Development of a 50-Year High-Resolution Global Dataset of Meteorological Forcings for Land Surface Modeling

Abstract Understanding the variability of the terrestrial hydrologic cycle is central to determining the potential for extreme events and susceptibility to future change. In the absence of long-term, large-scale observations of the components of the hydrologic cycle, modeling can provide consistent fields of land surface fluxes and states. This paper describes the creation of a global, 50-yr, 3-hourly, 1.0° dataset of meteorological forcings that can be used to drive models of land surface hydrology. The dataset is constructed by combining a suite of global observation-based datasets with the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis. Known…

• NA
  National Aeronautics and Space Administration
• UO
  University of East Anglia
• NO
  National Oceanic and Atmospheric Administration
• LR
  Langley Research Center
• JA
  Japan Aerospace Exploration Agency