An improved perspective in the spatial representation of soil moisture: potential added value of SMOS disaggregated 1 km resolution all weather product

This study uses the synergy of multi-resolution soil moisture (SM) satellite estimates from the Soil Moisture Ocean Salinity (SMOS) mission, a dense network of ground-based SM measurements, and a soil-vegetation-atmosphere transfer (SVAT) model, SURFEX (externalized surface), module ISBA (interactions between soil, biosphere and atmosphere), to examine the benefits of the SMOS level 4 (SMOS-L4) version 3.0, or all weather high-resolution soil moisture disaggregated product (SMOS-L4(3.0); similar to 1 km). The added value compared to SMOS level 3 (SMOS-L3; similar to 25 km) and SMOS level 2 (SMOS-L2; similar to 15 km) is investigated. In situ SM observations over the Valencia anchor station (VAS; SMOS calibration and validation -Cal/Val - site in Europe) are used for comparison. The SURFEX (ISBA) model is used to simulate point-scale surface SM (SSM) and, in combination with high-quality atmospheric information data, namely from the European Centre for Medium-Range Weather Forecasts (ECMWF) and the Systeme d'analyse fournissant des renseignements atmospheriques a la neige (SAFRAN) meteorological analysis system, to obtain a representative SSM mapping over the VAS. The sensitivity to realistic initialization with SMOS-L4(3.0) is assessed to simulate the spatial and temporal distribution of SSM. Results demonstrate the following: (a) All SMOS products correctly capture the temporal patterns, but the spatial patterns are not accurately reproduced by the coarser resolutions, probably in relation to the contrast with point-scale in situ measurements. (b) The potential of the SMOS-L4(3.0) product is pointed out to adequately characterize SM spatio-temporal variability, reflecting patterns consistent with intensive point-scale SSM samples on a daily timescale. The restricted temporal avail-ability of this product dictated by the revisit period of the SMOS satellite compromises the averaged SSM representation for longer periods than a day. (c) A seasonal analysis points out improved consistency during December-January-February and September-October-November, in contrast to significantly worse correlations in March-April-May (in relation to the growing vegetation) and June-July-August (in relation to low SSM values < 0.1 m(3) m(-3) and low spatial variability). (d) The combined use of the SURFEX (ISBA) SVAT model with the SAFRAN system, initialized with SMOS-L4(3.0) 1 km disaggregated data, is proven to be a suitable tool for producing regional SM maps with high accuracy, which could be used as initial conditions for model simulations, flood forecasting, crop monitoring and crop development strategies, among others.