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Dewan A, Shahid S, Bhuian MH, Hossain SMJ, Nashwan MS, Chung ES, Hassan QK, Asaduzzaman M. Developing a high-resolution gridded rainfall product for Bangladesh during 1901-2018. Sci Data 2022; 9:471. [PMID: 35922427 PMCID: PMC9349194 DOI: 10.1038/s41597-022-01568-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 07/13/2022] [Indexed: 11/22/2022] Open
Abstract
A high-resolution (1 km × 1 km) monthly gridded rainfall data product during 1901-2018, named Bangladesh Gridded Rainfall (BDGR), was developed in this study. In-situ rainfall observations retrieved from a number of sources, including national organizations and undigitized data from the colonial era, were used. Leave-one-out cross-validation was used to assess product's ability to capture spatial and temporal variability. The results revealed spatial variability of the percentage bias (PBIAS) in the range of -2 to 2%, normalized root mean square error (NRMSE) <20%, and correlation coefficient (R2) >0.88 at most of the locations. The temporal variability in mean PBIAS for 1901-2018 was in the range of -4.5 to 4.3%, NRMSE between 9 and 19% and R2 in the range of 0.87 to 0.95. The BDGR also showed its capability in replicating temporal patterns and trends of observed rainfall with greater accuracy. The product can provide reliable insights regarding various hydrometeorological issues, including historical floods, droughts, and groundwater recharge for a well-recognized global climate hotspot, Bangladesh.
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Affiliation(s)
- Ashraf Dewan
- Spatial Sciences discipline, Curtin University, Bentley 6102, Perth, Western Australia
| | - Shamsuddin Shahid
- School of Civil Engineering, Faculty of Engineering, Universiti Teknologi Malaysia (UTM), 81310, Johor Bahru, Malaysia
| | - Md Hanif Bhuian
- Department of Geography and Environment, Jagannath University, Dhaka, 1100, Bangladesh
| | | | - Mohamed Salem Nashwan
- Construction and Building Engineering Department, College of Engineering and Technology, Arab Academy for Science, Technology and Maritime Transport (AASTMT), 2033, Cairo, Egypt
| | - Eun-Sung Chung
- Department of Civil Engineering, Seoul National University of Science and Technology, Nowon-gu, 01811, Seoul, South Korea.
| | - Quazi K Hassan
- Department of Geomatics Engineering, University of Calgary, 2500 University Drive NW, T2N 1N4, Calgary, Canada
| | - Md Asaduzzaman
- Department of Engineering, School of Digital, Technologies and Arts, Staffordshire University, Stoke-on-Trent, UK
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Homogenization and Trends Analysis of Monthly Precipitation Series in the Fez-Meknes Region, Morocco. CLIMATE 2022. [DOI: 10.3390/cli10050064] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/07/2022]
Abstract
High quality and long-term precipitation data are required to study the variability and trends of rainfall and the impact of climate change. In developing countries like Morocco, the quality of climate data collected from various weather stations faces numerous obstacles. This paper presents methods for collecting, correcting, reconstructing, and homogenizing precipitation series of Morocco’s Fez-Meknes region from 1961 to 2019. Data collected from national specialized agencies based on 83 rain gauge stations was processed through an algorithm specially designed for the homogenization of climatic data (Climatol). We applied the Mann-Kendall test and Sen’s slope estimator to raw and homogenized data to calculate rainfall trend magnitudes and significance. The homogenization process allows for the detection of a larger number of stations with statistically significant negative trends with 95% and 90% confidence levels, particularly in the mountain ranges, that threatens the main sources of water in the largest watershed in the country. The regionalization of our rain gauge stations is highlighted and compared to previous studies. The monthly and annual means of raw and homogenized data show minor differences over the three main climate zones of the region.
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