Related papers: Comparing classical and Bayesian methods for predi…
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…
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.…
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…
Bayesian hierarchical models are proposed for modeling tropical cyclone characteristics and their damage potential in the Atlantic basin. We model the joint probability distribution of tropical cyclone characteristics and their damage…
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…
We continue with our program to derive simple practical methods that can be used to predict the number of US landfalling hurricanes a year in advance. We repeat an earlier study, but for a slightly different definition landfalling…
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…
In previous work, we have shown how to combine long and short historical baselines to make predictions of future hurricane numbers. We now ask: how should such combinations change if we are interested in predicting the future number of…
In this paper, we study the problem of forecasting the next year's number of Atlantic hurricanes, which is relevant in many fields of applications such as land-use planning, hazard mitigation, reinsurance and long-term weather derivative…
In previous work we have analysed the Atlantic basin hurricane number time-series to identify decadal time-scale change points. We now repeat the analysis but for US landfalling hurricanes. The results are very different.
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…
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?…
One way to predict hurricane numbers would be to predict sea surface temperature, and then predict hurricane numbers as a function of the predicted sea surface temperature. For certain parametric models for sea surface temperature and the…
Storm surge, the onshore rush of sea water caused by the high winds and low pressure associated with a hurricane, can compound the effects of inland flooding caused by rainfall, leading to loss of property and loss of life for residents of…
Classical confidence limits are compared to Bayesian error bounds by studying relevant examples. The performance of the two methods is investigated relative to the properties coherence, precision, bias, universality, simplicity. A proposal…
In light of intense hurricane activity along the U.S. Atlantic coast, attention has turned to understanding both the economic impact and behaviour of these storms. The compound Poisson-lognormal process has been proposed as a model for…
We propose a new statistical protocol for the estimation of precipitation using lightning data. We first identify rainy events using a scan statistics, then we estimate Rainfall Lighting Ratio (RLR) to convert lightning number into rain…
Building on recent research for prediction of hurricane trajectories using recurrent neural networks (RNNs), we have developed improved methods and generalized the approach to predict Bayesian intervals in addition to simple point…
Tropical cyclones present a serious threat to many coastal communities around the world. Many numerical weather prediction models provide deterministic forecasts with limited measures of their forecast uncertainty. Standard postprocessing…
This paper compares classical parametric methods with recently developed Bayesian methods for system identification. A Full Bayes solution is considered together with one of the standard approximations based on the Empirical Bayes paradigm.…