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This study attempts to derive the uncertainty of the soil moisture estimation from passive microwave satellite mission at global scale. To do so, the approach is based on the sensitivity of the Soil Moisture and Ocean Salinity (SMOS) soil moisture retrieval quality to the land surface characteristics within its footprint (presence of forest, topography, open water bodies, sand, clay, bulk density and soil organic carbon content). First, we performed a global assessment of SMOS using in situmeasurements from the International Soil Moisture Network (ISMN) as reference, with more than 1900 ISMN stations and 10 years of SMOS data. This assessment shows that the ubRMSD scores vary greatly between locations (with a mean of 0.074 m3m−3and an interquartile range of 0.030 m3m−3). Second, the scores are analyzed for different surface conditions within the satellite footprint. The best agreement between the ground measurement and SMOS time series are obtained for low forest cover, low topographic complexity, and marginal presence of open water bodies within the SMOS footprint. Soil parameters also have an impact, with better scores for sandier soils with a high bulk-density and low soil organic carbon content. Finally, we propose to extrapolate the obtained relationships, using a multiple linear regression, in order to derive a global map of SMOS uncertainties based on surface conditions. This map of predicted uncertainties show a diverse range of ubRMSD values across the globe (with a mean of 0.076 m3m−3and an interquartile range of 0.031 m3m−3) depending on the surface characteristics. At the ISMN site location, the predicted ubRMSD shows similar results than the comparison between SMOS and the in situmeasurements. The map of predicted SMOS ubRMSD represents an upper bound estimate of the SMOS uncertainty, as it includes the uncertainties of the in situsensor measurements and the scale mismatch. Further investigations will focus on the different components of this uncertainty budget to obtain a better assessment of the absolute uncertainties of SMOS soil moisture retrievals across the globe.

Changes in terrestrial tropical carbon stocks have an important role in the global carbon budget. However, current observational tools do not allow accurate and large-scale monitoring of the spatial distribution and dynamics of carbon stocks1. Here, we used low-frequency L-band passive microwave observations to compute a direct and spatially explicit quantification of annual aboveground carbon (AGC) fluxes and show that the tropical net AGC budget was approximately in balance during 2010 to 2017, the net budget being composed of gross losses of −2.86 PgC yr−1offset by gross gains of −2.97 PgC yr−1between continents. Large interannual and spatial fluctuations of tropical AGC were quantified during the wet 2011 La Niña year and throughout the extreme dry and warm 2015–2016 El Niño episode. These interannual fluctuations, controlled predominantly by semiarid biomes, were shown to be closely related to independent global atmospheric CO2growth-rate anomalies (Pearson’s r= 0.86), highlighting the pivotal role of tropical AGC in the global carbon budget. Tropical carbon stocks are essential for proper accounting of global carbon budgets, but difficult to monitor on a large scale. L-band microwave observations used here enable direct and spatially explicit accounting of annual carbon fluxes from different types of land surface.