Spatiotemporal characteristics of precipitation extremes based on reanalysis precipitation data during 1950–2020 over the Ganjiang River Basin and its surroundings, China

IF 2 4区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES Atmospheric Science Letters Pub Date : 2022-12-30 DOI:10.1002/asl.1149
Hongyi Li, Ameng Zou, Daqi Kong, Ziqiang Ma
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Abstract

Accurate knowledge on spatiotemporal characteristics of historical precipitation extremes could provide great potential guidance for preventing hydrological-related disasters caused by precipitation extremes in the future. On the basis of the fifth generation of atmospheric reanalysis precipitation data by the European Centre for Medium Range Weather Forecasts (ERA5, 0.25°, 1 hourly, 1950–2020) with high spatiotemporal resolutions, continuity and quality, this study analyzed the spatiotemporal characteristics of precipitation extremes over the Ganjiang River Basin and its surroundings during 1950–2020. The main conclusions include, but are not limited to, the following: (1) In general, precipitation extremes present increasing trends over most areas of the basin and its surroundings. For instance, areas showing upward trends of R10, SDII and PRCPTOT account for ~93.45%, ~66.36%, and ~88.18%, respectively. (2) The spatiotemporal variations of precipitation extremes over the Ganjiang River Basin and its surroundings show obvious northwest–southeast differences. For instance, precipitation extremes are increasing in the southeastern parts, but they are decreasing in the northwestern parts. (3) High-value clusters are also identified in the southeast (e.g., R10, SDII, R95P and PRCPTOT, accounting for ~20.71%, ~20.72%, ~25.88%, and ~22.56%, respectively) and low-value clusters in the northwest (e.g., Rx5day, SDII and R95P, accounting for ~18.05%, ~27.03%, and ~21.18%, respectively). (4) The spatiotemporal variations of precipitation extremes in both the southeast and northwest are quite stable. For example, regions with less than five abrupt change points of R10, SDII, and PRCPTOT account for 77.49%, 54.84%, and 81.74%, respectively.

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基于1950-2020年甘江流域及周边地区再分析降水资料的极端降水时空特征
准确认识历史极端降水的时空特征,对未来预防极端降水引起的水文灾害具有重要的指导意义。利用欧洲中期天气预报中心(ERA5, 0.25°,1 h, 1950—2020)第五代高时空分辨率、连续性和高质量的大气再分析降水资料,分析了1950—2020年甘江流域及周边地区极端降水的时空特征。主要结论包括但不限于:(1)总体上,流域及其周边大部分地区降水极端事件呈增加趋势;其中,R10、SDII和PRCPTOT呈上升趋势的地区分别占~93.45%、~66.36%和~88.18%。(2)赣江流域及周边地区极端降水时空变化呈现明显的西北—东南差异。例如,极端降水在东南部呈增加趋势,而在西北部呈减少趋势。(3)东南高值区(R10、SDII、R95P和PRCPTOT分别占20.71%、20.72%、25.88%和22.56%),西北低值区(Rx5day、SDII和R95P分别占18.05%、27.03%和21.18%)。(4)东南、西北极端降水的时空变化均较为稳定。例如,R10、SDII和PRCPTOT突变点小于5个的区域分别占77.49%、54.84%和81.74%。
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来源期刊
Atmospheric Science Letters
Atmospheric Science Letters METEOROLOGY & ATMOSPHERIC SCIENCES-
CiteScore
4.90
自引率
3.30%
发文量
73
审稿时长
>12 weeks
期刊介绍: Atmospheric Science Letters (ASL) is a wholly Open Access electronic journal. Its aim is to provide a fully peer reviewed publication route for new shorter contributions in the field of atmospheric and closely related sciences. Through its ability to publish shorter contributions more rapidly than conventional journals, ASL offers a framework that promotes new understanding and creates scientific debate - providing a platform for discussing scientific issues and techniques. We encourage the presentation of multi-disciplinary work and contributions that utilise ideas and techniques from parallel areas. We particularly welcome contributions that maximise the visualisation capabilities offered by a purely on-line journal. ASL welcomes papers in the fields of: Dynamical meteorology; Ocean-atmosphere systems; Climate change, variability and impacts; New or improved observations from instrumentation; Hydrometeorology; Numerical weather prediction; Data assimilation and ensemble forecasting; Physical processes of the atmosphere; Land surface-atmosphere systems.
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