Generation of Simulated Daily Precipitation and Air and Soil Temperatures

Paul D. Mitchell
January 2000  [00-WP 234]

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.

Full Text 771 kB