SMAP RADAR Calibration and Validation
Abstract
The Soil Moisture Active Passive (SMAP) mission launched on Jan 31, 2015. The mission employs L-band radar and radiometer measurements to estimate soil moisture with 4% volumetric accuracy at a resolution of 10 km, and freeze-thaw state at a resolution of 1-3 km. Immediately following launch, there was a three month instrument checkout period, followed by six months of level 1 (L1) calibration and validation. In this presentation, we will discuss the calibration and validation activities and results for the L1 radar data. Early SMAP radar data were used to check commanded timing parameters, and to work out issues in the low- and high-resolution radar processors. From April 3-13 the radar collected receive only mode data to conduct a survey of RFI sources. Analysis of the RFI environment led to a preferred operating frequency. The RFI survey data were also used to validate noise subtraction and scaling operations in the radar processors. Normal radar operations resumed on April 13. All radar data were examined closely for image quality and calibration issues which led to improvements in the radar data products for the beta release at the end of July. Radar data were used to determine and correct for small biases in the reported spacecraft attitude. Geo-location was validated against coastline positions and the known positions of corner reflectors. Residual errors at the time of the beta release are about 350 m. Intra-swath biases in the high-resolution backscatter images are reduced to less than 0.3 dB for all polarizations. Radiometric cross-calibration with Aquarius was performed using areas of the Amazon rain forest. Cross-calibration was also examined using ocean data from the low-resolution processor and comparing with the Aquarius wind model function. Using all a-priori calibration constants provided good results with co-polarized measurements matching to better than 1 dB, and cross-polarized measurements matching to about 1 dB in the beta release. During the second half of the L1 cal/val period, the RFI removal algorithm will be tuned for optimal performance, and the Faraday rotation corrections used in radar processing will be further developed and validated. This work is supported by the SMAP project at the Jet Propulsion Laboratory, California Institute of Technology.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2015
- Bibcode:
- 2015AGUFM.H21H1485W
- Keywords:
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- 1836 Hydrological cycles and budgets;
- HYDROLOGY;
- 1840 Hydrometeorology;
- HYDROLOGY;
- 1855 Remote sensing;
- HYDROLOGY;
- 1866 Soil moisture;
- HYDROLOGY