The PRISM (Parameter-elevation Regressions on Independent Slopes Model) knowledge-based system (Daly et al., 1994, 2000b, 2002, 2003) has been used to create 4-km2 climate grids (precipitation and minimum and maximum temperatures) for the United States and China. These grids were used to create the suitability maps used in this chapter. PRISM is a sophisticated climate mapping technology used in several major climate mapping efforts in the United States, including official maps for the USDA (Daly and Johnson, 1999; USDA-NRCS, 1998), a 111-yr monthly climate time series for the United States (Gibson et al., 2002; Daly et al., 2004), and a new climate atlas for the United States (NOAA-NCDC, 2002). The PRISM system also has been used internationally to create state-of-the-science climate maps in Europe (Schwarb et al., 2001), Canada (Milewska et al., 2002), and Asia (Daly et al., 2000a). PRISM is being updated to a grids resolution of ~800 m2.
The PRISM system uses point observational data, a digital elevation grid, and other spatial data sets to generate estimates of climatic variables on a regular grid that is GIS-compatible (Daly et al., 2002). The model is a moving-window linear regression of climate vs. elevation that is calculated for each grid cell in the digital elevation grid. Stations surrounding the grid cell provide data points for the regression. PRISM calculates a climate-elevation regression for each digital elevation model (DEM) grid cell, and stations entering the regression are assigned weights based primarily on the physiographic similarity of the station to the grid cell. Factors considered are location, elevation, coastal proximity, topographic facet orientation, vertical atmospheric layer, topographic position, and orographic effectiveness of the terrain. The PRISM data set for the United States was compared with the WorldClim and Daymet spatial climate data sets (Daly et al., 2008). Surface stations used in the analysis numbered nearly 13,000 for precipitation and 10,000 for temperature. The comparison demonstrated that using a relatively dense station data set and the physiographically sensitive PRISM interpolation process resulted in substantially improved climate grids over those of WorldClim and Daymet. Thus, PRISM is unique in its ability to create highly detailed and accurate climate grids (Daly et al., 2008).