In order to understand ongoing and future climate change and its impacts on ecosystem services, we must have a grasp on historical ranges of climate variability. Fortunately, detailed weather station data are available in the United States for thousands of locations over the last century. Moreover, sophisticated approaches have been developed for translating these measurements into unified datasets across the U.S., including climate estimates for locations that lack station data.The PRISM (Parameter-elevation Regressions on Independent Slopes Model) Climate Group produces such estimates from weather station data at daily, monthly, and annual time steps, incorporating data from 1895 to the present day. PRISM methods utilize digital elevation data and effects such as rain shadows and coastal influences to generate climate data that are widely used and recognized as among the highest-quality spatial climate data available. These datasets provide estimates of precipitation, temperature, and other derived climate variables. Among the most fundamental PRISM data and maps are the long-term average, or climate “normal,” estimates. These are based on monthly averages across 30 years, and the most recently developed climate normals are for the period 1981–2010. PRISM maps and data are widely used for educational purposes, in climate change research, to assess the vulnerability of social and ecological systems to climate variability, and for other conservation and management applications.
