中國臺(tái)風(fēng)災(zāi)害直接經(jīng)濟(jì)損失的主導(dǎo)影響因子評估與識別
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中國氣象局氣象發(fā)展與規(guī)劃院重點(diǎn)研究項(xiàng)目(ZDXM2023003)資助


Identification of Dominant Impact Factors of Typhoon Disaster Economic Losses in China
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    摘要:

    基于2004—2021年125個(gè)中國臺(tái)風(fēng)災(zāi)情資料以及地面氣象站風(fēng)雨觀測數(shù)據(jù)和社會(huì)經(jīng)濟(jì)統(tǒng)計(jì)數(shù)據(jù),綜合考慮致災(zāi)因子、承災(zāi)體和防災(zāi)減災(zāi)能力構(gòu)建臺(tái)風(fēng)災(zāi)害直接經(jīng)濟(jì)損失評估模型,并在此基礎(chǔ)上定量化研究影響中國臺(tái)風(fēng)災(zāi)害直接經(jīng)濟(jì)損失的主導(dǎo)因子。結(jié)果表明:在2004—2021年期間,中國臺(tái)風(fēng)定基直接經(jīng)濟(jì)損失和臺(tái)風(fēng)風(fēng)雨強(qiáng)度均呈現(xiàn)下降趨勢。以2012年(臺(tái)風(fēng)路徑集合預(yù)報(bào)實(shí)時(shí)訂正技術(shù)啟用年)為界,臺(tái)風(fēng)大風(fēng)指數(shù)是2004—2011年期間對臺(tái)風(fēng)災(zāi)害經(jīng)濟(jì)損失貢獻(xiàn)量最大的影響因子,但在2012年之后,卻是貢獻(xiàn)量最小的因子;臺(tái)風(fēng)降雨指數(shù)、地區(qū)GDP(Gross Domestic Product)總和、臺(tái)風(fēng)強(qiáng)度預(yù)報(bào)誤差和排水管道密度因子對臺(tái)風(fēng)災(zāi)害經(jīng)濟(jì)損失的貢獻(xiàn)在2012年之后均明顯增加,并且臺(tái)風(fēng)強(qiáng)度預(yù)報(bào)誤差的降低和排水管道密度的顯著增加是2012—2021年期間臺(tái)風(fēng)災(zāi)害經(jīng)濟(jì)損失下降的主導(dǎo)要素。本研究發(fā)現(xiàn)我國臺(tái)風(fēng)災(zāi)害經(jīng)濟(jì)損失的主導(dǎo)影響因子在不同研究時(shí)段內(nèi)存在差異,提高臺(tái)風(fēng)強(qiáng)度預(yù)報(bào)水平和改善排水設(shè)施等防災(zāi)減災(zāi)能力可有效降低臺(tái)風(fēng)災(zāi)害經(jīng)濟(jì)損失。

    Abstract:

    Based on comprehensive data spanning from 2004 to 2021, encompassing 125 typhoon disaster events within China, and in conjunction with wind and rain observation data collected from ground meteorological stations as well as synchronous social and economic statistical data, this study develops a robust model for assessing the direct economic losses of typhoon disasters. This model takes into account causative factors, receptor characteristics, and disaster prevention and reduction capacity. On the basis of this model, we design a quantitative analysis method to conduct an in-depth exploration and quantitative analysis of the dominant factors influencing the change in direct economic losses caused by typhoon disasters in China. The research findings indicate that during the observation period from 2004 to 2021, overall direct economic losses resulting from typhoon disasters in China exhibit a significant year-on-year decreasing trend. Simultaneously, there are discernible signs of weakening in the wind and rain intensity associated with these typhoons in China. Taking 2012 as the cut-off point (the year when real-time correction technology for ensemble forecast of typhoon paths is officially put into use), our study finds that prior to this year, the typhoon wind index is identified as the most significant factor contributing to economic losses from these disasters during the observation period from 2004 to 2021; however, its influence decreases significantly after 2012, becoming the smallest contributing factor to the direct economic losses of typhoon disasters during the observation period from 2012 to 2021. Compared with the observation period from 2004 to 2011, there is a notable increase in contributions to the direct economic losses of typhoon disasters in China from factors related to typhoons after 2012, such as the typhoon rain index, regional GDP, typhoon intensity forecast error, and drainage pipe density factor. Particularly noteworthy is our identification of improved accuracy in forecasting typhoon intensity along with substantial increases during the observation period from 2012 to 2021 regarding drainage pipe density being the dominant impact factor driving down direct economic losses resulting from typhoon-related disasters. This study not only reveals differences over different research periods regarding dominant influencing factors on direct economic losses caused by Chinese typhoon disasters but also emphasises strengthening development and application of technologies for forecasting typhoons alongside improving infrastructure like drainage systems can effectively reduce their impact on society’s economy. These findings provide crucial references for formulating more scientific and efficient strategies aimed at addressing typhoon-related disasters.

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徐金勤,申丹娜,王皘,孟明明.中國臺(tái)風(fēng)災(zāi)害直接經(jīng)濟(jì)損失的主導(dǎo)影響因子評估與識別[J].氣象科技,2024,52(6):869~878

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  • 收稿日期:2023-11-01
  • 最后修改日期:2024-08-14
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  • 在線發(fā)布日期: 2024-12-25
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