A Triple Collocation-Based Comparison of Three L-Band Soil Moisture Datasets, SMAP, SMOS-IC, and SMOS, Over Varied Climates and Land Covers

Abstract

Soil moisture plays an important role in the hydrologic water cycle. Relative to in-situ soil moisture measurements, remote sensing has been the only means of monitoring global scale soil moisture in near real-time over the past 40 years. Among these, soil moisture products from radiometry sensors operating at L-band, e.g., SMAP, SMOS, and SMOS-IC, are theoretically established to be more advantageous than previous C/X-band products. However, little effort has been made to investigate the inter-product differences of L-band soil moisture retrievals and provide insights into the optimal use of these products. In this regard, this study aims to identify the relative strengths and weaknesses of three L-band soil moisture products across diverse climate zones and land covers at the global scale using triple collocation analysis. Results show that SMOS-IC exhibits significantly improved soil moisture estimation skills, relative to the original SMOS product. This demonstrates the paramount importance of retrieval algorithm development in improving global soil moisture estimates—given both SMOS-IC and SMOS are using the same L-band brightness temperature information. Relative to SMOS-IC, SMAP is superior across 69% of global land surface in terms of error variances. However, SMOS-IC tends to outperform SMAP over temperate/arid regions including in the east of North America, South America, western Africa, northern China, and central Australia. Additionally, considerable performance degradation of all the L-band data products is observed over unvegetated areas. This may suggest that improving soil moisture retrieval accuracy over arid and semi-arid regions should be a key priority for future L-band soil moisture development, and model-based (e.g., GLDAS) soil moisture products appear to provide more accurate soil moisture estimates over these regions.