| dc.description.abstract |
In order to prepare atmospheric forcing data sets to drive the hydrologic models at
high spatial resolution, it is necessary to apply appropriate downscale methods and
bias correction schemes to the coarse reanalysis products. In this manuscript, first
we describe the methodology to derive a high-resolution (1×1 km2, hourly) atmospheric
forcing data set from 3-hr NARR (North American Regional Reanalysis) products originally
at 32×32km resolution, and second we illustrate the value and utility of the downscaled
products to drive hydrologic models offline through analysis of a long-term (5-year)
continuous simulation of water and energy budgets in the Southern Appalachians against
flux tower observations. The IPHEx-H4SE atmospheric forcing data set includes elevation
corrected air temperature and lapse rate, specific humidity, 46 friction velocity,
surface layer winds, incoming longwave radiation, and topographically and cloudiness
corrected incoming shortwave radiation that enable simulating water and energy fluxes
from diurnal to annual time-scales, and for extreme events. Although the 5-year simulation
presented here was conducted with a randomly selected rainfall product among those
recommended in the companion report ( EPL-2013-H4SE-3) without re-initialization or
data assimilation, and therefore does not represent an optimal simulation with the
hydrological model but rather a baseline control simulation that integrates and propagates
the uncertainty in all forcing data sets, the results clearly illustrate the benefit
of using the bias corrected NARR atmospheric forcing fields made available here.
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