NASA Soil Moisture Active Passive (SMAP) Mission Formulation  Dara Entekhabi  (MIT) Eni Njoku  (JPL Caltech/NASA) Peggy O'...
Talk Outline <ul><li>Traceability of SMAP Basic and Applied Science Applications to the  </li></ul><ul><li>NRC Earth Scien...
Project Milestones and Upcoming Activities <ul><li>Feb 2008: NASA announces start of SMAP project </li></ul><ul><li>SMAP i...
May 10  Dry soil, clear, mild winds. (LE≈H)  May 18  90 mm Rain May 20  Moist soil, clear, mild winds. (LE>H)  Pathways of...
Source: Cahill et al.,  J. Appl. Met ., 38 Key Determinants of Land Evaporation Latent heat flux (evaporation)  links  the...
NOAH CLM What Do We Do Today? Dirmeyer et al., J. Hydromet., 7,  1177-1198, 2006 Atmospheric model representations of this...
(*)  % classification accuracy (binary Freeze/Thaw)  (**) [cm 3  cm -3 ] volumetric water content, 1-sigma Science Require...
Sources: Global Forecast/Analysis System Bulletins http://www.emc.ncep.noaa.gov/gmb/STATS/html/model_changes.html The ECMW...
Operational Flood and Drought Applications Current : Empirical Soil Moisture Indices Based on Rainfall and Air Temperature...
SMAP Mission Concept <ul><li>L-band Unfocused SAR and Radiometer System, Offset-Fed 6 m Light-Weight Deployable Mesh Refle...
Data Products SMAP is Taking Aggressive Hardware & Softwate Measures to Detect & Partially Mitigate RFI  Product Descripti...
L-band Active/Passive Assessment <ul><li>Soil Moisture Retrieval Algorithms Build on Heritage of Microwave Modeling and Fi...
L2_SM_AP  Radar-Radiometer Algorithm  Heterogeneity in Vegetation and Roughness Conditions Estimated by Sensitivities  Γ  ...
SGP99, SMEX02, CLASIC and SMAPVEX08 WE2.T03.2 Paper #: 3398 Title: Evaluation of the SMAPCombined Radar-Radiometer Soil Mo...
<ul><ul><li>Using the SMAP Testbed to Develop  Value-Added Products in the Simulation Environment   </li></ul></ul><ul><ul...
SMAP Algorithm Testbed TB (K) L2_SM_AP  Combined Soil Moisture Product (9 km) L2_SM_P  Radiometer  Soil Moisture Product (...
<ul><li>Working Groups  Have Been Established to Facilitate Broad Science Participation in the SMAP Project. The Working G...
Back-Up Slides
<ul><li>Global mapping of   Soil Moisture and Freeze/Thaw state to : </li></ul><ul><li>Understand Processes That  Link  th...
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  • Oct. 23, 2008
  • 3178_IGARSS11.ppt

    1. 1. NASA Soil Moisture Active Passive (SMAP) Mission Formulation Dara Entekhabi (MIT) Eni Njoku (JPL Caltech/NASA) Peggy O'Neill (GSFC/NASA) Kent Kellogg (JPL Caltech/NASA) Jared Entin (NASA HQ) IGARSS’11 Session WE1.T03.1 Paper #3178
    2. 2. Talk Outline <ul><li>Traceability of SMAP Basic and Applied Science Applications to the </li></ul><ul><li>NRC Earth Science Decadal Survey </li></ul><ul><li>Key Upcoming Milestones and Activities </li></ul><ul><li>Latest on Data Products and Latencies </li></ul><ul><li>Key Algorithm Development and Testing Activities </li></ul><ul><li>Community Engagement With Project Elements Through Working Groups </li></ul>
    3. 3. Project Milestones and Upcoming Activities <ul><li>Feb 2008: NASA announces start of SMAP project </li></ul><ul><li>SMAP is a directed-mission with heritage from HYDROS </li></ul><ul><li>PDR Oct 10-12, 2011 Followed by KDP-C and Implementation Phase </li></ul><ul><li>Major Ongoing Hardware Fabrication and Testing </li></ul>2007 US National Research Council Report: “ Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond ” <ul><li>Ongoing and Upcoming : </li></ul><ul><li>Focus on Working With Applications Users </li></ul><ul><li>Independent ATBD Peer Review (Nov+ 2011) </li></ul><ul><li>SMEX’12 Airborne Experiment in US and Canada </li></ul><ul><li>Algorithm Testbed: End-to-End Simulation </li></ul><ul><li>in situ Testbed Cal/Val Instruments Testing </li></ul>Tier 1: 2010–2013 Launch Soil Moisture Active Passive (SMAP) ICESAT II DESDynI CLARREO Tier 2: 2013–2016 Launch SWOT HYSPIRI ASCENDS GEO-CAFE ACE Tier 3: 2016–2020 Launch LIST PATH GRACE-II SCLP GACM 3D-WINDS
    4. 4. May 10 Dry soil, clear, mild winds. (LE≈H) May 18 90 mm Rain May 20 Moist soil, clear, mild winds. (LE>H) Pathways of Soil Moisture Influence on Weather and Climate CASES’97 Field Experiment, BAMS , 81(4), 2000. Dry Soil Moist Soil 5°C Dry Surface Moist Surface Deep Mixing up to 1.5 km Altitude Shallow Mixing to 1.0 km
    5. 5. Source: Cahill et al., J. Appl. Met ., 38 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.
    6. 6. NOAH CLM What Do We Do Today? Dirmeyer et al., J. Hydromet., 7, 1177-1198, 2006 Atmospheric model representations of this function are essentially “guesses”, given scarcity of soil moisture and evaporation data.
    7. 7. (*) % classification accuracy (binary Freeze/Thaw) (**) [cm 3 cm -3 ] volumetric water content, 1-sigma Science Requirements (1) North of 45N latitude Requirement Hydro-Meteorology Hydro-Climatology Carbon Cycle Baseline Mission Soil Moisture Freeze/Thaw Resolution 4–15 km 50–100 km 1–10 km 10 km 3 km Refresh Rate 2–3 days 3–4 days 2–3 days (1) 3 days 2 days (1) Accuracy 4–6% ** 4–6%** 80–70%* 4%** 80%* 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 Testing Land Surface Models in General Circulation Models Drought and Agriculture Monitoring Seasonal Precipitation Prediction Hydroclimatology Regional Drought Monitoring Crop Outlook Flood Forecast Improvements River Forecast Model Initialization Hydrometeorology Flash Flood Guidance (FFG) NWP Initialization for Precipitation Forecast Human Health Seasonal Heat Stress Outlook Hydroclimatology Near-Term Air Temperature and Heat Stress Forecast Hydrometeorology Disease Vector Seasonal Outlook Hydroclimatology Disease Vector Near-Term Forecast (NWP) Hydrometeorology Boreal Carbon Freeze/Thaw Date Freeze/Thaw State
    8. 8. Sources: Global Forecast/Analysis System Bulletins http://www.emc.ncep.noaa.gov/gmb/STATS/html/model_changes.html The ECMWF Forecasting System Since 1979 http://ecmwf.int/products/forecasts/guide/The_general_circulation_model.html Trends in Short-Term Weather (0-14 Days) NWP Resolution Hydrometeorology Applications: NWP SMAP
    9. 9. Operational Flood and Drought Applications Current : Empirical Soil Moisture Indices Based on Rainfall and Air Temperature ( By Counties >40 km and Climate Divisions >55 km ) Future : SMAP Soil Moisture Direct Observations of Soil Moisture at 10 km
    10. 10. SMAP Mission Concept <ul><li>L-band Unfocused SAR and Radiometer System, Offset-Fed 6 m Light-Weight Deployable Mesh Reflector. Shared Feed For </li></ul><ul><ul><li>1.26 GHz Radar at 1-3 km (HH, VV, HV) </li></ul></ul><ul><ul><li>(30% Nadir Gap) </li></ul></ul><ul><ul><li>1.4 GHz Polarimetric Radiometer at 40 km </li></ul></ul><ul><ul><li>( H, V, 3 rd & 4 th Stokes) </li></ul></ul><ul><li>Conical Scan at Fixed Look Angle </li></ul><ul><li>Wide 1000 km Swath With 2-3 Days Revisit </li></ul><ul><li>Sun-Synchronous 6am/6pm Orbit (680 km) </li></ul><ul><li>Launch 2014 </li></ul><ul><li>Mission Duration 3 Years </li></ul>National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California
    11. 11. Data Products SMAP is Taking Aggressive Hardware & Softwate Measures to Detect & Partially Mitigate RFI Product Description Resolution Latency L1A_TB Radiometer Data in Time-Order - 12 hrs Instrument Data L1A_S0 Radar Data in Time-Order - 12 hrs L1B_TB Radiometer T B in Time-Order 36x47 km 12 hrs L1B_S0_LoRes Low Resolution Radar σ o in Time-Order 5x30 km 12 hrs L1C_S0_HiRes High Resolution Radar σ o in Half-Orbits 1-3 km 12 hrs L1C_TB Radiometer T B in Half-Orbits 36 km 12 hrs L2_SM_A Soil Moisture (Radar) 3 km 24 hrs Science Data (Half-Orbit) L2_SM_P Soil Moisture (Radiometer) 36 km 24 hrs L2_SM_A/P Soil Moisture (Radar+Radiometer) 9 km 24 hrs 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 L3_SM_P Soil Moisture (Radiometer) 36 km 50 hrs L3_SM_A/P Soil Moisture (Radar+Radiometer) 9 km 50 hrs 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
    12. 12. L-band Active/Passive Assessment <ul><li>Soil Moisture Retrieval Algorithms Build on Heritage of Microwave Modeling and Field Experiments </li></ul><ul><ul><li>MacHydro’90, Monsoon’91, Washita92, Washita94, SGP97, SGP99, SMEX02, SMEX03, SMEX04, SMEX05, CLASIC, SMAPVEX08, CanEx10 </li></ul></ul><ul><li>Radiometer - High Accuracy (Less Influenced by Roughness and Vegetation) but </li></ul><ul><li>Coarser Resolution (40 km) </li></ul><ul><li>Radar - High Spatial Resolution (1-3 km) but More Sensitive to Surface Roughness and Vegetation </li></ul><ul><ul><li>Combined Radar-Radiometer Product Provides </li></ul></ul><ul><ul><li>Blend of Measurements for Intermediate Resolution </li></ul></ul><ul><ul><li>and Intermediate Accuracy </li></ul></ul>National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California
    13. 13. L2_SM_AP Radar-Radiometer Algorithm Heterogeneity in Vegetation and Roughness Conditions Estimated by Sensitivities Γ in Radar HV Cross-Pol: T B ( M j ) is Used to Retrieve Soil Moisture at 9 km T B -Disaggregation Algorithm is: National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California Temporal Changes in T B and σ pp are Related. Relationship Parameter β is Estimated at Radiometer-Scale Using Successive Overpasses. Based on PALS Observations From: SGP99, SMEX02, CLASIC and SMAPVEX08
    14. 14. 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 Active-Passive Algorithm Performance Minimum Performance Algorithm RMSE: 0.055 [cm 3 cm -3 ] Active-Passive Algorithm RMSE: 0.033 [cm 3 cm -3 ]
    15. 15. <ul><ul><li>Using the SMAP Testbed to Develop Value-Added Products in the Simulation Environment </li></ul></ul><ul><ul><li>Making Available Basic SMAP Products with Moderate Latencies </li></ul></ul><ul><ul><li>Establishing a Community of Early-Adopters Through a Competitive, </li></ul></ul><ul><ul><li>Peer-Reviewed NASA Announcement of Opportunity </li></ul></ul><ul><ul><li>Steering End-Users to NASA Applied Sciences Program (ASP) Solicitations With Specific Mention of SMAP Product Applications </li></ul></ul><ul><ul><li>2 nd AppWG Workshop in DC October 11-12, 2011 </li></ul></ul>SMAP Applications Activities 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
    16. 16. SMAP Algorithm Testbed TB (K) L2_SM_AP Combined Soil Moisture Product (9 km) L2_SM_P Radiometer Soil Moisture Product (36 km) L3_SM_A Radar Soil Moisture Product (3 km) L1C_TB Radiometer Brightness Temperature Product (36km) Simulated products generated with prototype algorithms on the SDS Testbed National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California 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 L1C_S0_Hi-Res Radar Backscatter Product (1-3 km)
    17. 17. <ul><li>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. </li></ul><ul><li>Currently There are Four Working Groups: </li></ul><ul><li>Applications Working Group (AppWG) </li></ul><ul><ul><li>2nd Workshop in Oct. 2011; Early-Adopter DCL </li></ul></ul><ul><li>Calibration & Validation Working Group (CVWG) </li></ul><ul><ul><li>2nd Workshop in May 2011; Core-Sites DCL </li></ul></ul><ul><li>Algorithms Working Group (AWG) </li></ul><ul><li>Radio-Frequency Interference Working Group (RFIWG) </li></ul>SMAP Working Groups http:// smap.jpl.nasa.gov /science/wgroups/
    18. 18. Back-Up Slides
    19. 19. <ul><li>Global mapping of Soil Moisture and Freeze/Thaw state to : </li></ul><ul><li>Understand Processes That Link the Terrestrial Water, Energy & Carbon Cycles </li></ul><ul><li>Estimate Global Water and Energy Fluxes at the Land Surface </li></ul><ul><li>Quantify Net Carbon Flux in Boreal Landscapes </li></ul><ul><li>Enhance Weather and Climate Forecast Skill </li></ul><ul><li>Develop Improved Flood Prediction and Drought Monitoring Capability </li></ul>Mission Science Objective Primary Controls on Land Evaporation and Biosphere Primary Productivity Freeze/ Thaw Radiation Soil Moisture
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