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Robert T. Clemen and Allan H. Murphy

Abstract

This paper addresses two specific questions related to the interrelationships between objective and subjective probability of precipitation (PoP) forecasts: Do the subjective forecasts contain information not included in the objective forecasts? Do the subjective forecasts make full use of the objective forecasts? With respect to the first question, an analysis of more than 11 years of data indicates that the subjective PoP forecasts add information above and beyond that contained in the objective PoP forecasts for all combinations of geographical area, lead time, and season investigated in this study. For longer lead times, this conclusion appears to contradict the results of earlier studies in which the two types of PoP forecasts were compared using aggregate skill scores. With regard to the second question, the statistical results demonstrate that the subjective forecasts generally do not make full use of the objective forecasts. However, these latter results are not as strong, in a statistical sense, as the results related to the first question; moreover, they indicate that it is primarily in the vicinity of the climatological probability (i.e., 0.10 to 0.40) that better use could be made of the objective forecasts. This conclusion suggests that it may be possible to combine the objective and subjective forecasts to produce a PoP forecast with even greater information content.

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Robert T. Clemen and Allan H. Murphy

Abstract

This paper reports the results of an empirical investigation of some methods for improving the quality of precipitation probability forecasts. These methods include 1) techniques for adjusting subjective and objective forecasts using past reliability data and 2) techniques for combining these two types of forecasts via both averaging and a more sophisticated statistical aggregation procedure. The empirical results indicate that forecast performance can be improved through such methods, with the greatest improvements arising from averaging forecasts that have previously been adjusted.

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Allan H. Murphy, Yin-Sheng Chen, and Robert T. Clemen

Abstract

In this paper we investigate the interrelationships between objective and subjective temperature forecasts. An information-content approach is adopted within the overall context of a general framework for forecast verification. This approach can be used to address questions such as whether the subjective forecasts contain information regarding the corresponding observed temperatures that is not included in the objective forecasts. Two methods of analysis are employed: 1) ordinary least squares regression analysis and 2) a Bayesian information-content analysis.

Maximum and minimum temperature forecasts formulated operationally for six National Weather Service offices during the period 1980–86 are analyzed. Results produced by the two methods are quite consistent and can be summarized as follows: 1) the subjective forecasts contain information not included in the objective forecasts for all cases (i.e., stratifications) considered and 2) the objective forecasts contain information not included in the subjective forecasts in a substantial majority of these cases. Generally, the incremental information content in the subjective forecasts considerably exceeds the incremental information content in the objective forecasts. The implications of these results for operational short-range temperature forecasting are briefly discussed.

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