Reconstruction of soil moisture time series with characterisation of drydown attributes

• Ground observations can recharacterize satellite soil moisture drying attributes. • Drying characteristics are usable for redefining complete soil moisture dynamics. • Better performance can be seen at higher vegetated and sandy locations. Encapsulating soil water drying attributes in derived remote sensing products is essential for their application to various environmental studies. Systematic differences are observed for soil moisture (SM) drying phases (drydown) in Soil Moisture Active Passive (SMAP) level 4 (SMAP L4) product when compared to ground observations due to differences in measurement processes. An algorithm (BRF: Bivariate Recursive Filter) is able to translate drydown parameters, namely the drydown recession coefficient and initial wetness, to in-situ scale to enhance consistency with regional in-situ observations. Here, we propose a reconstruction procedure to structure the complete SM time series so that it is compatible with the bivariate transformed drydown attributes. The present study develops the reconstructed SM time series at any grid location SMAP L4 data is available at. The method is validated with 6 global in-situ networks and improvements have been observed in the reconstructed SMAP SM series. Significant enhancements are observed particularly during the drydown periods. Additional improvement is noticed when observations from spatially nearby in-situ stations for a target grid is used; this can assist in regional hydrological studies whenever ground data is available.