Alugula Boyaj , Palash Sinha , U.C. Mohanty , V. Vinoj , Karumuri Ashok , Sahidul Islam , A. Kaginalkar , M. Khare
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Our observational analysis shows that the ISM total and the frequency of low- to high-intensity rainfall events have significantly decreased mostly over the central northeastern, Jammu and Kashmir, and some places in the northeastern and central parts of India. However, they have significantly increased over Gujarat, the northwestern, the Western Ghats, and the southern parts of India during the present climate period (1991–2020) compared to the past climate period (1961–1990). Furthermore, we explored the fidelity of five Coordinated Regional Climate Downscaling Experiments (CORDEX) Regional Climate Models (RCMs) in simulating the spatiotemporal variability of ISM total rainfall and the frequency of low- to high-intensity rainfall events over India during the historical (1976–2005) and future periods (2006–2100). All CORDEX RCMs overestimate the ISM total rainfall over India's heavy rainfall zones during the historical period by ∼10–30 % compared to IMD observations. To improve CORDEX RCM's skills in simulating the frequency of low- to high-intensity rainfall events, we employed a percentile-based bias correction technique. Compared to non-bias-corrected outputs from the RCMs, the quantile-bias-corrected method significantly enhanced the probability of detection rate (hit rate) in all studied models for extreme, heavy, and moderate rainfall events, excluding light rainfall events. Interestingly, the improvement is greater for extreme events, followed by heavy and moderate rainfall events. The composite hit rate of all the models shows 381 %, 146 %, and 44 % improvement for extreme, heavy, and moderate events, respectively. It is noticed that the CCCMA model performed better than the other four CORDEX models in capturing the spatial patterns of ISM total rainfall and the frequency of total extreme and heavy rainfall events over higher rainfall zones in India. 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引用次数: 0
摘要
暴雨事件和相关的洪水已成为对社会的巨大威胁之一,主要表现为气候变化。印度夏季季风(ISM)的降雨量占全年降雨量的 80%,近来主要以高强度降雨事件(HREs)为特征。我们通过访问印度气象局(IMD)1961 年至 2020 年 ISM 季节的日网格降雨量观测数据集(0.25° × 0.25°),从气候变化的角度研究了高强度降雨事件的时空变异性。我们的观测分析表明,印度东北部中部、查谟和克什米尔以及印度东北部和中部的一些地方的 ISM 总降雨量和低强度至高强度降雨事件的频率明显下降。然而,与过去的气候期(1961-1990 年)相比,在目前的气候期(1991-2020 年),印度古吉拉特邦、西北部、西高止山脉和南部地区的降雨量明显增加。此外,我们还探讨了五个协调区域气候降尺度实验(CORDEX)区域气候模式(RCMs)在模拟历史时期(1976-2005 年)和未来时期(2006-2100 年)印度上空 ISM 总降雨量的时空变异性和低强度至高强度降雨事件频率方面的保真度。与 IMD 观测结果相比,所有 CORDEX RCM 都高估了历史时期印度暴雨区的 ISM 总降雨量,高估幅度在 10-30% 之间。为了提高 CORDEX RCM 模拟低强度到高强度降雨事件频率的能力,我们采用了基于百分位数的偏差校正技术。与未经偏差校正的 RCM 输出结果相比,量化偏差校正方法显著提高了所有研究模型对极端、暴雨和中雨事件(不包括小雨事件)的检出率(命中率)。有趣的是,极端降雨事件的检测率提高幅度更大,其次是暴雨和中雨事件。在极端、暴雨和中雨事件中,所有模型的综合命中率分别提高了 381%、146% 和 44%。研究发现,CCCMA 模式在捕捉印度高降雨区 ISM 总降雨量的空间模式以及总极端降雨和暴雨事件频率方面的表现优于其他四个 CORDEX 模式。此外,该研究还表明,未来印度上空的 ISM 总降雨量可能不会发生重大变化,但总极端降雨量和暴雨事件的频率很可能会增加,而在未来预测中,印度南部地区的中雨事件频率可能会减少。
Projected frequency of low to high-intensity rainfall events over India using bias-corrected CORDEX models
Heavy rainfall events and associated floods have emerged as one of the great threats to society that mainly manifested due the climate change. The Indian summer monsoon (ISM) contributes 80 % of annual rainfall and is characterized mainly by high-intensity rainfall events (HiREs) in the recent era. We investigated the spatiotemporal variability of HiREs from a climate change perspective by accessing the India Meteorological Department's (IMD) observed daily gridded rainfall dataset (0.25° × 0.25°) from 1961 to 2020 during the ISM season. Our observational analysis shows that the ISM total and the frequency of low- to high-intensity rainfall events have significantly decreased mostly over the central northeastern, Jammu and Kashmir, and some places in the northeastern and central parts of India. However, they have significantly increased over Gujarat, the northwestern, the Western Ghats, and the southern parts of India during the present climate period (1991–2020) compared to the past climate period (1961–1990). Furthermore, we explored the fidelity of five Coordinated Regional Climate Downscaling Experiments (CORDEX) Regional Climate Models (RCMs) in simulating the spatiotemporal variability of ISM total rainfall and the frequency of low- to high-intensity rainfall events over India during the historical (1976–2005) and future periods (2006–2100). All CORDEX RCMs overestimate the ISM total rainfall over India's heavy rainfall zones during the historical period by ∼10–30 % compared to IMD observations. To improve CORDEX RCM's skills in simulating the frequency of low- to high-intensity rainfall events, we employed a percentile-based bias correction technique. Compared to non-bias-corrected outputs from the RCMs, the quantile-bias-corrected method significantly enhanced the probability of detection rate (hit rate) in all studied models for extreme, heavy, and moderate rainfall events, excluding light rainfall events. Interestingly, the improvement is greater for extreme events, followed by heavy and moderate rainfall events. The composite hit rate of all the models shows 381 %, 146 %, and 44 % improvement for extreme, heavy, and moderate events, respectively. It is noticed that the CCCMA model performed better than the other four CORDEX models in capturing the spatial patterns of ISM total rainfall and the frequency of total extreme and heavy rainfall events over higher rainfall zones in India. Additionally, this study suggests that there will likely be no significant changes in ISM total rainfall over India in the future, but the frequency of total extreme and heavy rainfall events will most likely increase, while the frequency of moderate rainfall events will likely decrease mostly over southern parts of India in future projections.
期刊介绍:
The journal publishes scientific papers (research papers, review articles, letters and notes) dealing with the part of the atmosphere where meteorological events occur. Attention is given to all processes extending from the earth surface to the tropopause, but special emphasis continues to be devoted to the physics of clouds, mesoscale meteorology and air pollution, i.e. atmospheric aerosols; microphysical processes; cloud dynamics and thermodynamics; numerical simulation, climatology, climate change and weather modification.