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- W2074420030 abstract "To address the demand for high spatial resolution gridded climate data, we have advanced the Daymet point-based interpolation algorithm for downscaling global, coarsely gridded data with additional output variables. The updated algorithm, High-Resolution Climate Downscaler (HRCD), performs very good downscaling of daily, global, historical reanalysis data from 1° input resolution to 2.5 arcmin output resolution for day length, downward longwave radiation, pressure, maximum and minimum temperature, and vapor pressure deficit. It gives good results for monthly and yearly cumulative precipitation and fair results for wind speed distributions and modeled downward shortwave radiation. Over complex terrain, 2.5 arcmin resolution is likely too low and aggregating it up to 15 arcmin preserves accuracy. HRCD performs comparably to existing daily and monthly US datasets but with a global extent for nine daily climate variables spanning 1948–2006. Furthermore, HRCD can readily be applied to other gridded climate datasets." @default.
- W2074420030 created "2016-06-24" @default.
- W2074420030 creator A5032179615 @default.
- W2074420030 creator A5080328321 @default.
- W2074420030 date "2012-08-29" @default.
- W2074420030 modified "2023-10-18" @default.
- W2074420030 title "Evaluating a modified point-based method to downscale cell-based climate variable data to high-resolution grids" @default.
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- W2074420030 doi "https://doi.org/10.1007/s00704-012-0740-9" @default.
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