Spatiotemporal Changes in Temperature and Precipitation in West Africa. Part I: Analysis with the CMIP6 Historical Dataset

Quenum, Gandome Mayeul L. D.; Nkrumah, Francis; Klutse, Nana Ama Browne; Sylla, Mouhamadou Bamba

doi:10.3390/w13243506

Cited by 25 publications

(14 citation statements)

References 101 publications

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“…Over the entire African continent, Iyakaremye et al [115] state the increased number of warm nights in most parts of Africa, while Moberg et al [116] report increased warming for the European territory. In furtherance to this, the results revealed a significant decrease in TN10p throughout the study locations and for the entire zone, which agrees with the earlier research studies, such as [25,26,87,117,118]. The IPCC [1], in its fifth assessment report, underlines a decrease in cool nights in many land regions, which is consistent with this study.…”

Section: Discussionsupporting

confidence: 92%

Extreme Temperature and Rainfall Events and Future Climate Change Projections in the Coastal Savannah Agroecological Zone of Ghana

2023

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The global climate has changed, and there are concerns about the effects on both humans and the environment, necessitating more research for improved adaptation. In this study, we analyzed extreme temperature and rainfall events and projected future climate change scenarios for the coastal Savannah agroecological zone (CSAZ) of Ghana. We utilized the ETCCDI, the RClimDex software (version 1.0), the Mann–Kendall test, Sen’s slope estimator, and standardized anomalies to analyze homogeneity, trends, magnitude, and seasonal variations in temperature (Tmax and Tmin) and rainfall datasets for the zone. The SDSM was also used to downscale future climate change scenarios based on the CanESM2 (RCP 2.6, 4.5, and 8.5 scenarios) and HadCM3 (A2 and B2 scenarios) models for the zone. Model performance was evaluated using statistical methods such as R2, RMSE, and PBIAS. Results revealed more changepoints in Tmin than in Tmax and rainfall. Results again showed that the CSAZ has warmed over the last four decades. The SU25, TXn, and TN90p have increased significantly in the zone, and the opposite is the case for the TN10p and DTR. Spatially varied trends were observed for the TXx, TNx, TNn, TX10p, TX90p, and the CSDI across the zone. The decrease in RX1day, RX5day, SDII, R10, R95p, and R99p was significant in most parts of the central region compared to the Greater Accra and Volta regions, while the CDD significantly decreased in the latter two regions than in the former. The trends in CWD and PRCPTOT were insignificant throughout the zone. The overall performance of both models during calibration and validation was good and ranged from 58–99%, 0.01–1.02 °C, and 0.42–11.79 °C for R2, RMSE, and PBIAS, respectively. Tmax is expected to be the highest (1.6 °C) and lowest (−1.6 °C) across the three regions, as well as the highest (1.5 °C) and lowest (−1.6 °C) for the entire zone, according to both models. Tmin is projected to be the highest (1.4 °C) and lowest (−2.1 °C) across the three regions, as well as the highest (1.4 °C) and lowest (−2.3 °C) for the entire zone. The greatest (1.6 ℃) change in mean annual Tmax is expected to occur in the 2080s under RCP8.5, while that of the Tmin (3.2 ℃) is expected to occur in the 2050s under the same scenario. Monthly rainfall is expected to change between −98.4 and 247.7% across the three regions and −29.0 and 148.0% for the entire zone under all scenarios. The lowest (0.8%) and highest (79%) changes in mean annual rainfall are expected to occur in the 2030s and 2080s. The findings of this study could be helpful for the development of appropriate adaptation plans to safeguard the livelihoods of people in the zone.

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Section: Discussionsupporting

confidence: 92%

Extreme Temperature and Rainfall Events and Future Climate Change Projections in the Coastal Savannah Agroecological Zone of Ghana

2023

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“…Furthermore, their probability distribution functions clearly show a shift of the mean towards greater intensity values. This confirms previous studies that pointed to a significant increase in the intensity of extreme rainfall events [27,28]. In fact, global warming should lead to the intensification of the hydrological cycle [62,63].…”

Section: Discussionsupporting

confidence: 91%

“…Hence, the challenges related to the frequency and intensity of HRE in the Sahel are of vital importance for agriculture, energy, and human security, especially in the context of the upsurge in flood phenomena. Results were obtained for intense rainfall events, which indicate a significant increase in the intensity of extreme rainfall events [27,28]. Other results in the Philippines predicted that relative increases in annual maximum daily precipitation from the past to the year 2100 will be approximately 8.5% in the SSP2-4.5, 11.6% in the SSP3-7.0, and 17% in the SSP5-8.5 scenarios, respectively [29].…”

Section: Introductionmentioning

confidence: 84%

Present and Future of Heavy Rain Events in the Sahel and West Africa

Saley

Salack²

2023

Atmosphere

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Gridding precipitation datasets for climate information services in the semi-arid regions of West Africa has some advantages due to the limited spatial coverage of rain gauges, the limited accessibility to in situ gauge data, and the important progress in earth observation and climate modelling systems. Can accurate information on the occurrence of heavy precipitation in this area be provided using gridded datasets? Furthermore, what about the future of heavy rain events (HRE) under the shared socioeconomic pathways (SSP) of the Inter-Sectoral Impact Model Intercomparison Project (i.e., SSP126 and SSP370)? To address these questions, daily precipitation records from 17 datasets, including satellite estimates, interpolated rain gauge data, reanalysis, merged products, a regional climate model, and global circulation models, are examined and compared to quality-controlled in situ data from 69 rain gauges evenly distributed across West Africa’s semi-arid region. The results show a consensus increase in the occurrence of HRE, between observational and gridded data. All datasets showed three categories of HRE every season, but these categories had lower intensities and an overstated frequency of occurrence in gridded datasets compared to in situ rain gauge data. Eight out of 17 databases (~47%) show significant positive trends and only one showed a significant negative trend, indicating an increase in HRE for all categories in this region. The future evolution of HRE considered under the shared socioeconomic pathways SSP1-2.6 and SSP3-7.0, showed a trend toward the intensification of these events. In fact, the mean of the ensemble of the models showed significant changes toward higher values in the probability distribution function of the future HRE in West Africa, which may likely trigger more floods and landslides in the region. The use of gridded data sets can provide accurate information on the occurrence of heavy precipitation in the West African Sahel. However, it is important to consider the representation of heavy rain events in each data set when monitoring extreme precipitation, although in situ gauge records are preferred to define extreme rainfall locally.

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“…The Climatic Research Unit gridded time series (CRU TS) was used because of the lack of ground-based data. It was used by previous studies and presented satisfactory responses with respect to observational datasets [47,48]. The monthly precipitation from 1979 to 2019 was collected for each commune/prefecture.…”

Section: Climate and Hydrological Datamentioning

confidence: 99%

Comparing households’ perception of flood hazard with historical climate and hydrological data in the Lower Mono River catchment (West Africa), Benin and Togo

et al. 2023

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The comparison of local perception of flood hazards, with hydrological and climate parameters, can give more insight and understanding on the causes of flood, its impacts and the strategies to effectively address the problem. This study examines whether households’ perception of rainfall and flood occurrence are consistent with observed variation in climate parameter (rainfall) and hydrological (discharge) data in the Lower Mono River catchment (Togo-Benin, West Africa). Perceptions of the 744 households from the catchment were collected and compared to historical climatic and hydrological data using correlation analysis. The Standardized Precipitation Index was utilized to identify the extreme years in terms of precipitation. Chi-test and binary regression analyses were performed to identify the most affected communes within the catchment, and the factors that influence household perceptions on rainfall change, respectively. Findings reveal that 85% of the respondents perceived an excess in rainfall during the last 20 years and identify two particular years as the most affected by flood, which correspond to the climate data analysis. Households’ perceptions on flooded months are correlated with the monthly precipitation and discharge at the upper part of the catchment while the ones at down part are not correlated. Furthermore, the chi-test analysis shows that in the perception of households, the communes at the down part are more affected by flood than those at the upper part of the catchment. It is then important for decision maker to consider local communities’ perception for having insight regarding climate parameters, the causes of flood and in the decision making for implementing measures to cope with this phenomenon.

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Spatiotemporal Changes in Temperature and Precipitation in West Africa. Part I: Analysis with the CMIP6 Historical Dataset

Cited by 25 publications

References 101 publications

Extreme Temperature and Rainfall Events and Future Climate Change Projections in the Coastal Savannah Agroecological Zone of Ghana

Extreme Temperature and Rainfall Events and Future Climate Change Projections in the Coastal Savannah Agroecological Zone of Ghana

Present and Future of Heavy Rain Events in the Sahel and West Africa

Comparing households’ perception of flood hazard with historical climate and hydrological data in the Lower Mono River catchment (West Africa), Benin and Togo

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