Predicting Daily Maximum Temperatures Using Linear Regression and Eta Geopotential Thickness Forecasts

Abstract

The relationship between forecast geopotential thickness and observed maximum temperature is investigated, and regression equations are calculated using numerical model thickness forecasts for Nashville. Model thickness forecast accuracy is shown to have seasonal variability. Furthermore, the accuracy of eta regression forecasts is dependent on changes in the average low-level humidity. During December through March, most large eta regression forecast errors occurred during times when much drier air moved into the Nashville area. The eta regression forecast method was useful in making subjective improvements to the Model Output Statistics (MOS) from the Nested Grid Model (NGM), especially when the difference between the eta regression forecast and the NGM MOS was at least 3°F. The limitations of this study include potential error due to inaccurate model thickness forecasts and dependence on forecast thickness as the preferred predictor of afternoon maximum temperature.