Kechi Nzerem

Risk Management Solutions (United Kingdom)

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Stephen Jewson

Lambda

Thomas Laepple

University of Bremen

Enrica Bellone

Risk Management Solutions (United Kingdom)

Adam O’Shay

Risk Management Solutions (United Kingdom)

Jeremy Penzer

London School of Economics and Political Science

K. Coughlin

Risk Management Solutions (United Kingdom)

Shree Khare

Risk Management Solutions (United Kingdom)

Manuel Lonfat

Risk Management Solutions (United Kingdom)

Roman Binter

Cooperative Institutions

Risk Management Solutions (United Kingdom)

University of Reading

University of Washington

Imperial College London

NSF National Center for Atmospheric Research

Indian Institute of Tropical Meteorology

Florida State University

University of Miami

Lambda

Lambda Therapeutic Research (India)

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Predicting landfalling hurricane numbers from sea surface temperature: theoretical comparisons of direct and indirect approaches

arXiv (Cornell University) (2007)

Stephen Jewson Thomas Laepple Kechi Nzerem Jeremy Penzer

We consider two ways that one might convert a prediction of sea surface temperature (SST) into a prediction of landfalling hurricane numbers. First, one might regress historical numbers of landfalling hurricanes onto historical SSTs, and use the fitted regression relation to predict future landfalling hurricane numbers given predicted SSTs. We call this the direct approach. Second, one might regress \emph{basin} hurricane numbers onto historical SSTs, estimate the proportion of basin hurricanes that make landfall, and use the fitted regression relation and estimated proportion to predict future landfalling hurricane numbers. We call this the \emph{indirect} approach. Which of these two methods is likely to work better? We answer this question for two simple models. The first model is reasonably realistic, but we have to resort to using simulations to answer the question in the context of this model. The second model is less realistic, but allows us to derive a general analytical result.

10.48550/arxiv.physics/0701176

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Citations (1)

Correlations between hurricane numbers and sea surface temperature: why does the correlation disappear at landfall?

arXiv (Cornell University) (2007)

Thomas Laepple Enrica Bellone Stephen Jewson Kechi Nzerem

There is significant correlation between main development region sea surface temperature and the number of hurricanes that form in the Atlantic basin. The correlation between the same sea surface temperatures and the number of \emph{landfalling} hurricanes is much lower, however. Why is this? Do we need to consider complex physical hypotheses, or is there a simple statistical explanation?

Landfall

10.48550/arxiv.physics/0701175

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Five Year Prediction of the Number of Hurricanes that make United States Landfall

Springer eBooks (2008)

Stephen Jewson Enrica Bellone Thomas Laepple Kechi Nzerem Shree Khare

Landfall

10.1007/978-0-387-09410-6_5

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Predicting landfalling hurricane numbers from basin hurricane numbers: statistical analysis and predictions

arXiv (Cornell University) (2007)

Stephen Jewson Thomas Laepple Adam O’Shay Jeremy Penzer Enrica Bellone

One possible method for predicting landfalling hurricane numbers is to first predict the number of hurricanes in the basin and then convert that prediction to a prediction of landfalling hurricane numbers using an estimated proportion. Should this work better than just predicting landfalling hurricane numbers directly? We perform a basic statistical analysis of this question in the context of a simple abstract model, and convert some previous predictions of basin numbers into landfalling numbers.

Atlantic hurricane

Statistical Analysis

10.48550/arxiv.physics/0701166

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Predicting basin and landfalling hurricane numbers from sea surface temperature

arXiv (Cornell University) (2007)

Stephen Jewson Roman Binter Shree Khare Kechi Nzerem Adam O’Shay

We are building a hurricane number prediction scheme based on first predicting main development region sea surface temperature (SST), then predicting the number of hurricanes in the Atlantic basin given the SST prediction, and finally predicting the number of US landfalling hurricanes based on the prediction of the number of basin hurricanes. We have described a number of SST prediction methods in previous work. We now investigate the empirical relationship between SST and basin hurricane numbers, and put this together with the SST predictions to make predictions of both basin and landfalling hurricane numbers.

Atlantic hurricane

10.48550/arxiv.physics/0701170

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A relationship between all Atlantic hurricanes and those that make landfall in the USA

Quarterly Journal of the Royal Meteorological Society (2009)

K. Coughlin Enrica Bellone Thomas Laepple Stephen Jewson Kechi Nzerem

Abstract The interannual prediction of the number of hurricanes to strike the US coastline is of vital interest to those who live on the coast, those who insure property along the coast and policy makers who make decisions about infrastructure and mitigation measures. Here it is shown that these predictions can be made more accurate when information about the total number of Atlantic Basin hurricanes is considered. The proportion of Atlantic hurricanes that make landfall in the USA is a measure of the relationship between landfalling and basin hurricane numbers. In order to use basin numbers to help make predictions of landfalling numbers, we must first investigate the nature of this relationship. Here we run a number of statistical tests and find that there is a significant change in the relative proportion of Atlantic hurricanes that hit the US coastline between the first and second halves of the 20th century. This difference is ostensibly due to the lack of basin observations in the earlier period. However, after 1948, the proportion of Atlantic hurricanes that hit the US coast shows no evidence of change. By assuming that the proportion is constant, we are able to then use information about the total number of hurricanes in the Atlantic Basin and make more accurate estimates of landfalling hurricane activity. Copyright © 2009 Royal Meteorological Society

Landfall

Atlantic hurricane

East coast

10.1002/qj.367

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Change-point detection in the historical hurricane number time-series: why can't we detect change-points at US landfall?

arXiv (Cornell University) (2006)

Kechi Nzerem Stephen Jewson Thomas Laepple

The time series of the number of hurricanes per year in the Atlantic basin shows a clear change of level between 1994 and 1995. The time series of the number of hurricanes that make landfall in the US, however, does not show the same obvious change of level. Prima-facie this seems rather surprising, given that the landfalling hurricanes are a subset of the basin hurricanes. We investigate whether it really should be considered surprising or whether there is a simple statistical explanation for the disappearance of this change-point at landfall.

Landfall

10.48550/arxiv.physics/0611107

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Citations (6)