Ecohydrological Land Reanalysis: Vegetation Water Content and Soil Moisture Data by Land Data Assimilation

ABSTRACT The accurate estimation of terrestrial water and vegetation is a grand challenge in hydrometeorology. Many previous studies developed land data assimilation systems (LDASs) and provided global‐scale land surface data sets by integrating numerical simulation and satellite data. However, vegetation dynamics have not been explicitly solved in these land reanalysis data sets. Here we present the newly developed land reanalysis data set, ECoHydrological Land reAnalysis (ECHLA). ECHLA is generated by sequentially assimilating C‐ and X‐band microwave brightness temperature satellite observations into a land surface model which can explicitly simulate the dynamic evolution of vegetation biomass. The ECHLA data set provides semiglobal soil moisture from surface to 1.95 m depth, Leaf Area Index (LAI), and vegetation water content. The ECHLA data set is publicly available in the Japan Aerospace eXploration Agency's repository and is expected to contribute to understanding terrestrial ecohydrological cycles and water‐related natural disasters such as drought.