NASA Soil Moisture Active Passive (SMAP) Mission Formulation
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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


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

  • 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

Project milestones and upcoming activities
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

Pathways of Soil Moisture Influence on Weather and Climate



Deep Mixing up to 1.5 km Altitude

Dry Soil




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.

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

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.

Science Requirements

(*) % classification accuracy (binary Freeze/Thaw)

(**) [cm3 cm-3] volumetric water content, 1-sigma

(1)North of 45N latitude

Hydrometeorology Applications: NWP

Trends in Short-Term Weather (0-14 Days) NWP Resolution



Global Forecast/Analysis System Bulletins

The ECMWF Forecasting System Since 1979

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

Smap mission concept
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

Data Products

SMAP is Taking Aggressive Hardware & Softwate Measures to Detect & Partially Mitigate RFI

L band active passive assessment
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

National Aeronautics and Space Administration

Jet Propulsion Laboratory

California Institute of Technology

Pasadena, California


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

Active-Passive Algorithm Performance

Active-Passive Algorithm

RMSE: 0.033 [cm3 cm-3]

Minimum Performance Algorithm

RMSE: 0.055 [cm3 cm-3]


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

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

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

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)

Mission Science Objective






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