Unraveling unknowns of future tropical cyclone risks

Meiler, Simona; Ciullo, Alessio; Kropf, Chahan M.; Emanuel, Kerry; Bresch, David N.

doi:10.21203/rs.3.rs-2703613/v1

Cited by 4 publications

(4 citation statements)

References 44 publications

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“…The relative importance of this uncertainty with respect to all other risk model uncertainties from unknowns in the hazard, exposure, and vulnerability model must in general be assessed case by case and can be quantified with sensitivity analysis. Note that it is not possible to make a generic statement on the effect of resolution uncertainty on the risk model, as this depends strongly on the purpose of the study, the chosen output metrics, and the chosen set of modeled input uncertainties (Meiler et al 2023).…”

Section: Discussionmentioning

confidence: 99%

OpenStreetMap for multi-faceted climate risk assessments

Mühlhofer,

Kropf,

Riedel

et al. 2024

Environ. Res. Commun.

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Natural hazards pose significant risks to human lives, infrastructure, and ecosystems. Understanding risks along all these dimensions is critical for effective adaptation planning and risk management. However, climate risk assessments mostly focus on population, economic asset values, and road or building infrastructure, because publicly available data on more diverse exposures are scarce. The increasing availability of crowd-sourced geospatial data, notably from OpenStreetMap, opens up a novel means for assessing climate risk to a large range of physical assets. To this end, we present a stand-alone, lightweight, and highly flexible Python-based OpenStreetMap data extraction tool: OSM-flex. To demonstrate the potential and limitations of OpenStreetMap data for risk assessments, we couple OSM-flex to the open-source natural hazard risk assessment platform CLIMADA and compute winter storm risk and event impacts from winter storm Lothar across Switzerland to forests, UNESCO heritage sites, railways, healthcare facilities, and airports. Contrasting spatial patterns of risks on such less conventional exposure layers with more traditional risk metrics (asset damages and affected population) reveals that risk hot-spots are inhomogeneously and distinctly distributed. For instance, impacts on forestry are mostly expected in Western Switzerland in the Jura mountain chain, whereas economic asset damages are concentrated in the urbanized regions around Basel and Zurich and certain train lines may be most often affected in Central Switzerland and alpine valleys. This study aims to highlight the importance of conducting multi-faceted and high-resolution climate risk assessments and provides researchers, practitioners, and decision-makers with potential open-source software tools and data suggestions for doing so.

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Section: Discussionmentioning

confidence: 99%

OpenStreetMap for multi-faceted climate risk assessments

Mühlhofer,

Kropf,

Riedel

et al. 2024

Environ. Res. Commun.

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“…We further did not consider similar strong wind hazards such as winter storms, gales, or Derechos that might co-affect certain ecosystems. Finally, our study is bound by the limitations of the STORM model itself in representing current and future tropical cyclone activity [9,13,87], and is bound to the specific ecoregion boundaries defined by Dinerstein et al [55].…”

Section: Discussionmentioning

confidence: 99%

“…Climate change is expected to modify the intensity and frequency of tropical cyclones and their geographical impacts [7][8][9]. Tropical cyclones are intense low-pressure systems that form over warm ocean waters which can produce strong winds, heavy rainfall, and storm surges.…”

Section: Introductionmentioning

confidence: 99%

“…This may affect all dimensions, including the ecosystem's biogeochemistry, hydrography, mobile biota, sedentary biota, or micro-biota [5,12]. Beyond a change in cyclone severity, regional patterns are likely to change, thus exposing areas that have not historically experienced these types of storms [8,13,14], yielding unprecedented consequences for not only human societies [9,15] but also for natural ecosystems [12,16,17].…”

Section: Introductionmentioning

confidence: 99%

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

Kropf,

Vaterlaus,

Bresch

et al. 2023

Preprint

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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.

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Uncertainties and sensitivities in the quantification of future tropical cyclone risk

Meiler,

Ciullo,

Kropf

et al. 2023

Commun Earth Environ

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Tropical cyclone risks are expected to increase with climate change and socio-economic development and are subject to substantial uncertainties. We thus assess future global tropical cyclone risk drivers and perform a systematic uncertainty and sensitivity analysis. We combine synthetic tropical cyclones downscaled from CMIP6 global climate models for several emission scenarios with economic growth factors derived from the Shared Socioeconomic Pathways and a wide range of vulnerability functions. We highlight non-trivial effects between climate change and socio-economic development that drive future tropical cyclone risk. Furthermore, we show that the choice of climate model affects the output uncertainty most among all varied model input factors. Finally, we discover a positive correlation between climate sensitivity and tropical cyclone risk increase. We assert that quantitative estimates of uncertainty and sensitivity to model parameters greatly enhance the value of climate risk assessments, enabling more robust decision-making and offering a richer context for model improvement.

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Unraveling unknowns of future tropical cyclone risks

Cited by 4 publications

References 44 publications

OpenStreetMap for multi-faceted climate risk assessments

OpenStreetMap for multi-faceted climate risk assessments

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

Uncertainties and sensitivities in the quantification of future tropical cyclone risk

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