Predicted changes in future precipitation and air temperature across Bangladesh using CMIP6 GCMs

Understanding spatiotemporal variability in precipitation and temperature and their future projections is critical for assessing environmental hazards and planning long-term mitigation and adaptation. In this study, 18 Global Climate Models (GCMs) from the most recent Coupled Model Intercomparison P...

Full description

Saved in:
Bibliographic Details
Main Authors: Mohammad Kamruzzaman, Mohammad Kamruzzaman, Wahid, Shahriar, Shahid, Shamsuddin, Alam, Edris, Mohammed Mainuddin, Mohammed Mainuddin, Islam, H. M. Touhidul, Cho, Jeapil, Rahman, Md. Mizanur, Biswas, Jatish Chandra, Thorp, Kelly R.
Format: Article
Language:English
Published: Elsevier Ltd 2023
Subjects:
Online Access:http://eprints.utm.my/107556/1/ShamsuddinShahid2023_PredictedChangesInFuturePrecipitationAndAirTemperature.pdf
http://eprints.utm.my/107556/
http://dx.doi.org/10.1016/j.heliyon.2023.e16274
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utm.107556
record_format eprints
spelling my.utm.1075562024-09-23T06:10:59Z http://eprints.utm.my/107556/ Predicted changes in future precipitation and air temperature across Bangladesh using CMIP6 GCMs Mohammad Kamruzzaman, Mohammad Kamruzzaman Wahid, Shahriar Shahid, Shamsuddin Alam, Edris Mohammed Mainuddin, Mohammed Mainuddin Islam, H. M. Touhidul Cho, Jeapil Rahman, Md. Mizanur Biswas, Jatish Chandra Thorp, Kelly R. TA Engineering (General). Civil engineering (General) Understanding spatiotemporal variability in precipitation and temperature and their future projections is critical for assessing environmental hazards and planning long-term mitigation and adaptation. In this study, 18 Global Climate Models (GCMs) from the most recent Coupled Model Intercomparison Project phase 6 (CMIP6) were employed to project the mean annual, seasonal, and monthly precipitation, maximum air temperature (Tmax), and minimum air temperature (Tmin) in Bangladesh. The GCM projections were bias-corrected using the Simple Quantile Mapping (SQM) technique. Using the Multi-Model Ensemble (MME) mean of the bias-corrected dataset, the expected changes for the four Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) were evaluated for the near (2015–2044), mid (2045–2074), and far (2075–2100) futures in comparison to the historical period (1985–2014). In the far future, the anticipated average annual precipitation increased by 9.48%, 13.63%, 21.07%, and 30.90%, while the average Tmax (Tmin) rose by 1.09 (1.17), 1.60 (1.91), 2.12 (2.80), and 2.99 (3.69) °C for SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5, respectively. According to predictions for the SSP5-8.5 scenario in the distant future, there is expected to be a substantial rise in precipitation (41.98%) during the post-monsoon season. In contrast, winter precipitation was predicted to decrease most (11.12%) in the mid-future for SSP3-7.0, while to increase most (15.62%) in the far-future for SSP1-2.6. Tmax (Tmin) was predicted to rise most in the winter and least in the monsoon for all periods and scenarios. Tmin increased more rapidly than Tmax in all seasons for all SSPs. The projected changes could lead to more frequent and severe flooding, landslides, and negative impacts on human health, agriculture, and ecosystems. The study highlights the need for localized and context-specific adaptation strategies as different regions of Bangladesh will be affected differently by these changes. Elsevier Ltd 2023 Article PeerReviewed application/pdf en http://eprints.utm.my/107556/1/ShamsuddinShahid2023_PredictedChangesInFuturePrecipitationAndAirTemperature.pdf Mohammad Kamruzzaman, Mohammad Kamruzzaman and Wahid, Shahriar and Shahid, Shamsuddin and Alam, Edris and Mohammed Mainuddin, Mohammed Mainuddin and Islam, H. M. Touhidul and Cho, Jeapil and Rahman, Md. Mizanur and Biswas, Jatish Chandra and Thorp, Kelly R. (2023) Predicted changes in future precipitation and air temperature across Bangladesh using CMIP6 GCMs. Heliyon, 9 (5). pp. 1-21. ISSN 2405-8440 http://dx.doi.org/10.1016/j.heliyon.2023.e16274 DOI : 10.1016/j.heliyon.2023.e16274
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic TA Engineering (General). Civil engineering (General)
spellingShingle TA Engineering (General). Civil engineering (General)
Mohammad Kamruzzaman, Mohammad Kamruzzaman
Wahid, Shahriar
Shahid, Shamsuddin
Alam, Edris
Mohammed Mainuddin, Mohammed Mainuddin
Islam, H. M. Touhidul
Cho, Jeapil
Rahman, Md. Mizanur
Biswas, Jatish Chandra
Thorp, Kelly R.
Predicted changes in future precipitation and air temperature across Bangladesh using CMIP6 GCMs
description Understanding spatiotemporal variability in precipitation and temperature and their future projections is critical for assessing environmental hazards and planning long-term mitigation and adaptation. In this study, 18 Global Climate Models (GCMs) from the most recent Coupled Model Intercomparison Project phase 6 (CMIP6) were employed to project the mean annual, seasonal, and monthly precipitation, maximum air temperature (Tmax), and minimum air temperature (Tmin) in Bangladesh. The GCM projections were bias-corrected using the Simple Quantile Mapping (SQM) technique. Using the Multi-Model Ensemble (MME) mean of the bias-corrected dataset, the expected changes for the four Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) were evaluated for the near (2015–2044), mid (2045–2074), and far (2075–2100) futures in comparison to the historical period (1985–2014). In the far future, the anticipated average annual precipitation increased by 9.48%, 13.63%, 21.07%, and 30.90%, while the average Tmax (Tmin) rose by 1.09 (1.17), 1.60 (1.91), 2.12 (2.80), and 2.99 (3.69) °C for SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5, respectively. According to predictions for the SSP5-8.5 scenario in the distant future, there is expected to be a substantial rise in precipitation (41.98%) during the post-monsoon season. In contrast, winter precipitation was predicted to decrease most (11.12%) in the mid-future for SSP3-7.0, while to increase most (15.62%) in the far-future for SSP1-2.6. Tmax (Tmin) was predicted to rise most in the winter and least in the monsoon for all periods and scenarios. Tmin increased more rapidly than Tmax in all seasons for all SSPs. The projected changes could lead to more frequent and severe flooding, landslides, and negative impacts on human health, agriculture, and ecosystems. The study highlights the need for localized and context-specific adaptation strategies as different regions of Bangladesh will be affected differently by these changes.
format Article
author Mohammad Kamruzzaman, Mohammad Kamruzzaman
Wahid, Shahriar
Shahid, Shamsuddin
Alam, Edris
Mohammed Mainuddin, Mohammed Mainuddin
Islam, H. M. Touhidul
Cho, Jeapil
Rahman, Md. Mizanur
Biswas, Jatish Chandra
Thorp, Kelly R.
author_facet Mohammad Kamruzzaman, Mohammad Kamruzzaman
Wahid, Shahriar
Shahid, Shamsuddin
Alam, Edris
Mohammed Mainuddin, Mohammed Mainuddin
Islam, H. M. Touhidul
Cho, Jeapil
Rahman, Md. Mizanur
Biswas, Jatish Chandra
Thorp, Kelly R.
author_sort Mohammad Kamruzzaman, Mohammad Kamruzzaman
title Predicted changes in future precipitation and air temperature across Bangladesh using CMIP6 GCMs
title_short Predicted changes in future precipitation and air temperature across Bangladesh using CMIP6 GCMs
title_full Predicted changes in future precipitation and air temperature across Bangladesh using CMIP6 GCMs
title_fullStr Predicted changes in future precipitation and air temperature across Bangladesh using CMIP6 GCMs
title_full_unstemmed Predicted changes in future precipitation and air temperature across Bangladesh using CMIP6 GCMs
title_sort predicted changes in future precipitation and air temperature across bangladesh using cmip6 gcms
publisher Elsevier Ltd
publishDate 2023
url http://eprints.utm.my/107556/1/ShamsuddinShahid2023_PredictedChangesInFuturePrecipitationAndAirTemperature.pdf
http://eprints.utm.my/107556/
http://dx.doi.org/10.1016/j.heliyon.2023.e16274
_version_ 1811681220609703936
score 13.209306