State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China; Academy of Disaster Reduction and Emergency Management, Ministry of Civil Affairs & Ministry of Education, Faculty of Geographical Science, Beijing 100875, China.
State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China; Key Laboratory of Environmental Change and Natural Disaster, MOE, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China; Academy of Disaster Reduction and Emergency Management, Ministry of Civil Affairs & Ministry of Education, Faculty of Geographical Science, Beijing 100875, China.
Sci Total Environ. 2017 Aug 15;592:729-737. doi: 10.1016/j.scitotenv.2017.02.028. Epub 2017 Mar 21.
Vegetation phenology changes have been widely applied in the disaster risk assessments of the spring dust storms, and vegetation green-up date shifts have a strong influence on dust storms. However, the effect of earlier vegetation green-up dates due to climate warming on the evaluation of dust storms return periods remains an important, but poorly understood issue. In this study, we evaluate the spring dust storm return period (February to June) in Inner Mongolia, Northern China, using 165 observations of severe spring dust storm events from 16 weather stations, and regional vegetation green-up dates as an integrated factor from NDVI (Normalized Difference Vegetation Index), covering a period from 1982 to 2007, by building the bivariate Copula model. We found that the joint return period showed better fitting results than without considering the integrated factor when the actual dust storm return period is longer than 2years. Also, for extremely severe dust storm events, the gap between simulation result and actual return period can be narrowed up to 0.4888years by using integrated factor. Furthermore, the risk map based on the return period results shows that the Mandula, Zhurihe, Sunitezuoqi, Narenbaolige stations are identified as high risk areas. In this study area, land surface is extensively covered by grasses and shrubs, vegetation green-up date can play a significant role in restraining spring dust storm outbreaks. Therefore, we suggest that Copula method can become a useful tool for joint return period evaluation and risk analysis of severe dust storms.
植被物候变化已广泛应用于春季沙尘暴灾害风险评估中，而植被返青日期的变化对沙尘暴有很强的影响。然而，由于气候变暖导致植被更早返青对沙尘暴重现期评估的影响仍然是一个重要但尚未得到充分理解的问题。本研究利用 1982 年至 2007 年期间来自 16 个气象站的 165 次严重春季沙尘暴事件观测数据，以及作为综合因素的归一化植被指数（NDVI）的植被返青日期，构建了二元 Copula 模型，评估了中国北方内蒙古的春季沙尘暴重现期（2 月至 6 月）。结果表明，当实际沙尘暴重现期长于 2 年时，考虑综合因素的联合重现期比不考虑综合因素的拟合结果更好。此外，对于极其严重的沙尘暴事件，通过使用综合因素，模拟结果与实际重现期之间的差距可以缩小到 0.4888 年。此外，基于重现期结果的风险图显示，满都拉、朱日和、苏尼特左旗和那仁宝力格站被确定为高风险区域。在本研究区域，地表广泛覆盖着草地和灌木，植被返青日期在抑制春季沙尘暴爆发方面发挥着重要作用。因此，我们建议 Copula 方法可以成为评估严重沙尘暴的联合重现期和风险分析的有用工具。
