An Overview on the Project to Develop Consistent Earth System Data Records for the Global Terrestrial Water Cycle

We aim to develop consistent, long-term Earth System Data Records (ESDRs) for the major components (storages and fluxes) of the terrestrial water cycle at a spatial resolution of 0.5 degrees (latitude-longitude) and for the period 1950 to near-present. The resulting ESDRs are intended to provide a consistent basis for estimating the mean state and variability of the land surface water cycle at the spatial scale of the major global river basins. The ESDRs to produce include a) surface meteorology (precipitation, air temperature, humidity and wind), b) surface downward radiation (solar and longwave) and c) derived and/or assimilated fluxes and storages such as surface soil moisture storage, total basin water storage, snow water equivalent, storage in large lakes, reservoirs, and wetlands, evapotranspiration, and surface runoff. We construct data records for all variables back to 1950, recognizing that the post-satellite data will be of higher quality than pre-satellite (a reasonable compromise given the need for long-term records to define interannual and interdecadal variability of key water cycle variables). A distinguishing feature will be inclusion of two variables that reflect the massive effects of anthropogenic manipulation of the terrestrial water cycle, specifically reservoir storage, and irrigation water use. The overall goal of the project is to develop long term, consistent ESDRs for terrestrial water cycle states and variables by updating and extending previously funded Pathfinder data set activities to the investigators, and by making available the data set to the scientific community and data users via a state-of-the-art internet web-portal. The ESDRs will utilize algorithms and methods that are well documented in the peer reviewed literature. The ESDRs will merge satellite-derived products with predictions of the same variables by LSMs driven by merged satellite and in situ forcing data sets (most notably precipitation), with the constraint that the merged products will close the surface water budget. The primary land surface forcing variable, precipitation, will be formed by merging model (reanalysis) and in situ data with satellite-based precipitation products such as TRMM, GPCP, and CMORPH. Derived products will include surface soil moisture (from TRMM, AMSR-E, SMMR, SSM/I passive microwave and ERS microwave scatterometers), snow extent (from MODIS and AVHRR), evapotranspiration (model- derived using ISCCP radiation forcings from geostationary and LEO satellites), and runoff (from LSM predictions and in-situ measurements).