Probabilistic Temperature Forecasts: The Case for an Operational Program

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  • 1 Environmental and Societal Impacts Group, National Center for Atmospheric Research , Boulder, Colo. 80307
  • | 2 Graduate School of Business, Indiana University, Bloomington, Ind. 47401
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The case for an operational program involving the formulation and dissemination of probabilistic temperature forecasts is presented. First, the need for information concerning the uncertainty in temperature forecasts is discussed, and examples of formal and informal decision-making situations in which such information would be useful are described. The results of experiments in probabilistic temperature forecasting are then reviewed, and it is concluded that experienced weather forecasters can quantify the uncertainty inherent in temperature forecasts in a reliable and skillful manner. Finally, the essential components of an operational probabilistic temperature forecasting program are outlined, and some suggestions are made regarding specific temperature events that should receive probabilistic treatment on an operational basis.

1 Supported in part by the National Science Foundation under Grants ATM74–00161–A01 and ATM77–14060.

2 Address as of 1 February 1979: Department of Atmospheric Sciences, Oregon State University, Corvallis, Oreg. 97331.

3 The National Center for Atmospheric Research is sponsored by the National Science Foundation.

The case for an operational program involving the formulation and dissemination of probabilistic temperature forecasts is presented. First, the need for information concerning the uncertainty in temperature forecasts is discussed, and examples of formal and informal decision-making situations in which such information would be useful are described. The results of experiments in probabilistic temperature forecasting are then reviewed, and it is concluded that experienced weather forecasters can quantify the uncertainty inherent in temperature forecasts in a reliable and skillful manner. Finally, the essential components of an operational probabilistic temperature forecasting program are outlined, and some suggestions are made regarding specific temperature events that should receive probabilistic treatment on an operational basis.

1 Supported in part by the National Science Foundation under Grants ATM74–00161–A01 and ATM77–14060.

2 Address as of 1 February 1979: Department of Atmospheric Sciences, Oregon State University, Corvallis, Oreg. 97331.

3 The National Center for Atmospheric Research is sponsored by the National Science Foundation.

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