Generation of Simulated Daily Precipitation and Air and Soil Temperatures

Paul D. Mitchell

No 18503, Hebrew University of Jerusalem Archive from Hebrew University of Jerusalem

Abstract: This paper describes a maximum likelihood method using historical weather data to estimate a parametric model of daily precipitation and maximum and minimum air temperatures. Parameter estimates are reported for Brookings, SD, and Boone, IA, to illustrate the procedure. The use of this parametric model to generate stochastic time series of daily weather is then summarized. A soil temperature model is described that determines daily average, maximum, and minimum soil temperatures based on air temperatures and precipitation, following a lagged process due to soil heat storage and other factors.

Keywords: Resource/Energy; Economics; and; Policy (search for similar items in EconPapers)
Pages: 33
Date: 2000
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Persistent link: https://EconPapers.repec.org/RePEc:ags:hebarc:18503

DOI: 10.22004/ag.econ.18503

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