Improved CYGNSS Soil Moisture Product Characterization and Assessment

Soil moisture (SM) is a key climate variable influencing energy exchange between the land surface and atmosphere, and its monitoring across spatiotemporal scales is essential for hydrologic study, agricultural management, and climate modeling. The NASA Cyclone Global Navigation Satellite System (CYGNSS) is a GNSS Reflectometry (GNSS-R) constellation of satellites with demonstrated sensitivity to land surface reflectivity and SM. In this study, we evaluate the performance of the newly released CYGNSS V3.2 SM product, which incorporates improved engineering calibration and a refined SM retrieval algorithm. SM estimates are produced at 9 and 36 km spatial resolution and with daily (24-hour) and sub-daily (6-hour) temporal sampling. The data product is available from 2018 top the present. One example CYGNSS SM map, obtained on 8 Nov 2018, is shown in Figure 1a.In this study, we compare CYGNSS SM retrievals with SMAP and in-situ observations from 280 International Soil Moisture Network (ISMN) stations spanning diverse land cover types. An example 1-year comparison between collocated CYGNSS and ISMN ARM Ashton in-situ SM is shown in Figure 1b. Both the 9 and 36 km km products are evaluated using standard performance metrics—correlation, bias, RMSD, and unbiased RMSD—and using triple collocation analysis with SMAP, ESA Climate Change Initiative (CCI), and ISMN to quantify random errors and characterize error covariance. The v3.2 product demonstrates clear improvements over previous versions, with lower random errors and better long term consistency. We further explore the impact of land cover homogeneity and seasonal vegetation cycles on retrieval accuracy. Our analysis highlights the unique capability of spaceborne GNSS-R to provide high-temporal-resolution SM observations at intermediate spatial scales, helping bridge the scale gap between point measurements and coarse-resolution satellite products. These results support the inclusion of GNSS-R in integrated, hierarchical soil moisture monitoring systems and underscore its potential for hydrologic and environmental applications.