NWS,andNWPmodelingcommunities)


Obj 3: Convective StormsA CC

P

ODO


Minimum

√ 3,4,10,12-15 Verticalairvelocity Above5km,>2m/s

√ √ (√) 3,4,6,7,8,10,15,16 Cloudtopheight

√ (√) 3,4,6,7,8,10,15,16 Cloudtoptemperature

√ (√) 3,4 Icewaterpath

√ (√) 3,4,7,12-15 Convectiveclassification

√ 3,4,6,7,15 Cloudlifecyclecategories

√ Diurnallyresolvedcloudcoverandcloudtopheight

√ (√) 3,4,6,8,11-16 Precipitationrateprofile

√ (√) 3,4,15 Cloudverticalstructure Inconvection,abovemeltinglayer

√ (√) 3,4,10,15,16 Meltinglayerdetection(baseandtopheight)

√ (√) 4,7,10,15 Stratiform/convectiveprecipitationdiscrimination

√ 3,4,6 Aerosolextinctionprofile

√ S (√) AOD Column,PBL

√ Synopticscalemotion Environmentalshear


Enhanced(=Minimum+)

√ (√) 3,4,8 Latentheatingprofile

√ (√) 3,4,6,10-16 Precipitationphase

√ (√) 3,4,6,10,15,16 Precipitationparticlesize

√ 3,7,10,12-15 Convectivecoresize

√ 3,4 Aerosoleffectiveradius Profile

√ 3,4 Aerosolnon-sphericity Profile&column

√ 3,4 AAOD Profile


PEA3-Aerosolsimpactonprecipitationandstormdevelopment(NOAA,NWPcenters,IBM)PEA4-Improvedmodelinitializationofaerosolsandseverestormdevelopment(NWPandmodelcomm.)PEA6-GeospatialAnalytics–Bigdataforplanetaryresourcesurveillance(Defense

department,publicandprivateindustry,IBM)PEA7-Cloudevolutionforaviationandweatherprediction(FAA,DoD,DoE,NOAA)PEA8-Cloudparameterizationsformodelinitiation(NWPandmodelingcommunities)PEA10–Characterizationofhaileventsanddamage(NWP,reinsurance,andagricultural)PEA11-Hydrologicmodeling,diseasetracking,animalmigration,insurancemodelingand

disasterapplications(CDC,NOAA,RedCross,WorldBank,public/privatesector)PEA12-Forecastingheavyrain,snow,floodingevents(NOAA,DoD,FAO,reinsurance)PEA13-Floodandlandslidemonitoringandforecastinginmountains(NOAA,FEMA,USGS)PEA14-Streamflow,flooding,drought,energy,andagriculturalmonitoringandmodeling

(USDA,Waterresourcemanagers)PEA15-Warningsforlightning,severestormdevelopment(NWPmodelingcommunities)PEA16-Forecastingsnow/mixedprecipitationevents(NWP,privateweathercompanies)

A+CCP

A CCP Objectives

O3ConvectiveStorms

Minimum:Relateverticalmotionwithinconvectivestormsanditscloud-andprecipitation-structurestoa)stormlifecycle,b)localenvironmentthermodynamicandkinematicfactorssuchastemperature,humidity,andverticalwindshear,c)ambientaerosols,andd)surfaceproperties.

Enhanced:Relateverticalmotionwithinconvectivestormsandotherstormtypesandtheircloud-andprecipitation-structurestoa)latentheatingprofiles,b)stormlifecycle,c)localenvironmentthermodynamicandkinematicfactorssuchastemperature,humidity,andverticalwindshear,d)ambientaerosols,ande)surfaceproperties.

�11


PEA6-GeospatialAnalytics–Bigdataforplanetaryresourcesurveillance(Defensedepartment,publicandprivateindustry,IBM)

PEA11-Hydrologicmodeling,diseasetracking,animalmigration,insurancemodelinganddisasterapplications(CDC,NOAA,RedCross,WorldBank,public/privatecomp.)PEA12-Forecastingheavyrain,snow,floodingevents(NOAA,DoD,FAO,reinsurance)PEA13-Floodandlandslidemonitoringandforecastingwithinmountainenvironments

(modelingandemergencyresponsecommunities,NGOs,PDC)PEA14-Streamflow,flooding,drought,energy,andagriculturalmonitoringand

modeling(USDA,Waterresourcemanagers)PEA16-Forecastingsnow/mixedprecipitationevents(NWP,privateweather

companies)

Obj 4: Falling Snow ProcessesA+CCP

ACCP Objectives


Minimum:Detectandquantifyverticalprofilesoffallingsnowrateandrelatethesetocloudphysicalproperties,meteorologicalforcingandregime,orography,andlandsurfaceproperties.

Enhanced:EnhancementofMinimumwithanadditionalfocusonthesurfaceenergybalanceparticularlyathigherlatitudes.

A CCP

ODO


Minimum

√ √ 6,16 Cloudtopheight

√ 6,16 Cloudtoptemperature

√ 6,11-14,16 Icewaterpath

√ M (√) 6,11-14,16 Surfaceornearsurfaceprecipitationrate

√ 11-14,16 Verticalairvelocity >2m/s

√ (√) 6,11-14,16 Precipitationrateprofile

√ 16 Cloudliquidwaterpath

√ (√) 6,11-14,16 Surfaceornearsurfaceprecipitationphase



Enhanced(=Minimum+)

√ 16 Bulksnowparticlesize

√ 11-14,16 Snowfallvertical(Doppler)motion <1m/s

√ 6 Volumetriccloudfraction

√ S 6,16 Cloudphase

√ 6,16 Blowingsurfacesnow

√ S (√) 6,16 Cloudopticaldepth

√ Watervaporadvection

√ √ √ Cloudradiativeeffects,LW&SW

√ √ √ Surfaceradiationbudget �12Legend:√Neededtomeetobjective,(√)FromPoRbutinsufficienttomeetobjective,SComplimentaryobservationfromSBG,MComplimentaryobservationfromMC

Obj 5: Aerosol RedistributionA+CCP

A CCP

Objectives


Minimum:Characterizetheremovalandredistributionofaerosolsbycloudsandlightprecipitation(<2mm/hr).

Enhanced:Characterizetheremovalandredistributionofaerosolsbycloudsandheavyprecipitation(>2mm/hr).

A CCP

ODO


Minimum

√ 3,4,5 Aerosolextinctionprofile

√ S (√) 3,4,5 AOD

√ (√) 1,3,4 Cloudliquidwaterpath

√ √ (√) 1,3,4,5 Cloudtopheight

√ S (√) 1,3,4,5 Cloudopticaldepth

√ S (√) 1,3,4,5 Clouddropleteffectiveradius

√ (√) 1,3,4 Surfaceornearsurfaceprecipitationrate <2mm/hr

√ (√) 1,3,4 Precipitationphase

√ (√) 1,3,4 Precipitationrateprofile

√ Synoptic-scalemotion


√ (√) PBLheight

Enhanced(=Minimum+)

√ 3,4,5 Finemodeaerosolextinctionprofile

√ Angstromexponent Column

√ (√) 1,3,4 Surfaceornearsurfaceprecipitationrate >2mm/hr

√ 1,3,4,5 Volumetriccloudfraction

√ 1,3,4.5 Verticalairvelocity >2m/s

√ (√) 1,3,4,5 Meltinglayerdetection(baseandtopheight)

�13


PEA1-Weather,agriculture,energyandairqualitymodeling(NWPcenters,USDA,IBM,AFWA,PrivateCompanies)

PEA3-Modeling/forecastingimpactofaerosolsonprecipitationandstormdevelopment(NOAA,NWPcenters,IBM)

PEA4-Improvedmodelinitializationofaerosolsandseverestormdevelopment(NWPandmodelcomm.)

PEA5-Estimateradiativefluxesforairqualitymodeling,solarinsolation,andagriculturalforecasting.




PEA2-Issuingalertsoffog/vog(airqualityandweathercommunities)PEA6-GeospatialAnalytics–Bigdataforplanetaryresourcesurveillance

(Defensedepartment,publicandprivateindustry,IBM)PEA17–Sourceattributionofpollution(EPA,NOAA,stateAQagencies)PEA18–Aviationindustryandsafety(FAA,VAACs,privateindustry:GE,

P&W,RR,NG)PEA19–Wildfiremanagement(EPA,NOAA,StateAQagencies)PEA20–Humanhealthstudies&healthriskestimation(CDC,WHO,NIH,

universities,reinsuranceindustry)PEA21–AQrule-making(EPA,stateAQagencies)PEA22–Operationalweather&AQforecasting(NOAA,stateAQagencies)

Obj 6: Aerosol AttributionA+CCP

A CCP

Objectives

O6AerosolAttributionMinimum:Determineaerosolspeciationtoquantifythecontributionsofdifferentaerosoltypestoobservedaerosolpropertiesandimproveemissionestimatesofthedifferentaerosolsources.

Enhanced:Characterizechangesinaerosolamountsandpropertiesoverspaceandtimeintermsof3Dtransportandspatiallyresolvedemissionsources.

A CCP

ODO


Minimum

√ 1,2,6,17-19,21,22

Aerosolextinctionprofile Totalandnon-spherical

√ 1,2,6,17-19 Aerosollayerheight

√ S (√) 1,6,19-22 AOD PBLandcolumn

√ 6,19,20 AAOD/SSA PBLandcolumn

√ 6,19,20,22 FinemodeAOD PBLandcolumn

√ (√) 17-20 Angstromexponent PBLandcolumn

√ (√) 17-20 Indexofrefraction Column

√ 17-20 Aerosolnon-sphericity Profile&column

√ (√) 1,2,6,19-22 PBLheight


Enhanced(=Minimum+)

√ 17,19,21,22 Aerosoleffectiveradius Profile

√ 17,19,21,22 Angstromexponent Profile


√ 17,19,21,22 Finemodeaerosolextinction Profile


√ 22 Verticalairvelocity >2m/s �14Legend:√Neededtomeetobjective,(√)FromPoRbutinsufficienttomeetobjective,SComplimentaryobservationfromSBG,MComplimentaryobservationfromMC

Obj 7: Air QualityA+CCP

ACCP Objectives

O7AirQuality

Minimum:Enhanceunderstandingoftheprocessescontrollingboundarylayerandnearsurfacespeciatedextinctionasmeanstoconstrainairqualitypredictionsandestimatesofhumanhealthimpacts.

Enhanced:DeterminethespatialandtemporalvariationsinboundarylayerandnearsurfacespeciatedPMconcentrationsasmeanstoconstrainairqualitypredictionsandestimatesofhumanhealthimpacts.

A CCPODO


Minimum

√ 6,19,21,22Aerosolextinctionprofile Totalandnon-

spherical

√ 6,17,19,21,22 Aerosollayerheight

√ S (√) 6,21,22 AOD PBLandcolumn

√ 6,17,21,22 AAOD/SSA PBLandcolumn

√ 6,17,19,21,22 FinemodeAOD PBLandcolumn

√ (√) 6,17,19,21,22 Angstromexponent PBLandcolumn

√ (√) 6,17,19,20,21,22

Indexofrefraction Column

√ 6,17,20,21,22 Aerosolnon-sphericity Profile&column

√ √ 6,17,20,21,22 PBLheight


Enhanced(=Minimum+)

√ (√) 17,19,20,21 PMconcentration

√ 17,19,20,21 Aerosoleffectiveradius Profile

√ 17,19,20,21 Angstromexponent Profile


√ 17,19,20,21 Finemodeaerosolextinctionprofile

√ Precursorgasconcentration�15


PEA6–GeospatialAnalytics–Bigdataforplanetaryresourcesurveillance(IBM,WeatherUnderground,etc.)

PEA17–Sourceattributionofpollution(EPA,NOAA,stateAQagencies)

PEA19–Wildfiremanagement(EPA,NOAA,StateAQagencies)PEA20–Humanhealthstudies&healthriskestimation(CDC,WHO,

NIH,universities,reinsuranceindustry)PEA21–AQrule-making(EPA,stateAQagencies)PEA22–Operationalweather&AQforecasting(NOAA,stateAQagencies)


what can we expect/use from PoR?

Obj 8: Absorbing AerosolsA+CCP

A CCP

Objectives

O8AbsorbingAerosolsMinimum:QuantifytheimpactofabsorbingaerosolontheEarth’sradiativebalanceatTOAandsurface,andonatmosphericstability.Enhanced:Quantifytheimpactofabsorbingaerosolsonverticallyresolvedradiativeheatingrates.

A CCP

ODO


Minimum

√ 3,6,20-22

Aerosolextinctionprofile

√ 3,6,17,20-22

Aerosollayerheight

√ S (√) 1,3,6,20-22

AOD PBLandcolumn

√ 17,20-22

AAOD PBLandcolumn


√ Surfacealbedo

√ 1,22 Cloudreflectance

√ √ (√) 1,22 Cloudtopheight

√ 1,22 TOAandsurfaceradiativefluxes(derived)

Enhanced(=Minimum+)

√ 3,6,20 Aerosolabsorptioncoefficientprofile

�16



PEA3-Aerosolsimpactonprecipitationandstormdevelopment(NOAA,NWPcenters,IBM)PEA6–GeospatialAnalytics–Bigdataforplanetaryresource

surveillance(IBM,WeatherUnderground,etc.)PEA17–Sourceattributionofpollution(EPA,NOAA,stateAQagencies)PEA20–Humanhealthstudies&healthriskestimation(CDC,WHO,

NIH,universities,reinsuranceindustry)PEA21–AQrule-making(EPA,stateAQagencies)PEA22Operationalweather&AQforecasting(NOAA,stateAQ

agencies)



PEA5–Estimateradiativefluxesforairqualitymodeling,solarinsolation,andagriculturalforecasting.–(EPA,CMAQ,WRFChem)PEA6–GeospatialAnalytics–Bigdataforplanetaryresourcesurveillance(IBM,WeatherUnderground,etc.)PEA17–Sourceattributionofpollution(EPA,NOAA,stateAQagencies)PEA20–Humanhealthstudies&healthriskestimation(CDC,WHO,NIH,

universities,reinsuranceindustry)PEA21–AQrule-making(EPA,stateAQagencies)PEA22–Operationalweather&AQforecasting(NOAA,stateAQagencies)

Obj 9: Aerosol Direct EffectA+CCP

ACCP Objectives

O9AerosolDirectEffectMinimum:Reduceuncertaintiesinestimatesofglobalmeanclearandall-skyshortwavedirectradiativeeffects(DRE)to±1.2W/m2atTOAand±1.6W/m2atsurfacewithcommensurateimprovementsinregionalestimatesofDREandanthropogenicaerosolradiativeforcing.Enhanced:Quantifyverticallyresolvedaerosolradiativeforcings.

A CCP

ODO


Minimum

√ 6,17,20,21,22 Aerosolextinctionprofile

√ 6,17,21,22 Aerosollayerheight

√ Non-sphericalaerosolextinctionprofile

√ S (√) 5,6,17,21,22 AOD Column

√ (√) 6,17,21,22 AAOD Column

√ (√) 5,6,17,21,22 FinemodeAOD Column

√ (√) 6,17,21,22 Angstromexponent Column

√ (√) 6,17,21,22 Indexofrefraction Column

√ 17,21 Aerosolnon-sphericity Profile&column


√ Surfacealbedo

√ 5,6,22 Cloudreflectance

x √ 5,6,22 Cloudtopheight

√ √ √ 5,6,22 TOAandsurfaceradiativefluxes(derived)

Enhanced(=Minimum+)

√ 17,20,21 Aerosoleffectiveradius Profile

√ 17,20,21 Angstromexponent Profile

√ 5,17,20,21 Aerosolabsorptioncoefficientprofile �17Legend:√Neededtomeetobjective,(√)FromPoRbutinsufficienttomeetobjective,SComplimentaryobservationfromSBG,MComplimentaryobservationfromMC

Obj 10: Aerosol Indirect Effect (1/2)A+CCP

A CCP

Objectives


(SeenextslideforEnhanced)

�18

A CCP

ODO POR PEA# GeophysicalVariables Qualifiers

Minimum

√ S (√) 6,17,21,22 AOD PBLandcolumn

√ 6,17,21,22 Angstromexponent PBLandcolumn

√ 6,17,21,22 FinemodeAOD PBLandcolumn

√ 6,17,21,22 Aerosolextinctionprofile

√ √ (√) 2,5,22 CloudLWP

√ (√) 2,5,22 Cloudopticaldepth

√ (√) 2,5,22 Clouddropleteffectiveradius

√ √ 2,5,22 Clouddropletconcentration Layer

√ 2,5,22 Cloudtopphase

√ x (√) 2,5,22 Cloudtopheight

√ √ 5 Arealcloudfraction

√ 5 Cloudreflectance

√ (√) Surfaceornearsurfaceprecipitationrate <2mm/hr

√ √ 6,17,20-22 PBLheight Lidarandreanalysis




PEA2-Issuingalertsoffog/vog(airqualityandweathercommunities)PEA5–Estimateradiativefluxesforairqualitymodeling,solar

insolation,andagriculturalforecasting.–(EPA,CMAQ,WRFChem)

PEA6–GeospatialAnalytics–Bigdataforplanetaryresourcesurveillance(IBM,WeatherUnderground,etc.)

PEA17–Sourceattributionofpollution(EPA,NOAA,stateAQagencies)PEA20–Humanhealthstudies&healthriskestimation(CDC,WHO,

NIH,universities,reinsuranceindustry)PEA21–AQrule-making(EPA,stateAQagencies)PEA22–Operationalweather&AQforecasting(NOAA,stateAQ

agencies)


Obj 10: Aerosol Indirect Effect (2/2)A+CCP

ACCP Objectives


A CCP

ODO


Enhanced(=Minimum+)

√ 6,17,20-22 PBLaerosolnumberconcentration

√ 6,17,20-22 Aerosoleffectiveradius PBL

√ √ 2,22 Clouddropletconcentration Layer

√ 2,22 Cloudtopextinction

2,22 Cloudtopdropletsize

2,22 Cloudtopdropletconcentration

√ √ 2,22 Cloudbaseheight

√ 17,22 Verticalairvelocity >1m/s

√ (√) 22 Precipitationphase

√ Diurnallyresolvedcloudcover

√ Surfaceturbulentfluxes(landandocean)

√ √ 6,22 Icecrystalnumberconcentration

√ √ 6,22 Icecrystalparticlesize


PEA6–GeospatialAnalytics–Bigdataforplanetaryresourcesurveillance(IBM,WeatherUnderground,etc.)PEA17–Sourceattributionofpollution(EPA,NOAA,stateAQagencies)PEA20–Humanhealthstudies&healthriskestimation(CDC,WHO,

NIH,universities,reinsuranceindustry)PEA21–AQrule-making(EPA,stateAQagencies)PEA22–Operationalweather&AQforecasting(NOAA,stateAQagencies)

�19Legend:√Neededtomeetobjective,(√)FromPoRbutinsufficienttomeetobjective,SComplimentaryobservationfromSBG,MComplimentaryobservationfromMC

Geo. Vars: O1 Low Clouds (1/2)

!20

O1LowCloudsGeophysicalVariables

DesiredCapability

Observables NotesRange Precision/

Accuracy

Resolution

Δx Δz Swath

Minimum

Cloud LWP 20-400gm-2 20 gm-2 fp VIS + SWNIR reflection ~5%, µwave radiances NEΔT~ 3K matched to radar, radar reflectivity Z<-15dBZ

Uwave and optical based methods match under carefully prescribed conditions

Cloud optical depth 0.3-100 15% 20km VIS reflectance, ~3%

Cloud droplet effective radius

4-100 µm 2µm ~ 3 OD

20km VIS + SWNIR reflection ~ 3% Re is needed as deep into cloud as we can get - (~3 OD) for purpose of deriving LWP - 2.1um Re aPEArs to most optimally match uwave based LWP

Cloud top phase Liquid,Solid or mixed

30% ~ 1 OD

fp Polarized backscatter , Δβ>0.05km-1, SWNIR reflectance ~5%

also with DOLP

Cloud top height 0.5-15km 100m 100m fp VIS backscatter, Δβ>0.05km-1 Expect to address this this from lidar backscatter

Areal cloud fraction 0.05-1.00 5% N/A 20km VIS reflection ~5% Cloud amount matched radar/lidar footprints and will be used in diagnostic analysis

Precipitation phase Liquid,Solid or mixed

30% 5km N/A fp Z Bright band, ΔVr, polarimetric radar linear depolarization ratio (LDR; e.g., Ka > ~-15 dB), differential reflectivity ΔZ~2dBZ , dual-frequency ratio (snow index), polarimetric VIS backscatter , Δβ>??5km-1

Basic separation of liquid and frozen phases in stratiform is most straight forward.

Precipitation rate profile <2 mm/hr

PBL height <3 km 250 m GPS RO might be source

(continue…)

Geo. Vars: O1 Low clouds (2/2)

O1LowCloudsGeophysicalVariables

DesiredCapability

Observables NotesRange PrecisionA

ccuracy

Resolution

Δx Δz Swath

Minimum (continued)

Synoptic scale motion From met analysis

Environmental thermodynamic profiles

From met analysis

Cloud Albedo (derived) 0.1-0.8 5% absolute

5km N/A fp A calculated quantity with threshold inputs. Can then be cross calibrated with PoR (CERES & EVC)

Enhanced

Cloud droplet concentration 10-1000 cm-3

50% 1km VIS + SWNIR reflection ~5%, µwave radiances NEΔT~ 3K matched to radar, radar reflectivity Z<-15dBZ

We are advocating a completely new approach using cloud and precip data jointly.

Cloud base height 250 m-15 km

250 m 250m Radar reflectivity >35GHz

Total water path (cloud+precipitation)

20-400 gm-2

20 gm-2 1km N/A fp VIS + SWNIR reflection ~5%, µwave radiances NEΔT~ 3K matched to radar, radar reflectivity Z<-15dBZ

Volumetric cloud fraction

Diurnally resolved cloud cover 0.05-1.00 5% 5km N/A wide VIS reflection/IR - Geostationary from PoR For context only

Surface turbulent fluxes (land and ocean)

TBD - this is a link to SBG

!21

Geo. Vars: O2 High Clouds

!22

O2HighCloudsGeophysicalVariables

DesiredCapability

Observables NotesRange Precision

Accuracy

Resolution

Δx Δz Swath

Minimum

Enhanced

PlaceHo

lder

Geo. Vars: O3 Convective Storms

!23

O3ConvectiveStormsGeophysicalVariables

DesiredCapability


Accuracy

Resolution

Δx Δz Swath

Minimum

Enhanced

PlaceHo

lder

Geo. Vars: O4 Falling Snow Processes

!24


GeophysicalVariables

DesiredCapability


Accuracy

Resolution

Δx Δz Swath

Minimum

Enhanced

PlaceHo

lder

Geo. Vars: O5 Aerosol Redistribution



DesiredCapability


Accuracy

Resolution

Δx Δz Swath

Minimum

Enhanced

PlaceHo

lder

Geo. Vars: O6 Aerosol Attribution

!26

O6AerosolAttributionGeophysicalVariables

DesiredCapability


Accuracy

Resolution

Δx Δz Swath

Minimum

Enhanced

PlaceHo

lder

Geo. Vars: O7 Air Quality

!27

O7AirQualityGeophysicalVariables

DesiredCapability


Accuracy

Resolution

Δx Δz Swath

Minimum

Enhanced

PlaceHo

lder

Geo. Vars: O8 Absorbing Aerosols

!28

O8AbsorbingAerosolsGeophysicalVariables

DesiredCapability


Accuracy

Resolution

Δx Δz Swath

Minimum

Enhanced

PlaceHo

lder

Geo. Vars: O9 Aerosol Direct Effect

!29

O9AerosolDirectEffect


DesiredCapability


Accuracy

Resolution

Δx Δz Swath

Minimum

Enhanced

PlaceHo

lder

Geo. Vars: O10 Aerosol Ind. Effect

!30

O10AerosolIndirectEffect


DesiredCapability


Accuracy

Resolution

Δx Δz Swath

Minimum

Enhanced

PlaceHo

lder

Enabled Applications: 1-8Enabled Applications: 1-8A+CCP

A CCP

PEA#

EnabledApplications Partners GeophysicalVariablesRelevant

Objective(s)

X 1Cloudandprecipitationpropertiesenabletheweatherpredictionandmodelingcommunitiestoimproveparameterizationsofcloudstoimproveweatherforecasting,energyplanning,airqualitymodeling,andagricultureforecasting.

NWPCenters(NOAA,NRL,ECMWF,JMA,NCAR),USDA,AFWA,IBM,PrivateCompanies

Cloudheight,depth,radius,amount,phase,precipitationrateandphase

O1,O5,O6,O8

X 2 Observationsofaerosolandcloudpropertiesusedbytheweatherandairqualitycommunitiestounderstandandissuealertsaboutthedevelopmentoffog/vog.

NOAA,NCAR,NASA,EPAandStateAgencies

Aerosolandcloudproperties O1,O6,O10

X 3Observationsofaerosolsandcloudsenabletheweatherforecastingandmodelingcommunitiestoimprovemodeling/forecastingtheimpactofaerosolsonprecipitationandstormdevelopment,includingcyclonesandhurricanes.

NOAA,NASA,NCAR,NWPmodelingcommunity,IBM

Aerosols,precipitation,andcloudproperties O3,O5,O8

X 4Observationsofaerosol,precipitationandcloudproperties,andverticalvelocitiesareusedtoimprovedmodelingofverticaltransport,scavenging,wetdeposition,andlinkstoiceparticlesandseverestormdevelopment.

NWS,NOAA,CTM,EPA,stateAQagencies,othermodelingcommunities

Verticalvelocity,aerosol,cloud,andprecipitationproperties O3,O5

X 5

Cloudandaerosolopticaldepthsareusedtoestimateradiativefluxesforapplicationssuchasestimatingavailablephotosyntheticallyactiveradiation(PAR)forairqualitymodeling,attenuatedsolarinsolationforsolarpowercompanies,andagriculturalforecasting.Solarpowercompaniesuseestimatesofsizeresolvedaerosolconcentrationsandprecipitationtomodeldryandwetdepositiononthepanels,respectively.

Airqualitymodelers(EPA,NOAA,stateagencies),solarenergycompanies,agriculturalcommunities

AerosolOpticalDepth,AerosolConcentrationProfiles,AerosolSpeciation,cloudproperties O5,O9,O10

X 6

Datafusiontechniquesthroughgeospatialanalyticsand“bigdata”managementrelyonaerosol,cloudandprecipitationpropertiestoprovidecontinuous,detailed,multidimensional,andglobalmonitoringasaninvaluabletoolforplanetaryresourcesurveillance.

Privateindustry(e.g.,IBM,WeatherUnderground),DefenseDepartment,publiccompanies(e.g.Marscorporation)

AerosolOpticalDepth,AerosolConcentrationProfiles,AerosolSpeciation,brightnesstemperatures,surfaceprecipitation

O3,O4,O6,O7,O8,O9,

O10

7 Observationsofcloudheightanddropletsenabletheaviationindustryandweatherpredictioncommunitytoimprovesituationalawarenessofcloudevolution.

NOAA,FAA,DoD,DoE Cloudphase,height,depth,radius,andamount

O1,O3

8Brightnesstemperatureandprecipitationratesenabletheweatherforecastingandmodelingcommunitiestoimprovestormtrackandintensityforecastsofhurricanesandseverestorms.

NOAA,NASA,NCAR,ECMWF,NRL,JTWC,andotherNWPcenters,IBM

Brightnesstemperature(Cloudtoptemperature)andprecipitationrates

O3

�31

Enabled Applications 9-16

A+CCP

ACCP

PEA#


Objective(s)

9Estimatesoficecontent,opticaldepthandcloudheightareusedbytheaviationindustrytoinformrimeicing,threatstoengineperformance,andvisibilityhazards.

NOAA,FAA,AFWA,AirlinesIcecontent,opticaldepthandcloudheight

O1,O2

10Informationonmicrophysicalpropertiescaninformthedevelopmentofhaileventsandareusedbytheweatherforecasting,reinsuranceandagriculturalcommunitiestoforecastandasseshaileventsanddamage.

NOAA,reinsurance,andagriculturalcommunities

Microphysicalproperties(cloudphase,verticalmotion,radius)

O2,O3

11

Surfaceprecipitationobservationsareusedbyarangeofpublicandprivatecommunities,internationalanddomesticgovernmentalorganizationsandNGOsasinputsintohydrologicmodels,vectorandwaterbornediseasemodeling,animalmigrationtracking,insurancemodels,anddisastersapplications.

CDC,NOAA,RedCross,NASA,reinsurance,WorldBankandagriculturalcommunities,publicandprivatecompanies(e.g.,Johnson&Johnson,Agvesto,MiCRO)

Surfaceprecipitation O3,O4

12Observationsofsurfaceprecipitationrateareusedbytheweatherforecastcommunitytoanticipateheavyrain,snow,orfloodinginareaswithgapsintheinsituobservationalnetwork.

NOAA,RedCross,NASA,FAO,USArmy,reinsurancecommunity


13Estimatesofextremeandorographicallyenhancedprecipitationwithinmountainousregionsareusedbythehydrologicmodelingandemergencyresponsecommunitiesformodeling/estimatingfloodingandlandslidehazards.

NOAA,RedCross,NASA,reinsurancecommunity,hydrologicmodelingcommunities,RedCross,NGOs,PDC


14

Estimatesoftotalwatervolumeandlong-termsurfaceprecipitationobservationsarecriticalforwaterresourcemanagers,agriculturalcommunities,andenergycompaniesforestimatingstreamflow,floodingandinundationimpacts,assessingdroughtconditions,andmodeling/forecastingcropyields.

USDA,WaterResourceManagementcommunity


15Estimatesoficecontent,andverticalmotionareusedbytheweatherforecastandNWPmodelingcommunitiesasaproxyforlightninginitiationtoanticipateseverestormdevelopment.

NOAA,AFWA,NWPmodelingcommunities

icecontentandverticalmotion O1,O2,O3

Observationsofcloud/precipitationverticalstructure,surfaceprecipitationrate,andNOAA,NWPmodeling

Cloud/precipitationvertical�32

Enabling Applications 17-22

A+CCP

ACCP

PEA#


Objective(s)

17Observationsofaerosolsareusedforsourceattributionofpollution,includinginterhemispherictransport.

FederalweatherandAQagencies(EPA,NOAA),stateAQagencies,othermodelingcommunities

AerosolOpticalDepth,AerosolConcentrationProfiles,AerosolSpeciation

O6,O9,O10

18

Observationsofaerosolsareusedtoestimateconcentrationsandlocationofvolcanicashandissueaviationsafetyalerts,whicharevitaltotheaviationcommunity.AircraftenginemanufacturersuseambientaerosolconcentrationdatatoassessimpactofPMonengineperformance.

AviationIndustry:FAA,VAACs,privateindustry(e.g.,GeneralElectric,PrattandWhitney,RollsRoyce,NorthropGrumman)

AerosolOpticalDepth,AerosolConcentrationProfiles,AerosolSpeciation O6

19Observationsofaerosolsareusedtoestimatewildfiresmokeinjectionheights,whichenablemoreaccurateinitializationofsmoketransportmodelsforimprovingairqualityforecastsandestimatingexposuretowildfirePMandco-emittedtracegaspollutants.

Wildfiremanagement:FederalAQagencies(EPA,NOAA,ForestService),stateAQagencies,othermodelingcommunities


O6,O7

20

Observationsofaerosolareusedtoinferspatio-temporalvariations&trendsofspeciatedsurface-levelPM(PM1,PM2.5,PM10),whichareusedforhealthstudies,suchastoassociatetheeffectsofexposuretoPMwithspecifichealthoutcomes,andtocalculatehealthrisksandlongevity.

Health:CDC,WHO,NIH,healthresearchersatuniversities(e.g.,GlobalBurdenofDisease),reinsuranceindustry


O6,O7,O9

21Observationsofaerosolareusedtoinferspatio-temporalvariations&trendsofspeciatedsurface-levelPM(PM1,PM2.5,PM10),whichusedtosupportAQrule-makinganddefineexceptionalevents.

AQRule-making:EPA,stateAQagencies


O6,O7,O9,O10

22Aerosolobservationsareusedtoinfervertically-resolved,speciatedPMforoperationalweatherandAQforecasting(e.g.,forecastinitialization),trackingdustplumes,andissuingAQalerts.

OperationalAQForecasts:Federal(NOAA)andstateAQagencies


O6,O7,O8,O9,O10

�33

DS Traceability Goals 1-22017DecadalSurveyObjectives

(fromAppendixB) A-CCPGoals

C-2a Reduce uncertainty in low and high cloud feedback. W-1a Determine the effects of key boundary layer processes on weather, hydrological, and air quality forecasts

at minutes to subseasonal time scales. W-2a Improve the observed and modeled representation of natural, low-frequency modes of weather/climate

variability. C-2g Quantify the contribution of the UTS to climate feedbacks and change.

G1CloudFeedbacks

Reducetheuncertaintyinlow-andhigh-cloudclimatefeedbacksbyadvancingourabilitytopredictthepropertiesoflowandhighclouds.

C-5c Quantify the effect that aerosol has on cloud. C-2g Quantify the contribution of the UTS to climate feedbacks and change. H-1b Quantify rates of precipitation and its phase (rain and snow/ice) worldwide at convective and orographic

scales suitable to capture flash floods and beyond. W-1a Determine the effects of key boundary layer processes on weather, hydrological, and air quality. W-2a Improve the observed and modeled representation of natural, low-frequency modes of weather/climate

variability. W-4a Measure the vertical motion within deep convection to within 1 m/s and heavy precipitation rates to within 1

mm/hour to improve model representation of extreme precipitation and to determine convective transport and redistribution of mass, moisture, momentum, and chemical species.

G2StormDynamics


MostImportant VeryImportant

DS Traceability Goals 3-52017DecadalSurveyObjectives

(fromAppendixB) A-CCPGoals

H-1b Quantify rates of precipitation and its phase (rain and snow/ice) worldwide at convective and orographic scales suitable to capture flash floods and beyond.

H-1c Quantify rates of snow accumulation, snowmelt, ice melt, and sublimation from snow and ice worldwide at scales driven by topographic variability.

W-1a Determine the effects of key boundary layer processes on weather, hydrological, and air quality. S-4a Quantify global, decadal landscape change produced by abrupt events and by continuous reshaping of

Earth's surface due to surface processes, tectonics, and societal activity. (Recommended measurement of rainfall and snowfall rates).

G3FallingSnow


W-1a (boundary layer processes) W-5a (air pollution and health) C-5a Improve estimates of the emissions of natural and anthropogenic aerosols

G4AerosolProcesses


C-2a Reduce uncertainty in low and high cloud feedback. C-2h Reduce aerosol radiative forcing uncertainty C-5c Quantify the effect that aerosol has on cloud

G5AerosolRadiativeForcing

ReducetheuncertaintyinDirect(D)andIndirect(I)aerosol-relatedradiativeforcingoftheclimatesystem.

MostImportant VeryImportant

DS Traceability Goals 3-5

Acronyms (1/3)

�36

A AerosolsAFWA AirForceWeatherAgencyAAOD AbsorbingAerosolOpticalDepthAOD AerosolOpticalDepthAQ AirQualityCCP Clouds,Convection,andPrecipitationCDC CentersforDiseaseControlCMAQ TheCommunityMultiscaleAirQualityModelingSystem

CTM ChemicalTransportModel

D DirectDOD DepartmentofDefenseDOE DepartmentofEnergyDRE DirectRadiativeEffectECMWF EuropeanCentreforMedium-RangeWeatherForecastsEPA EnvironmentalProtectionAgencyFAA FederalAviationAdministrationFAO FoodandAgricultureOrganizationFP FootprintG GoalGE GeneralElectricGPS GlobalPositioningSystem

Acronyms (2/3)

�37

I IndirectIR InfraredJMA JapanMeteorologicalAgencyJTWC JointTyphoonWarningCenterLW LongwaveLWP LiquidWaterPathNCAR NationalCenterforAtmosphericResearchNIH NationalInstitutesofHealthNG NorthropGrummanNOAA NationalOceanicandAtmosphericAdministrationNRL NavalResearchLaboratoryNWP NumericalWeatherPredictionO ObjectiveOD OpticalDepthPBL PlanetaryBoundaryLayerPDC PacificDisasterCenterPEA PotentialEnabledApplicationPM ParticulateMatterPoR ProgramofRecordP&W Pratt&WhitneyRO RadioOccultationRR RollsRoyce

Acronyms (3/3)

�38

S SBG(SurfaceBiologyandGeology)SW ShortwaveSWNIR Shortwave-NearInfraredTBD ToBeDeterminedTOA TopOfAtmosphereUSDA UnitedStatesDepartmentofAgricultureVAAC VolcanicAshAdvisoryCenterVIS VisibleWHO WorldHealthOrganizationsWRF WeatherResearchandWeather(ForecastingModel)

science and applications traceability matrix · 2) to what extent do clouds and precipitation...

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