Intercomparison of regional loss estimates from global synthetic tropical cyclone models

Meiler, Simona; Vogt, Thomas; Bloemendaal, Nadia; Ciullo, Alessio; Lee, Chia‐Ying; Camargo, Suzana J.; Emanuel, Kerry; Bresch, David N.

doi:10.21203/rs.3.rs-1429968/v1

Cited by 3 publications

(13 citation statements)

References 56 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The models from the intercomparison project of Meiler et al. (2022) each use different approaches to represent TC intensity. The MIT wind model is based upon the aforementioned CHIPS model.…”

Section: Event Setsmentioning

confidence: 99%

“…But as Meiler et al. (2022) remark, post‐processing CHAZ's frequency of events is still required. In our paper, we borrow the MIT approach to generate a fixed number of storms in the event set production (left‐hand side of Figure 1), whereas we use a typical count distribution to generate consistent seasonal frequency (right‐hand side of Figure 1).…”

Section: Annual Catalogsmentioning

confidence: 99%

“…STORM simulates the RMW by sampling from observations depending on pressure in each of three stages: at genesis, peak intensity and dissipation. To overcome the discrepancies in available wind profiles, Meiler et al (2022) couple each model with the same parametric wind field model from Holland (2008).…”

Section: Size and Radial Profilementioning

confidence: 99%

“…Annual catalogs are obtained by randomly sampling the trajectories from the event sets in accordance with the annual frequency of TCs in any given basin. Our overall model is in line with those analyzed in Meiler et al (2022) (MIT, CHAZ, and STORM) and we will therefore borrow their nomenclature to compare each of our model's components with the latter. The model components and key steps are summarized in Figure 1.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

UQAM‐TCW: A Global Hybrid Tropical Cyclone Wind Model Based Upon Statistical and Coupled Climate Models

Carozza,

Boudreault,

Grenier

et al. 2024

J Adv Model Earth Syst

View full text Add to dashboard Cite

Tropical 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.

show abstract

Section: Event Setsmentioning

confidence: 99%

Section: Annual Catalogsmentioning

confidence: 99%

Section: Size and Radial Profilementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

UQAM‐TCW: A Global Hybrid Tropical Cyclone Wind Model Based Upon Statistical and Coupled Climate Models

Carozza,

Boudreault,

Grenier

et al. 2024

J Adv Model Earth Syst

View full text Add to dashboard Cite

show abstract

“…Code to reproduce the results of this paper is available at a GitHub repository with the identifier https://doi.org/10.5281/zenodo.6782091 67 .…”

Section: Data Availabilitymentioning

confidence: 99%

Intercomparison of regional loss estimates from global synthetic tropical cyclone models

et al. 2022

View full text Add to dashboard Cite

Tropical cyclones (TCs) cause devastating damage to life and property. Historical TC data is scarce, complicating adequate TC risk assessments. Synthetic TC models are specifically designed to overcome this scarcity. While these models have been evaluated on their ability to simulate TC activity, no study to date has focused on model performance and applicability in TC risk assessments. This study performs the intercomparison of four different global-scale synthetic TC datasets in the impact space, comparing impact return period curves, probability of rare events, and hazard intensity distribution over land. We find that the model choice influences the costliest events, particularly in basins with limited TC activity. Modelled direct economic damages in the North Indian Ocean, for instance, range from 40 to 246 billion USD for the 100-yr event over the four hazard sets. We furthermore provide guidelines for the suitability of the different synthetic models for various research purposes.

show abstract

Global vulnerability and resilience of coastal ecosystems to tropical cyclones in a warming climate

Kropf,

Vaterlaus,

Bresch

et al. 2023

Preprint

View full text Add to dashboard Cite

Coastal ecosystems are recognized to provide a large range of services including erosion prevention, clean water provision, or protection from tropical cyclones storms. However, with climate change, the increase in frequency and intensity of tropical cyclones may alter the composition of the ecosystems themselves potentially degrading the various services they provide. While in general ecosystems are adapted to external perturbations, extreme events can promote rapid and durable shifts. In this study, we quantify the vulnerability of all ecosystems described as ecoregions at a global scale by analyzing the wind fields of tropical cyclones generated from probabilistic historical tracks. We then investigate how tropical cyclone intensity and frequency shifting in a warming climate might lead to ecosystem modifications. We show that a combined 13% of the surface of all terrestrial ecosystems is susceptible to transformation due to cyclone pattern changes between 2020 and 2050 under current policies. Even for the most resilient ecosystems already experiencing winds above 60 m/s regularly, the average interval between two storms is projected to decrease from 19 to 12 years which is potentially close to their recovery time. Our global probabilistic approach being embedded in the established IPCC climate risk frameworks enables the study of a broad temporal range, and advocates for a shift in the consideration of the tropical cyclone impact from immediate damage to effects on long-term natural recovery cycles.

show abstract

Intercomparison of regional loss estimates from global synthetic tropical cyclone models

Cited by 3 publications

References 56 publications

UQAM‐TCW: A Global Hybrid Tropical Cyclone Wind Model Based Upon Statistical and Coupled Climate Models

UQAM‐TCW: A Global Hybrid Tropical Cyclone Wind Model Based Upon Statistical and Coupled Climate Models

Intercomparison of regional loss estimates from global synthetic tropical cyclone models

Global vulnerability and resilience of coastal ecosystems to tropical cyclones in a warming climate

Contact Info

Product

Resources

About