NASA Soil Moisture Active Passive (SMAP) Mission Formulation

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NASA Soil Moisture Active Passive (SMAP) Mission
Formulation
IGARSS11 Session WE1.T03.1 Paper 3178
Dara Entekhabi (MIT) Eni Njoku (JPL
Caltech/NASA) Peggy O'Neill (GSFC/NASA) Kent
Kellogg (JPL Caltech/NASA) Jared Entin (NASA HQ)
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Talk Outline

• Traceability of SMAP Basic and Applied Science
  Applications to the
• NRC Earth Science Decadal Survey
• Key Upcoming Milestones and Activities
• Latest on Data Products and Latencies
• Key Algorithm Development and Testing Activities
• Community Engagement With Project Elements
  Through Working Groups

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Project Milestones and Upcoming Activities
2007 US National Research Council Report Earth
Science and Applications from Space National
Imperatives for the Next Decade and Beyond
Tier 1 20102013 Launch Tier 1 20102013 Launch
Soil Moisture Active Passive (SMAP)
ICESAT II
DESDynI
CLARREO
Tier 2 20132016 Launch Tier 2 20132016 Launch
SWOT
HYSPIRI
ASCENDS
GEO-CAFE
ACE
Tier 3 20162020 Launch Tier 3 20162020 Launch
LIST
PATH
GRACE-II
SCLP
GACM
3D-WINDS

• Feb 2008 NASA announces start of SMAP project
• SMAP is a directed-mission with heritage from
  HYDROS
• PDR Oct 10-12, 2011 Followed by KDP-C and
  Implementation Phase
• Major Ongoing Hardware Fabrication and Testing

• Ongoing and Upcoming
• Focus on Working With Applications Users
• Independent ATBD Peer Review (Nov 2011)
• SMEX12 Airborne Experiment in US and Canada
• Algorithm Testbed End-to-End Simulation
• in situ Testbed Cal/Val Instruments Testing

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Pathways of Soil Moisture Influence on Weather
and Climate
May 10 Dry soil, clear, mild winds. (LEH) May
18 90 mm Rain May 20 Moist soil, clear, mild
winds. (LEgtH)
CASES97 Field Experiment, BAMS, 81(4), 2000.
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Key Determinants of Land Evaporation
Latent heat flux (evaporation) links the water,
energy, and carbon cycles at the surface.
Closure relationship, yet virtually
unknown. Lack of knowledge of soil moisture
control on surface fluxes causes uncertainty in
weather and climate models.
Source Cahill et al., J. Appl. Met., 38
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What Do We Do Today?
NOAH
Dirmeyer et al., J. Hydromet., 7, 1177-1198, 2006
CLM
Atmospheric model representations of this
function are essentially guesses, given
scarcity of soil moisture and evaporation data.
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Science Requirements
DS Objective Application Science Requirement
Weather Forecast Initialization of Numerical Weather Prediction (NWP) Hydrometeorology
Climate Prediction Boundary and Initial Conditions for Seasonal Climate Prediction Models Hydroclimatology
Climate Prediction Testing Land Surface Models in General Circulation Models Hydroclimatology
Drought and Agriculture Monitoring Seasonal Precipitation Prediction Hydroclimatology
Drought and Agriculture Monitoring Regional Drought Monitoring Hydroclimatology
Drought and Agriculture Monitoring Crop Outlook Hydroclimatology
Flood Forecast Improvements River Forecast Model Initialization Hydrometeorology
Flood Forecast Improvements Flash Flood Guidance (FFG) Hydrometeorology
Flood Forecast Improvements NWP Initialization for Precipitation Forecast Hydrometeorology
Human Health Seasonal Heat Stress Outlook Hydroclimatology
Human Health Near-Term Air Temperature and Heat Stress Forecast Hydrometeorology
Human Health Disease Vector Seasonal Outlook Hydroclimatology
Human Health Disease Vector Near-Term Forecast (NWP) Hydrometeorology
Boreal Carbon Freeze/Thaw Date Freeze/Thaw State
Requirement Hydro-Meteorology Hydro-Climatology Carbon Cycle Baseline Mission Baseline Mission
Requirement Hydro-Meteorology Hydro-Climatology Carbon Cycle Soil Moisture Freeze/Thaw
Resolution 415 km 50100 km 110 km 10 km 3 km
Refresh Rate 23 days 34 days 23 days(1) 3 days 2 days(1)
Accuracy 46 46 8070 4 80
() classification accuracy (binary
Freeze/Thaw) () cm3 cm-3 volumetric water
content, 1-sigma
(1)North of 45N latitude
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Hydrometeorology Applications NWP
Trends in Short-Term Weather (0-14 Days) NWP
Resolution
SMAP
Sources Global Forecast/Analysis System
Bulletins http//www.emc.ncep.noaa.gov/gmb/STATS/h
tml/model_changes.html The ECMWF Forecasting
System Since 1979 http//ecmwf.int/products/foreca
sts/guide/The_general_circulation_model.html
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Operational Flood and Drought Applications
Current Empirical Soil Moisture Indices Based on
Rainfall and Air Temperature ( By Counties gt40
km and Climate Divisions gt55 km ) Future SMAP
Soil Moisture Direct Observations of Soil
Moisture at 10 km
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SMAP Mission Concept
National Aeronautics and Space
Administration Jet Propulsion Laboratory Californ
ia Institute of Technology Pasadena, California

• L-band Unfocused SAR and Radiometer System,
  Offset-Fed 6 m Light-Weight Deployable Mesh
  Reflector. Shared Feed For
• 1.26 GHz Radar at 1-3 km (HH, VV, HV)
• (30 Nadir Gap)
• 1.4 GHz Polarimetric Radiometer at 40 km
• (H, V, 3rd 4th Stokes)
• Conical Scan at Fixed Look Angle
• Wide 1000 km Swath With 2-3 Days Revisit
• Sun-Synchronous 6am/6pm Orbit (680 km)
• Launch 2014
• Mission Duration 3 Years

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Data Products
Product Description Resolution Latency Latency
L1A_TB Radiometer Data in Time-Order - 12 hrs Instrument Data
L1A_S0 Radar Data in Time-Order - 12 hrs Instrument Data
L1B_TB Radiometer TB in Time-Order 36x47 km 12 hrs Instrument Data
L1B_S0_LoRes Low Resolution Radar so in Time-Order 5x30 km 12 hrs Instrument Data
L1C_S0_HiRes High Resolution Radar so in Half-Orbits 1-3 km 12 hrs Instrument Data
L1C_TB Radiometer TB in Half-Orbits 36 km 12 hrs Instrument Data
L2_SM_A Soil Moisture (Radar) 3 km 24 hrs Science Data (Half-Orbit)
L2_SM_P Soil Moisture (Radiometer) 36 km 24 hrs Science Data (Half-Orbit)
L2_SM_A/P Soil Moisture (RadarRadiometer) 9 km 24 hrs Science Data (Half-Orbit)
L3_F/T_A Freeze/Thaw State 3 km 50 hrs Science Data (Daily Composite)
L3_SM_A Soil Moisture (Radar) 3 km 50 hrs Science Data (Daily Composite)
L3_SM_P Soil Moisture (Radiometer) 36 km 50 hrs Science Data (Daily Composite)
L3_SM_A/P Soil Moisture (RadarRadiometer) 9 km 50 hrs Science Data (Daily Composite)
L4_SM Soil Moisture (Surface and Root Zone ) 9 km 7 days Science Value-Added
L4_C Carbon Net Ecosystem Exchange (NEE) 9 km 14 days Science Value-Added
SMAP is Taking Aggressive Hardware Softwate
Measures to Detect Partially Mitigate RFI
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L-band Active/Passive Assessment

• Soil Moisture Retrieval Algorithms Build on
  Heritage of Microwave Modeling and Field
  Experiments
• MacHydro90, Monsoon91, Washita92, Washita94,
  SGP97, SGP99, SMEX02, SMEX03, SMEX04, SMEX05,
  CLASIC, SMAPVEX08, CanEx10

• Radiometer - High Accuracy (Less Influenced by
  Roughness and Vegetation) but
• Coarser Resolution (40 km)
• Radar - High Spatial Resolution (1-3 km) but More
  Sensitive to Surface Roughness and Vegetation
• Combined Radar-Radiometer Product Provides
• Blend of Measurements for Intermediate Resolution
• and Intermediate Accuracy

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National Aeronautics and Space
Administration Jet Propulsion Laboratory Californ
ia Institute of Technology Pasadena, California
L2_SM_AP Radar-Radiometer Algorithm
Temporal Changes in TB and spp are Related.
Relationship Parameter ß is Estimated at
Radiometer-Scale Using Successive Overpasses.
Based on PALS Observations From SGP99, SMEX02,
CLASIC and SMAPVEX08
Heterogeneity in Vegetation and Roughness
Conditions Estimated by Sensitivities G in Radar
HV Cross-Pol
TB-Disaggregation Algorithm is
TB( Mj ) is Used to Retrieve Soil Moisture at 9
km
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Active-Passive Algorithm Performance
Active-Passive Algorithm RMSE 0.033 cm3 cm-3
Minimum Performance Algorithm RMSE 0.055 cm3
cm-3
SGP99, SMEX02, CLASIC and SMAPVEX08
WE2.T03.2 Paper 3398 Title Evaluation of the
SMAPCombined Radar-Radiometer Soil Moisture
Algorithm Authors N. Das, D. Entekhabi, S. Chan,
S. Kim, E. Njoku, R. Dunbar, J.C. Shi
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SMAP Applications Activities

• Using the SMAP Testbed to Develop Value-Added
  Products in the Simulation Environment
• Making Available Basic SMAP Products with
  Moderate Latencies
• Establishing a Community of Early-Adopters
  Through a Competitive,
• Peer-Reviewed NASA Announcement of Opportunity
• Steering End-Users to NASA Applied Sciences
  Program (ASP) Solicitations With Specific Mention
  of SMAP Product Applications
• 2nd AppWG Workshop in DC October 11-12, 2011

WE1.T03.2 Paper 2906 Title The Soil Moisture
Active Passive (SMAP) Applications
Aactivity Authors M. Brown, S. Moran, V.
Escobar, D. Entekhabi, P. O'Neill, E. Njoku
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National Aeronautics and Space
Administration Jet Propulsion Laboratory Californ
ia Institute of Technology Pasadena, California
SMAP Algorithm Testbed
Simulated products generated with prototype
algorithms on the SDS Testbed
L1C_TB Radiometer Brightness Temperature Product
(36km)
TB (K)
L3_SM_A Radar Soil Moisture Product (3 km)
L2_SM_AP Combined Soil Moisture Product (9 km)
L2_SM_P Radiometer Soil Moisture Product (36 km)
WE2.T03.1 Paper 2069 Title Utilization of
ancillary data sets for SMAP Algorithm
Development and Product Generation Authors P.
O'Neill, E. Podest, E. Njoku
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SMAP Working Groups

• Working Groups Have Been Established to
  Facilitate Broad Science Participation in the
  SMAP Project. The Working Groups Communicate via
  Workshops, E-Mail and at Conferences and Other
  Venues.
• Currently There are Four Working Groups
• Applications Working Group (AppWG)
• 2nd Workshop in Oct. 2011 Early-Adopter DCL
• Calibration Validation Working Group (CVWG)
• 2nd Workshop in May 2011 Core-Sites DCL
• Algorithms Working Group (AWG)
• Radio-Frequency Interference Working Group
  (RFIWG)

http//smap.jpl.nasa.gov/science/wgroups/
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Back-Up Slides
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Mission Science Objective

• Global mapping of Soil Moisture and Freeze/Thaw
  state to
• Understand Processes That Link the Terrestrial
  Water, Energy Carbon Cycles
• Estimate Global Water and Energy Fluxes at the
  Land Surface
• Quantify Net Carbon Flux in Boreal Landscapes
• Enhance Weather and Climate Forecast Skill
• Develop Improved Flood Prediction and Drought
  Monitoring Capability

Primary Controls on Land Evaporation and
Biosphere Primary Productivity