|Diluzio, Mauro - TEXAS AGRILIFE|
|Johnson, Gregory - NRCS|
|Daly, Christopher - OREGON STATE UNIV|
|Eischeid, Jon - UNIV OF COLORADO|
Submitted to: Journal of Applied Meteorology and Climatology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: March 27, 2007
Publication Date: February 15, 2008
Citation: Di Luzio, M., Johnson, G.L., Daly, C., Eischeid, J.K., Arnold, J.G. 2008. Constructing retrospective gridded daily precipitation and temperature datasets for the conterminous United States. Journal of Applied Meteorology and Climatology. 47(2):475-497. Interpretive Summary: Regional and national assessments related to the environment, conservation practices, biofuel production, and climate change require daily weather to drive decision support tools. In this study, we took all existing weather gages in the conterminous U.S. (7,565 stations) and used an interpolation scheme to obtain gridded precipitation and temperature data. The interpolation scheme accounts for elevation, slope, and aspect. The new gridded data sets provide daily precipitation and maximum and minimum temperature values for 4 square kilometer cells for 1960-2001 across the U.S. The data is currently being used in national conservation and environmental assessments by the Natural Resources Conservation Service and by the U.S. Environmental Protection Agency.
Technical Abstract: This paper presents and evaluates a method for the construction of long-range and wide-area temporal spatial datasets of daily precipitation and temperature (maximum and minimum). This method combines the interpolation of daily ratios/fractions derived from ground-based meteorological station records and respective fields of monthly estimates. Data sources for the described implementation over the conterminous United States (CONUS) are two independent and quality-controlled inputs: 1) an enhanced compilation of daily observations derived from the National Climatic Data Center digital archives and 2) the Parameter–Elevation Regressions on Independent Slopes Model (PRISM) maps. The results of this study show that this nonconventional interpolation preserves the spatial and temporal distribution of both the PRISM maps (monthly, topography-sensitive patterns) and the original daily observations. Statistics of a preliminary point comparison with the observed values at high-quality and independent reference sites show a reasonable agreement and a noticeable improvement over the nearest station method in orographically sensitive areas. The implemented datasets provide daily precipitation and temperature values at 2.5-min (around 4 km) resolution for 1960–2001. Combining seamless spatial and temporal coverage and topographic sensitivity characteristics, the datasets offer the potential for supporting current and future regional and historical hydrologic assessments over the CONUS.