Automated Temperature Guidance Based on Three-Month Seasons

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  • 1 Techniques Development Laboratory, Systems Development Office, National Weather Service, NOAA, Silver Spring, Md. 20910
  • | 2 Systems Development Office, National Weather Service, NOAA, Silver Spring, Md. 20910
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Abstract

For the last few years the National Weather Service has been producing centralized guidance forecasts of calendar day maximum and minimum temperatures by applying multiple regression equations derived statistically from numerical model output. At fist the equations were developed from a six-month stratification of the numerical forecasts, but later we were able to stratify the dependent data into three-month seasons. At the same time we added a number of new potential predictors. These two changes increased the skill of the automated guidance. Here we discuss the dependent data statistics for the three-month season equations and compare their forecasts with those made by the older six-month equations. Finally, we present verification statistics on the objective guidance for the fall and winter seasons from August 1973 to February 1976.

Abstract

For the last few years the National Weather Service has been producing centralized guidance forecasts of calendar day maximum and minimum temperatures by applying multiple regression equations derived statistically from numerical model output. At fist the equations were developed from a six-month stratification of the numerical forecasts, but later we were able to stratify the dependent data into three-month seasons. At the same time we added a number of new potential predictors. These two changes increased the skill of the automated guidance. Here we discuss the dependent data statistics for the three-month season equations and compare their forecasts with those made by the older six-month equations. Finally, we present verification statistics on the objective guidance for the fall and winter seasons from August 1973 to February 1976.

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