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Evaluating a modified point-based method to downscale cell-based climate variable data to high-resolution grids

Authors :
Alan V. Di Vittorio
Norman L. Miller
Source :
Theoretical and Applied Climatology. 112:495-519
Publication Year :
2012
Publisher :
Springer Science and Business Media LLC, 2012.

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.

Details

ISSN :
14344483 and 0177798X
Volume :
112
Database :
OpenAIRE
Journal :
Theoretical and Applied Climatology
Accession number :
edsair.doi...........53d89847c546a6fc6982525a90862e7e