| Paper: | WE-A1.1 |
| Session: | Land Applications of Radiometry I |
| Time: | Wednesday, March 28, 09:00 - 09:20 |
| Presentation: |
Oral
|
| Topic: |
Soil moisture, soil state and vegetation: |
| Title: |
Development and Improvement of the SMAP Enhanced Passive Soil Moisture Product |
| Authors: |
Steven Chan; NASA Jet Propulsion Laboratory | | |
| | Rajat Bindlish; NASA Goddard Space Flight Center | | |
| | Peggy O'Neill; NASA Goddard Space Flight Center | | |
| | Thomas Jackson; USDA ARS Hydrology and Remote Sensing Laboratory | | |
| | Julian Chaubell; NASA Jet Propulsion Laboratory | | |
| | Andreas Colliander; NASA Jet Propulsion Laboratory | | |
| | Fan Chen; USDA ARS Hydrology and Remote Sensing Laboratory | | |
| Abstract: |
The NASA Soil Moisture Active Passive (SMAP) mission is designed to provide frequent and high resolution global mapping of soil moisture and freeze/thaw state through the synergy of a radar (active) and a radiometer (passive) operating at L-band frequencies (~1.4 GHz). Despite a hardware mishap that rendered the radar non-operational, the radiometer has been operating nominally since SMAP’s launch in January 2015, returning L-band brightness temperature data that enable global estimation of soil moisture at a 36 km spatial scale. Since December 2016, SMAP has released an optimally-interpolated enhanced version of the original 36 km passive soil moisture product (L2_SM_P). The new product (L2_SM_P_E) leverages the oversampling of the SMAP radiometer in the across-track direction. These oversampled observations provide an opportunity to apply the Backus-Gilbert optimal interpolation technique to the radiometer data, and the resulting enhanced brightness temperature observations are then used with high-resolution ancillary data to produce the L2_SM_P_E product. The new product is a global soil moisture product posted on a 9 km Earth-fixed grid whose retrieval uncertainty has been shown to be less than 0.040 m3/m3 based on comparison with long-term in situ soil moisture measurements collected at core validation sites and sparse networks.
In this presentation, the development of L2_SM_P_E will be discussed. Examples of this enhanced product will be given at regional and global scales to illustrate the additional spatial details not apparent in the standard passive soil moisture product. In addition, algorithm updates that are under development will also be presented. These updates include correction of soil moisture due to water contamination with the SMAP radiometer's field-of-view (FOV), mitigation of soil moisture retrieval bias caused by ancillary data, and an investigation of optimal model parameters used in the geophysical inversion process. |
