Abstract
Abstract. Closing the terrestrial water budget is necessary to provide 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. Conditioned on the current limited data availability, 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 under the assumption that the deviation from the ensemble mean of all data sources for the same budget variable is used as a proxy of the uncertainty in individual water budget variables. The resulting long-term (1984–2010), monthly 0.5∘ resolution global terrestrial water cycle Climate Data Record (CDR) data set is developed under the auspices of the National Aeronautics and Space Administration (NASA) Earth System Data Records (ESDRs) program. This data set 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 data set 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.
Highlights
Quantification of the terrestrial water budget and its evolution over time at fine spatial resolutions is critical to understanding the availability and variability of Earth’s terrestrial water budget and the exchanges and interactions among the terrestrial, atmospheric, and oceanic branches of the hydrosphere, and to assess the risk of hydrological extremes such as floods and droughts at regional to global scales
The ensemble mean of the total water storage change (TWSC) from GeoForschungsZentrum Potsdam (GFZ), Center for Space Research (CSR), and Jet Propulsion Laboratory (JPL) is taken as the best TWSC product derived from GRACE, and this is used in the later water budget analysis together with TWSC from VIC
The interannual monthly climatological bias, which is the monthly mean precipitation merged from Princeton Global Forcing data set (PGF), Global Precipitation Climate Centre (GPCC), Climate Hazard group InfraRed Precipitation with Stations (CHIRPS), and Colorado State University (CSU) minus that merged from PGF, GPCC, and CHIRPS, is added to the interannual monthly mean precipitation during the incomplete data records period (i.e., 1984–1997)
Summary
Quantification of the terrestrial water budget and its evolution over time at fine spatial resolutions is critical to understanding the availability and variability of Earth’s terrestrial water budget and the exchanges and interactions among the terrestrial, atmospheric, and oceanic branches of the hydrosphere, and to assess the risk of hydrological extremes such as floods and droughts at regional to global scales. Building on an increasingly available inventory of global water budget data sets from in situ, satellite, reanalysis, and land surface models, the study reported here has five advances over previously reported work These are to (1) expand the use of the CKF data assimilation technique in closing the water budget from that reported by Pan et al (2012) and Sahoo et al (2011), (2) extend the data records back in time to 1984 (vs 2000 in Rodell et al (2015) and forward to 2010 (vs previous analyses which usually stop near the turn of the 21st century), (3) refine the spatial resolution to 0.5◦ for the land surface (vs basin-scale analysis in Pan et al, 2012 and Sahoo et al, 2011, and continental and oceanic analysis in Rodell et al, 2015 and Trenberth and Fasullo, 2013a) and account for the oblateness of Earth, (4) develop a harmonized global terrestrial water cycle CDR by merging the full combination of in situ and satellite remote sensing observations, LSM simulations, and reanalysis model outputs at monthly and 0.5◦ spatial resolution for the period of 1984–2010 (the CDR data set includes estimates for all major terrestrial water budget variables, i.e., P , ET, R, and TWSC, with budget closure at the grid scale), and (5) validate the CDR against in situ observations not used in the development of the data set.
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