Affiliation:
1. Department of Mathematics Université du Québec à Montréal Montréal QC Canada
2. Climatic Hazards and Advanced Risk Modelling The Co‐operators General Insurance Company Québec QC Canada
3. Ouranos Montréal QC Canada
Abstract
AbstractTropical cyclones (TCs) are among the most destructive natural hazards and yet, quantifying their financial impacts remains a significant methodological challenge. It is therefore of high societal value to synthetically simulate TC tracks and winds to assess potential impacts along with their probability distributions for example, land use planning and financial risk management. A common approach to generate TC tracks is to apply storm detection methodologies to climate model output, but such an approach is sensitive to the method and parameterization used and tends to underestimate intense TCs. We present a global TC model (the UQAM‐TCW model thereafter) that melds statistical modeling, to capture historical risk features, with a climate model large ensemble, to generate large samples of physically coherent TC seasons. Integrating statistical and physical methods, the model is probabilistic and consistent with the physics of how TCs develop. The model includes frequency and location of cyclogenesis, full trajectories with maximum sustained winds and the entire wind structure along each track for the six typical cyclogenesis basins from IBTrACS. Being an important driver of TCs globally, we also integrate ENSO effects in key components of the model. The global TC model thus belongs to a recent strand of literature that combines probabilistic and physical approaches to TC track generation. As an application of the model, we show global hazard maps for direct and indirect hits expressed in terms of return periods. The global TC model can be of interest to climate and environmental scientists, economists and financial risk managers.
Funder
Mitacs
Fonds de recherche du Québec
Natural Sciences and Engineering Research Council of Canada
Marine Environmental Observation Prediction and Response Network
Publisher
American Geophysical Union (AGU)
Reference74 articles.
1. Baddeley A. &Rubak E.(2022a).spatstat.geom: Spatial data classes and geometrical functionality for the spatstat family (version 3.0.3)[Software].https://github.com/spatstat/spatstat.geom.GitHub
2. Baddeley A. &Rubak E.(2022b).spatstat.random: Random generation and simulation for the spatstat family (version 3.0.1)[Software].https://github.com/spatstat/spatstat.random.GitHub
3. spatstat: AnRPackage for Analyzing Spatial Point Patterns