Soil Moisture Active Passive (SMAP) Mission: a NASA Opportunity

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1 Soil Moisture Active Passive (SMAP) Mission: a NASA Opportunity Robert Gurney University of Reading WIF Workshop 17 th October 2012

2 National Aeronautics and Space Administration L-band Active/Passive Soil Jet Propulsion Laboratory California Institute of Technology Pasadena, California Moisture Mapping Soil moisture retrieval algorithms are derived from a long heritage of microwave modeling and field experiments MacHydro 90, Monsoon 91, Washita92, Washita94, SGP97, SGP99, SMEX02, SMEX03, SMEX04, SMEX05, CLASIC, SMAPVEX08, CanEx10, SMAP-Ex3 Radiometer - High accuracy (less influenced by roughness and vegetation) but coarser spatial resolution (40 km) Radar - High spatial resolution (1-3 km) but more sensitive to surface roughness and vegetation Combined Radar-Radiometer product provides intermediate resolution and intermediate accuracy to meet science objectives

3 ESA s SMOS (Soil Moisture and Ocean Salinity) mission launched on November 2 nd, 2009 The synthetic antenna measures the passive L- band emission of the Earth s surface every three days at a resolution of 40km, allowing the system to focus on different points on the Earth s surface and, as the satellite moves, examine areas at a range of angles. The emission is then used to estimate soil moisture and ocean salinity.

4 2011 US drought as measured by SMOS and USDA The US Department of Agriculture combines a number of data sources to produce the Drought Monitor, indicating drought severity. Mean soil moisture estimates from SMOS over the period January July 2011

5 Mississippi Floods, April/May th April 8 th May 3 rd May SMOS soil moisture Illinois flooded over 200 sq. miles, 100 homes affected Cumulative precipitation for April 2011 Levees demolished, causing a muddy torrent surge into the Illinois plains. The increased nutrient pollution is likely to substantially enlarge The Gulf of Mexico s hypoxic dead zone.

6 The effect of lower rainfall on the UK An unusually dry March and April in 2011 caused a 3.7% absolute reduction in mean April soil moisture between 2010 and 2011, compared to a 2010 mean of around 15%

7 NASA Soil Moisture Active/Passive mission SMAP Projected launch November 1 st, 2014 The SMAP system is similarly specified to SMOS in most respects, but uses a simpler fixed passive microwave antenna allowing only one angle of the ground to be viewed, but it has an additional active radar antenna which will enable higher resolution measurements down to 1-3km.

8 SMAP Science Applications SMAP will provide high-resolution and frequent-revisit global observations of soil moisture and freeze/thaw state 3-day mapping coverage Frozen Landscape Soil moisture is defined in terms of volume of water per unit volume of soil. Freeze/thaw state is defined as the phase of the water contained within the landscape including soil and vegetation. SMAP measurements of soil moisture and freeze/thaw state address a wide range of Earth science applications Surface soil moisture [cm 3 /cm 3 ] NRC Earth Science Decadal Survey Report, 2007

9 Requirement Hydro- Meteorology SMAP Science Requirements Decadal Survey Objective Application Science Requirement Weather Forecast Initialization of Numerical Weather Prediction (NWP) Hydrometeorology Climate Prediction Boundary and Initial Conditions for Seasonal Climate Prediction Models Testing Land Surface Models in General Circulation Models Hydroclimatology Seasonal Precipitation Prediction Drought and Agriculture Regional Drought Monitoring Monitoring Crop Outlook Hydroclimatology River Forecast Model Initialization Flood Forecast Improvements Flash Flood Guidance (FFG) Hydrometeorology NWP Initialization for Precipitation Forecast Seasonal Heat Stress Outlook Hydroclimatology Human Health 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 Key Level 1 Requirements (Derived from science objectives) Hydro- Climatology Carbon Cycle Baseline Mission Soil Moisture Freeze/ Thaw Minimum Mission Soil Moisture Freeze/ Thaw Resolution 4 15 km km 1 10 km 10 km 3 km 10 km 10 km Refresh Rate 2 3 days 3 4 days 2 3 days (a) 3 days 2 days 3 days 3 days Accuracy (c) % (b) % % (a) North of 45N latitude (b) Percent classification accuracy (binary freeze/thaw) (c) Volumetric water content, 1-σ in [cm 3 /cm 3 ] units

10 SMAP Soil Moisture Applications SMAP data will improve numerical weather prediction (NWP) over continents by more accurately initializing land surface states Buffalo Creek, CO Radar-Observed Rainfall (Caused Flash-Flood) 0000Z to 0400Z 13/7/96 24-Hours Ahead Atmospheric Model Forecasts With Realistic Soil Moisture Without Realistic Soil Moisture Major operational weather centers linked to SMAP: NOAA Weather ECMWF Air Force Weather Environment Canada NOAA Climate SMAP will provide 10 km soil moisture data product to help meet operational user needs

11 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 HH, VV, HV Radar at 1-3 km (30% nadir gap) 1.4 GHz H, V, 3 rd and 4 th Stokes Radiometer at 40 km Contiguous 1000 km swath with 2-3 days revisit (8 day repeat) Sun-synchronous 6am/6pm orbit (680 km) Launch November 2014 Mission duration 3 years Conical scan, fixed incidence angle across swath Nadir gap in high res radar data (~300 km)

12 SMAP Science Data Products Product Description Gridding (Resolution) Latency ** L1A_Radiometer Radiometer Data in Time-Order - 12 hrs L1A_Radar 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 km (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 L2_SM_P Soil Moisture (Radiometer) 36 km 24 hrs L2_SM_AP Soil Moisture (Radar + Radiometer) 9 km 24 hrs Instrument Data Science Data (Half-Orbit) L3_FT_A Freeze/Thaw State (Radar) 3 km 50 hrs L3_SM_A Soil Moisture (Radar) 3 km 50 hrs L3_SM_P Soil Moisture (Radiometer) 36 km 50 hrs L3_SM_AP Soil Moisture (Radar + Radiometer) 9 km 50 hrs L4_SM Soil Moisture (Surface and Root Zone ) 9 km 7 days L4_C Carbon Net Ecosystem Exchange (NEE) 9 km 14 days Science Data (Daily Composite) Science Value-Added * Over outer 70% of swath. ** The SMAP Project will make a best effort to reduce the data latencies beyond those shown in this table.

13 Latency of SMAP Instrument Data

14 Proactive Engagement on Applications SMAP leading the way and deeply engaged in realizing the applied science potential of the mission Actions: Developed an Applications Plan Formed Applications Working Group (AppWG) to engage community Appointed a SMAP Applications Coordinator Formed three levels of engagement with applications partners (1. Workshops, 2. Tutorials and 3. Focus Groups) So far two SMAP Applications workshops hosted by applications partners (NOAA and USDA) Released calls for Early-Adopters (total of 50 applied) to engage with SDT and project to demonstrate value of SMAP data to their decision support systems early on Co-organize two workshops on applications across Decadal Survey missions (SMAP-ICESat2-AirMOSS and SMAP-GPM-GRACE/FO-SWOT-CARVE)

15 SMAP s Proactive Applications Approach Deemed a Best Practice in Recent NRC Mid-Term Report BOX 2.2 SMAP Mission Applications Engagement: A Best Practice SMAP is implementing a strategy that promotes applications research and engages a broad community of users in SMAP applications. The [Applications Workshops] make it clear that the project is reaching out to its identified end users and looking for ways to entrain even more of them.

16 Science Organization Science Team Leader D. Entekhabi (MIT) Project Scientist E. Njoku (JPL) Deputy Project Scientist P. E. O Neill (GSFC) Science Definition Team (SDT) (ROSES) International K. McDonald (JPL) J. van Zyl (JPL) R. Koster (GSFC) R. Reichle (GSFC) W. Crow (USDA) S. Moran (USDA) T. Jackson (USDA) J. Johnson (Ohio St U) J. Kimball (U Mont) M. Moghaddam (U So Cal) J. Shi (UCSB) L. Tsang (U Wash) S. Belair (Canada) P. de Rosnay (UK) R. J. Gurney (UK) Y. Kerr (France) S. Paloscia (Italy) J. Walker (Australia) Applications Coordinator Molly Brown and Vanessa Escobar (GSFC) Working Groups: 1. Applications 2. Algorithms 3. Cal/Val 4. RFI