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NASA Soil Moisture Active Passive (SMAP) Mission Formulation

NASA Soil Moisture Active Passive (SMAP) Mission Formulation. IGARSS’11 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). Talk Outline.

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NASA Soil Moisture Active Passive (SMAP) Mission Formulation

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  1. NASA Soil Moisture Active Passive (SMAP) Mission Formulation IGARSS’11 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)

  2. 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

  3. Project Milestones and Upcoming Activities 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 2007 US National Research Council Report: “Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond” • Ongoing and Upcoming: • Focus on Working With Applications Users • Independent ATBD Peer Review (Nov+ 2011) • SMEX’12 Airborne Experiment in US and Canada • Algorithm Testbed: End-to-End Simulation • in situTestbed Cal/Val Instruments Testing

  4. Pathways of Soil Moisture Influence on Weather and Climate Dry Surface Deep Mixing up to 1.5 km Altitude Dry Soil Moist Surface 5°C Shallow Mixing to 1.0 km Moist Soil May 10 Dry soil, clear, mild winds. (LE≈H) May 18 90 mm Rain May 20 Moist soil, clear, mild winds. (LE>H) CASES’97 Field Experiment, BAMS, 81(4), 2000.

  5. 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

  6. 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.

  7. Science Requirements (*) % classification accuracy (binary Freeze/Thaw) (**) [cm3 cm-3] volumetric water content, 1-sigma (1)North of 45N latitude

  8. 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/html/model_changes.html The ECMWF Forecasting System Since 1979 http://ecmwf.int/products/forecasts/guide/The_general_circulation_model.html

  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. SMAP Mission Concept National Aeronautics and Space Administration Jet Propulsion Laboratory California 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

  11. Data Products SMAP is Taking Aggressive Hardware & Softwate Measures to Detect & Partially Mitigate RFI

  12. L-band Active/Passive Assessment National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California • Soil Moisture Retrieval Algorithms Build on Heritage of Microwave Modeling and Field Experiments • MacHydro’90, Monsoon’91, 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

  13. National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California L2_SM_AP Radar-Radiometer Algorithm Temporal Changes in TBand σppare Related. Relationship Parameter β 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 Γin Radar HV Cross-Pol: TB-Disaggregation Algorithm is: TB( Mj) is Used to Retrieve Soil Moisture at 9 km

  14. 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

  15. 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

  16. National Aeronautics and Space Administration Jet Propulsion Laboratory California 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) L1C_S0_Hi-Res Radar Backscatter Product (1-3 km) TB (K) L3_SM_A Radar Soil Moisture Product (3 km) L2_SM_P Radiometer Soil Moisture Product (36 km) L2_SM_AP Combined Soil Moisture Product (9 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

  17. 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/

  18. Back-Up Slides

  19. Mission Science Objective Soil Moisture Freeze/ Thaw Radiation Global mapping ofSoil 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

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