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Generation of Simulated Daily Precipitation and Air and Soil Temperatures

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Author Info
Paul D. Mitchell

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Abstract

Mitchell describes a maximum likelihood method using historical weather data to estimate a parametric model of daily precipitation and maximum and minimum air temperatures. Historical weather data from Brookings, SD, and Boone, IA, are used to create the model. Mitchell describes the process of estimation for the precipitation parametric model, and then reports the actual parametric estimates. Next, he presents an algorithm designed to generate a simulated time series of weather variables using the parametric model. Finally, he describes a model that determines soil temperatures as functions of air temperatures and precipitation.

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Publisher Info
Paper provided by Center for Agricultural and Rural Development (CARD) at Iowa State University in its series Center for Agricultural and Rural Development (CARD) Publications with number 00-wp234.

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Date of creation: Jan 2000
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Handle: RePEc:ias:cpaper:00-wp234

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  1. Kiniry, J. R. & Williams, J. R. & Gassman, P. W. & Debacke, P., 1992. "General, Process-Oriented Model for Two Competing Plant Species (A)," Staff General Research Papers 483, Iowa State University, Department of Economics.
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  1. Mitchell, Paul D. & Riedell, Walter, 2000. "Stochastic Dynamic Northern Corn Rootworm Population Model," Staff General Research Papers 1716, Iowa State University, Department of Economics. [Downloadable!]
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