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首页> 外文期刊>Climatic Change >Projections of Extreme Dry and Wet Spells in the 21(st) Century India Using Stationary and Non-stationary Standardized Precipitation Indices
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Projections of Extreme Dry and Wet Spells in the 21(st) Century India Using Stationary and Non-stationary Standardized Precipitation Indices

机译:使用平稳和非平稳标准化降水指数对印度21世纪极端干湿法术的预测

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摘要

The conventional approach to projecting meteorological extremes involves the application of indices such as the Standardized Precipitation Index (SPI) to rainfall simulated by General Circulation Models (GCMs). However, the sensitivity of SPI to the length of the records and the poor skills of GCMs in simulating rainfall are major drawbacks, leading to implausible projections. It is imperative to quantify and address these limitations before implementation of the approach. Here, we project the frequency of extreme dry and wet spells during the 21(st) century over India, incorporating special measures to alleviate the aforementioned limitations of the approach. We deploy kernel regression-based statistical downscaling to obtain improved 0.25-degree resolution monthly rainfall projections for India based on five GCMs and three emission scenarios (RCP2.6, RCP4.5, and RCP8.5) belonging to phase five of the Coupled Model Intercomparison Project. We also establish that the Standardized non-stationarity Precipitation Index (SnsPI), which incorporates changing climatic conditions considering linearly varying non-stationary scale parameter of the gamma distribution, is less sensitive to the length of the records as compared to SPI and we use both indices to obtain the frequency of future meteorological extremes. The results show an increase in the occurrences of extreme dry spells (EDS) over central, southeast coast, eastern region and some parts of northeast India. Differences between SPI and SnsPI based on the sensitivity are observed over, central India, where SPI overestimates EDS. Also, both the indices show diametrically opposite trends for areas under the influence of extreme wet spells in the future (2070-2099).
机译:预测极端天气的常规方法涉及将诸如标准降水指数(SPI)之类的指标应用到由通用环流模型(GCM)模拟的降雨中。但是,SPI对记录长度的敏感性和GCM模拟降雨的能力很差是主要缺点,导致难以置信的预测。在实施该方法之前,必须量化并解决这些局限性。在这里,我们预测了在21世纪印度全境极端干旱和潮湿天气的发生频率,并采用了减轻上述限制的特殊措施。我们基于核回归模型进行统计缩减,以基于耦合模型第五阶段的五个GCM和三个排放情景(RCP2.6,RCP4.5和RCP8.5)获得改进的0.25度分辨率印度月降雨量预测比对项目。我们还确定,考虑到线性变化的伽玛分布的非平稳尺度参数而考虑了气候条件变化的标准化非平稳降水指数(SnsPI)与SPI相比对记录的长度较不敏感,因此我们将两者结合使用指标以获取未来气象极端事件的频率。结果表明,印度中部,东南沿海,东部地区和东北部某些地区的极端干旱(EDS)的发生率增加。在印度中部观察到基于灵敏度的SPI和SnsPI之间的差异,那里SPI高估了EDS。同样,在未来(2070-2099),受极端湿气影响的地区,两个指数都显示出截然相反的趋势。

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