Heat Extremes in Bangladesh | Climate Projection

Dry-bulb temperature

Click on the map grid to view detailed data.

Visualizations:

Model and Methods

To identify the near-term-future risks of heat stress, MIT Regional Climate Model (MRCM) is applied at a 10-km grid spacing. The dynamical core of the MRCM originates from ICTP Regional Climate Model version 3 (Pal et al., 2007). The most pronounced feature of the model is its coupling with the Integrated Biosphere Simulator, enabling better representation of land surface processes (Winter et al., 2009). Additionally, significant improvements in model physics are included in the MRCM (Gianotti, 2012; Gianotti & Eltahir, 2014a, 2014b; Marcella, 2012; Marcella & Eltahir, 2012).

The latest version of the MRCM has demonstrated remarkable robustness in capturing regional climate features across diverse geographical domains, ranging from North America and West Africa to South Asia and the Maritime Continent (Winter et al., 2009; Im et al., 2014, 2017, 2018; Pal & Eltahir, 2016; Choi et al., 2021).

To specify boundary conditions in constraining MRCM simulations, a small set of CMIP5 and CMIP6 Global Climate Models (GCMs) were carefully selected through a rigorous screening process. The selection process heavily relied on GCM's performance in simulating key climate features over Bangladesh, including mean climate and climate trends. High-resolution regional climate information was then produced for the most climate-vulnerable country, Bangladesh, over the 76 years (1975-2050), forced by 3 CMIP5 (ACCESS 1.0, CCSM4, MPI-ESM-MR) and 3 CMIP6 (EC-Earth3, HadGEM3-GC31-MM, UKESM1-0-LL) GCMs under different climate-change scenarios. To account for the impact of landfalling tropical cyclones, larger model domain was considered, covering Bangladesh, the North Indian Ocean, and the Bay of Bengal. The horizontal resolution is 10 km in both longitudinal and latitudinal directions. The reliability of climate projections is enhanced by removing systematic biases in MRCM outputs using Parametric Quantile Mapping method.

References

Choi, Y.-W., Campbell, D. J., Aldridge, J. C., & Eltahir, E. A. B. (2021). Near-term regional climate change over Bangladesh. Climate Dynamics, 57(11-12), 3055-3073. https://doi.org/10.1007/s00382-021-05856-z

Gianotti, R. L. (2012). Regional climate modeling over the Maritime Continent: Convective cloud and rainfall processes, PhD dissertation. Massachusetts Institute of Technology.

Gianotti, R. L., & Eltahir, E. A. B. (2014a). Regional climate modeling over the Maritime continent. Part I: New parameterization for convective cloud fraction. Journal of Climate, 27(4), 1488-1503. https://doi.org/10.1175/JCLI-D-13-00127.1

Gianotti, R. L., & Eltahir, E. A. B. (2014b). Regional climate modeling over the Maritime continent. Part II: New parameterization for autoconversion of convective rainfall. Journal of Climate, 27(4), 1504-1523. https://doi.org/10.1175/JCLI-D-13-00171.1

Im, E.-S., Gianotti, R. L., & Eltahir, E. A. B. (2014). Improving the simulation of the West African Monsoon using the MIT regional climate model. Journal of Climate, 27(6), 2209-2229. https://doi.org/10.1175/JCLI-D-13-00188.1

Im, E.-S., Pal, J. S., & Eltahir, E. A. B. (2017). Deadly heat waves projected in the densely populated agricultural regions of South Asia. Science Advances, 3(8), e1603322. https://doi.org/10.1126/sciadv.1603322

Im, E. S., Kang, S., & Eltahir, E. A. B. (2018). Projections of rising heat stress over the western Maritime Continent from dynamically downscaled climate simulations. Global and Planetary Change, 165, 160-172. https://doi.org/10.1016/j.gloplacha.2018.02.014

Marcella, M. P. (2012). Biosphere-atmosphere interactions over semi-arid regions: Modeling the role of mineral aerosols and irrigation in the regional climate system, PhD dissertation. Massachusetts Institute of Technology.

Marcella, M. P., & Eltahir, E. A. B. (2012). Modeling the summertime climate of southwest Asia: The role of land surface processes in shaping the climate of semiarid regions. Journal of Climate, 25(2), 704-719. https://doi.org/10.1175/2011JCLI4080.1

Pal, J. S., & Eltahir, E. A. B. (2016). Future temperature in southwest Asia projected to exceed a threshold for human adaptability. Nature Climate Change, 6(2), 197-200. https://doi.org/10.1038/nclimate2833

Pal, J. S., Giorgi, F., Bi, X., Elguindi, N., Solmon, F., Gao, X., et al. (2007). Regional climate modeling for the developing world: The ICTP RegCM3 and RegCNET. Bulletin of the American Meteorological Society, 88(9), 1395-1410. https://doi.org/10.1175/bams-88-9-1395

Winter, J. M., Pal, J. S., & Eltahir, E. A. B. (2009). Coupling of integrated biosphere simulator to regional climate model version 3. Journal of Climate, 22(10), 2743-2757. https://doi.org/10.1175/2008JCLI2541.1

Other Information

This interactive web application has been developed to inform proactive climate change adaptation strategies for infrastructure development, disaster preparedness, resource management, and agricultural practice in the southwestern Bangladesh.

Research Team

Prof. Elfatih Eltahir (eltahir@mit.edu) (MIT)
Dr. Yeon-Woo Choi (choiyw@mit.edu) (MIT)
Xin Qiu (xqiu@arcadiafunds.com) (Arcadia Funds)

2021