Predicting basin and landfalling hurricane numbers from sea surface temperature

Year-ahead prediction of US landfalling hurricane numbers

We present a simple method for the year-ahead prediction of the number of hurricanes making landfall in the US. The method is based on averages of historical annual hurricane numbers, and we perform a backtesting study to find the length of averaging window that would have given the best predictions in the past.

Year ahead prediction of US landfalling hurricane numbers: the optimal combination of long and short baselines

Annual levels of US landfalling hurricane activity averaged over the last 11 years (1995-2005) are higher than those averaged over the previous 95 years (1900-1994). How, then, should we best predict hurricane activity rates for next year? Based on the assumption that the higher rates will continue we use an optimal combination of averages over the long and short time-periods to produce a prediction that minimises MSE.

Year ahead prediction of US landfalling hurricane numbers: the optimal combination of multiple levels of activity since 1900

In earlier work we considered methods for predicting future levels of hurricane activity based on the assumption that historical mean activity was at one constant level from 1900 to 1994, and has been at another constant level since then. We now make this model a little more subtle, and account for the possibility of four different levels of mean hurricane activity since 1900.

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

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?

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

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.

Comments by William M. Gray (Colorado State University) on the recently published paper in Science by Webster et al., titled "Changes in tropical cyclone number, duration, and intensity in a warming environment." (September 2005, Vol. 309, pp. 1844-1846, www.sciencemag.org)

Recent US major landfalling hurricanes Katrina and Rita and last year's four U.S. landfalling major hurricanes have spawned an abundance of questions concerning the role that global warming might be playing in these events. This idea has been given added credence by the September 2005 Science paper of Webster, Holland, Curry and Chang (Vol. 304, pp. 1844-1846) showing that the global number of Category 4-5 hurricanes have increased in the last 15 years (1990-2004) in comparison with the prior 15-year period of 1975-1989. They report 171 Category 4-5 hurricanes in the earlier 15-year period vs.…

Predicting hurricane regional landfall rates: comparing local and basin-wide track model approaches

We compare two methods for making predictions of the climatological distribution of the number of hurricanes making landfall along short sections of the North American coastline. The first method uses local data, and the second method uses a basin-wide track model. Using cross-validation we show that the basin-wide track model gives better predictions for almost all parts of the coastline. This is the first time such a comparison has been made, and is the first rigourous justification for the use of basin-wide track models for predicting hurricane landfall rates and hurricane risk.

厄尔尼诺-南方涛动与大西洋多年代际振荡对北大西洋盆地飓风的影响

El Nino Southern Oscillation and Atlantic Multidecadal Oscillation Impact on Hurricanes North Atlantic Basin

本研究利用1950-2023年观测数据及相关气候指数，分析ENSO、AMO和海表温度对北大西洋盆地热带气旋强度与频率的影响，发现海温升高对应气旋更强、暖相位AMO对应频率更高等关联，为提升热带气旋季节预报提供依据。

Using the QBO to predict the number of hurricanes hitting the U.S

A simple study of the relationship between the QBO and the number of hurricanes in the Atlantic, both in the Basin and hitting the U.S. coastline, demonstrates that the QBO is not a particularly useful index to help predict hurricane numbers on five-year time scales. It is shown that there is very little difference between the number of hurricanes following easterly winds in the equatorial stratosphere and the number that follow westerly winds. Given this it is reasonable one would make better predictions just using the mean number of hurricanes in lieu of using the QBO and this is also simply…

A Universal Hurricane Frequency Function

Evidence is provided that the global distribution of tropical hurricanes is principally determined by a universal function H of a single variable z that in turn is expressible in terms of the local sea surface temperature and latitude. The data-driven model presented here carries stark implications for the large increased numbers of hurricanes which it predicts for a warmer world. Moreover, the rise in recent decades in the numbers of hurricanes in the Atlantic, but not the Pacific basin, is shown to have a simple explanation in terms of the specific form of H(z), which yields larger percentag…

Variability of North Atlantic hurricanes: seasonal versus individual-event features

Tropical cyclones are affected by a large number of climatic factors, which translates into complex patterns of occurrence. The variability of annual metrics of tropical-cyclone activity has been intensively studied, in particular since the sudden activation of the N Atl in the mid 1990's. We provide first a swift overview on previous work by diverse authors about these annual metrics for the NAtl basin, where the natural variability of the phenomenon, the existence of trends, the drawbacks of the records, and the influence of global warming have been the subject of interesting debates. Next, …

Data-Based Models for Hurricane Evolution Prediction: A Deep Learning Approach

Fast and accurate prediction of hurricane evolution from genesis onwards is needed to reduce loss of life and enhance community resilience. In this work, a novel model development methodology for predicting storm trajectory is proposed based on two classes of Recurrent Neural Networks (RNNs). The RNN models are trained on input features available in or derived from the HURDAT2 North Atlantic hurricane database maintained by the National Hurricane Center (NHC). The models use probabilities of storms passing through any location, computed from historical data. A detailed analysis of model foreca…