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Journal ArticleDOI

What Is a Good Forecast? An Essay on the Nature of Goodness in Weather Forecasting

Allan H. Murphy
- 01 Jun 1993 - 
- Vol. 8, Iss: 2, pp 281-293
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TLDR
Three distinct types of goodness are identified in this paper: the correspondence between forecasters’ judgments and their forecasts, the correspondencebetween the forecasts and the matching observations, and the incremental economic and/or other benefits realized by decision makers through the use of the forecasts (type 3 goodness, or value).
Abstract
Differences of opinion exist among forecasters—and between forecasters and users—regarding the meaning of the phrase “good (bad) weather forecasts.” These differences of opinion are fueled by a lack of clarity and/or understanding concerning the nature of goodness in weather forecasting. This lack of clarity and understanding complicates the processes of formulating and evaluating weather forecasts and undermines their ultimate usefulness. Three distinct types of goodness are identified in this paper: 1) the correspondence between forecasters’ judgments and their forecasts (type 1 goodness, or consistency), 2) the correspondence between the forecasts and the matching observations (type 2 goodness, or quality), and 3) the incremental economic and/or other benefits realized by decision makers through the use of the forecasts (type 3 goodness, or value). Each type of goodness is defined and described in some detail. In addition, issues related to the measurement of consistency, quality, and value ar...

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Forecast verification: a practitioner's guide in atmospheric science

TL;DR: Jolliffe et al. as mentioned in this paper proposed a framework for verification of spatial fields based on binary and categorical events, and proved the correctness of the proposed framework with past, present and future predictions.
BookDOI

Principles of forecasting

J. Armstrong
TL;DR: A review of the evidence showed that role playing was effective in matching results for seven of eight experiments and was correct for 56 percent of 143 predictions, while unaided expert opinions were correct for 16 percent of 172 predictions.
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Ensemble forecasting

TL;DR: The extent to which the current ECMWF ensemble prediction system is capable of predicting flow-dependent variations in uncertainty is assessed for the large-scale flow in mid-latitudes.
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Trading Wind Generation From Short-Term Probabilistic Forecasts of Wind Power

TL;DR: In this article, a general methodology for deriving optimal bidding strategies based on probabilistic forecasts of wind generation, as well as on modeling of the sensitivity a wind power producer may have to regulation costs is presented.
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Current Approaches to Seasonal to Interannual Climate Predictions

TL;DR: This article presented an assessment of the current state of knowledge and capability in seasonal climate prediction at the end of the 20th century, including the theory and empirical evidence for predictability, predictions of surface boundary conditions, such as sea surface temperatures (SSTs), and predictions of the climate.