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您的检索式：作者名="C.Leckebusch"
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| 1 | Hazard Footprint-Based Normalization of Economic Losses from Tropical Cyclones in China During 1983–2015显示文摘Loss normalization is the prerequisite for understanding the effects of socioeconomic development,vulnerability, and climate changes on the economic losses from tropical cyclones. In China, limited studies have been done on loss normalization methods of damages caused by tropical cyclones, and most of them have adopted an administrative division-based approach to define the exposure levels. In this study, a hazard footprint-based normalization method was proposed to improve the spatial resolution of affected areas and the associated exposures to influential tropical cyclones in China. The meteorological records of precipitation and near-surface wind speed were used to identify the hazard footprint of each influential tropical cyclone. Provincial-level and national-level(total)economic loss normalization(PLN and TLN) were carried out based on the respective hazard footprints, covering loss records between 1999–2015 and 1983–2015, respectively.Socioeconomic factors—inflation, population, and wealth(GDP per capita)—were used to normalize the losses. A significant increasing trend was found in inflation-adjusted losses during 1983–2015, while no significant trend was found after normalization with the TLN method. The proposed hazard footprint-based method contributes to amore realistic estimation of the population and wealth affected by the influential tropical cyclones for the original year and the present scenario. | Wenfang Chen Yi Lu Shao Sun Yihong Duan Gregor C.Leckebusch | 2018 | International Journal of Disaster Risk Science2018，9，2： | 2 |
| 2 | The 2003 European summer heatwaves and drought –synoptic diagnosis and impacts显示文摘 | Andreas H.Fink TimBrücher AndreasKrüger Gregor C.Leckebusch Joaquim G.Pinto UweUlbrich | 2006 | Weather2006，，8： | 1 |
| 3 | A Causality-guided Statistical Approach for Modeling Extreme Mei-yu Rainfall Based on Known Large-scale Modes——A Pilot Study显示文摘Extreme Mei-yu rainfall(MYR)can cause catastrophic impacts to the economic development and societal welfare in China.While significant improvements have been made in climate models,they often struggle to simulate local-to-regional extreme rainfall(e.g.,MYR).Yet,large-scale climate modes(LSCMs)are relatively well represented in climate models.Since there exists a close relationship between MYR and various LSCMs,it might be possible to develop causality-guided statistical models for MYR prediction based on LSCMs.These statistical models could then be applied to climate model simulations to improve the representation of MYR in climate models.In this pilot study,it is demonstrated that skillful causality-guided statistical models for MYR can be constructed based on known LSCMs.The relevancy of the selected predictors for statistical models are found to be consistent with the literature.The importance of temporal resolution in constructing statistical models for MYR is also shown and is in good agreement with the literature.The results demonstrate the reliability of the causality-guided approach in studying complex circulation systems such as the East Asian summer monsoon(EASM).Some limitations and possible improvements of the current approach are discussed.The application of the causality-guided approach opens up a new possibility to uncover the complex interactions in the EASM in future studies. | Kelvin S.NG Gregor C.LECKEBUSCH Kevin I.HODGES | 2022 | Advances in Atmospheric Sciences2022，39，11： | 0 |
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