Abstract
The spaceborne Global Navigation Satellite System-Reflectometry (GNSS-R) has proven its worth in terrestrial remote sensing applications. Its application to detecting land surface soil moisture (SSM) is particularly intriguing, as it can provide fine-scale SSM products to supplement traditional satellite-based active and passive missions. Various retrieval algorithms have been developed to produce SSM products using spaceborne GNSS-R. However, detailed evaluations of product reliability and robustness are still absent. In this study, we used three data sources to evaluate the level-3 SSM products from the CYclone Global Navigation Satellite System (CYGNSS) mission: (1) satellite-based microwave radiometry product from Soil Moisture Active and Passive (SMAP) mission; (2) a model-based product of Modern-Era Retrospective analysis for Research and Applications; and (3) in situ measurements from over 1800 ground stations in the Chinese soil moisture monitoring network. The study uses typical relative skill metrics and triple collocation approach (TCA)-based metrics, along with corresponding confidence intervals, to analyze the performance of SSM products derived from CYGNSS observations. According to the pixel-by-pixel validation and overall statistical findings, the results reveal that the current CYGNSS-based SSM exhibits low performance in southern China when compared to the radiometry-based data. The coefficient of determination (R2) is low (median R2=0.088) and the unbiased root-mean-square-difference (ubRMSD) is 0.057 cm3cm−3, which is poorer than the results from SMAP against in situ measurements (median R2=0.25, ubRMSD=0.046 cm3cm−3). The TCA-based analysis also revealed that CYGNSS had a relatively poor performance, with the lowest median R2 value of 0.167 and the largest median error standard deviation (ESD) value of 0.055 cm3cm−3. To obtain improved results that can better support related operational applications in the future, enhanced retrieval algorithms and high-accuracy calibration referenced data must be utilized.
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Data availability
The CYGNSS data that support the findings of this study are freely available in the Physical Oceanography Distributed Active Archive Center (PODAAC, https://podaac.jpl.nasa.gov/datasetlist?values=CYGNSS&view=list&ids=Projects). The reference SMAP data are openly available in National Snow and Ice Data Center (NSIDC, https://nsidc.org/data/spl3smp/versions/8). The MERRA-2 data at https://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/.
Code availability
The code related to the manuscript will be made available from the corresponding author on reasonable request.
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Acknowledgements
The authors would like to acknowledge the CYGNSS team and other institutions for providing the data set used in this study.
Funding
This work was supported by National Natural Science Foundation of China (Grant number 42204014).
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All authors contributed to the study conception and design. Material preparation, data collection, programming development, and analysis were performed by Zhounan Dong and Shuanggen Jin. The first draft of the manuscript was written by Zhounan Dong. Li Li and Peng Wang commented on and reviewed the manuscript. All authors read and approved the final manuscript.
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Dong, Z., Jin, S., Li, L. et al. Validation of CYGNSS soil moisture products using in situ measurements: a case study of Southern China. Theor Appl Climatol 153, 1085–1103 (2023). https://doi.org/10.1007/s00704-023-04531-z
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DOI: https://doi.org/10.1007/s00704-023-04531-z