Evaluation and projection of mean surface temperature using CMIP6 models over East Africa

Ayugi, Brian; Ngoma, Hamida; Babaousmail, Hassen; Karim, Rizwan; Iyakaremye, Vedaste; Sian, Kenny Thiam Choy Lim Kam; Ongoma, Victor

doi:10.1016/j.jafrearsci.2021.104226

Cited by 51 publications

(27 citation statements)

References 123 publications

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“…Projected changes in PRCPTOT and CWD signifying an increase in mean seasonal precipitation and more wet days will likely be of great benefit to the various sectors that support the economy of the region (Figures 2 and 3). For instance, the projected decline in PRCPTOT over southern parts of Tanzania under SSP2-4.5 scenario will have catastrophic impact on the ecosystem and the livelihoods of people who continue to face the impact of abrupt declines in seasonal precipitation leading to drought episodes since 1990s [32,34,45,46,76]. Meanwhile, R95 p shows large uncertainties over the study area during MAM season as compared to other indices, with larger interquartile model spread exhibited (Figure 4).…”

Section: Discussionmentioning

confidence: 96%

“…For instance, many sub-regions have experienced notable changes in precipitation over the recent decades [4,21,26]. Similarly, positive trajectories in temperature have been observed and are projected to increase significantly across the continent [20,[27][28][29][30][31][32]. This will affect the broader population's livelihoods that mainly rely on rainfed agriculture [33].…”

Section: Introductionmentioning

confidence: 99%

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Future Changes in Precipitation Extremes over East Africa Based on CMIP6 Models

Ayugi

Dike

Ngoma

et al. 2021

Water

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This paper presents an analysis of projected precipitation extremes over the East African region. The study employs six indices defined by the Expert Team on Climate Change Detection Indices to evaluate extreme precipitation. Observed datasets and Coupled Model Intercomparison Project Phase six (CMIP6) simulations are employed to assess the changes during the two main rainfall seasons: March to May (MAM) and October to December (OND). The results show an increase in consecutive dry days (CDD) and decrease in consecutive wet days (CWD) towards the end of the 21st century (2081–2100) relative to the baseline period (1995–2014) in both seasons. Moreover, simple daily intensity (SDII), very wet days (R95 p), very heavy precipitation >20 mm (R20 mm), and total wet-day precipitation (PRCPTOT) demonstrate significant changes during OND compared to the MAM season. The spatial variation for extreme incidences shows likely intensification over Uganda and most parts of Kenya, while a reduction is observed over the Tanzania region. The increase in projected extremes may pose a serious threat to the sustainability of societal infrastructure and ecosystem wellbeing. The results from these analyses present an opportunity to understand the emergence of extreme events and the capability of model outputs from CMIP6 in estimating the projected changes. More studies are recommended to examine the underlying physical features modulating the occurrence of extreme incidences projected for relevant policies.

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Section: Discussionmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Future Changes in Precipitation Extremes over East Africa Based on CMIP6 Models

Ayugi

Dike

Ngoma

et al. 2021

Water

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“…Studies, e.g., [35][36][37], have shown that climate change will still affect the socioeconomic development of less developed countries due to their dependence on climatic conditions even under low emission scenarios. Researchers have also indicated that East Africa has experienced a reduction in Interannual rainfall variability and a quick rise in surface air temperature (SAT), which may further intensify the drought conditions over the region [38,39]. A recent study [40] indicates that rainfall highly fluctuates in the short rainy season during October to November (OND) than the long rainy season of March to May (MAM).…”

Section: Introductionmentioning

confidence: 99%

Observed Changes in Meteorological Drought Events during 1981–2020 over Rwanda, East Africa

Uwimbabazi

Jing²,

Iyakaremye

et al. 2022

Sustainability

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Drought is one of the most complex natural phenomena affecting the life and livelihood of people, especially in the current time of human-induced climate change. This research employs ground-based observations to assess the recent spatiotemporal characteristics of meteorological drought events over Rwanda. The drought is examined based on the Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Precipitation Index (SPI) at seasonal and annual time scales from 1981 to 2020. The Man–Kendal test was used to evaluate the trends in rainfall, temperature, and SPEI values at the annual scale and during the March to May (MAM) and October to December (OND) seasons. The analysis revealed nonsignificant trends in annual (8.4 mm/decade), MAM (−3.4 mm/decade), and OND (4.5 mm/decade) rainfall, while an apparent significant increasing trend in surface air temperature was obtained during the MAM (0.19 °C/decade), OND (0.2 °C/decade), and annual (0.23 °C/decade) time slices. Overall, the SPEI characteristics indicated that the country is more prone to moderate drought events than severe and extreme drought events during MAM and OND seasons. However, the intensity, duration, and frequency differ spatially among seasons. The findings of this study inform policy and decision-makers on the past experienced drought behavior, which can serve as a baseline for future drought mitigation and adaptation plans.

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“…In recent years, the research on GCMs has made great progress, and the coupled model intercomparison project has been developed to the sixth stage (CMIP6) (Kim et al 2020;Xu et al 2021). The CMIP6 adds special test designs that are closer to actual physical and biogeochemical processes from the perspective of how to assess future climate change (Ayugi et al 2021;Srivastava et al 2020;Yazdandoost et al 2021). Therefore, the CMIP6 can carry out more numerical experiments according to the new numerical experiment design scheme, thereby continuing to improve the resolution of the models (Mondal et al 2021;Rivera and Arnould 2020;Shafeeque and Luo 2021).…”

Section: Introductionmentioning

confidence: 99%

“…The Hanjiang River Basin (HRB) is located in the climate transition zone between China's north and south, and it is more sensitive and susceptible to climate change (Mohanty and Simonovic 2021;Yazdandoost et al 2021;Zhu and Yang 2020). The analysis of the changes in the spatio-temporal distribution characteristics of water resources in the HRB under future climate change is conducive to coping with the uncertain challenges brought by climate change (Ayugi et al 2021;Mondal et al 2021). Affected by the rapid economic and social development, the demand for water resources in the HRB has grown rapidly (Rivera and Arnould 2020;Shafeeque and Luo 2021;Wang et al 2021).…”

Section: Introductionmentioning

confidence: 99%

Spatio-temporal changes of precipitation in the Hanjiang River Basin under climate change

Jin

Chen

Zhong

et al. 2021

Theor Appl Climatol

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The Hanjiang River is the source of water for the Middle Route of the South-to-North Water Diversion Project. So a reasonable evaluation on water resources future changes in the Hanjiang River Basin (HRB) is essential to ensure its water safety. In this study, we firstly evaluated the China meteorological forcing dataset (CMFD), and then used it to measure the applicability of the eight global climate models (GCMs). Finally, the empirical orthogonal function (EOF) and clustering algorithms were used to analyze the spatial distribution status of precipitation in the HRB. The results showed that the BCC-CSM2-MR model has the best effect, followed by the IPSL-CM6A-LR model. In the SSP126, SSP245, SSP370, and SSP585 scenarios, total precipitation in the HRB all shows an increasing trend. However, the difference in the spatial distribution of precipitation intensified, for the upstream and downstream tended to be wetter, while the middle reaches had less precipitation. In the future climate scenarios, the areas with more precipitation (Class 1) increased significantly, while the areas with medium precipitation (Class 3) decreased significantly, which will enlarge the precipitation difference between regions in the HRB. The increase in the total amount of precipitation, coupled with the increase in the spatial heterogeneity of precipitation, will make the HRB more vulnerable to flooding disasters. Therefore, the water resources management measures in the HRB should be strengthened in the future.

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Evaluation and projection of mean surface temperature using CMIP6 models over East Africa

Cited by 51 publications

References 123 publications

Future Changes in Precipitation Extremes over East Africa Based on CMIP6 Models

Future Changes in Precipitation Extremes over East Africa Based on CMIP6 Models

Observed Changes in Meteorological Drought Events during 1981–2020 over Rwanda, East Africa

Spatio-temporal changes of precipitation in the Hanjiang River Basin under climate change

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