Assessment of climate change impact on temperature extremes in a tropical region with the climate projections from CMIP6 model

Das, Samiran; Islam, Abu Reza Md. Towfiqul; Kamruzzaman, Mohammad

doi:10.1007/s00382-022-06416-9

Cited by 16 publications

(10 citation statements)

References 67 publications

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“…A study [ 63 ] found that the average T max and daily average temperature were increased by 1.16°C and 0.47°C, respectively, but the average T min has been decreased by 0.40°C from 1988–2017, which is consistent with our study. Another two studies [ 4 , 64 ] observed similar findings in Bangladesh.…”

Section: Discussionsupporting

confidence: 60%

“…For most scenarios, the global surface temperature will likely increase to 1.5°C and exceed 2.0°C in several scenarios by the end of the 21 st century [ 5 ]. There is strong evidence that rainfall pattern variations have occurred on regional [ 4 ] and global [ 6 ] scales due to global warming. Therefore, understanding climatic trends and long-term changes on the regional and local scales is essential for sustainable agronomic strategies, climate change adaptation, and disaster management planning in Bangladesh.…”

Section: Introductionmentioning

confidence: 99%

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Climate change in Bangladesh: Temperature and rainfall climatology of Bangladesh for 1949–2013 and its implication on rice yield

Alam,

Hridoy,

Tusher

et al. 2023

PLoS ONE

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Bangladesh has been ranked as one of the world’s top countries affected by climate change, particularly in terms of agricultural crop sector. The purpose of this study is to identify spatial and temporal changes and trends in long-term climate at local and national scales, as well as their implications for rice yield. In this study, Modified Mann-Kendall and Sen’s slope tests were used to detect significant trends and the magnitude of changes in temperature and rainfall. The temperature and rainfall data observed and recorded at 35 meteorological stations in Bangladesh over 65-years in the time span between the years 1949 and 2013 have been used to detect these changes and trends of variation. The results show that mean annual Tmean, Tmin, and Tmax have increased significantly by 0.13°C, 0.13°C, and 0.13°C/decade, respectively. The most significant increasing trend in seasonal temperatures for the respective Tmean, Tmin, and Tmax was 0.18°C per decade (post-monsoon), 0.18°C/decade (winter), and 0.23°C/decade (post-monsoon), respectively. Furthermore, the mean annual and pre-monsoon rainfall showed a significant increasing trend at a rate of 4.20 mm and 1.35 mm/year, respectively. This paper also evaluates climate variability impacts on three major rice crops, Aus, Aman, and Boro during 1970–2013. The results suggest that crop yield variability can be explained by climate variability during Aus, Aman, and Boro seasons by 33, 25, and 16%, respectively. Maximum temperature significantly affected the Aus and Aman crop yield, whereas rainfall significantly affected all rice crops’ yield. This study sheds light on sustainable agriculture in the context of climate change, which all relevant authorities should investigate in order to examine climate-resilient, high-yield crop cultivation.

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Section: Discussionsupporting

confidence: 60%

Section: Introductionmentioning

confidence: 99%

Climate change in Bangladesh: Temperature and rainfall climatology of Bangladesh for 1949–2013 and its implication on rice yield

Alam,

Hridoy,

Tusher

et al. 2023

PLoS ONE

Self Cite

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“…However, they still cannot fully describe many regional climate dynamics because of their coarser resolution (Ali et al, 2021;Wang et al, 2021). Downscaling strategies, which can retrieve higher resolution data from coarse resolution datasets, are crucial for addressing this difficulty for regional or local scale climate modeling (Kamruzzaman et al, 2019b;Kamruzzaman et al, 2021a;Kamruzzaman et al, 2021b;Das et al, 2022a;Das et al, 2022b). Statistical Downscaling (SD) and Dynamic Downscaling (DD) are the two main approaches used for climate downscaling.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal changes in temperature projections over Bangladesh using multi-model ensemble data

Islam

Kamruzzaman

Shahid

et al. 2023

Front. Environ. Sci.

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Temperature rise is a concern for future agriculture in different regions of the globe. This study aimed to reveal the future changes and variabilities in minimum temperature (Tmin) and maximum temperature (Tmax) in the monthly, seasonal, and annual scale over Bangladesh using 40 General Circulation Models (GCMs) of Coupled Model Intercomparison Project Phase 5 (CMIP5) for two radiative concentration pathways (RCPs, RCP4.5 and RCP8.5). The statistical downscaling climate model (SimCLIM) was used for downscaling and to ensemble temperature projections (Tmax and Tmin) for the near (2021–2060) and far (2071–2100) periods compared to the base period (1986–2005). Multi-model ensemble (MME) exhibited increasing Tmax and Tmin for all the timescales for all future periods and RCPs. Sen’s slope (SS) analysis showed the highest increase in Tmax and Tmin in February and relatively less increase in July and August. The mean annual Tmax over Bangladesh would increase by 0.61°C and 1.75°C in the near future and 0.91°C and 3.85°C in the far future, while the mean annual Tmin would rise by 0.65°C and 1.85°C in the near future and 0.96°C and 4.07°C in the far future, for RCP4.5 and RCP8.5, respectively. The northern and northwestern parts of the country would experience the highest rise in Tmax and Tmin, which have traditionally been exposed to temperature extremes. In contrast, the southeastern coastal region would experience the least rise in temperature. A higher increase in Tmin than Tmax was detected for all timescales, signifying a future decrease in the diurnal temperature range (DTR). The highest increase in Tmax and Tmin will be in winter compared to other seasons for both the periods and RCPs. The spatial variability of Tmax and Tmin changes can be useful for the long-term planning of the country.

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“…Collazo et al 18 considered CMIP6 models' ability to represent observed extreme temperatures and concluded that the chosen models could not simulate cold days trends. Das et al 19 assessed the impact of climate change on temperature extremes and projected a substantial rise in temperature extremes. Wei et al 20 evaluated 23 CMIP6 models' ability to simulate extreme climate events over China and stated that considerable uncertainties remain in future climate projections.…”

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

The trend and spatial spread of multisectoral climate extremes in CMIP6 models

Adeyeri

Zhou

Wang

et al. 2022

Sci Rep

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Climate change could exacerbate extreme climate events. This study investigated the global and continental representations of fourteen multisectoral climate indices during the historical (1979–2014), near future (2025–2060) and far future (2065–2100) periods under two emission scenarios, in eleven Coupled Model Intercomparison Project (CMIP) General Circulation Models (GCM). We ranked the GCMs based on five metrics centred on their temporal and spatial performances. Most models followed the reference pattern during the historical period. MPI-ESM ranked best in replicating the daily precipitation intensity (DPI) in Africa, while CANESM5 GCM ranked first in heatwave index (HI), maximum consecutive dry days (MCCD). Across the different continents, MPI-LR GCM performed best in replicating the DPI, except in Africa. The model ranks could provide valuable information when selecting appropriate GCM ensembles when focusing on climate extremes. A global evaluation of the multi-index causal effects for the various indices shows that the dry spell total length (DSTL) was the most crucial index modulating the MCCD for all continents. Also, most indices exhibited a positive climate change signal from the historical to the future. Therefore, it is crucial to design appropriate strategies to strengthen resilience to extreme climatic events while mitigating greenhouse gas emissions.

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Assessment of climate change impact on temperature extremes in a tropical region with the climate projections from CMIP6 model

Cited by 16 publications

References 67 publications

Climate change in Bangladesh: Temperature and rainfall climatology of Bangladesh for 1949–2013 and its implication on rice yield

Climate change in Bangladesh: Temperature and rainfall climatology of Bangladesh for 1949–2013 and its implication on rice yield

Spatiotemporal changes in temperature projections over Bangladesh using multi-model ensemble data

The trend and spatial spread of multisectoral climate extremes in CMIP6 models

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