Evaluation of Improvement Schemes for FY-3B Passive Microwave Soil-Moisture Estimates Retrieved Using the Land Parameter Retrieval Model

Author:

Liu Haonan1,Wang Guojie2ORCID,Hagan Daniel Fiifi Tawia13ORCID,Hu Yifan2,Nooni Isaac Kwesi4ORCID,Yeboah Emmanuel2ORCID,Zhou Feihong1

Affiliation:

1. School of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China

2. School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China

3. Hydro-Climate Extremes Lab, Ghent University, 9000 Ghent, Belgium

4. School of Atmospheric Science and Remote Sensing, Wuxi University, Wuxi 214105, China

Abstract

Satellite observations have provided global and regional soil-moisture estimates in the last four decades. However, the accuracy of these observations largely depends on reducing uncertainties in the retrieval algorithms. In this study, we address two challenges affecting the quality of soil-moisture estimates from a widely used soil-moisture-retrieval model, the land parameter retrieval model (LPRM). We studied two improvement schemes that were aimed at reducing uncertainties in open water signals (the LPRMv6_OWF) and vegetation signals (the LPRMv6_Veg), as well as a scheme to reduce their combined impacts (the LPRMv6_OWFVeg) on LPRM-retrieved soil moisture using the FengYun-3B (FY-3B) satellite observations. To assess the impacts of the improvement schemes, we utilized in situ soil moisture from the Jiangsu and Jiangxi provinces in China. We found that the retrievals (Rs) of the LPRMv6_Veg and the LPRMv6_OWFVeg were mainly in the range of 0.2 to 0.5 in Jiangsu and Jiangxi, with increases of 0.1 compared to those of the LPRMv6. The standard deviation (SD) of the LPRMv6_OWFVeg increased in Jiangsu, while the R of the LPRMv6_OWF increased in Jiangsu by 0.05–0.1 compared to that of the LPRMv6, but the SD tended to become worse. In Jiangxi, there was an increase of 0.1 in R. The results show that each of these algorithms improved the accuracy of soil-moisture inversion to some extent, compared to the original algorithm, with the LPRMv6_OWFVeg showing the greatest improvement, followed by the LPRMv6_Veg. The accuracy of both the LPRMv6_OWF and the LPRMv6_OWFVeg decreased to some extent when the open-water fraction (OWF) was greater than 0.2. Full areal extent analyses based on triple collocation showed significant improvements in correlations and minimized errors across different vegetation scenarios over the entire region of China in both the LPRMv6_OWF and the LPRMv6_Veg. However, reduced qualities were found in arid regions in northern China because of the nonlinear relationships between land-surface temperature, vegetation, and soil moisture in the LPRM. These results highlight important lessons for developing comprehensive improvement schemes for soil-moisture retrievals from passive microwave satellite observations.

Funder

National Natural Science Foundation of China

Sino-German Cooperation Group Program

Postgraduate Research and Practice Innovation Program of Jiangsu Province

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

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