Assessment of retrieval errors of AirMOSS root-zone soil moisture products

We have concluded that before calculation of the AirMOSS project overall RMSE, not only the behavior and location of in-situ soil moisture probes need to be carefully evaluated but also the present error biases-associated with the in-situ probes, radar calibration, vegetation parameterization, forward model inaccuracy, and the inversion algorithm bias-need to be removed. Several measures have been taken over the course of AirMOSS mission to increase the accuracy of RZSM products. The overall RMSE was reported for each study site. We can show that the overall AirMOSS retrieval error for the top 25 cm in BERMS, Metolius, MOISST, Tonzi Ranch, and Walnut Gulch meets the mission RMSE requirement. This error would be calculated in terms of RMSE between the retrieved and actual moisture values over all qualified validation points, all sites, and all dates. The retrieval performance is expected to improve even more with reprocessing of some of the flights using recalibrated radar data.

[1]  Sermsak Jaruwatanadilok,et al.  Soil Moisture Estimation Under Tropical Forests Using UHF Radar Polarimetry , 2015, IEEE Transactions on Geoscience and Remote Sensing.

[2]  Mahta Moghaddam,et al.  A generalized radar scattering model for multispecies forests with multilayer subsurface soil , 2012, 2012 IEEE International Geoscience and Remote Sensing Symposium.

[3]  Mahta Moghaddam,et al.  P-Band Radar Retrieval of Subsurface Soil Moisture Profile as a Second-Order Polynomial: First AirMOSS Results , 2015, IEEE Transactions on Geoscience and Remote Sensing.