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Daily meteorological data are required to initialize and run the Agro-BGC ecosystem model (Di Vittorio et al., 2010). To obtain these data for high-resolution, gridded simulations I implemented an algorithm to downscale daily, global, reanalysis climate data to a specified grid (HRCD, Di Vittorio and Miller, in review). The downscaled data are restricted to terrestrial areas and the highest resolutions are 3 arcsec between +-60 degrees latitude and 30 arcsec outside of this range. HRCD is based on the Daymet algorithm (Thornton et al., 1997) and is a statistical algorithm that relates elevation differences to meteorological variable differences at each time step. The source climate data (1x1 degree, 1948 - 2006) are maintained by the Land Surface Hydrology Research Group at Princeton University (Sheffield et al., 2006). HRCD development was funded by the Energy Biosciences Institute at the University of California, Berkeley.
The HRCD source code is written in C and is available for non-commercial use. Please read the instructions (user_guide_hrcd1.pdf) to understand the outputs and the requirements for setting up and running HRCD. Send me an email (firstname.lastname@example.org) if you would like to obtain the source code. Please include your institutional affiliation and information on how you plan to use the code and its outputs.
The grayscale values in the figure at left represent downscaled maximum temperature on Jan. 1, 2003 for portions of California and Nevada, USA. The black region represents ocean. HRCD calculated these values at 2.5 arcmin resolution for this 5x5 degree extent.
Sheffield, J., G. Goteti, E.F. Wood, (2006). Development of a 50-year high-resolution global dataset of meteorological forcings for land surface modeling. Journal of Climate, 19:3088-3111.
Thornton, P.E., S.W. Running, M.A. White, (1997). Generating surfaces of daily meteorological variables over large regions of complex terrain. Journal of Hydrology, 190:214-251.