Soil Moisture Retrieval Using CYGNSS Data in a Time-Series Ratio Method: Progress Update and Error Analysis, Part II

Abstract

This works reports updates to a previously-reported time-series ratio (TSR) algorithm for surface soil moisture retrieval from Cyclone Global Navigation Satellite System (CYGNSS) reflectivity data. Both the original and updated algorithms are based on ratios between consecutive, angle-corrected CYGNSS normalized radar cross section or reflectivity measurements, but the new algorithm implements a denoising approach, which involves the application of a fractional exponent term to these ratios. In addition, modifications have been made to several quality control parameters and to the bounds used in the algorithm's bounded linear least-squares solver. Error statistics for several variations of the TSR algorithm are reported using cross-validation with soil moisture retrievals from the soil moisture active passive sensor. The final results show that the updated algorithm produces similar retrieval errors to the previously reported approach, but increases the data retained in the retrieval so that coverage is improved.