Stochastic simulation of daily air temperature and precipitation from monthly normals in North America north of Mexico |
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Authors: | Jacques Régnière Rémi St-Amant |
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Institution: | (1) Natural Resources Canada, Canadian Forest Service, Laurentian Forestry Centre, 1055 PEPS Street, P.O. Box 10380, Stn. Sainte-Foy, Quebec, QC, G1V 4C7, Canada |
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Abstract: | A simple, stochastic daily temperature and precipitation generator (TEMPGEN) was developed to generate inputs for the study
of the effects of climate change on models driven by daily weather information when climate data are available as monthly
summaries. The model uses as input only 11 sets of monthly normal statistics from individual weather stations. It needs no
calibration, and was parameterized and validated for use in Canada and the continental United States. Monthly normals needed
are: mean and standard deviation of daily minimum and maximum temperature, first and second order autoregressive terms for
daily deviations of minimum and maximum temperatures from their daily means, correlation of deviations of daily minimum and
maximum temperatures, total precipitation, and the interannual variance of total precipitation. The statistical properties
and distributions of daily temperature and precipitation data produced by this generator compared quite favorably with observations
from 708 stations throughout North America (north of Mexico). The algorithm generates realistic seasonal patterns, variability
and extremes of temperature, precipitation, frost-free periods and hot spells. However, it predicts less accurately the daily
probability of precipitation, extreme precipitation events and the duration of extreme droughts. |
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Keywords: | Stochastic model Climate change Autoregressive model Daily weather generator Low-frequency variability |
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