A long short-term memory (LSTM) neural network is proposed to predict hurricane-forced
significant wave heights (SWHs) in the Caribbean Sea (CS) based on a dataset of 20 CS …

This study investigates the interdecadal changes in the intensity of tropical cyclones (TCs)
formed within or entered the South China Sea (SCS) in the TC season (June to November) …

Tropical cyclone (TC) intensification over marginal seas, especially rapid intensification (RI),
often poses great threat to lives and properties in coastal regions and is subject to large …

Tropical cyclones (TCs) pose a significant threat in terms of wind-induced damage and
storm risk to the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) of China. In this …

The differences in the characteristics of the rapid intensification (RI) during the TCs that form
in the SCS (referred as local TCs) and that enter the SCS from the western North Pacific …

The present study investigates the variation in large-scale environments during the
maximum intensity of tropical cyclones (TCs) formed in the Bay of Bengal. TC tracks are …

With increasing air and sea temperatures, the thermodynamic environments over the oceans
are becoming more favourable for the development of intense tropical cyclones (TCs) with …

Tropical cyclones are responsible for a large share of global damage resulting from natural
disasters, and estimating cyclone-related damage at a national level is a challenge …

Despite substantial progress in the tropical cyclone (TC) intensity forecasting, the prediction
of rapid intensification (RI) of TCs is still a key challenge to the operational forecasting …

This research project aims at estimating financial risks related to climate change. Beyond the
applications and quantitative findings, the main objective of the chapters of this thesis is to …