HR: 1330h
AN: H22B-0921    [PDF]
TI: A 50-yr Global Dataset of Land Surface Fluxes and States
AU: * Sheffield, J
EM: justin@princeton.edu
AF: Princeton University, Dept. of Civil and Environmental Engineering, Princeton, NJ 08544 United States
AU: Wood, E F
EM: efwood@runoff.princeton.edu
AF: Princeton University, Dept. of Civil and Environmental Engineering, Princeton, NJ 08544 United States
AU: Goteti, G
EM: ggoteti@princeton.edu
AF: Princeton University, Dept. of Civil and Environmental Engineering, Princeton, NJ 08544 United States
AU: Adam, J
EM: jenny@hydro.washington.edu
AF: University of Washington, Dept. of Civil and Environmental Engineering, Seattle, WA 98195 United States
AU: Lettenmaier, D P
EM: dennisl@u.washington.edu
AF: University of Washington, Dept. of Civil and Environmental Engineering, Seattle, WA 98195 United States
AB: Model simulations of large scale water and energy balances are useful for the study of climate change and variability, and in some cases can act as surrogates for observations that are sparse or nonexistent. We describe a global, 50-yr sub-daily, 1.0 degree terrestrial dataset of water and energy fluxes and states using observation based forcings and a state of the art land surface model. The forcing dataset is constructed from a combination of global monthly precipitation and temperature data disaggregated to subdaily time steps using the NCEP/NCAR Reanalysis. Known biases in the Reanalysis precipitation and near-surface meteorology are corrected using observations where available. Corrections are made to the wet-dry day statistics of the reanalysis precipitation which have been found to exhibit a spurious wave-like pattern in the high-latitude winter. Wind-induced undercatch of solid precipitation is corrected using the results from the World Meteorological Organization (WMO) Solid Precipitation Measurement Intercomparison. Underestimation of precipitation in mountainous regions is corrected using a hydrologic water balance approach based on watershed runoff ratios and historical discharge data. This version of the dataset is available at daily and 2 degree resolution. A second version has been created at 3-hourly and 1.0 degree resolution to capture the finer temporal and spatial variability of land surface fluxes and states. This dataset is obtained by disaggregating the 2 degree precipitation by statistical downscaling using relationships developed with the 0.5 degree GPCP daily 1997-present dataset. Temporal disaggregation from daily to 3-hourly also uses statistical downscaling but with the TRMM 1/4 deg 3-hourly dataset (Feb 2002 - Jan 2003). The forcing dataset is used to drive the Variable Infiltration Capacity (VIC) land surface model to produce fields of land surface water and energy fluxes and states. Calibration of the model is achieved through the use of a multi-objective and multi-seasonal calibration strategy which uses representative sampling techniques and geostatistical interpolation to reduce the computational overhead. The final product provides a long-term, globally-consistent dataset of land surface water and energy fluxes and states that are useful for the study of seasonal and inter-annual variability and for the evaluation of coupled models and other land surface prediction schemes.
DE: 1655 Water cycles (1836)
DE: 1833 Hydroclimatology
DE: 1836 Hydrologic budget (1655)
SC: Hydrology [H]
MN: 2003 Fall Meeting