A knowledge-based approach to the statistical mapping of climate

The demand for spatial climate data in digital form has risen dramatically in recent years. In response to this need, a variety of statistical techniques have been used to facilitate the production of GIS-compatible climate maps. However, observational data are often too sparse and unrepresentative to directly support the creation of high-quality climate maps and data sets that truly represent the current state of knowledge. An effective approach is to use the wealth of expert knowledge on the spatial patterns of climate and their relationships with geographic features, termed 'geospatial climatology', to help enhance, control, and parameterize a statistical technique. Described here is a dynamic…

• UD
  U.S. Department of Commerce
• UD
  U.S. Department of Agriculture
• UD
  U.S. Department of the Interior
• OS
  Oregon State University
• NO
  National Oceanic and Atmospheric Administration
• UG
  U.S. Geological Survey
• UF
  U.S. Forest Service
• NR
  Natural Resources Conservation Service
• NW
  National Weather Service