Related papers: Multivariate Spatial-Temporal Variable Selection w…
We are developing schemes that predict future hurricane numbers by first predicting future sea surface temperatures (SSTs), and then apply the observed statistical relationship between SST and hurricane numbers. As part of this overall…
There is a clear positive correlation between boreal summer tropical Atlantic sea-surface temperature and annual hurricane numbers. This motivates the idea of trying to predict the sea-surface temperature in order to be able to predict…
The rising number of extreme climate events in the past decades has motivated the need for a thorough consideration of tropical cyclone genesis and intensity, given the sea-surface temperature (SST). In this paper, we present an analysis of…
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…
One possible method for the year-ahead prediction of hurricane numbers would be to make a year-ahead prediction of sea surface temperature (SST), and then to apply relationships that link SST to hurricane numbers. As a first step towards…
Sea surface temperature (SST) is a fundamental determinant of global climate dynamics and economic activity. Reliable projections of future SST patterns depend critically on a rigorous characterization of the underlying spatial random…
Occurrences of tropical cyclones at a location are rare, and for many locations, only short periods of observations or hindcasts are available. Hence, estimation of return values (corresponding to a period considerably longer than that for…
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…
We employ a statistical model of North Atlantic tropical cyclone (TC) tracks to investigate the relationship between sea-surface temperature (SST) and North American TC landfall rates. The track model is conditioned on summer SST in the…
Annual North Atlantic tropical cyclone (TC) counts are frequently modeled as a Poisson process with a state-dependent rate. We provide a lower bound on the forecasting error of this class of models. Remarkably we find that this bound is…
The spatial pattern of sea surface temperature (SST) plays a central role in shaping the climate system, yet the influence of land surface temperature (LST) remains poorly understood. Using a state-of-the-art coupled ocean--land--atmosphere…
The sea surface temperature (SST), a key environmental parameter, is crucial to optimizing production planning, making its accurate prediction a vital research topic. However, the inherent nonlinearity of the marine dynamic system presents…
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…
The frontal structure of the Southern Ocean is investigated using a sophisticated frontal detection methodology, the Wavelet/Higher Order Statistics Enhancement (WHOSE) method, introduced in \cite{Chapman2014}. This methodology is applied…
We are building a hurricane number prediction scheme that relies, in part, on statistical modelling of the empirical relationship between Atlantic sea surface temperatures and landfalling hurricane numbers. We test out a number of simple…
The spatiotemporal variation in tropical air-sea interaction is investigated by applying a simple model that considers the fundamental dynamics in tropical oceans. The model decomposes sea surface temperature anomaly (SSTA) variation into a…
Tropical cyclones (TCs), including hurricanes and typhoons, cause significant property damage and result in fatalities, making it crucial to understand the factors driving extreme TCs. The El Nino Southern Oscillation (ENSO) influences TC…
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…
Latent heat flux is a primary pathway for ocean-atmosphere exchange of heat and moisture, yet the influence of sea surface temperature variability at fine scales ($\leq$ 100 km) on latent heat flux variability, particularly over the…
The growing adoption of machine learning (ML) in modelling atmospheric and oceanic processes offers a promising alternative to traditional numerical methods. It is essential to benchmark the performance of both ML and physics-informed ML…