The CATDS Centre (Centre Aval de Traitement des Données) recently released global daily gridded surface soil moisture (SSM) products derived from the SMOS (Soil Moisture and Ocean Salinity) satellite brightness temperatures observations, the so called SMOS level 3 SSM datasets. To further improve the Level-3 retrieval algorithm, evaluation of the accuracy of the spatio-temporal variability of the SMOS Level 3 products (SMOSL3) is necessary. For this purpose, a comparative analysis of SMOS Level 3 ascending (SMOSL3-ASC) and descending (SMOSL3-DES) with a SSM product derived from the observations of the Advanced Microwave Scanning Radiometer (AMSR-E) computed by implementing the Land Parameter Retrieval Model (LPRM) algorithm, referred to as AMSR-LPRM, was conducted. The comparison of both products was made against SM-DAS-2 SSM products produced at ECMWF (European Centre for Medium-Range Weather Forecasts) during the 03/2010-09/2011 period at the global scale. Global maps of correlation coefficient (R) were computed and averaged as a function of biome types. We found that SMOSL3 (ASC and DES) and AMSR-E are capable of reproducing the temporal dynamics of the SM-DAS-2 SSM products over most of the globe. The SMOSL3-ASC product performed better than the descending one but both were found to better capture the SSM temporal dynamics in highly vegetated biomes (“Tropical humid”, “Temperate Humid”, etc.) than AMSR-LPRM. AMSR-LPRM was more capable of capturing the temporal dynamics over arid (“Desert temperate” and “Desert tropical”) biomes. Finally, we show that the accuracy of the remotely sensed SSM products is strongly related to leaf area index (LAI). Both the SMOSL3 and AMSR-LPRM (slightly better) SSM products correlate best with the SM-DAS-2 products over biomes with an average value of LAI of ~ 1.86.Read less <