资源环境科技发展态势分析平台

This paper implements a newly-developed combined active and passive algorithm for the retrieval of snow water equivalent (SWE) by using three-channel active and two-channel passive observations. First, passive microwave observations at 19 and 37 GHz are used to determine the scattering albedo of snow. An a priori scattering albedo is obtained by averaging over time series observations. Second, 13.3 GHz is introduced to formulate a three-channel (9.6, 13.3, and 17 GHz) radar algorithm which reduces effects of background scattering from the snow-soil interface, and improves SWE retrieval. In the algorithm, the bicontinuous dense media radiative transfer (DMRT-Bic) is used to compute look-up tables (LUTs) of both radar backscatter and radiometer brightness temperatures (TBs) of the snowpack. To accelerate the retrieval, a parameterized model is derived from LUT by regression training, which links backscatter to the scattering albedo at 9.6 GHz or 13.3 GHz and to SWE. The volume scattering of snow is obtained by subtracting the background scattering from radar observations. SWE is then retrieved through a cost function that is guided by the a priori scattering albedo obtained from the passive microwave observations. The proposed algorithm, along with the active-only version, is evaluated against the Finnish Nordic Snow Radar Experiment (NoSREx) dataset measured in 2009-2013. The combined active-passive algorithm achieves root mean square errors (RSME) less than 27 mm and correlation coefficients above 0.68 for 2009-2010, RMSE less than 21 mm and correlation above 0.85 for 2010-2011, and RMSE less than 40 mm and correlation above 0.38 for 2012-2013.

This article is protected by copyright. All rights reserved.