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Bias-corrected climate projections for South Asia from Coupled Model Intercomparison Project-6
Climate change is likely to pose enormous challenges for agriculture, water resources, infrastructure, and livelihood of millions of people living in South Asia. Here, we develop daily bias-corrected data of precipitation, maximum and minimum temperatures at 0.25° spatial resolution for South Asia (...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7550601/ https://www.ncbi.nlm.nih.gov/pubmed/33046709 http://dx.doi.org/10.1038/s41597-020-00681-1 |
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author | Mishra, Vimal Bhatia, Udit Tiwari, Amar Deep |
author_facet | Mishra, Vimal Bhatia, Udit Tiwari, Amar Deep |
author_sort | Mishra, Vimal |
collection | PubMed |
description | Climate change is likely to pose enormous challenges for agriculture, water resources, infrastructure, and livelihood of millions of people living in South Asia. Here, we develop daily bias-corrected data of precipitation, maximum and minimum temperatures at 0.25° spatial resolution for South Asia (India, Pakistan, Bangladesh, Nepal, Bhutan, and Sri Lanka) and 18 river basins located in the Indian sub-continent. The bias-corrected dataset is developed using Empirical Quantile Mapping (EQM) for the historic (1951–2014) and projected (2015–2100) climate for the four scenarios (SSP126, SSP245, SSP370, SSP585) using output from 13 General Circulation Models (GCMs) from Coupled Model Intercomparison Project-6 (CMIP6). The bias-corrected dataset was evaluated against the observations for both mean and extremes of precipitation, maximum and minimum temperatures. Bias corrected projections from 13 CMIP6-GCMs project a warmer (3–5°C) and wetter (13–30%) climate in South Asia in the 21(st) century. The bias-corrected projections from CMIP6-GCMs can be used for climate change impact assessment in South Asia and hydrologic impact assessment in the sub-continental river basins. |
format | Online Article Text |
id | pubmed-7550601 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-75506012020-10-19 Bias-corrected climate projections for South Asia from Coupled Model Intercomparison Project-6 Mishra, Vimal Bhatia, Udit Tiwari, Amar Deep Sci Data Data Descriptor Climate change is likely to pose enormous challenges for agriculture, water resources, infrastructure, and livelihood of millions of people living in South Asia. Here, we develop daily bias-corrected data of precipitation, maximum and minimum temperatures at 0.25° spatial resolution for South Asia (India, Pakistan, Bangladesh, Nepal, Bhutan, and Sri Lanka) and 18 river basins located in the Indian sub-continent. The bias-corrected dataset is developed using Empirical Quantile Mapping (EQM) for the historic (1951–2014) and projected (2015–2100) climate for the four scenarios (SSP126, SSP245, SSP370, SSP585) using output from 13 General Circulation Models (GCMs) from Coupled Model Intercomparison Project-6 (CMIP6). The bias-corrected dataset was evaluated against the observations for both mean and extremes of precipitation, maximum and minimum temperatures. Bias corrected projections from 13 CMIP6-GCMs project a warmer (3–5°C) and wetter (13–30%) climate in South Asia in the 21(st) century. The bias-corrected projections from CMIP6-GCMs can be used for climate change impact assessment in South Asia and hydrologic impact assessment in the sub-continental river basins. Nature Publishing Group UK 2020-10-12 /pmc/articles/PMC7550601/ /pubmed/33046709 http://dx.doi.org/10.1038/s41597-020-00681-1 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article. |
spellingShingle | Data Descriptor Mishra, Vimal Bhatia, Udit Tiwari, Amar Deep Bias-corrected climate projections for South Asia from Coupled Model Intercomparison Project-6 |
title | Bias-corrected climate projections for South Asia from Coupled Model Intercomparison Project-6 |
title_full | Bias-corrected climate projections for South Asia from Coupled Model Intercomparison Project-6 |
title_fullStr | Bias-corrected climate projections for South Asia from Coupled Model Intercomparison Project-6 |
title_full_unstemmed | Bias-corrected climate projections for South Asia from Coupled Model Intercomparison Project-6 |
title_short | Bias-corrected climate projections for South Asia from Coupled Model Intercomparison Project-6 |
title_sort | bias-corrected climate projections for south asia from coupled model intercomparison project-6 |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7550601/ https://www.ncbi.nlm.nih.gov/pubmed/33046709 http://dx.doi.org/10.1038/s41597-020-00681-1 |
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