Zanpin Xing ¹ Xiaojun Li ^2* Lei Fan ³ Frédéric Frappart ² Hyunglok Kim ⁴ Karthikeyan Lanka ⁵ Preethi Konkathi ⁵ Yuqing Liu ² Lin Zhao ⁶ Jean-Pierre Wigneron ²

• ¹ Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences (CAS), Lanzhou, China
• ² INRAE ​​Nouvelle-Aquitaine Bordeaux, Bordeaux, Aquitaine, France
• ³ Southwest University, Chongqing, Chongqing Municipality, China
• ⁴ University of Virginia, Charlottesville, Virginia, United States
• ⁵ Centre of Studies in Resources Engineering, Indian Institute of Technology Bombay, Mumbai, Maharashtra, India
• ⁶ Nanjing University of Information Science and Technology, Nanjing, Jiangsu Province, China

Two L-band passive microwave satellite sensors, onboard the Soil Moisture and Ocean Salinity (SMOS) launched in 2009 and Soil Moisture Active Passive (SMAP) launched in 2015, are specifically designed for surface soil moisture (SM) monitoring. The first global continuous fused L-band satellite SM product based on SMOS and SMAP observations (SMOS-SMAP-INRAE-BORDEAUX, the socalled Fused-IB) was recently released to the public. Currently, the performance of Fused-IB has only been evaluated collectively over the entire data records in the study period, without specific evaluation for individual seasons. To fill this gap, this study intercompared the Fused-IB and the enhanced SMAP-L3 version 6 (SMAP-E) SM products against in-situ SM data from the International Soil Moisture Network (ISMN) from 2016 to 2020 regarding the whole period and different seasons. We aim to investigate the performance of these two products at different time scales and to explore the potential eco-hydrological factors (i.e., precipitation and vegetation) driving their seasonal variations. Results show that both SM products are in good agreement with the in-situ measurements, demonstrating high median correlation (R) and low ubRMSD (median R = 0.70 and ubRMSD = 0.058 m 3 /m 3 for Fused-IB vs. R = 0.68 and ubRMSD = 0.059 m 3 /m 3 for SMAP-E) during 2016-2020. For most land use and land cover (LULC) types, Fused-IB outperformed SMAP-E with higher accuracy and lower errors, particularly in forests, partly due to the advantage of the robust SMAP-IB (SMAP-INRAE-BORDEAUX) algorithm used to generate Fused-IB in forests, which avoids the pronounced saturation effects of vegetation optical depth caused by relying on optical information. Besides, both products had superior performances across most LULC types in summer (JJA) and autumn (SON), yet increased uncertainties were observed in forests, grasslands, and croplands during spring (MAM) and winter (DJF). These uncertainties could be mainly attributed to the impact of vegetation growth in forests, grasslands, and croplands, and the rainfall events in grasslands. The results of this study can serve as a reference for algorithm developers to enhance the accuracy of SM and thus promote hydrometeorological applications that benefit from L-band radiometer soil moisture products.