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Andrew R. Solow and Laura Moore

Abstract

The record of annual counts of basinwide North Atlantic hurricanes is incomplete prior to 1946. This has restricted efforts to identify a long-term trend in hurricane activity to the postwar period. In contrast, the complete record of U.S. landfalling hurricanes extends back to 1930 or earlier. Under the assumption that the proportion of basinwide hurricanes that make landfall is constant over time, it is possible to use the record of landfalling hurricanes to extend a test for trend in basinwide hurricane activity beyond the postwar period. This note describes and illustrates a method for doing this. The results suggest that there has been a significant reduction in basinwide hurricane activity over the period 1930–98.

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Andrew R. Solow and Laura J. Moore

Abstract

The detection of a trend in hurricane activity in the North Atlantic basin has been restricted by the incompleteness of the record prior to 1946. In an earlier paper, the complete record of U.S. landfalling hurricanes was used to extend the period of analysis back to 1930. In this paper, a further extension is made back to 1900. In doing so, the assumption in the earlier paper of an exponential linear trend is relaxed and the trend is estimated nonparametrically. The results show no significant trend in basinwide hurricane activity over the period 1900–98.

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Andrew R. Solow and James M. Broadus

Abstract

Probabilistic forecasts of the occurrence of precipitation have been used routinely in the United States since 1965. Studies of the reliability of such forecasts often show a tendency towards over-forecasting (i.e., for forecast probabilities to exceed observed relative frequencies). A simple model is described that explains over-forecasting in terms of an asymmetric loss function. The model is applied to some results of a previous study.

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Gerrit Hansen, Maximilian Auffhammer, and Andrew R. Solow

Abstract

There is growing interest in assessing the role of climate change in observed extreme weather events. Recent work in this area has focused on estimating a measure called attributable risk. A statistical formulation of this problem is described and used to construct a confidence interval for attributable risk. The resulting confidence is shown to be surprisingly wide even in the case where the event of interest is unprecedented in the historical record.

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