Theoretical and Applied Climatology

, Volume 112, Issue 3–4, pp 495–519 | Cite as

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

  • Alan V. Di VittorioEmail author
  • Norman L. Miller
Original Paper


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.


Root Mean Square Error Gridded Data Input Cell National Climatic Data Center Scale Mismatch 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Day length


Downward long wave radiation




Surface pressure


Relative humidity


Specific humidity


Downward shortwave radiation


Average air temperature


Average daytime temperature


Dew point temperature


Maximum temperature


Minimum temperature


Vapor pressure deficit


Wind speed


High-Resolution Climate Downscaler



The Energy Biosciences Institute funded this research under grant EBI07-J120. The ISLSCP Initiative II elevation data are courtesy of Kristen Verdin, the United States Geological Survey, and the Eros data center. Work performed at Lawrence Berkeley National Laboratory, including manuscript revision, was supported by the Director, Office of Science, Office of Basic Energy Sciences of the US Department of Energy under contract no. DE-AC02-05CH11231.


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Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  1. 1.Energy Biosciences InstituteUniversity of CaliforniaBerkeleyUSA
  2. 2.Earth Sciences DivisionLawrence Berkeley National LaboratoryBerkeleyUSA
  3. 3.Department of GeographyUniversity of CaliforniaBerkeleyUSA

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