Record Search Query: ServiceParameters>MODELS
Spatial Bioclimatology: Daymet
Entry ID: Daymet
Abstract: Daymet is a group of computer programs that produce surfaces of daily
temperature, precipitation, radiation, and humidity over large regions, taking
into account the effects of complex terrain. Observations can be included from
an arbitrarily large number of stations. The relationships of temperature and
precipitation to elevation are determined directly from the observations. In
addition to the ... daily observations from a network of stations, Daymet requires
digital elevation data for the region of interest.
The interpolation 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 is accomplished with an
iterative station density estimation algorithm.
The extrapolation with elevation depends on the station observations and the
station elevations. These relationships vary in space and time, and Daymet
makes a new diagnosis of these relationships for each spatial modeling unit and
for each day of observed conditions.
Precipitation estimates are performed in two steps: first a binary estimate of
precipitation occurrence, and contingent on occurrence, an estimation of
precipitation amount, corrected for elevation effects.
Radiation and humidity are estimated using the same relationships as in the
MT-CLIM model, following the completion of temperature and precipitation
(Summary adapted from
Bristow, K.L., and G.S. Campbell, 1984. On the relationship
between incoming solar radiation and daily maximum and minimum
temperature. Agricultural and Forest Meteorology, 31:159-166.
Running, S.W., R.R. Nemani, and R.D. Hungerford,
1987. Extrapolation of synoptic meteorological data in
mountainous terrain and its use for simulating forest
evaporation and photosynthesis. Canadian Journal of Forest
Glassy, J.M., and S.W. Running, 1994. Validating diurnal
climatology of the MT-CLIM model across a climatic gradient in
Oregon. Ecological Applications, 4(2):248-257.
Kimball, J.S., S.W. Running, and R. Nemani, 1997. An improved
method for estimating surface humidity from daily minimum
temperature. Agricultural and Forest Meteorology, 85:87-98.
Thornton, P.E., S.W. Running, and M.A. White, 1997. Generating
surfaces of daily meteorological variables over large regions of
complex terrain. Journal of Hydrology, 190:214-251.
Thornton, P.E., and S.W. Running, 1999. An improved algorithm
for estimating incident daily solar radiation from measurements
of temperature, humidity, and precipitation. Agricultural and
Forest Meteorology, 93:211-228.
Creation and Review Dates