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European extra-tropical storm damage risk from a multi-model ensemble of dynamically-downscaled global climate models

机译:欧洲额外热带风暴损害动态较低的全球气候模型的多模型集合

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Uncertainty in the return levels of insured loss from European wind storms was quantified using storms derived from twenty-two 25 km regional climate model runs driven by either the ERA40 reanalyses or one of four coupled atmosphere-ocean global climate models. Storms were identified using a model-dependent storm severity index based on daily maximum 10 m wind speed. The wind speed from each model was calibrated to a set of 7 km historical storm wind fields using the 70 storms with the highest severity index in the period 1961–2000, employing a two stage calibration methodology. First, the 25 km daily maximum wind speed was downscaled to the 7 km historical model grid using the 7 km surface roughness length and orography, also adopting an empirical gust parameterisation. Secondly, downscaled wind gusts were statistically scaled to the historical storms to match the geographically-dependent cumulative distribution function of wind gust speed. The calibrated wind fields were run through an operational catastrophe reinsurance risk model to determine the return level of loss to a European population density-derived property portfolio. The risk model produced a 50-yr return level of loss of between 0.025% and 0.056% of the total insured value of the portfolio.
机译:欧洲风暴的返回水平的不确定性是使用从二十二千25公里处的区域气候模型的风暴量化,这些气候模型运行由ERA40 Reanalyses或四个耦合的大气全球气候模型中的一个。使用基于每日最大10米风速的模型依赖的风暴严重性指数识别出风暴。使用具有两个阶段校准方法的70次暴风雨,使用70次暴风雨来校准来自每个模型的风速到一套7公里的历史风暴风场,采用了两个阶段校准方法。首先,使用7公里的表面粗糙度长度和地形,25公里的每日最大风速缩小到7公里的历史模型网格,也采用了经验阵风参数化。其次,缩小的风阵列在统计上缩放到历史风暴,以匹配风力阵风的地理上依赖性累积分配功能。校准的风场通过操作灾难再保险风险模型进行,以确定欧洲人口密度衍生的财产投资组合的恢复水平。风险模型产生了50 yr返回损失的损失率为0.025 %和0.056 %的产品组合的总保险价值的0.056‰。

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