Meteorology at the land surface affects many processes in the terrestrial biogeochemical system. Measurements of near-surface meteorological conditions are made at many locations, but researchers are often faced with having to perform ecosystem process simulations in areas where no meteorological measurements have been taken. To overcome these limitations, the Daymet model was developed by Dr. Peter Thornton while with the Numerical Terradynamic Simulation Group (NTSG) at the School of Forestry, University of Montana.
Daymet is a collection of algorithms and computer software designed to interpolate and extrapolate from daily meteorological observations to produce gridded estimates of daily weather parameters. Weather parameters generated include daily surfaces of minimum and maximum temperature, precipitation, humidity, and radiation produced on a 1 km x 1 km gridded surface over the conterminous United States, Mexico, and Southern Canada.
The required model inputs include a digital elevation model and observations of maximum temperature, minimum temperature, and precipitation from ground-based meteorological stations. The Daymet method is based on the spatial convolution of a truncated Gaussian weighting filter with the set of station locations. Sensitivity to the typical heterogeneous distribution of stations in complex terrain is accomplished with an iterative station density algorithm.
More information on the DayMet dataset can be found here: http://daymet.ornl.gov/overview
This summary of the precipitation variable from DayMet was created by attributing the dataset to every 12 digit hydrologic unit using the Geo Data Portal, documented here: https://my.usgs.gov/confluence/display/GeoDataPortal/ The summary data are distributed using a server that offers several options for data access including an Open Geospatial Consortium Sensor Observation Service, and OPeNDAP. These data are also offered through a user friendly interface in the National Water Census Platform Portal.
