Comment on essd-2025-728

Abstract. The Soil Moisture and Ocean Salinity (SMOS) mission delivers the first multi-angular L-band observations for retrieving global soil moisture (SM) and vegetation optical depth (VOD), two critical variables for understanding terrestrial water and carbon cycles. However, the combined effects of non-identical fields of view and aliasing in multi-angular SMOS brightness temperature (TB) observations can introduce noise and biases when the TBs are averaged to a nominal incidence angle, as done in the SMOS L3 dataset, thereby degrading land parameter retrievals. To address this issue, an optimized SMOS TB dataset was initially produced at a fixed 40° incidence angle, consistent with the Soil Moisture Active Passive (SMAP) mission. We then developed the first SMOS mono-angular SM and VOD products designed to achieve performance comparable to SMAP and improved relative to conventional multi-angle SMOS retrievals. The 40° TB optimization was performed using the L-band Microwave Emission of the Biosphere (L-MEB) model, and the inversion relied on the SMAP-INRAE-BORDEAUX (SMAP-IB) algorithm, yielding a global 40° SMOS TB record and associated SM and VOD products for 2010–2024 at 25 km spatial resolution, collectively referred to as SMOS-IB. Results showed that the optimized 40° TB reached a performance level comparable to SMAP and improved relative to SMOS-L3, both in its sensitivity to in-situ SM from the International Soil Moisture Network (ISMN) and in the reduction of global pixel-scale noise. When multiple evaluation metrics are considered, the SMOS-IB SM and VOD data, benefiting from the use of the optimized TB as input and a newly optimized soil roughness (Hr) parameterization, showed improved performance compared with those derived from SMOS L3 40° TB or from the multi-angular SMOS products. The SMOS-IB TB, SM and VOD products can be used for L-band algorithm development and SMAP harmonization, global drought monitoring, and studies of vegetation water and biomass dynamics. SMOS-IB is publicly available at https://zenodo.org/records/17647385 (Xing et al., 2025).