High-resolution meteorological forcing data for hydrological modelling and climate change impact analysis in the Mackenzie River Basin

• Published in: Earth System Science Data
• Main Authors: Z. E. Asong, M. E. Elshamy, D. Princz, H. S. Wheater, J. W. Pomeroy, A. Pietroniro, A. Cannon
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2020
• Subjects: Environmental sciences; GE1-350; Geology; QE1-996.5; Canada; Mackenzie River; glacier*; Mackenzie river; permafrost
• Online Access: https://doi.org/10.5194/essd-12-629-2020; https://doaj.org/article/e44ba67a1e9c44979c7838ff6da6fcc3

Cold region hydrology is very sensitive to the impacts of climate warming. Impacts of warming over recent decades in western Canada include glacier retreat, permafrost thaw, and changing patterns of precipitation, with an increased proportion of winter precipitation falling as rainfall and shorter durations of snow cover, as well as consequent changes in flow regimes. Future warming is expected to continue along these lines. Physically realistic and sophisticated hydrological models driven by reliable climate forcing can provide the capability to assess hydrological responses to climate change. However, the provision of reliable forcing data remains problematic, particularly in data-sparse regions. Hydrological processes in cold regions involve complex phase changes and so are very sensitive to small biases in the driving meteorology, particularly in temperature and precipitation, including precipitation phase. Cold regions often have sparse surface observations, particularly at high elevations that generate a large amount of runoff. This paper aims to provide an improved set of forcing data for large-scale hydrological models for climate change impact assessment. The best available gridded data in Canada are from the high-resolution forecasts of the Global Environmental Multiscale (GEM) atmospheric model and outputs of the Canadian Precipitation Analysis (CaPA), but these datasets have 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) for hydrological modelling and climate change impact assessment over the Mackenzie River Basin. First, a multivariate generalization of the quantile mapping technique was implemented to bias-correct WFDEI against GEM-CaPA at 3 h <math xmlns="http://www.w3.org/1998/Math/MathML" id="M1" ...