Soil Moisture Retrievals Using CYGNSS Data in a Time-Series Ratio Method: Progress Update and Error Analysis

Abstract

A previously reported time-series ratio method for retrieving soil moisture information from Cyclone Global Navigation Satellite System (CYGNSS) measurements is updated to improve the algorithm used for excluding CYGNSS measurements from the time series, thereby improving the algorithm’s computational efficiency while eliminating the requirement for contemporary soil moisture information from Soil Moisture Active Passive (SMAP). Daily CYGNSS soil moisture estimates are retrieved and presented on a 36-km grid over the 27-month period January 2018–May 2020 and show an overall root mean square error <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\approx 4.46$ </tex-math></inline-formula> %, an overall correlation for all attempted retrievals of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\approx 80.53$ </tex-math></inline-formula> %, and an average correlation for individual pixels of 48.61% relative to SMAP using the updated time-series algorithm. An analysis of the errors of the updated algorithm is also provided as a function of surface properties.