The impacts of temperature forecast uncertainty on Bayesian load forecasting

A.P. Douglas; A.M. Breipohl; F.N. Lee; R. Adapa

doi:10.1109/59.736298

The impacts of temperature forecast uncertainty on Bayesian load forecasting

IEEE Transactions on Power Systems ◽

10.1109/59.736298 ◽

1998 ◽

Vol 13 (4) ◽

pp. 1507-1513 ◽

Cited By ~ 89

Author(s):

A.P. Douglas ◽

A.M. Breipohl ◽

F.N. Lee ◽

R. Adapa

Keyword(s):

Load Forecasting ◽

Forecast Uncertainty ◽

Temperature Forecast

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Analysis and Modeling of Temperature Forecast Uncertainty for Stochastic Trajectory Synthesis

12th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference and 14th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference ◽

10.2514/6.2012-5422 ◽

2012 ◽

Cited By ~ 3

Author(s):

Qian Maggie Zheng ◽

Yiyuan Zhao

Keyword(s):

Forecast Uncertainty ◽

Temperature Forecast

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Communicating Uncertainty in Weather Forecasts: A Survey of the U.S. Public

Weather and Forecasting ◽

10.1175/2008waf2007088.1 ◽

2008 ◽

Vol 23 (5) ◽

pp. 974-991 ◽

Cited By ~ 160

Author(s):

Rebecca E. Morss ◽

Julie L. Demuth ◽

Jeffrey K. Lazo

Keyword(s):

Weather Forecast ◽

Nationwide Survey ◽

Forecast Uncertainty ◽

Weather Forecasts ◽

Temperature Forecast ◽

Different Types ◽

Probability Of Precipitation ◽

Uncertainty Information ◽

The U.S ◽

Do So

Abstract Weather forecasts are inherently uncertain, and meteorologists have information about weather forecast uncertainty that is not readily available to most forecast users. Yet effectively communicating forecast uncertainty to nonmeteorologists remains challenging. Improving forecast uncertainty communication requires research-based knowledge that can inform decisions on what uncertainty information to communicate, when, and how to do so. To help build such knowledge, this article explores the public’s perspectives on everyday weather forecast uncertainty and uncertainty information using results from a nationwide survey. By contributing to the fundamental understanding of laypeople’s views on forecast uncertainty, the findings can inform both uncertainty communication and related research. The article uses empirical data from a nationwide survey of the U.S. public to investigate beliefs commonly held among meteorologists and to explore new topics. The results show that when given a deterministic temperature forecast, most respondents expected the temperature to fall within a range around the predicted value. In other words, most people inferred uncertainty into the deterministic forecast. People’s preferences for deterministic versus nondeterministic forecasts were examined in two situations; in both, a significant majority of respondents liked weather forecasts that expressed uncertainty, and many preferred such forecasts to single-valued forecasts. The article also discusses people’s confidence in different types of forecasts, their interpretations of the probability of precipitation forecasts, and their preferences for how forecast uncertainty is conveyed. Further empirical research is needed to study the article’s findings in other contexts and to continue exploring perception, interpretation, communication, and use of weather forecast uncertainty.

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