summary: Archived and distributed through the ORNL DAAC, the Daymet data set provides gridded estimates of daily weather parameters for North America, including daily continuous surfaces of minimum and maximum temperature, precipitation occurrence and amount, humidity, shortwave radiation, snow water equivalent, and day length. The daily time step, 1 km x 1 km spatial resolution, and North American spatial extent of the data set makes it a unique and valuable contribution to scientific, research, and educational communities. The literature shows that Daymet data have been broadly applied to fields including hydrology, terrestrial vegetation growth models, carbon cycle science, and regional to large scale climate change analysis.Daymet data are available for 1980 through the latest full calendar year and includes the United States, Mexico, Canada, Hawaii, and Puerto Rico.Daymet is supported by funding from NASA through the Earth Science Data and Information System (ESDIS) and the Terrestrial Ecosystem Program. The continued development of the Daymet algorithm and processing is also supported by the Office of Biological and Environmental Research within the U.S. Department of Energy's Office of Science.
Citation = "Thornton, P.E., M.M. Thornton, B.W. Mayer, Y. Wei, R. Devarakonda, and N. Wilhelmi. 2016. Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 3. ORNL DAAC, Oak Ridge, Tennessee, USA. Accessed Month DD, YYYY. Time period: YYYY-MM-DD to YYYY-MM-DD. Spatial Range: N=DD.DD, S=DD.DD, E=DDD.DD, W=DDD.DD. http://dx.doi.org/10.3334/ORNLDAAC/1328"
Citation = "Thornton PE, Running SW, White MA. 1997. Generating surfaces of daily meteorological variables over large regions of complex terrain. Journal of Hydrology 190: 214-251. http://dx.doi.org/10.1016/S0022-1694(96)03128-9"
Citation = "Thornton, P.E., H. Hasenauer, and M.A. White. 2000. Simultaneous estimation of daily solar radiation and humidity from observed temperature and precipitation: An application over complex terrain in Austria. Agricultural and Forest Meteorology 104:255-271"
Citation = "Thornton, P.E. and S.W. Running. 1999. An improved algorithm for estimating incident daily solar radiation from measurements of temperature, humidity, and precipitation. Agriculture and Forest Meteorology. 93:211-228"