Spatial Heterogeneity of Temporal Shifts in Extreme Precipitation across India

IF 0.7 Q4 METEOROLOGY & ATMOSPHERIC SCIENCES Journal of Climate Change Pub Date : 2019-03-01 DOI:10.3233/JCC190003
Manas Khan, F. Muñoz-Arriola, S. Rehana, P. Greer
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引用次数: 8

Abstract

When analyzing trends and patterns of extreme precipitation, one can easily generalize the shifts caused by external climate forcings and map a single temporal shift of annual precipitation. However, the complexity of a changing environment evidences spatially distributed shifts particularly those of extreme precipitation which are essential in planning and designing enterprises and, ultimately, in managing infrastructure across scales. The goal of this study is to characterize the spatial heterogeneity of shifts in the increasing pace of extreme events over India. The study has a two-part hypothesis: (1) the number of grid cells with significant trends in annual precipitation (P), extreme precipitation (R95) and very extreme precipitation (R99) will reflect the extent of geophysically vulnerable areas subject to increasing or decreasing annual precipitation and (2) the dispersion of cells with significant shifting points (which has occurred at different historical periods) will evidence the heterogeneity of the changes in P, R95 and R99 regimes. To test this hypothesis, we used the Mann-Kendall and Pettitt’s tests to estimate the significance of the increasing and decreasing trends and shifting points, respectively, in P, R95 and R99 from 1901-2015 for mainland India. digitalcommons.unl.edu Published in Journal of Climate Change, Vol. 5, No. 1 (2019), pp. 19-31. doi:10.3233/JCC190003 Submitted August 20, 2018; revised and accepted November 15, 2018 Khan et al . in Journal of Cl imate Change 5 (2019) 2 Based on a gridded dataset of 0.25° resolution, results showed significant temporal trends for spatially averaged R95 and R99, whereas non-significant inclining temporal trend was found for P. Trend analyses applied to the precipitation gridded product of the Indian Meteorological Department revealed statistically significant trends for almost 38%, 36% and 31% of India’s territory for P, R95 and R99, respectively. Further, the magnitude of these trends proved higher for R95 (i.e., 0.42 mm year-1) compared with R99 (i.e., 0.31 mm year-1), supporting the idea of an increasing liability for flash floods. Results also showed that most of the temporal shifts in the time series of P, R95 and R99 occurred between 1941-1980, at 34%, 31% and 22% of the grids, respectively. In addition, the opposite trends before and after the inflection point were found for locations showing significant temporal shifts in R95 and R99.
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印度极端降水时空变化的空间异质性
在分析极端降水的趋势和模式时,可以很容易地归纳出由外部气候强迫引起的变化,并绘制出年降水量的单一时间变化图。然而,不断变化的环境的复杂性证明了空间分布的变化,特别是极端降水的变化,这对于规划和设计企业以及最终跨尺度管理基础设施至关重要。本研究的目的是表征印度极端事件增加速度变化的空间异质性。研究提出了两部分假设:(1)年降水(P)、极端降水(R95)和极极端降水(R99)具有显著趋势的网格单元的数量将反映受年降水增加或减少影响的地球物理脆弱区程度;(2)具有显著移位点的网格单元的离散度(发生在不同历史时期)将证明P、R95和R99制度变化的异质性。为了验证这一假设,我们使用Mann-Kendall和Pettitt的检验分别估计了1901-2015年印度大陆P、R95和R99的上升趋势和下降趋势和转移点的重要性。发表于《气候变化学报》2019年第5卷第1期,第19-31页。doi:10.3233/JCC190003 2018年8月20日提交;2018年11月15日汗等。基于0.25°分辨率的网格化数据集,结果显示空间平均R95和R99的时间趋势显著,而P的时间趋势不显著。应用于印度气象部门降水网格化产品的趋势分析显示,P、R95和R99分别在印度近38%、36%和31%的领土上具有统计学显著趋势。此外,与R99(即0.31 mm -1)相比,R95(即0.42 mm -1)的这些趋势的幅度更高,这支持了山洪暴发责任增加的观点。结果还表明,P、R95和R99的时间序列变化主要发生在1941-1980年,分别占栅格数的34%、31%和22%。此外,在R95和R99有显著时间变化的地点,在拐点前后的趋势相反。
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来源期刊
Journal of Climate Change
Journal of Climate Change METEOROLOGY & ATMOSPHERIC SCIENCES-
自引率
16.70%
发文量
18
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