The objective of this research is to assess the mathematical downscaling of the union-wise administrative area of Bangladesh that simulations and future projections of rainfall and mean temperature of CMIP6 (SSP2–4.5 and 5–8.5). Models were used to determine uncertainty with spatiotemporal variability of rainfall and mean temperature projections. Model data NETCDF file has been converted to Raster with cell size of 1, 1 decimal degree which means that each cell contains 100 km x 100 km area coverage. After preparing the dataset of 0.01, 0.01 decimal degree cell size (1km x1km), the dataset of Bangladesh has been extracted union-wise by the Bilinear resampling technique. An average value has been generated from the multiple values belonging to the specific union. After that, the dataset of Bangladesh has been generated. Mathematical downscaling and bias correction are made for the selected 16 model runs. The CMIP6 models for the model and observed values of rainfall show Kling-Gupta Efficiency (KGE) values in a range of 0.58-0.72 and for mean temperature in a range of 0.85- 0.90. The CMIP6 models show Pearson's correlation coefficient (R) in the range of 0.83-0.90 for rainfall and in a range of 0.86-0.93 for mean temperature. Also, CMIP6 models showed Nash Sutcliffe in the range of 0.06-0.78 for rainfall and 0.73-0.89 for mean temperature from the model and observed value. The projected change of future rainfall and mean temperature in the study increases the rainfall intensities due to the increment of temperature.
| Published in | Earth Sciences (Volume 12, Issue 5) |
| DOI | 10.11648/j.earth.20231205.13 |
| Page(s) | 140-158 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
Mathematical Downscaling, CMIP6 Climate Models, Climate Change
| [1] | Bangladesh Bureau of Statistics-Government of the People\’s Republic of Bangladesh. (n. d.). Retrieved March 21, 2022, from http://www.bbs.gov.bd/site/page/2888a55d-d686-4736-bad0-54b70462afda/- |
| [2] | Arias, P. A., Ortega, G., Villegas, L. D., Martínez, J. A., Arias, P. A., Ortega, G., Villegas, L. D., & Martínez, J. A. (2021). Colombian climatology in CMIP5/CMIP6 models: Persistent biases and improvements. Revista Facultad de Ingeniería Universidad de Antioquia, 100, 75–96. https://doi.org/10.17533/UDEA.REDIN.20210525 |
| [3] | Bangladesh - Climatology | Climate Change Knowledge Portal. (n. d.). Retrieved March 16, 2022, from https://climateknowledgeportal.worldbank.org/country/bangladesh/climate-data-historical |
| [4] | Bangladesh Geography - Banglapedia. (n. d.). Retrieved March 16, 2022, from https://en.banglapedia.org/index.php?title=Bangladesh_Geography |
| [5] | Download Data | Climate Change Knowledge Portal. (n. d.). Retrieved March 16, 2022, from https://climateknowledgeportal.worldbank.org/download-data |
| [6] | Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., & Taylor, K. E. (2016). Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geoscientific Model Development, 9(5), 1937–1958. https://doi.org/10.5194/GMD-9-1937-2016 |
| [7] | Flato: Climate change 2013: the physical science... - Google Scholar. (n. d.). Retrieved March 20, 2022, from https://scholar.google.com/scholar_lookup?title=Climate change 2013%3A the physical science basis. Contribution of working group i to the fifth assessment report of the intergovernmental panel on climate change&author=G. Flato&publication_year=2013#d=gs_cit&u=%2Fscholar%3Fq%3Dinfo%3AxRUqyWumvvkJ%3Ascholar.google.com%2F%26output%3Dcite%26scirp%3D0%26hl%3Den |
| [8] | Gebresellase, S. H., Wu, Z., Xu, H., Wada, I. M., & Muhammad, W. I. (2022a). Evaluation of CMIP6 Climate Models for Climate Change Impact Assessments in Upper Awash Basin, Ethiopia. https://doi.org/10.21203/RS.3.RS-1231424/V1 |
| [9] | Gebresellase, S. H., Wu, Z., Xu, H., Wada, I. M., & Muhammad, W. I. (2022b). Evaluation of CMIP6 Climate Models for Climate Change Impact Assessments in Upper Awash Basin, Ethiopia. https://doi.org/10.21203/RS.3.RS-1231424/V1 |
| [10] | Hamed, M. M., Nashwan, M. S., & Shahid, S. (2021). Performance evaluation of reanalysis precipitation products in Egypt using fuzzy entropy time series similarity analysis. International Journal of Climatology, 41 (11), 5431–5446. https://doi.org/10.1002/JOC.7286 |
| [11] | Hamed, M. M., Nashwan, M. S., Shahid, S., Ismail, T. bin, Wang, X. jun, Dewan, A., & Asaduzzaman, M. (2022). Inconsistency in historical simulations and future projections of temperature and rainfall: A comparison of CMIP5 and CMIP6 models over Southeast Asia. Atmospheric Research, 265, 105927. https://doi.org/10.1016/J.ATMOSRES.2021.105927 |
| [12] | Malamos, N., & Koutsoyiannis, D. (2016). Bilinear surface smoothing for spatial interpolation with optional incorporation of an explanatory variable. Part 2: Application to synthesized and rainfall data. Https://Doi.Org/10.1080/02626667.2015.1080826, 61 (3), 527–540. https://doi.org/10.1080/02626667.2015.1080826 |
| [13] | Moss, R. H., Edmonds, J. A., Hibbard, K. A., Manning, M. R., Rose, S. K., Van Vuuren, D. P., Carter, T. R., Emori, S., Kainuma, M., Kram, T., Meehl, G. A., Mitchell, J. F. B., Nakicenovic, N., Riahi, K., Smith, S. J., Stouffer, R. J., Thomson, A. M., Weyant, J. P., & Wilbanks, T. J. (2010). The next generation of scenarios for climate change research and assessment. Nature 2010 463: 7282, 463 (7282), 747–756. https://doi.org/10.1038/nature08823 |
| [14] | O’Neill, B. C., Tebaldi, C., Van Vuuren, D. P., Eyring, V., Friedlingstein, P., Hurtt, G., Knutti, R., Kriegler, E., Lamarque, J. F., Lowe, J., Meehl, G. A., Moss, R., Riahi, K., & Sanderson, B. M. (2016). The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6. Geoscientific Model Development, 9 (9), 3461–3482. https://doi.org/10.5194/GMD-9-3461-2016 |
| [15] | Online Free Calculators. (n. d.). Retrieved March 21, 2022, from https://agrimetsoft.com/calculators/ |
| [16] | Project Management Service. (n. d.). Retrieved March 16, 2022, from https://code.mpimet.mpg.de/ |
| [17] | Shahriar, S. A., Siddique, M. A. M., & Rahman, S. M. A. (2021). Climate change projection using statistical downscaling model over Chittagong Division, Bangladesh. Meteorology and Atmospheric Physics, 133 (4), 1409–1427. https://doi.org/10.1007/S00703-021-00817-X |
APA Style
Razimul Karim, Syed Arman Akib Rahman, Champa Rani Saha, Mostafizur Rahman, Shakil Ahmed, et al. (2023). Mathematical Downscaling of Temperature and Rainfall from the Future Projected Dataset Based on CMIP6 Model: A Case Study of Bangladesh Regarding Climate Change. Earth Sciences, 12(5), 140-158. https://doi.org/10.11648/j.earth.20231205.13
ACS Style
Razimul Karim; Syed Arman Akib Rahman; Champa Rani Saha; Mostafizur Rahman; Shakil Ahmed, et al. Mathematical Downscaling of Temperature and Rainfall from the Future Projected Dataset Based on CMIP6 Model: A Case Study of Bangladesh Regarding Climate Change. Earth Sci. 2023, 12(5), 140-158. doi: 10.11648/j.earth.20231205.13
AMA Style
Razimul Karim, Syed Arman Akib Rahman, Champa Rani Saha, Mostafizur Rahman, Shakil Ahmed, et al. Mathematical Downscaling of Temperature and Rainfall from the Future Projected Dataset Based on CMIP6 Model: A Case Study of Bangladesh Regarding Climate Change. Earth Sci. 2023;12(5):140-158. doi: 10.11648/j.earth.20231205.13
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Download@article{10.11648/j.earth.20231205.13,
author = {Razimul Karim and Syed Arman Akib Rahman and Champa Rani Saha and Mostafizur Rahman and Shakil Ahmed and Mahiba Musharrat},
title = {Mathematical Downscaling of Temperature and Rainfall from the Future Projected Dataset Based on CMIP6 Model: A Case Study of Bangladesh Regarding Climate Change},
journal = {Earth Sciences},
volume = {12},
number = {5},
pages = {140-158},
doi = {10.11648/j.earth.20231205.13},
url = {https://doi.org/10.11648/j.earth.20231205.13},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.earth.20231205.13},
abstract = {The objective of this research is to assess the mathematical downscaling of the union-wise administrative area of Bangladesh that simulations and future projections of rainfall and mean temperature of CMIP6 (SSP2–4.5 and 5–8.5). Models were used to determine uncertainty with spatiotemporal variability of rainfall and mean temperature projections. Model data NETCDF file has been converted to Raster with cell size of 1, 1 decimal degree which means that each cell contains 100 km x 100 km area coverage. After preparing the dataset of 0.01, 0.01 decimal degree cell size (1km x1km), the dataset of Bangladesh has been extracted union-wise by the Bilinear resampling technique. An average value has been generated from the multiple values belonging to the specific union. After that, the dataset of Bangladesh has been generated. Mathematical downscaling and bias correction are made for the selected 16 model runs. The CMIP6 models for the model and observed values of rainfall show Kling-Gupta Efficiency (KGE) values in a range of 0.58-0.72 and for mean temperature in a range of 0.85- 0.90. The CMIP6 models show Pearson's correlation coefficient (R) in the range of 0.83-0.90 for rainfall and in a range of 0.86-0.93 for mean temperature. Also, CMIP6 models showed Nash Sutcliffe in the range of 0.06-0.78 for rainfall and 0.73-0.89 for mean temperature from the model and observed value. The projected change of future rainfall and mean temperature in the study increases the rainfall intensities due to the increment of temperature.},
year = {2023}
}
TY - JOUR T1 - Mathematical Downscaling of Temperature and Rainfall from the Future Projected Dataset Based on CMIP6 Model: A Case Study of Bangladesh Regarding Climate Change AU - Razimul Karim AU - Syed Arman Akib Rahman AU - Champa Rani Saha AU - Mostafizur Rahman AU - Shakil Ahmed AU - Mahiba Musharrat Y1 - 2023/09/27 PY - 2023 N1 - https://doi.org/10.11648/j.earth.20231205.13 DO - 10.11648/j.earth.20231205.13 T2 - Earth Sciences JF - Earth Sciences JO - Earth Sciences SP - 140 EP - 158 PB - Science Publishing Group SN - 2328-5982 UR - https://doi.org/10.11648/j.earth.20231205.13 AB - The objective of this research is to assess the mathematical downscaling of the union-wise administrative area of Bangladesh that simulations and future projections of rainfall and mean temperature of CMIP6 (SSP2–4.5 and 5–8.5). Models were used to determine uncertainty with spatiotemporal variability of rainfall and mean temperature projections. Model data NETCDF file has been converted to Raster with cell size of 1, 1 decimal degree which means that each cell contains 100 km x 100 km area coverage. After preparing the dataset of 0.01, 0.01 decimal degree cell size (1km x1km), the dataset of Bangladesh has been extracted union-wise by the Bilinear resampling technique. An average value has been generated from the multiple values belonging to the specific union. After that, the dataset of Bangladesh has been generated. Mathematical downscaling and bias correction are made for the selected 16 model runs. The CMIP6 models for the model and observed values of rainfall show Kling-Gupta Efficiency (KGE) values in a range of 0.58-0.72 and for mean temperature in a range of 0.85- 0.90. The CMIP6 models show Pearson's correlation coefficient (R) in the range of 0.83-0.90 for rainfall and in a range of 0.86-0.93 for mean temperature. Also, CMIP6 models showed Nash Sutcliffe in the range of 0.06-0.78 for rainfall and 0.73-0.89 for mean temperature from the model and observed value. The projected change of future rainfall and mean temperature in the study increases the rainfall intensities due to the increment of temperature. VL - 12 IS - 5 ER -
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