IDENTIFICATION OF CORRELATIONS BETWEEN PRECIPITATION INDICES AND MONTHLY DRY DAYS IN SEASONAL CLIMATE ANALYSIS

被引：0

作者：

Osmani, Shabbir Ahmed ^{[1
]}

Cha, Hoyoung ^{[1
]}

Park, Kihong ^{[2
]}

Baik, Jongjin ^{[2
]}

Jun, Changhyun ^{[1
,2
]}

机构：

[1] Chung Ang Univ, Dept Smart Cities, Seoul, South Korea

[2] Chung Ang Univ, Dept Civil & Environm Engn, Seoul, South Korea

来源：

2024 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2024) | 2024年

关键词：

Correlation; Monthly dry days; Extreme precipitation indices; Anomalies;

D O I：

10.1109/IGARSS53475.2024.10640700

中图分类号：

P9 [自然地理学];

学科分类号：

0705 ; 070501 ;

摘要：

Climate indices play a pivotal role in deciphering and monitoring complex climatic patterns, providing essential insights into long-term trends and variations. This research, spanning multiple seasons, aims to provide comprehensive insights into the dynamics between extreme precipitation indices and the frequency of monthly dry days (MDD) through correlation analysis. By utilizing calculated indices to grasp a range of precipitation patterns, this study places emphasis not just on the intensity but also on how these correlations are spread across different regions. Through rigorous analysis of correlations and long-term anomalies, there are meaningful associations between the precipitation indices and MDD. Such insights are valuable for advancing our understanding of regional climate variations within the seasonal extreme precipitation indices and the dry days and hold significance for applications in the fields of agriculture and water resource management.

引用

页码：5651 / 5653

页数：3

共 8 条

[1] Extreme temperature and rainfall events in Bangladesh: A comparison between coastal and inland areas [J].

Abdullah, Abu Yousuf Md ;

Bhuian, Md Hanif ;

Kiselev, Grigory ;

Dewan, Ashraf ;

Hasan, Quazi K. ;

Rafiuddin, M. .

INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2022, 42 (06) :3253-3273

[2] Spatiotemporal Variations of Extreme Precipitation in Wuling Mountain Area (China) and Their Connection to Potential Driving Factors [J].

Du, Hong ;

Xia, Jun ;

Yan, Yi ;

Lu, Yumeng ;

Li, Jinhua .

SUSTAINABILITY, 2022, 14 (14)

[3]

Fischer EM, 2013, NAT CLIM CHANGE, V3, P1033, DOI [10.1038/nclimate2051, 10.1038/NCLIMATE2051]

[4] Spatiotemporal changes and modulations of extreme climatic indices in monsoon-dominated climate region linkage with large-scale atmospheric oscillation [J].

Islam, H. M. Touhidul ;

Islam, Abu Reza Md. Towfiqul ;

Abdullah-Al-Mahbub, Md. ;

Shahid, Shamsuddin ;

Tasnuva, Anjum ;

Kamruzzaman, Mohammad ;

Hu, Zhenghua ;

Elbeltagi, Ahmed ;

Kabir, Mohammad Mahbub ;

Salam, Mohammed Abdus ;

Ibrahim, Sobhy M. .

ATMOSPHERIC RESEARCH, 2021, 264

[5]

Li J., 2021, Geoscience, V4, P25

[6] Prediction of monthly dry days with machine learning algorithms: a case study in Northern Bangladesh [J].

Osmani, Shabbir Ahmed ;

Kim, Jong-Suk ;

Jun, Changhyun ;

Sumon, Md Wahiduzzaman ;

Baik, Jongjin ;

Lee, Jinwook .

SCIENTIFIC REPORTS, 2022, 12 (01)

[7] Changing climate extremes in the Northeast United States: observations and projections from CMIP5 [J].

Thibeault, Jeanne M. ;

Seth, Anji .

CLIMATIC CHANGE, 2014, 127 (02) :273-287

[8] A New Scheme for Improving the Seasonal Prediction of Summer Precipitation Anomalies [J].

Wang, Huijun ;

Fan, Ke .

WEATHER AND FORECASTING, 2009, 24 (02) :548-554

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