Hydrology and Earth System Sciences | Zhang et al. 
Closing the terrestrial water budget is necessary to providing consistent estimates of budget components for understanding water resources and changes over time. Given the lack of in-situ observations of budget components at anything but local scale, merging information from multiple data sources (e.g. in-situ observation, satellite remote sensing, land surface model and reanalysis) through data assimilation techniques that optimize the estimation of fluxes is a promising approach. In this study, a systematic method is developed to optimally combine multiple available data sources for precipitation (P), evapotranspiration (ET), runoff (R) and the total water storage change (TWSC) at 0.5° spatial resolution globally and to obtain water budget closure (i.e. to enforce P − ET − R − TWSC = 0) through a Constrained Kalman Filter (CKF) data assimilation technique. The resulting long-term (1984–2010), monthly, 0.5° resolution global terrestrial water cycle Climate Data Record (CDR) dataset is developed under the auspices of the National Aeronautics and Space Administration (NASA) Earth System Data Records (ESDRs) program. This dataset serves to bridge the gap between sparsely gauged regions and the regions with sufficient in-situ observations in investigating the temporal and spatial variability in the terrestrial hydrology at multiple scales. The CDR created in this study is validated against in-situ measurements like river discharge from the Global Runoff Data Centre (GRDC) and the United States Geological Survey (USGS) and ET from FLUXNET. The dataset is shown to be reliable and can serve the scientific community in understanding historical climate variability in water cycle fluxes and stores, benchmarking the current climate, and validating models.
Full text can be found here.