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A Bias-Corrected 3-hourly 0.125 Gridded Meteorological Forcing Data Set (1979 – 2016) for Land Surface Modeling in North America

Description: Cold regions hydrology is very sensitive to the impacts of climate warming. Future warming is expected to increase the proportion of winter precipitation falling as rainfall. Snowpacks are expected to undergo less sublimation, form later and melt earlier and possibly more slowly, leading to earlier spring peak streamflow. More physically realistic and sophisticated hydrological models driven by reliable climate forcing can provide the capability to assess hydrologic responses to climate change. However, hydrological processes in cold regions involve complex phase changes and so are very sensitive to small biases in the driving meteorology, particularly temperature and precipitation. Cold regions often have sparse surface observations, particularly at high elevations that generate the major amount of runoff. The effects of mountain topography and high latitudes are not well reflected in the observational record. The best available gridded data in these regions is from the high resolution forecasts of the Global Environmental Multiscale (GEM) atmospheric model and the Canadian Precipitation Analysis (CaPA) reanalysis but this dataset has a short historical record. The EU WATCH ERA-Interim reanalysis (WFDEI) has a longer historical record, but has often been found to be biased relative to observations over Canada. The aim of this study, therefore, is to blend the strengths of both datasets (GEM-CaPA and WFDEI) to produce a less-biased long record product (WFDEI-GEM-CaPA). First, a multivariate generalization of the quantile mapping technique was implemented to bias-correct WFDEI against GEM-CaPA at 3h x 0.125ᵒ resolution during the 2005-2016 period, followed by a hindcast of WFDEI-GEM-CaPA from 1979.
Authors: Asong, Zilefac Elvis; University of Saskatchewan;
Wheater, Howard; University of Saskatchewan
Pomeroy, John; University of Saskatchewan
Pietroniro, Alain; Environment and Climate Change Canada
Elshamy, Mohamed; University of Saskatchewan;
Keywords: cold regions processes
bias correction
North America
Date: 20-Sep-2018
Publisher: Federated Research Data Repository / dépôt fédéré de données de recherche

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If you use this dataset please add this citation to your publication:
Asong, Zilefac Elvis; Wheater, Howard; Pomeroy, John; Pietroniro, Alain; Elshamy, Mohamed, "A Bias-Corrected 3-hourly 0.125 Gridded Meteorological Forcing Data Set (1979 – 2016) for Land Surface Modeling in North America," 2018,