nasa soil moisture active passive (smap) mission formulation dara entekhabi (mit) eni njoku (jpl...
TRANSCRIPT
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’11Session WE1.T03.1
Paper #3178
National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
Talk Outline
1. Traceability of SMAP Basic and Applied Science Applications to the NRC Earth Science Decadal Survey
2. Key Upcoming Milestones and Activities
3. Latest on Data Products and Latencies
4. Key Algorithm Development and Testing Activities
5. Community Engagement With Project Elements Through Working Groups
National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
2007 US National Research Council Report: “Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond”
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
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
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 situ Testbed Cal/Val Instruments Testing
National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
Dry Soil
Moist Soil
5°C
Dry Surface
Moist Surface
Deep Mixing up to 1.5 km Altitude
Shallow Mixing to 1.0 km
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.
National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
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.
pE
E
National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
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.
National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
RequirementHydro-
MeteorologyHydro-
ClimatologyCarbon 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%*(*) % classification accuracy (binary Freeze/Thaw) (**) [cm3 cm-3] volumetric water content, 1-sigma
Science Requirements
(1)North of 45N latitude
DS Objective Application Science RequirementWeather Forecast Initialization of Numerical Weather Prediction (NWP) Hydrometeorology
Climate PredictionBoundary and Initial Conditions for Seasonal Climate Prediction Models HydroclimatologyTesting Land Surface Models in General Circulation Models
Drought and Agriculture Monitoring
Seasonal Precipitation PredictionHydroclimatologyRegional Drought Monitoring
Crop Outlook
Flood Forecast Improvements
River Forecast Model InitializationHydrometeorology
Flash Flood Guidance (FFG)NWP Initialization for Precipitation Forecast
Human Health
Seasonal Heat Stress Outlook HydroclimatologyNear-Term Air Temperature and Heat Stress Forecast HydrometeorologyDisease Vector Seasonal Outlook HydroclimatologyDisease Vector Near-Term Forecast (NWP) Hydrometeorology
Boreal Carbon Freeze/Thaw Date Freeze/Thaw State
National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
Sources:Global Forecast/Analysis System Bulletinshttp://www.emc.ncep.noaa.gov/gmb/STATS/html/model_changes.html
The ECMWF Forecasting System Since 1979http://ecmwf.int/products/forecasts/guide/The_general_circulation_model.html
Trends in Short-Term Weather (0-14 Days) NWP Resolution
Hydrometeorology Applications: NWP
SMAP
National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
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
• 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
National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
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 TB in Time-Order 36x47 km 12 hrs
L1B_S0_LoRes Low Resolution Radar σo in Time-Order 5x30 km 12 hrs
L1C_S0_HiRes High Resolution Radar σo in Half-Orbits 1-3 km 12 hrs
L1C_TB Radiometer TB in Half-Orbits 36 km 12 hrs
L2_SM_A Soil Moisture (Radar) 3 km 24 hrsScience 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-AddedL4_C Carbon Net Ecosystem Exchange (NEE) 9 km 14 days
Data Products
SMAP is Taking Aggressive Hardware & Softwate Measures to Detect & Partially Mitigate RFI
National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
L-band Active/Passive Assessment
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 ProvidesBlend of Measurements for Intermediate Resolutionand Intermediate Accuracy
L2_SM_AP Radar-Radiometer Algorithm
Heterogeneity in Vegetation and Roughness Conditions Estimated by Sensitivities Γ in Radar HV Cross-Pol:
Cjpqjpp MM , Slope
TB( Mj ) is Used to Retrieve Soil Moisture at 9 km
TB-Disaggregation Algorithm is:
CM
CM
CTMT
pqjpq
ppjpp
BjB pp
National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
hvvvhh
hv
2
8RVI
hvvvhh
hv
2
8RVI
CppBT , Slope
Temporal Changes in TB and σpp are Related.
Relationship Parameter β is Estimated at Radiometer-Scale Using Successive Overpasses.
Based on PALS Observations From: SGP99, SMEX02, CLASIC and SMAPVEX08
National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
0 0.1 0.2 0.3 0.40
0.1
0.2
0.3
0.4
Average of Field Measurements [cm3/cm3]B
asel
ine
Alg
ori
thm
[cm
3/c
m3]
RMSE: 0.033 [cm3/cm3]
0 0.1 0.2 0.3 0.40
0.1
0.2
0.3
0.4
Average of Field Measurements [cm3/cm3]
Min
imu
m P
erf
orm
an
ce [
cm3/c
m3] RMSE: 0.055 [cm3/cm3]
SGP99, SMEX02, CLASIC and SMAPVEX08
WE2.T03.2 Paper #: 3398Title: Evaluation of the SMAPCombined Radar-Radiometer Soil Moisture AlgorithmAuthors: N. Das, D. Entekhabi, S. Chan, S. Kim, E. Njoku, R. Dunbar, J.C. Shi
Active-Passive Algorithm Performance
Minimum Performance AlgorithmRMSE: 0.055 [cm3 cm-3]
Active-Passive AlgorithmRMSE: 0.033 [cm3 cm-3]
National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
• 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
SMAP Applications Activities
WE1.T03.2 Paper #2906Title: The Soil Moisture Active Passive (SMAP) Applications AactivityAuthors: M. Brown, S. Moran, V. Escobar, D. Entekhabi, P. O'Neill, E. Njoku
SMAP Algorithm Testbed
TB (K)
L2_SM_AP CombinedSoil Moisture Product (9 km)
L2_SM_P Radiometer Soil Moisture Product (36 km)
L3_SM_A RadarSoil Moisture Product (3 km)
L1C_S0_Hi-Res Radar Backscatter Product (1-3 km)
L1C_TB RadiometerBrightness Temperature Product (36km)
Simulated products generated with prototype algorithms on the SDS Testbed
National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
WE2.T03.1 Paper #2069Title: Utilization of ancillary data sets for SMAP Algorithm Development and Product Generation Authors: P. O'Neill, E. Podest, E. Njoku
National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
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:
1.Applications Working Group (AppWG)2nd Workshop in Oct. 2011; Early-Adopter DCL
2.Calibration & Validation Working Group (CVWG)2nd Workshop in May 2011; Core-Sites DCL
3.Algorithms Working Group (AWG)
4.Radio-Frequency Interference Working Group (RFIWG)
SMAP Working Groups
http://smap.jpl.nasa.govsmap.jpl.nasa.gov/science/wgroups/
National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
Back-Up Slides
National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
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
Mission Science Objective
Primary Controls on Land Evaporation and Biosphere Primary Productivity
Freeze/Thaw
Radiation
Soil Moisture