Unraveling the unknowns of global tropical cyclone risk in the future

Abstract

<p>Tropical cyclones (TCs) are among the most devastating natural hazards putting populations and assets at risk. This risk is expected to increase further in a warming climate and with socio-economic development. It is, therefore, of great importance and the aim of our study to assess the drivers and uncertainties of global TC risk in the future. We use a large set of synthetic TCs downscaled from various general circulation models (GCMs) and different warming scenarios of the CMIP6 generation to simulate TC activity at the middle and end of this century. In parallel, we derive economic growth factors from different Shared Socioeconomic Pathways (SSPs) to approximate socio-economic development. We combine these future representations of hazard and exposure data with vulnerability functions to estimate the TC risk increase in the future, using an open-source probabilistic impact model (CLIMADA). Furthermore, we perform a systematic uncertainty and sensitivity analysis to understand which of the model input factors contribute most to the uncertainty in the future TC risk increase. First, we find a non-linear effect between climate change and socio-economic development that drives the total future risk. Second, we show that the choice of GCM affects the output uncertainty most among all varied input factors. However, we note that exposure and vulnerability data are notoriously sparse and that advances in future TC risk assessment also depend on a better representation of these components. Ultimately, unraveling these unknowns of global TC risk in the future may help focus future research efforts and enables better-informed adaptation decisions and mitigation strategies.</p>

Navigating uncertainty and sensitivity analysis of future tropical cyclone risk estimates

“…We systematically quantify uncertainties and sensitivities in future TC risk change estimates in the middle and at the end of the century, encompassing uncertainties in all risk model components: hazard, exposure, and vulnerability. Contrasting results from two previous studies assessing uncertainties and sensitivities in the quantification of future TC risks, each using a different TC hazard model, show that the results of such uncertainty and sensitivity quantification depend on the scope of the study, which is defined a priori by investigator choice -in other words, uncertainty assessment is itself uncertain (16,28,29).…”

“…There, climate change raises EAD values from CHAZ by 10% (9%) and IBTrACS_p by 23% (23%) in 2050 (2090), respectively. Only the results from STORM remain low due to known high-intensity biases in the reference period hazard set (15,29). The North Indian Ocean is, furthermore, the region where uncertainties in climate-driven risk change are highest across all hazard models.…”

Unraveling unknowns of future tropical cyclone risks

“…Nonetheless, we note that TC risk estimates also vary depending on the TC hazard model 33 . For example, future TC risk calculations based on a fully statistical TC model 32 yield comparable findings for assessing future TC risk drivers but differ in the results of the sensitivity analysis due to the differences in the underlying modelling approach 34 . Therefore, one may consider multiple TC models for future TC risk estimations.…”

Uncertainties and sensitivities in the quantification of future tropical cyclone risk

“…Similar to the epistemic uncertainty discussed for changing TC frequency in a warming climate, uncertainties exist among TC hazard models. For example, future TC risk calculations based on a fully statistical TC model 42 yield comparable findings for assessing future TC risk drivers but differ in the results of the sensitivity analysis due to the differences in the underlying modeling approach and model structure 43 . More generally speaking, in the context of uncertainty and sensitivity analysis, the choice of model and its meta-parameters represent normative uncertainty 12,44 .…”

“…We compare the increase of future TC risk over four main global regions shown in Fig. 1a and previously defined by Meiler et al (2022) 24 and also used in a study of analogous setup but different TC hazard model 43 . The regions broadly reflect distinct TC areas with a focus on the landmasses affected by the respective TC activity in contrast to regionalizations focused on the ocean basins of TC origin.…”