Soil Moisture SMAP Early Adopters - Commons

National Aeronautics and Space AdministrationSoil MoistureActive PassiveMissionSMAPSMAP Early AdoptersBarry WeissJet Propulsion LaboratoryCalifornia Institute of Technology California Institute of Technology. Government Sponsorship Acknowledged

SMAP Data ProductsData ProductShort NameDescriptionBeta ionBeginsAverage Latency toUser Communityafter AcquisitionL1A RadarParsed Radar Instrument Telemetry8/1/201511/1/201512 hoursL1A RadiometerParsed Radiometer Instrument Telemetry8/1/201511/1/201512 hoursL1B S0 LoResLow Resolution Radar σo in Time Order8/1/201511/1/201512 hoursL1C S0 HiResHigh Resolution Radar σo on Swath GridL1B TBRadiometer TB in Time OrderL1C TBRadiometer TBL2 SM ARadar Soil MoistureL2 SM PRadiometer Soil MoistureL2 SM APActive-Passive Soil 165/1/201612 hours12 hours12 hours24 hours24 hours24 hoursL3 FT ADaily Global Composite Freeze/Thaw State11/1/20155/1/201650 hoursL3 SM ADaily Global Composite Radar Soil Moisture11/1/20155/1/201650 hoursL3 SM PDaily Global Composite Radiometer Soil Moisture11/1/20155/1/201650 hoursL3 SM APDaily Global Composite Active-Passive SoilMoisture11/1/20155/1/201650 hoursL4 SMSurface & Root Zone Soil Moisture11/1/20155/1/20167 daysL4 CCarbon Net Ecosystem Exchange11/1/20155/1/201614 daysJuly 16, 2015 California Institute of Technology. Government Sponsorship AcknowledgedBHW-1

SMAP Early Adopters SMAP was the first NASA Earth mission to sponsor an EarlyAdopter program Early Adopters foresee value in mission data for their designand implementation of applications Early Adopters gain access to product design and simulateddata well before launch. Value is symbiotic: Early Adopters build or modify applications to employ mission data well beforelaunch Early Adopters present plans to mission team and other Early Adopters Early Adopters provide feedback about mission product design. SMAP currently has 55 Early Adopters– Topics are highly varied Scientific Social Scientific EconomicJuly 16, 2015 California Institute of Technology. Government Sponsorship AcknowledgedBHW-2

Provisions for Early Adopters Early Adopter candidates propose an application that usesmission data Team from Science and Science Data System review thecandidate application and accept or reject them– Proposal must be viable and display an adequate understanding ofproduct content Mission requires that approved applicants sign agreement thatspecifies:– The data are simulated, have no value for scientific research– The data may not be distributed beyond the Early Adopter team Based on additional criteria, some Early Adopters currentlyreceive pre-Beta data– Early Adopter demonstrated effective use of simulated data– Data collected during pre-beta period is relevant to their researchJuly 16, 2015 California Institute of Technology. Government Sponsorship AcknowledgedBHW-3

Numerical Weather PredictionJonathan Case, Clay Blankenship and Bradley Zavodsky, NASAShort-term Prediction Research and Transition (SPoRT) Center;SMAP Contact: Molly BrownAMPLE: NUMERICAL WEATHER PREDICTIONData assimilation of SMAP observations, and impact on weatherforecasts in a coupled simulation environment The NASA SPoRT Center isassimilating SMOS into the WeatherResearch and Forecasting numericalweather prediction NWP modelthrough coupling with the LandInformation System (LIS). By assimilating soil moistureobservations, modelers can improvea land surface model’s ability tosimulate evapotranspiration andlatent and sensible heating at thesurface, important inputs to NWPmodels.NASA Short-Term Prediction Research and Transition Center (SPoRT)mplementing the assimilation of soil moisture observations from SMOSthe WRF numerical weather prediction (NWP) model through couplingtheLandInformationto 1)Instituteinvestigatethe impact of soil SystemCaliforniaof Technology.GovernmentJuly16, 2015Sponsorship AcknowledgedBHW-4

Agricultural ProductivityCatherine Champagne, Agriculture and Agri-Food Canada (AAFC);SMAP Contact: Stephane BélairSoil moisture monitoring in Canada Currently, weekly nationalmaps of soil moisturecondition are producedusing sensors such asAMSR and SMOS AAFC will integrate thesoil moisture informationfrom SMAP into existingmonitoring programs andachieve improvementsfrom increased spatialresolution and datacontinuity that willenhance agriculturalmonitoring capacity.July 16, 2015 California Institute of Technology. Government Sponsorship AcknowledgedBHW-5

Use of AMSR, SMOS and SMAP soil moisture forAgro-climate risk monitoringJuly 16, 2015 California Institute of Technology. Government Sponsorship AcknowledgedBHW-6

National Soil Moisture ModelingZhengwei Yang and Rick Mueller, USDA National AgriculturalStatistical Service (NASS); SMAP Contact: Wade CrowUS National cropland soil moisture monitoring using SMAP The USDA National Agricultural Statistical Service (NASS) has launched a webbased U.S. crop vegetation condition assessment and monitoringapplication: VegScape (http://nassgeodata.gmu.edu/VegScape/). This web-based application has been designed to be a platform for accessing,visualization, assessing and disseminating crop soil moisture condition derivativedata products produced using SMAP data.July 16, 2015 California Institute of Technology. Government Sponsorship AcknowledgedBHW-7

Agricultural DroughtCurt Reynolds, USDA Foreign Agricultural Service (FAS); SMAPContact: Wade CrowEnhancing USDA’s global crop production monitoring system usingSMAP soil moisture products The figure describesareas of theworld where the assimilation of AMSR-EEXAMPLE: AGRICULTURALDROUGHTsurface soil moistureretrievals significantly impacts the sampled crossAreas of world where assimilation of AMSR-E surface soil moisture retrievalssignificantly impactssampled cross-correlationbetweensoil moisturecorrelation betweensoil themoistureanomaliesandNDVIanomaliesanomalies.for month i and NDVI anomalies for month i-1. As a result, red areas correspond to Red areas correspondto regionswheresurfacethesoilavailabilityof satellite-based surfaceregions where the availabilityof satellite-basedmoisture retrievalsimproves our ability to forecast agricultural drought using off-line watersoil moisturesignificantlyretrievalssignificantly improves our ability to forecast agriculturalbalance modeling. Assimilation model is the standard USDA Foreign AgriculturalService,waterbalance modeland plotted valuesare sigma-levelsofdrought relativeto2-Layerthe Palmerwaterbalancemodelingsystemcurrentlyemployed bystatistical significance for changes in cross-correlation relative to a model-onlyUSDA FAS. baseline (Bolton et al., 2013).July 16, 2015 California Institute of Technology. Government Sponsorship AcknowledgedBHW-8

Effect of the soil moisture on dust emissionHosni Ghedira, Masdar Institute, UAE; SMAP Contact: DaraEntekhabiEstimating and mapping the extent of Saharan dust emissions usingSMAP-derived soil moisture data.3.5a)April to mid JuneMid June to July3 The AERONET aerosol opticaldepth (AOT870) was correlatedto the SMOS soil moisturedata collected from 2010 to2011 in south Sahel. The results show that as theSMOS soil moisture increase,the AERONET AOT decreaseup to a threshold moisturecontent above which no dustemission takes 53SMOS SM (m /m )July 16, 2015 California Institute of Technology. Government Sponsorship AcknowledgedBHW-9

Vehicle MobilityGary McWilliams, Army Research Laboratory (ARL); GeorgeMason, U.S. Army Engineer Research and Development Center(ERDC) Geotechnical and Structures Laboratory (GSL); Li Li, NavalResearch Laboratory (NRL); and Andrew Jones, Colorado StateUniversity (CSU); SMAP Contact: Susan MoranExploitation of SMAP data for Army and Marine Corps mobilityassessment Soil moisture can be usedto estimate soil strength,which is a key factor interrain trafficability. This figure shows a sampleof the difference in theestimated time to target fora military ground vehicleusing satellite soil moisturedata (left) versus not usingsatellite soil moisture data(right).July 16, 2015 California Institute of Technology. Government Sponsorship AcknowledgedBHW-10

Military Maneuver PlanningJohn Eylander and Susan Frankenstein, U.S. Army Engineer Researchand Development Center (ERDC) Cold Regions Research andEngineering Laboratory (CRREL); SMAP Contact: Susan MoranU. S. Army ERDC SMAP adoption for USACE civil and militarytactical supportThe soil strength quantified using theRating Cone Index (RCI) as an indicatorof soil shear strength with climatologicaldata (left) and SMAP simulated data(right). These images are used to mapvehicle speeds for the Army maneuvers.July 16, 2015 California Institute of Technology. Government Sponsorship AcknowledgedBHW-11

Cryosphere ProcessesLars Kaleschke, Institute of Oceanography, University of Hamburg;SMAP Contact: Simon YuehSMOS to SMAP migration for cryosphere and climate application Conducted successful SMOS Icevalidation campaign in the BarentsSea east of Svalbard (Left) The advantage of the high-resolutionactive SMAP radar data(L1C S0 HiRes) is to developmethods to account for the subpixelscale heterogeniety for the retrievalof geophysical snow and iceparameters from the low-resolutionbrightness temperaturemeasurements (L1B TB or L1C TB).Coincident L-band radiometer (EMIRAD-2)and ice thickness measurements, CryoSat2satellite underflightsJuly 16, 2015 California Institute of Technology. Government Sponsorship AcknowledgedBHW-12

Global Flash Flood GuidanceKonstantine Georgakakos, Hydrologic Research Center; SMAPContact: Narendra DasDevelopment of a strategy for the evaluation of the utility ofSMAP products for the Global Flash Flood Guidance Program ofthe Hydrologic Research CenterA pre-launch prototype ofa Flash Flood GuidanceSystem to ingest andassimilate L3 SM A/PdataAn example of FFG estimated top-soil saturation fraction base mapfrom operational Southern Africa Flash Flood Guidance system.July 16, 2015 California Institute of Technology. Government Sponsorship AcknowledgedBHW-13

Flood ForecastingKashif Rashid and Emily Niebuhr, UN World Food Programme;SMAP Contact: Eni NjokuApplication of a SMAP-based index for flood forecasting indata-poor regionsWe have run about 10years of daily ECMWFre-analysis rainfall datathru VIC to compute soilmoisture as a surrogatefor SMAP dataStrong correlations of precipitation total and top layer soil moisture and thedownstream floodplain inundation volume (m3) were derived (0.88 - using rainfallonly gives 0.49 - 0.52, resp.), clearly indicating that both rainfall and soilmoisture can be used as predictors for flood inundation in our regionJuly 16, 2015 California Institute of Technology. Government Sponsorship AcknowledgedBHW-14

Flood ForecastingLuca Brocca, Research Institute for Geo-Hydrological Protection,Italian Dept. of Civil Protection; SMAP contact: Dara EntekhabiUse of SMAP soil moisture products for operational floodforecasting: data assimilation and rainfall correctionWith existing satellite SM data1) Improving flood forecasting through the assimilation of ASCATand AMSR-E soil moisture products2) Rainfall estimation from ASCAT, AMSR-E, and SMOS SM dataWith SMAP simulated SM data Estimation of rainfall through SM2RAIN algorithm over EuropeJuly 16, 2015 California Institute of Technology. Government Sponsorship AcknowledgedBHW-15