Comparison of CMIP6 and CMIP5 model performance in simulating historical precipitation and temperature in Bangladesh: a preliminary study

Kamruzzaman, Mohammad; Shahid, Shamsuddin; Islam, Abu Reza Md. Towfiqul; Hwang, Syewoon; Cho, Jaepil; Zaman, Md. Asad Uz; Ahmed, Muzahed Uddin; Rahman, Md. Mizanur; Hossain, Md. Belal

doi:10.1007/s00704-021-03691-0

Cited by 70 publications

(24 citation statements)

References 78 publications

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“…The HighResMIP GCMs showed a better capability in capturing temperature than precipitation over the JRB, and similar findings have been reported in other CMIP6 models [65]. The low-resolution models were unable to capture the seasonal precipitation cycle over the JRB accurately compared to the moderate-and high-resolution models.…”

Section: Discussionsupporting

confidence: 82%

Resolution Dependence of Regional Hydro-Climatic Projection: A Case-Study for the Johor River Basin, Malaysia

Tan

Liang

Hawcroft

et al. 2021

Water

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High resolution models from the High-Resolution Model Intercomparison Project (HighResMIP), part of CMIP6, have the capacity to allow a better representation of the climate system in tropical regions, but how different model resolutions affect hydrological outputs remains unclear. This research aims to evaluate projections of hydro-climatic change of the Johor River Basin (JRB) in southern Peninsular Malaysia between 1985 to 2015 and 2021 to 2050, focusing on uncertainty quantification of hydrological outputs from low (>1°), medium (0.5° to 1°) and high (≤0.5°) horizontal resolution models. These projections show future increases in annual precipitation of 0.4 to 3.1%, minimum and maximum temperature increases of 0.8 to 0.9 °C and 0.9 to 1.1 °C, respectively. These projected climate changes lead to increases in annual mean streamflow of 0.9% to 7.0% and surface runoff of 7.0% to 20.6% in the JRB. These annual mean changes are consistent with those during the wet period (November to December), e.g., streamflow increases of 4.9% to 10.8% and surface runoff of 28.8 to 39.9% in December. Disagreement in the direction of change is found during the dry seasons, (February to March and May to September), where high resolution models project a decrease in future monthly precipitation and streamflow, whilst increases are projected by the medium- and low-resolution models.

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Section: Discussionsupporting

confidence: 82%

Resolution Dependence of Regional Hydro-Climatic Projection: A Case-Study for the Johor River Basin, Malaysia

Tan

Liang

Hawcroft

et al. 2021

Water

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“…Nevertheless, SD is utilized more commonly and extensively since it is easier to execute and less expensive in general (Rashid et al, 2015;Ali et al, 2021). GCM simulations are always associated with uncertainties because of the model structure, initial assumption, and future scenarios (Kamruzzaman et al, 2021;Katzenberger et al, 2021;Song et al, 2021). Different strategies have been proposed to address the uncertainties in climate projections.…”

mentioning

confidence: 99%

Future precipitation projection in Bangladesh using SimCLIM climate model: A multi‐model ensemble approach

Islam

Shahid

et al. 2022

Intl Journal of Climatology

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Appraisal of the long-term precipitation trends and variability is crucial for sustainable water resources management. This research intended to evaluate Bangladesh's monthly, seasonal, and annual spatiotemporal rainfall variability using 40 global climate models for two representative concentration pathways (RCPs), RCP4.5 and RCP8.5. Statistical downscaling climate model (SimCLIM) was used for downscaling and ensemble projection of rainfall in near (2011-2040), middle (2041-2070), and far (2071-2100) futures. Modified Mann-Kendall test was applied to detect future rainfall trends. The results revealed a significant increasing trend in rainfall in near and middle futures for RCP4.5 and in all three future periods for RCP8.5 at all meteorological stations of Bangladesh during significant rainfall months (May-October). The results also showed a decreasing trend in rainfall in dry months (December-January) at many stations. The highest increase in rainfall was projected in June at a rate of 0.10-1.11 mmÁyear −1 for RCP4.5 and 3.34-4.98 mmÁyear −1 for RCP8.5 in different future periods. Monsoon rainfall showed the highest increase, and winter rainfall the lowest increase for all RCPs and future periods. The increase in annual precipitation over Bangladesh was projected 2.76-5.98% in three future periods for RCP4.5 and 6.98-26.

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“…al. 2014; Shahid et al, 2016; Islam et al, 2020a; Jerin et al 2021;Kamruzzaman et al 2021). Besides, the results also reveal different climatic in uences on rice yield to show the strong regional variations of rice yields in northwest Bangladesh.Rice yields for several rice varieties showed a distinct regional pattern, with the Aus yield being more favorable in Dinajpur and Rajshahi regions than other regions.…”

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confidence: 85%

Variability of climate-induced rice yields in northwest Bangladesh using multiple statistical modeling

Islam

Nabila

Hasanuzzaman

et al. 2022

Theor Appl Climatol

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Because of evident climatic variations and signi cant contribution to national food production, Bangladesh is a climate extreme hotspot region of examination for climatic consequences for rice (Oryza Sativa) crop production. This study intends to explore the variability of climatic variables (e.g., variations in mean temperature, rainfall, relative humidity, and sunshine duration) with rice yields (e.g., Aus, Aman, and Boro rice varieties) in northwest Bangladesh. The modi ed Mann-Kendall test, Theil-Sen slope estimator, and multiple linear regression (MLR) modeling were used to estimate the association among these factors. Heteroskedasticity and autocorrelation constant standard error (HAC) and feasible generalized least square (FGLS) technique were adopted to measure the climate-rice crop nexus using the regional level dataset for 1976-2015. Furthermore, the spatiotemporal variation of rice yield trends with climatic variables was mapped and assessed by the coe cient of variation. The results show that observed temperature and humidity trends were bene cial for Aus and Aman yields but not Boro yields. In contrast, observed rainfall and sunshine trends were negative for all three rice seasons. The outcomes of the MLR model explained 67%, 92%, and 83% of the variability in Aus, Aman, and Boro rice yields in the study region. The model outcomes showed that humidity and rainfall have negatively affected Aus and Aman rice crops, while temperature and rainfall positively in uence Boro rice yield. Regarding the climate change issues and safeguarding food safety at the regional level, the concerned authorities should provide substantial attention to improving heat and drought-tolerance high-yielding varieties against climate effects on Aus and Aman rice varieties.

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Comparison of CMIP6 and CMIP5 model performance in simulating historical precipitation and temperature in Bangladesh: a preliminary study

Cited by 70 publications

References 78 publications

Resolution Dependence of Regional Hydro-Climatic Projection: A Case-Study for the Johor River Basin, Malaysia

Resolution Dependence of Regional Hydro-Climatic Projection: A Case-Study for the Johor River Basin, Malaysia

Future precipitation projection in Bangladesh using SimCLIM climate model: A multi‐model ensemble approach

Variability of climate-induced rice yields in northwest Bangladesh using multiple statistical modeling

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