1. Role of Soil Moisture/Climate Networks in SMAP Validation T. J
Role of Soil Moisture/Climate Networks in SMAP Validation T. J. Jackson USDA ARS Hydrology and Remote Sensing Lab Beltsville, MD Dec. 4, 2008

2. Outline Remote sensing of soil moisture SMAP Overview
SMAP Cal/Val plan
Experiences with AMSR-E
Some things that must be addressed

3. Remote Sensing of Soil Moisture
Soil moisture information derives from changes in the dielectric properties resulting from changes in water content.
Freeze-thaw information derives from changes in the dielectric properties resulting from temperature changes
Progress has been limited by the available sensors: sensitivity and spatial resolution.
So far there have not been any missions designed for soil moisture.

4. Meteorological Satellites
Sensitivity: Lower Frequencies Provide Information on a Deeper Soil Layer and are Less Affected by the Vegetation
Sensitivity of brightness temperature to changes in soil moisture
An optimal system maximizes sensitivity for both bare and vegetated surfaces
L-band: 1.4 GHz or 21 cm
2002
1970s
High
SMOS Aquarius SMAP
Aqua
Meteorological Satellites
Bare
Sensitivity
Vegetated
Low 1 2 3 5 10 20 30 50
Frequency (GHz)

5. Spatial Resolution: Overcoming Passive Microwave Limitations
Lower frequency means deeper soil sensing and less vegetation interference.
It also means coarser spatial resolution using conventional antenna technology.
Spatial resolution restricts potential applications.
The challenge is to achieve better sensing with higher spatial resolution.
SMOS will explore a potential technology but will provide only a 40 km resolution.
SMAP will explore a potential technology and different instrument design and will provide a 10 km resolution.

6. Evolution of L-Band Remote Sensing (Land)
Day
SMOS
SMAP Radar-Radiometer
Climate Applications
Aquarius
Weather Applications
Week
Resolved Temporal Scales
Evolution
of L-Band
Sensing
Radiometer
Carbon Cycle
Applications
Radar
Month
ALOS SAR
100 km
10 km
1 km
Resolved Spatial Scales
*Material from SMAP Science Team

7. Spatial Resolution: Overcoming Passive Microwave Limitations
Lower frequency means deeper soil sensing and less vegetation interference.
It also means coarser spatial resolution using conventional antenna technology.
Spatial resolution restricts potential applications.
The challenge is to achieve better sensing with higher spatial resolution.
SMOS will explore a potential technology but will provide only a 40 km resolution.
SMAP will explore a potential technology and different instrument design and will provide a 10 km resolution.

8. Soil Moisture Active Passive (SMAP) Satellite

9. Soil Moisture Active Passive Mission (SMAP)
NASA
One of the first missions resulting from the NRC Decadal Survey
Soil moisture and freeze-thaw
Three day global coverage
Launch 2013

10. SMAP Mission Concept
L-band radar and radiometer system with 6-m reflector
Solution to spatial resolution is two-fold; a technology that uses a large antenna (deployable mesh) and enhanced resolution by combining high accuracy radiometry retrieval with high resolution radar. Soil moisture products;
Radar resolution: 3 km
Radiometer resolution: 40 km
Combined product: 10 km

11. SMAP Status SMAP Project and Program (March 2008)
Key Project Personnel
Program Executive: E. Ianson (NASA/Hq)
Program Scientist: J. Entin (NASA/Hq)
Project Manager: K. Kellogg (JPL)
Project Scientist: E. Njoku (JPL)
Deputy Project Scientist: P. O'Neill (GSFC)
Science Definition Team (SDT) (Selected Oct. 2008)
D. Entekhabi, MIT, Team Leader
W. Crow, U.S. Department of Agriculture
T. Jackson, U.S. Department of Agriculture (Validation WG)
J. Johnson, Ohio State University (RFI WG)
J. Kimball, University of Montana
R. Koster, NASA Goddard Space Flight Center
K. McDonald, Jet Propulsion Laboratory
M. Moghaddam, University of Michigan (Algorithm WG)
S. Moran, U.S. Department of Agriculture (Applications WG)
R. Reichle, NASA Goddard Space Flight Center
J. Shi, University of California, Santa Barbara
L. Tsang, University of Washington
J. van Zyl, Jet Propulsion Laboratory
SRR/MDR/PNAR Review (February 2009)
Algorithm and C/V Workshop (June 2009)
Applications Workshop (September 2009)

12. SMAP Validation
Based on SMAP mission requirements and mission product ATBDs
Objectives:
Demonstrate that the science requirements have been met post-launch and over the mission life
Improve soil moisture and freeze-thaw algorithms and products
Demonstrate the impact or value of mission products on specific applications

13. SMAP L1 Requirements Traceability

14. SMAP Science Data Products
Description
L1B_S0_LoRes
Low Resolution Radar so in Time Order
L1C_S0_HiRes
High Resolution Radar so on Earth Grid
L1B_TB
Radiometer TB in Time Order
L1C_TB
Radiometer TB on Earth Grid
L3_SM_HiRes_3km
Radar Soil Moisture on Earth Grid
L3_SM_40km
Radiometer Soil Moisture on Earth Grid
L3_SM_A/P_10km
Radar/Radiometer Soil Moisture on Earth Grid
L3_F/T_HiRes
Freeze/Thaw State on Earth Grid
L4_SM
Soil Moisture Model Assimilation on Earth Grid
L4_F/T
Freeze/Thaw Model Assimilation on Earth Grid }
Surface 0-5 cm
Profile
ATBDs under development.

15. Demonstrate that the science requirements have been met post-launch and over the mission life
Approach
Provide verified estimates of soil moisture over an area and depth equivalent to that measured by the SMAP radiometer and radar instruments or derived products throughout the project life
Provide a robust set of cover conditions and geographic/climate domains for validation
Provide continuous, consistent, and long term records with minimal latency
Elements:
Ground based soil moisture observations that represent footprint/grid soil moisture either by replication or scaling, which has been verified
Field experiments
Satellite product comparisons
Model product comparisons

16. SMAP Science Data Products
Description
Validation
Networks
Field Exp.
Satellite Products
Model Products
L1B_S0_LoRes
Low Resolution Radar so in Time Order x
Aquarius
L1C_S0_HiRes
High Resolution Radar so on Earth Grid
PALSAR
L1B_TB
Radiometer TB in Time Order
SMOS Aquarius
L1C_TB
Radiometer TB on Earth Grid
SMOS
L3_SM_HiRes_3km
Radar Soil Moisture on Earth Grid
L3_SM_40km
Radiometer Soil Moisture on Earth Grid
GCOM-W
L3_SM_A/P_10km
Radar/Radiometer Soil Moisture on Earth Grid
L3_F/T_HiRes
Freeze/Thaw State on Earth Grid
TBD
L4_SM
Soil Moisture Model Assimilation on Earth Grid
L4_F/T
Freeze/Thaw Model Assimilation on Earth Grid

17. In Situ Soil Moisture Core element of validation-challenging problems
A single point within a satellite footprint is not going to provide a reliable estimate of the spatial average.
Robust validation requires international cooperation
AMSR-E experiences

18. Global In Situ Soil Moisture Validation Resources
There are a substantial number of in situ resources available for validation. Only a few provide the right kind of data (depth, frequency, latency, access)
Some regions (OK and NSW) have exceptional resources.
Coverage gaps: some are real, others are the due to communication or cooperation
There are issues that need to be addressed if these are to be of value to validation.
Continuity
Calibration
Replication
Scaling
Coverage gaps
Infrastructure
USA Oklahoma Networks Little Washita
Australia New South Wales Networks Kyeemba

19. In Situ Soil Moisture Core element of validation-challenging problems
A single point within a satellite footprint is not going to provide a reliable estimate of the spatial average.
Robust validation requires international cooperation
AMSR-E experiences

20. Validation of AMSR-E Soil Moisture Products Using Watershed Networks
Lessons Learned
Validation of AMSR-E Soil Moisture Products Using Watershed Networks
Standards
Infrastructure
Diverse Conditions
Replication
Installation
Calibration
SMEX+
Scaling
Archive
Algorithm Validation

21. Little Washita Vitel Network

22. AMSR-E U.S. Soil Moisture Validation Sites
Little River, GA
Reynolds Creek, ID
Walnut Gulch, AZ
Little Washita, OK

23. Validation of AMSR-E Soil Moisture Products Using Watershed Networks
Lessons Learned
Validation of AMSR-E Soil Moisture Products Using Watershed Networks
Standards
Infrastructure
Diverse Conditions
Replication
Installation
Calibration
SMEX+
Scaling
Archive
Algorithm Validation

24. Algorithm Comparison
Three algorithms
5 years of data

25. Algorithm Validation-Summary

26. SMAP Soil Moisture Validation: In Situ Resources
Ground based networks are a core component: provide actual quantitative soil moisture observations to evaluate algorithm performance
Continue/establish a number of dedicated soil moisture validation sites
Develop techniques for scaling sparse networks to footprints
International cooperation
Access and archiving
Similar issues with freeze-thaw (temperature) and profile SM