Abstract

The persistence of drought events largely determines the severity of socioeconomic and ecological impacts, unfortunately the performance of current weather forecasting models (WFM) to simulate such events is subject to great uncertainties. This study is investigating time-domain characteristics of drought persistence over Turkey by applying the detrended fluctuation analysis (DFA) method to the Palmer drought severity index (PDSI). The existence of long-range power-law correlation in PDSI fluctuations is demonstrated for time scales ranging from monthly to decadal. Understanding of such statistical patterns in PDSI values can definitely be a step forward in drought predictability. From a climatological point of view, it is found that the areas with high level DFA scaling exponent (generalized Hurst) indicate the areas of higher sensitivity to droughts and associated risks. Furthermore, the characteristics of the persistence of the PDSI in climate zones have also been examined by applying the Holdridge Life Zones (HLZ) classification. HLZ classification over Turkey leads to two climate-zones: cool-temperate and warm-temperate. In addition, when topography is taken in account, montane (cool-temperate) and lower-montane (warm-temperate) climate zones can be treated as two different zones. It has been observed that the predictable index (PI) of the PDSI derived from the DFA Hurst exponent is relatively high in the cool-temperate and montane climate zones compared to others. In fact, very different PI values were also obtained in a few HLZ climate classes within the same climate zone and with same vegetation index (i.e. steppe, dry-forest, warm-forest etc.).

中文翻译：

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通过趋势波动分析分析干旱中的长期记忆

摘要

干旱事件的持续性在很大程度上决定了社会经济和生态影响的严重性，不幸的是，目前用于模拟此类事件的天气预报模型（WFM）的性能存在很大的不确定性。这项研究通过对帕尔默干旱严重性指数（PDSI）应用去趋势波动分析（DFA）方法来研究土耳其持续干旱的时域特征。PDSI波动中存在长期幂律相关性，证明时间尺度从每月到十年不等。理解PDSI值的此类统计模式绝对可以是干旱预测性的一个进步。从气候学的角度来看，发现具有高水平DFA缩放指数的区域（广义赫斯特）表明该区域对干旱和相关风险的敏感性更高。此外，还通过应用Holdridge生命区（HLZ）分类检查了PDSI在气候区中的​​持久性特征。土耳其的HLZ分类导致两个气候区：凉温带和暖温带。此外，如果考虑到地形，则可以将山区（凉爽的）和较低山区（暖温的）的气候区视为两个不同的区域。已经观察到，与其他区域相比，在低温和山区气候区域中，源自DFA Hurst指数的PDSI的可预测指数（PI）相对较高。事实上，