Assessing the adverse impacts caused by tropical cyclones has become increasingly important as both climate change and human coastal development increase the damage potential. In order to assess tropical cyclone risk, direct economic damage is frequently modeled based on hazard intensity, asset exposure, and vulnerability, the latter represented by impact functions. In this study, we show that assessing tropical cyclone risk on a global level with one single impact function calibrated for the USA – which is a typical approach in many recent studies – is problematic, biasing the simulated damage by as much as a factor of 36 in the north West Pacific. Thus, tropical cyclone risk assessments should always consider regional differences in vulnerability, too. This study proposes a calibrated model to adequately assess tropical cyclone risk in different regions by fitting regional impact functions based on reported damage data. Applying regional calibrated impact functions within the risk modeling framework CLIMADA (CLIMate ADAptation) at a resolution of 10 km worldwide, we find global annual average direct damage caused by tropical cyclones to range from USD 51 up to USD 121 billion (value in 2014, 1980–2017) with the largest uncertainties in the West Pacific basin where the calibration results are the least robust. To better understand the challenges in the West Pacific and to complement the global perspective of this study, we explore uncertainties and limitations entailed in the modeling setup for the case of the Philippines. While using wind as a proxy for tropical cyclone hazard proves to be a valid approach in general, the case of the Philippines reveals limitations of the model and calibration due to the lack of an explicit representation of sub-perils such as storm surges, torrential rainfall, and landslides. The globally consistent methodology and calibrated regional impact functions are available online as a Python package ready for application in practical contexts like physical risk disclosure and providing more credible information for climate adaptation studies.

中文翻译：

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区域热带气旋影响函数用于全球一致的风险评估

随着气候变化和人类沿海发展都增加了潜在破坏，评估热带气旋造成的不利影响变得越来越重要。为了评估热带气旋风险，经常基于危害强度，资产暴露和脆弱性来建模直接经济损失，后者以影响函数表示。在这项研究中，我们表明，使用为美国校准的单个影响函数（这是许多近期研究中的一种典型方法），在全球范围内评估热带气旋风险是有问题的，将模拟破坏的偏倚程度提高了36倍。在西北太平洋。因此，热带气旋风险评估也应始终考虑脆弱性的区域差异。这项研究提出了一个校准模型，通过基于报告的破坏数据拟合区域影响函数，可以充分评估不同区域的热带气旋风险。在风险建模框架CLIMADA（CLIMate ADAptation）中以全球10 km的分辨率应用区域校准的影响函数，我们发现热带气旋造成的全球年度平均直接损害范围从51美元到1210亿美元（2014、1980年的价值–2017年），在西太平洋盆地不确定性最大的地方，校准结果最不可靠。为了更好地理解西太平洋地区的挑战并补充本研究的全球视野，我们探索了菲律宾案例建模设置中的不确定性和局限性。一般说来，用风代替热带气旋危险是一种有效的方法，但菲律宾的情况却显示出该模型和标定的局限性，因为它没有明确表示次生灾害，例如风暴潮，暴雨和山崩。全球一致的方法论和已校准的区域影响函数可作为Python软件包在线获得，可以在实际环境中使用，例如物理风险披露，并为气候适应研究提供更可靠的信息。