Long-term average hourly, daily, and annual temperature prediction model

Date

1992-05

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Abstract

Research has been completed to predict long-term average hourly, daily, and annual temperatures both in the United States and around the world. This temperature has been expressed by statistical approaches using latitude and elevation for annual and daily temperature, as well as using relative humidity and cloud cover for hourly temperature. The research also describes a procedure for modeling longterm hourly, daily, and annual temperatures. Predicted temperatures have been compared with measured values, which shows the predicted values are very close to the measured values; R2 and coefficient of variation have been summarized for 99 locations in the United States and 140 locations around the world. Combining all locations together, the annual temperature prediction model proved to be a good predictor giving an R-square of 0.89, which was highly significant (a=O.Ol). A computer program has been developed to predict hourly, daily, and annual temperature all over the world based on the developed models. The necessary data for program input is only latitude and elevation for annual and daily temperature prediction; and for hourly temperature prediction, relative humidity and cloud cover data also are required.

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Keywords

Temperature measurements, Temperature measuring instruments -- Automation

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