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SMAP Cal/Val

SMAP Cal/Val. T. J. Jackson USDA ARS Hydrology and Remote Sensing Lab December 11, 2012. Outline. Soil Moisture Satellite Missions: Past, Present and Future SMAP Mission Cal/Val Sparse Networks in Cal/Val Challenges to using COSMOS. Evolution of Microwave Remote Sensing (Land). Day.

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SMAP Cal/Val

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  1. SMAP Cal/Val T. J. Jackson USDA ARS Hydrology and Remote Sensing Lab December 11, 2012

  2. Outline • Soil Moisture Satellite Missions: Past, Present and Future • SMAP • Mission • Cal/Val • Sparse Networks in Cal/Val • Challenges to using COSMOS

  3. Evolution of Microwave Remote Sensing (Land) Day ClimateApplications Weather Applications Week Resolved Temporal Scales Passive CarbonCycle Applications Historic Perspective on Remote Sensing Active Month Scale ranges are based on the NRC Decadal Survey 100 km 10 km 1 km Resolved Spatial Scales

  4. Evolution of Microwave Remote Sensing (Land) Day ASCAT GCOM-W AMSR-E ASCAT ClimateApplications Weather Applications Week Resolved Temporal Scales 2012 GCOM-W Soil moisture product is the same as AMSR-E 2002-2011 AMSR-E X-band 40 km CarbonCycle Applications Month ALOSSAR ALOS-2 Scale ranges are based on the NRC Decadal Survey 100 km 10 km 1 km Resolved Spatial Scales

  5. Soil Moisture and Ocean Salinity Mission (SMOS) • European Space Agency (ESA) • 1.4 GHz Microwave Radiometer • 40 km footprint, three day global coverage • Launch November 2009

  6. 1.4 GHz 6.0 GHz 10.0 GHz Evolution of Microwave Remote Sensing (Land) Day AMSR-E ASCAT SMOS ClimateApplications Weather Applications Week Resolved Temporal Scales • Same resolution but a better product • Technology demo CarbonCycle Applications Month 100 km 10 km 1 km Resolved Spatial Scales

  7. Aquarius/SAC-D • Mission (NASA and CONAE) • Sun-synch orbit • 6 am (Des.)/6 pm (Asc.) • Night time look direction • 657 km Alt; 7 day revisit • Launch: June 2011 • Aquarius Instrument • L-band Polarimetric • Radiometer and Scatterometer • 3 Beam Pushbroom • Incidence angles of 29.36°, 38.49°, and 46.29° • SAC-D • MWR • Other Middle beam 84×120 km Outer beam 96×156 km Inner beam 76×94 km 390 km

  8. Evolution of Microwave Remote Sensing (Land) Day AMSR-E ASCAT SMOS ClimateApplications Aquarius Weather Applications Week Resolved Temporal Scales Active and passive L-band but coarser spatial resolution and temporal repeat CarbonCycle Applications Month Scale ranges are based on the NRC Decadal Survey 100 km 10 km 1 km Resolved Spatial Scales

  9. SAOCOM: SAtélite Argentino de Observación COn Microondas • Comisión Nacional de Actividades Espaciales (CONAE)-Argentina Space Agency • Constellation of two identical satellites SAOCOM 1A and SAOCOM 1B carrying an L-band polarimetric SAR instrument • SAOCOM will be in a sun-synchronous nearly circular frozen polar orbit (06:12 am LTAN/619.6 km) • Repeat cycle of 16 days (8 days with full constellation of 2 satellites) • Launch of SAOCOM 1A in 2015. • Challenge: Infer surface soil moisture values from SAR measurements with varying incidence angles.

  10. Evolution of Microwave Remote Sensing (Land) Day GCOM-W ASCAT SMOS ClimateApplications Aquarius Weather Applications SAOCOM Week Resolved Temporal Scales Commitment to a soil moisture product CarbonCycle Applications Month ALOS-2 Scale ranges are based on the NRC Decadal Survey 100 km 10 km 1 km Resolved Spatial Scales

  11. Outline • Soil Moisture Satellite Missions: Past, Present and Future • SMAP • Mission • Cal/Val • Sparse Networks in Cal/Val • Challenges to using COSMOS

  12. SMAP Level 1 Science Requirements • The NRC Decadal Survey identified numerous potential applications for SM/FT observations. • These were grouped into three categories with a spatial resolution, refresh rate, and accuracy. (a) North of 45N latitude, (b) Percent classification accuracy (binary freeze/thaw), (c) Volumetric water content, 1-σ in [cm3/cm3] units • These are the L1 priority products and requirements. Other product accuracies derive from L2 requirements. Defines the baseline mission. • The SMAP Project proposed the active-passive approach for meeting these requirements.

  13. SMAP Project Approach • 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, 3rd and 4th Stokes • Radiometer at 40 km • Conical scan, fixed incidence angle (40o across swath • Contiguous 1000 km swath with 2-3 days revisit (8 day repeat) • Sun-synchronous 6am/6pm orbit (680 km) • Launch October 31, 2014 (now in Phase C/D) • Mission duration 3 years

  14. SMAP Science Products * Over outer 70% of swath. ** The SMAP project will make a best effort to reduce the data latencies beyond those shown in this table. TJJ–14

  15. Evolution of Microwave Remote Sensing (Land) Day GCOM-W ASCAT SMOS SMAP Radar-Radiometer ClimateApplications Aquarius Weather Applications SAOCOM Week Resolved Temporal Scales SMAP will support established climate and carbon cycle applications and will open up new applications in weather and carbon cycle. CarbonCycle Applications Month ALOS-2 Scale ranges are based on the NRC Decadal Survey 100 km 10 km 1 km Resolved Spatial Scales

  16. SMAP L1 Requirements Impacting Cal/Val What the SMAP Project and NASA have agreed to do. Level 1 (Baseline) Science Requirements and Mission Success Criteria Provide estimates of soil moisture in the top 5 cm of soil with an error of no greater than 0.04 m3/m3 volumetric (one sigma) at 10 km spatial resolution and 3-day average intervals over non-excluded regions. Provide estimates of surface binary freeze/thaw state in the region north of 45N latitude, which includes the boreal forest zone, with a classification accuracy of 80% at 3 km spatial resolution and 2-day average intervals. Conduct a calibration and validation program to verify data delivered meets the requirements. Threshold mission requirements are 0.06 m3/m3 and 70%

  17. CEOS Validation Stages Adopted for SMAP Validation: The process of assessing, by independent means, the quality of the data products derived from the system outputs. The quality is determined with respect to the specified requirements.

  18. SMAP Validation Methodologies

  19. SMAP Cal/Val Approach Pre-launch • Focus on insuring that there are means in place to fulfill the mission objectives • Acquire and process data with which to calibrate, test, and improve models and algorithms used for retrieving SMAP science data products • Develop and test the infrastructure and protocols for post-launch validation Post-launch • Focus on validating that the products meet their quantified requirements • Calibrate, verify, and improve the performance of the science algorithms • Validate accuracies of the science data products as specified in L1 science requirements according to Cal/Val timeline

  20. Science Data Validation and Delivery Timeline

  21. Outline • Soil Moisture Satellite Missions: Past, Present and Future • SMAP • Mission • Cal/Val • Sparse Networks in Cal/Val • Challenges to using COSMOS

  22. SMAP Validation Methodologies

  23. SMAP Cal/Val Partners Program • In situ observations are essential to SMAP Cal/Val • There were only a few high quality resources available • Increasing the number was constrained by • The time and effort to establish a site • No $ to support these • Action: ROSES DCL • No cost collaboration • Minimum standards • In situ data in exchange for early access to SMAP products • Based on responses • Refined definitions • Missed some important resources

  24. SMAP Cal/Val Partners: Site Types • Core Validation Sites: In situ observing sites that provide well-characterized estimates of a L2-L4 product at a matching spatial scale, a direct benchmark reference for the products. Additional minimum criteria are: • Provides calibration of the in situ sensors • Up-scaling strategy provided (implemented by Project) • Provides data in a timely manner • Long term commitment by the sponsor/host • Contributing Validation Sites: In situ observing sites that provide estimates of a L2-L4 product but do not meet all of the minimum criteria for a Core Validation Site. (i.e. sparse networks) • Contributing Validation Sites are a supplemental resource (In assessing meeting mission requirements but important in Stage 2 Validation). • The baseline approach to using sparse networks is the triple-collocation technique. Efforts to improve this approach are desirable.

  25. Outline • Soil Moisture Satellite Missions: Past, Present and Future • SMAP • Mission • Cal/Val • Sparse Networks in Cal/Val • Challenges to using COSMOS • Up-scaling • Contributing depth • Integrating networks • Resolving “noise”

  26. Challenge: Scaling Points to Footprints • Proposed best practices*: • First, apply temporal stability analysis (Cosh et al., 2006; 2008) to select sampling sites with temporal dynamics that best mimic footprint scale variability. • Second, use land surface modeling (Crow et al., 2005) and/or an intensive field campaign (De Rosnay et al. 2009) to refine understanding of the relationship between point- and footprint-scale variability (i.e., F↑ on left). • Third, apply triple collocation (Mirrales et al., 2010) to estimate impact of residual sampling errors on RMSE validation results. Footprint-scale F↑ (θPOINT) θPOINT Up-scaling Challenge: Using point-scale soil moisture observations to validate footprint-scale SMAP retrievals. *Based on: Crow et al., “Upscaling sparse ground-based soil moisture observations for the validation of coarse-resolution satellite soil moisture products,” Reviews of Geophysics, 50, RG2002, doi:10.1029/2011RG000372, 2012.

  27. Application of Triple Co-Location To Estimate Random Sampling Error in Sparse Ground Observations 1) Obtain three independent (and uncertain) estimates of footprint-scale soil moisture: Remote Sensing (RS)-SMAP Land Surface Model (LSM) Sparse Ground Observation (SPARSE) 2) Assume independent errors and sample the following temporal average to estimate random sampling error in SPARSE: 3) Use this estimate to correct soil moisture RMSE estimates derived from RS versus SPARSE comparisons for sampling error in SPARSE.

  28. Challenge: Scaling Points to Footprints • Intensive sampling of a limited number of sites? • Exploit the Rover? How many conditions?

  29. Challenge: Matching Depth to a SMAP Product • We all understand why the contributing depth varies with the wetness and shape of the profile. • SMAP is only concerned with soil moisture of two layers; 0-5 cm and the root-zone (1 m) (for validation). • Can COSMOS produce standard depth products?

  30. Challenge: Integrating Networks • Lots of points that are currently not compatible. • Still need to address the variable contributing depth issue but there are more options for matching the depths of other networks. • First step: co-location of instruments (i.e MOISST)

  31. Natural Resource Conservation Service monitoring • SMAP Soil Moisture (surface and profile) • CONUS - 181 • Telemetry and FTP • Hourly • Status – Operating and Developing USDA-NRCS-Soil Climate Analysis Network – D. Harms

  32. USCRN observes climate change • Soil Moisture/Temperature Product Validation with sparse network • 114 sites, 20 field calibrated in FY13 • Satellite to NCDC, Internet to SMAP • 2-3 hours • Instruments in place, communication in place, gravimetric sampling of subset planned for FY13 U.S. Climate Reference NetworkM. A. Palecki and J.E. Bell, NCDC

  33. Challenge: Resolving “Noise” • Vegetation, atmosphere,….

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