Application of remote sensing precipitation data and the CONNECT algorithm to investigate spatiotemporal variations of heavy precipitation: Case study of major floods across Iran (Spring 2019)
Application of remote sensing precipitation data and the CONNECT algorithm to investigate spatiotemporal variations of heavy precipitation: Case study of major floods across Iran (Spring 2019)
复制标题
应用遥感降水数据和CONNECT算法研究强降水时空变化：以伊朗特大洪水为例（2019年春季）
DOI：
10.1016/j.jhydrol.2021.126569
复制
发表时间：
2021
影响因子：
6.4
通讯作者：
Sorooshian, Soroosh
中科院分区：
文献类型：
--
作者：
Sadeghi, Mojtaba;Shearer, Eric J.;Mosaffa, Hamidreza;Gorooh, Vesta Afzali;Rahnamay Naeini, Matin;Hayatbini, Negin;Katiraie-Boroujerdy, Pari-Sima;Analui, Bita;Nguyen, Phu;Sorooshian, Soroosh
近年来，伊朗在早春（3月21日至4月20日，在伊朗被称为“Farvadin”月）发生前所未有的降雨事件后，洪水的数量有所增加。虽然有许多研究探讨了全国各地从日到年的不同时间尺度上的极端气候变化和降水趋势，但很少考虑对短时间和强降水的分析，特别是近年来的分析。此外，大多数研究利用伊朗各地数量有限的天气气象站调查极端情况和总降水量的变化。这项研究评估了在Farvardin月期间，在0.04°空间和3小时时间分辨率下强降水（降水强度大于或等于3 mm/3 h）的变化。此外，伊朗的大气河流条件的影响和他们可能的联系，以加强强降水进行了探讨。为此目的，连接对象（CNOECT）算法应用于降水数据集，降水估计从遥感信息使用人工神经网络云分类系统（PERSIANN-CCS），和综合水汽输送（IVT）数据集从美国航天局现代回顾分析研究和应用版本2（MERRA-2）。结果表明，近年来洪涝灾害次数的增加与强降水事件的强度和量的增加有关，虽然强降水事件的频率和持续时间没有明显变化。此外，研究结果表明，在每年最极端的事件发生的同一窗口期间，全国的大气河流条件都存在。据发现，伊朗上空13个最大的AR中有8个来自非洲和红海上空的水汽羽流。
In recent years, the number of floods following unprecedented rainfall events have increased in Iran during early spring (March 21st to April 20th, referred to in Iran as the month of “Farvadin”). While numerous studies have addressed changes in climate extremes and precipitation trends at different temporal scales from daily to annual across the country, analyses of short-duration and heavy precipitation, especially during recent years, are rarely considered. Furthermore, most studies investigate the variations in extremes and total precipitation using a limited number of synoptic weather stations across Iran. This study assesses the variations in heavy precipitation (precipitation with intensities greater than or equal to 3 mm/3 h) at 0.04° spatial and 3-hourly temporal resolution during the month of Farvardin. In addition, the effect of atmospheric river conditions over Iran and their possible link to intensifying heavy precipitation is explored. For this purpose, the CONNected-objECT (CONNECT) algorithm is applied on a precipitation dataset, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS), and an Integrated Water Vapor Transport (IVT) dataset from the NASA Modern-Era Retrospective Analysis for Research and Applications Version-2 (MERRA-2). The results suggest that the increase in the number of floods in recent years is related to the increase in the intensity and volume of heavy precipitation events, although the frequency and duration of heavy precipitation events have not changed significantly. Furthermore, the results show that atmospheric river conditions over the country are present during the same window as each year’s most extreme events. It is found that 8 out of 13 of the largest ARs over Iran come from moisture plumes with pathways over the African and Red Sea.
登录
查看更多内容
影响因子：
3.2
作者：
S. Davolio;S. D. Fera;S. Laviola;M. Miglietta;V. Levizzani
通讯作者：
S. Davolio;S. D. Fera;S. Laviola;M. Miglietta;V. Levizzani
DOI：
10.1111/j.1467-8306.1985.tb00075.x
发表时间：
1985
期刊：
Annals of The Association of American Geographers
影响因子：
--
作者：
B. Alijani;J. R. Harman
通讯作者：
J. R. Harman
识别大气河流事件及其进入伊朗的路径
影响因子：
3.4
作者：
N. Esfandiari;H. Lashkari
通讯作者：
H. Lashkari
伊朗及周边地区500 hPa气流型变化及其与伊朗气候的关系
影响因子：
3.4
作者：
B. Alijani
通讯作者：
B. Alijani
DOI：
10.1016/j.envsoft.2020.104856
发表时间：
2020-09
期刊：
Environ. Model. Softw.
影响因子：
--
作者：
M. Sadeghi;P. Nguyen;K. Hsu;S. Sorooshian
通讯作者：
M. Sadeghi;P. Nguyen;K. Hsu;S. Sorooshian