Long-term rainfall projection based on CMIP6 scenarios for Kurau River Basin of rice-growing irrigation scheme, Malaysia

Adib, Muhammad Nasir Mohd; Harun, Sobri; Rowshon, M. K.

doi:10.1007/s42452-022-04952-x

Cited by 12 publications

(3 citation statements)

References 40 publications

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“…Climate change scenarios of CMIP6 were also studied in various regions; for example, duration of rainy season was found to be extended for the monsoon domains over India, Indochina peninsula, and Southern Africa under SSP5-8.5 for the long-term period [19]. The increasing trend of rainfall during wet season also was indicated in Malaysia and the long-term period showed significantly higher compared to the nearterm [20].…”

Section: Discussionmentioning

confidence: 99%

Future rainfall characteristics under AR6 climate change scenarios, case study of Pasak River basin, Thailand

Sittichok

2022

21st International Scientific Conference Engineering for Rural Development Proceedings

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Thailand is located in Southeast Asia where it is indicated as highly vulnerable to climate change. This country will likely be one of the countries that have experienced negative impacts of climate change. To reduce the impact of climate change on drought and flood, a water management plan under climate change needs to be prepared. The changes of future rainfalls under climate change emission scenarios play an important role and need to be investigated. This study aims to describe projected rainfall characteristics under AR6 climate change scenarios. Rainfalls generated from 10 GCMs were downscaled to a basin scale at the Pasak River Basin using the quantile mapping method. After the downscaling process simulated precipitation significantly improved in both magnitude and volume compared to the observed data using the Nash-Sutcliff coefficient and volume error methods. Slight differences between downscaled and observed precipitation were found with acceptable results using the coefficient of determination. Variabilities of future precipitation under four scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) of each model were revealed. Annual average of projected rainfalls was slightly different between the models, but large variation compared to others could be found in INM-CM5. The standardized anomaly index was then calculated for historical and two future periods: the near-term (2015-2050) and the long-term (2051-2100), and the frequencies of wet and dry incidents were presented. Very-extremely wet and dry years often occurred in 2051-2100 under SSP2-4.5 and SSP1-2.6 respectively. Finally, the increments in annual rainfalls were obviously seen in SSP2-4.5, SSP3-7.0 and SSP5-8.5 for the near-term and in all scenarios of the long-term. Slight decreasing trend was only found in the near-term under SSP1-2.6.

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Section: Discussionmentioning

confidence: 99%

Future rainfall characteristics under AR6 climate change scenarios, case study of Pasak River basin, Thailand

Sittichok

2022

21st International Scientific Conference Engineering for Rural Development Proceedings

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“…Various studies selected the SSPs for their analysis [22,[55][56][57]. Oshiro et al [22] considered the socio-economic conditions by considering the SSP2 scenario for attaining the net-zero emissions pathway by 2050 in Japan.…”

Section: Carbon Prices Without Ccs In the Ct Scenariomentioning

confidence: 99%

“…Pradhan et al [55] analyzed the emission reduction target with the carbon price profiles under SSP5 during 2015-2050. Adib et al [57] assessed the future rainfall pattern considering climate change in Malaysia in the SSP1-2.6, the SSP2-4.5, and the SSP5-8.5 scenarios during 2021-2080.…”

Section: Carbon Prices Without Ccs In the Ct Scenariomentioning

confidence: 99%

Thailand’s mid-century greenhouse gas emission pathways to achieve the 2 degrees Celsius target

et al. 2022

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Background The Paris Agreement aims at minimizing threats of climate change by keeping global temperature rise well below 2 degrees Celsius above the pre-industrial level and to pursue efforts to limit the rise to 1.5 degrees Celsius. The Representative Concentration Pathways (RCPs) are developed to investigate GHG emission pathways. RCP2.6 focuses on limiting the global temperature rise to less than 2 degrees Celsius. This paper assesses the impacts of carbon price and CCS on energy and GHG emissions in Thailand. The no carbon price (T0) and the carbon price pathways are compared. In addition, the net-zero emissions and year are discussed. Results The decarbonized energy system with low-carbon power generation and increased electricity usage in the final energy consumption is the main pillar of GHG mitigation. Imposing carbon prices; increasing solar, wind, and biomass electricity generation; energy efficiency improvements in power generation; and energy savings in the industry and the building sectors, will be the key options for clean power generation in the carbon prices (CT) scenarios. Renewable electricity, coal and natural gas, coupled with CCS and bio-energy with CCS (BECCS) will be utilized significantly to curb GHG emissions. The increase of renewable energy and the electrification of end-use plays a key role in reducing GHG emissions. Fuel switching from diesel to biodiesel, energy efficiency improvement and electric pick-ups and trucks will help reducing GHG emissions in the transport sector. Conclusions There are three major policy implications to meet Thailand’s 2 degrees Celsius target. First, carbon prices will be the mechanism to accelerate the transformation in the energy sector. Wind and solar electricity will be key pillars of clean electricity in 2050. Policy-makers should update the renewable electricity plans to meet Thailand’s 2 degrees Celsius target in 2050. Second, coal- and gas-fired plants, and BECCS will become important options in reducing CO2 emissions. The policy-makers should investigate the application of CCS in the power sector and the storage location. Third, a major transformation in the transport sector is critically needed. Liquid biofuel and electrification in pick-ups, sedans, and trucks will help reduce GHG emissions.

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Using quantile mapping and random forest for bias‐correction of high‐resolution reanalysis precipitation data and CMIP6 climate projections over Iran

Raeesi,

Zolfaghari,

Kaboli

et al. 2024

Intl Journal of Climatology

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Climate change is expected to cause important changes in precipitation patterns in Iran until the end of 21st century. This study aims at evaluating projections of climate change over Iran by using five climate model outputs (including ACCESS‐ESM1‐5, BCC‐CSM2‐MR, CanESM5, CMCC‐ESM2 and MRI‐ESM2‐0) of the Coupled Model Intercomparison Project phase 6 (CMIP6), and performing bias‐correction using a novel combination of quantile mapping (QM) and random forest (RF) between the years 2015 and 2100 under three shared socioeconomics pathways (SSP2‐4.5, SSP3‐7.0 and SSP5‐8.5). First, bias‐correction was performed on ERA5‐Land reanalysis data as reference period (1990–2020) using the QM method, then the corrected ERA5‐Land reanalysis data was considered as measured data. Based on the corrected ERA5‐Land reanalysis data (1990–2020) and historical simulations (1990–2014), the future projections (2015–2100) were also bias‐corrected utilizing the QM method. Next, the accuracy of the QM method was validated by comparing the corrected ERA5‐Land reanalysis data with model outputs for overlapping years between 2015 and 2020. This comparison revealed persistent biases; hence, a combination of QM‐RF method was applied to rectify future climate projections until the end of the 21st century. Based on the QM result, CMCC‐ESM2 revealed the highest RMSE in both SSP2‐4.5 and SSP3‐7.0 amounting to 331.74 and 201.84 mm·year−1, respectively. Particularly, the exclusive use of the QM method displayed substantial errors in projecting annual precipitation based on SSP5‐8.5, notably in the case of ACCESS‐ESM1‐5 (RMSE = 431.39 mm·year−1), while the RMSE reduced after using QM‐RF method (197.75 mm·year−1). Obviously, a significant enhancement in results was observed upon implementing the QM‐RF combination method in CMCC‐ESM2 under both SSP2‐4.5 (RMSE = 139.30 mm·year−1) and SSP3‐7.0 (RMSE = 151.43 mm·year−1) showcasing approximately reduction in RMSE values by 192.43 and 50.41 mm·year−1, respectively. Although each bias‐corrected model output was evaluated individually, multi‐model ensemble (MME) was also created to project the annual future precipitation pattern in Iran. By considering that combination of QM‐RF method revealed the lower errors in correcting model outputs, we used the QM‐RF technique to create the MME. Based on SSP2‐4.5, the MME climate projections highlight imminent precipitation reductions (>10%) across large regions of Iran, conversely projecting increases ranging from 10% to over 20% in southern areas under SSP3‐7.0. Moreover, MME projected dramatic declines under SSP5‐8.5, especially impacting central, eastern, and northwest Iran. Notably, the most pronounced possibly decline patterns are projected for arid regions (central plateau) and eastern areas under SSP2‐4.5, SSP3‐7.0 and SSP5‐8.5.

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Long-term rainfall projection based on CMIP6 scenarios for Kurau River Basin of rice-growing irrigation scheme, Malaysia

Cited by 12 publications

References 40 publications

Future rainfall characteristics under AR6 climate change scenarios, case study of Pasak River basin, Thailand

Future rainfall characteristics under AR6 climate change scenarios, case study of Pasak River basin, Thailand

Thailand’s mid-century greenhouse gas emission pathways to achieve the 2 degrees Celsius target

Using quantile mapping and random forest for bias‐correction of high‐resolution reanalysis precipitation data and CMIP6 climate projections over Iran

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