Browsing by Author "Klutse, N.A.B."

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Assessing uncertainties in the regional projections of precipitation in CORDEX-AFRICA
(Climatic Change, 2020) Bichet, A.; Diedhiou, A.; Hingray, B.; Evin, G.; Touré, N.E.; Klutse, N.A.B.; Kouadio, K.
Over the past decades, large variations of precipitation were observed in Africa, which often led to dramatic consequences for local society and economy. To avoid such disasters in the future, it is crucial to better anticipate the expected changes, especially in the current context of climate change and population growth. To this date, however, projections of precipitation over Africa are still associated with very large uncertainties. To better understand how this uncertainty can be reduced, this study uses an advanced Bayesian analysis of variance (ANOVA) method to characterize, for the first time in the regional climate projections of CORDEX-AFRICA, the different sources of uncertainty associated with the projections of precipitation over Africa. By 2090, the ensemble mean precipitation is projected to increase over the Horn of Africa from September to May and over the eastern Sahel and Guinea Coast from June to November. It is projected to decrease over the northern coast and southern Africa all year long, over western Sahel from March to August, and over the Sahel and Guinea Coast from March to May. Most of these projections however are not robust, i.e., the magnitude of change is smaller than the associated uncertainty. Over time, the relative contribution of internal variability (excluding interannual variability) to total uncertainty is moderate and quickly falls below 10%. By 2090, it is found that over the Horn of Africa, northern coast, southern Africa, and Sahel, most of the uncertainty results from a large dispersion across the driving Global Climate Models (in particular MIROC, CSIRO, CCCma, and IPSL), whereas over the tropics and parts of eastern Africa, most of the uncertainty results from a large dispersion across Regional Climate Models (in particular CLMcom).
Assessment of Patterns of Climate Variables and Malaria Cases in Two Ecological Zones of Ghana
(Open Journal of Ecology, 2014) Klutse, N.A.B.; Aboagye-Antwi, F.; Owusu, K.; Ntiamoa-Baidu, Y.
Climate change is projected to impact human health, particularly incidence of water related and vector borne diseases, such as malaria. A better understanding of the relationship between rainfall patterns and malaria cases is thus required for effective climate change adaptation strategies involving planning and implementation of appropriate disease control interventions. We analyzed climatic data and reported cases of malaria spanning a period of eight years (2001 to 2008) from two ecological zones in Ghana (Ejura and Winneba in the transition and coastal savannah zones respectively) to determine the association between malaria cases, and temperature and rainfall patterns and the potential effects of climate change on malaria epidemiological trends. Monthly peaks of malaria caseloads lagged behind monthly rainfall peaks. Correlation between malaria caseloads and rainfall intensity, and minimum temperature were generally weak at both sites. Lag correlations of up to four months yielded better agreement between the variables, especially at Ejura where a two-month lag between malaria caseloads and rainfall was significantly high but negatively correlated (r = −0.72; p value < 0.05). Mean monthly maximum temperature and monthly malaria caseloads at Ejura showed a strong negative correlation at zero month lag (r = −0.70, p value < 0.05), with a similar, but weaker relationship at Winneba, (r = −0.51). On the other hand, a positive significant correlation (r = 0.68, p value < 0.05) between malaria caseloads and maximum temperature was observed for Ejura at a four-month lag, while Winneba showed a strong correlation (r = 0.70; p value < 0.05) between the parameters at a two-month lag. The results suggest maximum temperature as a better predictor of malaria trends than minimum temperature or precipitation, particularly in the transition zone. Climate change effects on malaria caseloads seem multi-factorial. For effective malaria control, interventions could be synchronized
Bias-corrected NASA data for aridity index estimation over tropical climates in Ghana, West Africa
(Journal of Hydrology:Regional Studies, 2024) Asilevi, P.J.; Klutse, N.A.B.; Amekudzi, L.K.; et al.
Study region: Ghana, West Africa. Study focus: NASA’s Prediction of Worldwide Energy Resource (NASA POWER) satellite-based reanalysis products are used for estimating the aridity index (AI) in Ghana, West Africa. The NASA estimates are compared and bias-corrected with temperature-based potential evapotrans piration estimates and rainfall data from 22 synoptic climate stations. The cumulative distribution function (CDF) matching technique was used for bias correction New Hydrological Insights for the region: The results indicated a previous 36% over-estimation of arid conditions in dryland climates and an under-estimation of wetland climate regions by the NASA POWER data compared with the station-based estimation. Post bias-correction, the satellite-based estimates showed substantial improvements, as evidenced by a correlation coef ficient of R2 = 0.87. The rectified data suggests that with accurate interpretations and calibra tions, satellite-based metrics can play a pivotal role in advancing hydrological studies and water resource management in West Africa Sub-region. This insight underscores the potential of satellite data in augmenting regional hydrological research, establishing a foundation for similar studies in analogous global environments.
A change comparison of heat wave aspects in climatic zones of Nigeria.
(Environmental Earth Sciences, 2019) Ragatoa, D.S.; Ogunjobi, K.O.; Klutse, N.A.B.; Okhimamhe, A.A.; Eichie, J.O.
Studies have shown an increase in the frequency and severity of heat waves during the last decades under climate change. This study employs four temperature-based definitions, the percentile based TN90th—the 90th percentile of minimum temperature, and TX90th—the 90th percentile of maximum temperature, the Excess Heat Factor (EHF) and the Heat Wave Magnitude Index daily (HWMId), to investigate the present occurrence of heat waves (1981–2016) in five climatic zones of Nigeria. ERA-INTERIM reanalysis daily minimum and maximum temperature data were retrieved from ECMWF database for the purpose. Five characteristics were studied, the heat wave number, duration, frequency, amplitude and the magnitude. The study of heat wave characteristics in different climatic zones revealed that, from 1981 to 2016, heat waves occurred and covered more zones in the last decades. The first heat wave definitions (TN90, TX90 and EHF) revealed almost the same pattern of heat wave number (HWN) in Nigeria from 1981 to 2016 showing that of 1983, 1987, 1997, 2006 and 2007 where the latter had the highest number of events. The general coverage of the number of events increased from 1999. The Sahel was seriously affected by the highest number of events and the highest number of days for the duration and the frequency. The HWMId was used to quantify and compare the intensity of heat waves in the present time and revealed super extreme heat waves (HWMId>32) in the Sahel and extreme heat waves in the south
Changes in Rainfall Characteristics in Wenchi and Saltpond Farming Areas of Ghana.
(International Journal of Geosciences, 2017-03) Quagraine, K.A.; Klutse, N.A.B.; Nkrumah, F.; Adukpo, D.C.; Owusu, K.
Ghana’s economy heavily relies on agriculture, which is predominantly rainfed across its agro-ecological zones. As a result of this, it is vulnerable to rainfall variability, which tends to have a major impact on the industrial and agricultural production sectors of the country. This study investigates the variations occurring across two major farming areas (Wenchi and Saltpond) within the Transition and Coastal Savannah agro-ecological zones of Ghana respectively. Rainfall variations are studied with rainfall data from 1968-2011 from Ghana Meteorological Agency (GMet). The rainfall analysis is done over two Climatological Periods (CP), 1968-1989 as CP1 and 1990-2011 as CP2. This study uses two climatic extreme indices as well as rainfall amounts and onset over these two agro-ecological zones to investigate the changes that have occurred in rainfall. The study found that in the Coastal agro-ecological zone, CP1 had a decreasing rainfall trend as compared to CP2 with higher variations in Saltpond. In the Transition agro-ecological zone, Wenchi, CP1 also exhibited a decreasing trend as compared to CP2. In addition, onset of rains in Saltpond mostly occurred in May for CP1 but for CP2, it oscillated between April and May. For Wenchi, onset of rains was in March for CP1 and predominantly April for CP2. In going forward, farmers in these agro-ecological zones should be supported to practice effective adaptation and mitigation measures so as to improve their yields in this challenging climate.
Climate Change Issues: where we have come from and where we are going
(2020-02-18) Klutse, N.A.B.
The earth is warming at a steady pace and is having a devastating impact on the earth’s climate. Climate change is mostly natural. However, clear evidence exists that the rate of the occurrence of the changes we are experiencing in the climate and the intensity of the impacts are closely related to human activity. We understand the reason for this is the increase in human-caused greenhouse gases causing more warming of the earth's climate. How much have humans contributed to the greenhouse gases and what is the contribution of humans to climate change is still a global discussion. The presentation will focus on what climate change is, where we have come from and where we are going with the level of human influence. A debate on whether climate change mitigation is a moral or political issue will also be opened.
The Climatic Analysis of Summer Monsoon Extreme Precipitation Events over West Africa in CMIP6 Simulations
(Springer, 2021) Klutse, N.A.B.; Quagraine, K.A.; Nkrumah, F.; Quagraine, K.T.; Berkoh‑Oforiwaa, R.; Dzrobi, J.F.; Sylla, M.B.
We evaluate the capability of 21 models from the new state-of-the-art Coupled Model Intercomparison Project, Phase 6 (CMIP6) in the representation of present-day precipitation characteristics and extremes along with their statistics in simulating daily precipitation during the West African Monsoon (WAM) period (June–September). The study uses a set of standard extreme precipitation indices as defined by the Expert Team on Climate Change Detection and Indices constructed using CMIP6 models and observational datasets for comparison. Three observations; Global Precipitation Climatology Project (GPCP), Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), and Tropical Applications of Meteorology using SATellite and ground-based observation (TAMSAT) datasets are used for the validation of the model simulations. The results show that observed datasets present nearly the same spatial pattern but discrepancies in the magnitude of rainfall characteristics. The models show substantial discrepancies in comparison with the observations and among themselves. A number of the models depict the pattern of rainfall intensity as observed but some models overestimate the pattern over the coastal parts (FGOALS-f3-L and GFDL-ESM4) and western part (FGOALS-f3-L) of West Africa. All model simulations explicitly show the pattern of wet days but with large discrepancies in their frequencies. On extreme rainfall, half of the models express more intense extremes in the 95th percentiles while the other half simulate less intense extremes. All the models overestimate the mean maximum wet spell length except FGOALS-f3-L. The spatial patterns of the mean maximum dry spell length show a good general agreement across the different models, and the observations except for four models that show an overestimation in the Sahara subregion. INM-CM4-8 and INM-CM5-0 display smaller discrepancies from their long-term average rainfall characteristics, in terms of extreme rainfall estimates than the other CMIP6 datasets. For the frequency of heavy rainfall, TaiESM1 and IPSL-CMGA-LR perform better when compared with observational datasets. MIROC6 and GFDL-ESM4 displayed the largest error in representing the frequency of heavy rainfall and 95th percentile extremes, and therefore, cannot be reliable. The study has assessed how rainfall extremes are captured in both observation and the models. Though there are some discrepancies, it gives room for improvement of the models in the next version of CMIP.
Daily characteristics of West African summer monsoon precipitation in CORDEX simulations
(Springer-Verlag Wien, 2016) Klutse, N.A.B.; Sylla, M.B.; Diallo, I.; Sarr, A.; Dosio, A.; Diedhiou, A.; Kamga, A.; Lamptey, B.; Ali, A.; Owusu, K.; Lennard, C.; Hewitson, B.; Nikulin, G.; Paintsil, H.-J.; Buchner, M.; Gbobaniyi, E.O.
We analyze and intercompare the performance of a set of ten regional climate models (RCMs) along with the ensemble mean of their statistics in simulating daily precipitation characteristics during the West African monsoon (WAM) period (June–July–August–September). The experiments are conducted within the framework of the COordinated Regional Downscaling Experiments for the African domain. We find that the RCMs exhibit substantial differences that are associated with a wide range of estimates of higher-order statistics, such as intensity, frequency, and daily extremes mostly driven by the convective scheme employed. For instance, a number of the RCMs simulate a similar number of wet days compared to observations but greater rainfall intensity, especially in oceanic regions adjacent to the Guinea Highlands because of a larger number of heavy precipitation events. Other models exhibit a higher wet-day frequency but much lower rainfall intensity over West Africa due to the occurrence of less frequent heavy rainfall events. This indicates the existence of large uncertainties related to the simulation of daily rainfall characteristics by the RCMs. The ensemble mean of the indices substantially improves the RCMs’ simulated frequency and intensity of precipitation events, moderately outperforms that of the 95th percentile, and provides mixed benefits for the dry and wet spells. Although the ensemble mean improved results cannot be generalized, such an approach produces encouraging results and can help, to some extent, to improve the robustness of the response of the WAM daily precipitation to the anthropogenic greenhouse gas warming. © 2015, Springer-Verlag Wien.
Development in astronomy and space science in Africa
(Macmillan Publishers Limited, 2018) Pović, M.; Backes, M.; Baki, P.; Baratoux, D.; Tessema, S.B.; Benkhaldoun, Z.; Bode, M.; Klutse, N.A.B.; et al.
The development of astronomy and space science in Africa has grown significantly over the past few years. These advancements make the United Nations Sustainable Development Goals more achievable, and open up the possibility of new beneficial collaborations.
Identification of Potential Drought Areas in West Africa Under Climate Change and Variability
(Earth Systems and Environment, 2019-10-30) Klutse, N.A.B.; Quenum, G.M.L.D.; Dieng, D.; Laux, P.; Arnault, J.; Kodja, J.D.; Oguntunde, P.G.
The study investigates how the rising global temperature will affect the spatial pattern of rainfall and consequently drought in West Africa. The precipitation and potential evapotranspiration variables that are obtained from the Rossby Centre regional atmospheric model (RCA4) and driven by ten (10) global climate models under the RCP8.5 scenario were used. The model data were obtained from the Coordinated Regional Climate Downscaling Experiment (CORDEX) and analyzed at four specific global warming levels (GWLs) (i.e., 1.5 °C, 2.0 °C, 2.5 °C, and 3.0 °C) above the pre-industrial level. This study utilized four (4) indices: the standardized precipitation index, the precipitation concentration index, the precipitation concentration degree, and the precipitation concentration period over West Africa to explore the spatiotemporal variations in the characteristics of precipitation concentrations. Additionally, studying the impact of the four GWLs on consecutive dry days, consecutive wet days, and frequency of the intense rainfall events led to a better understanding of the spatiotemporal pattern of extreme precipitation. The results show that, at each GWL studied, the onset of rainfall comes 1 month earlier in the Gulf of Guinea compared to the historical period (1971–2000) with increasing rainfall intensity in the whole study domain, and the northeastern part of the study area becomes wetter. The rainfall concentration is uniformly distributed over the Gulf of Guinea and the Savanna zone for both the historical period and RCP8.5 scenario, while the Sahel zone which has shown an irregular concentration of rainfall for the historical period shows a uniform concentration of rainfall under all four GWLs.
Long-Term Study on Medium-Scale Traveling Ionospheric Disturbances Observed over the South American Equatorial Region
(Atmosphere, 2021) Essien, P.; Figueiredo, C.AO.B.; Takahashi, H.; Wrasse, C.M.; Barros, D.; Klutse, N.A.B.; Lomotey, S.O.; Ayorinde, T.T.; Gobbi, D.; Bilibio, A.V.
Using data collected by the GNSS dual-frequency receivers network, de-trended TEC maps were generated to identify and characterize the medium-scale traveling ionospheric disturbances (MSTIDs) over the South American equatorial region (latitude: 0 ◦ to 15◦ S and longitude: 30◦ to 55◦ W) during solar cycle 24 (from January 2014 to December 2019). A total of 712 MSTIDs were observed during quiet geomagnetic conditions. The Frequency of occurrence of MSTID is high during the solar maximum and low in the minimum phase. This might be due to the solar cycle dependence of gravity wave activity in the lower atmosphere and gravity wave propagation conditions in the thermosphere. The predominant daytime MSTIDs, representing 80% of the total observations, occurred in winter (June-August season in the southern hemisphere) with the secondary peak in the equinox; while the evening time MSTIDs, representing 18% of the entire events, occurred in summer (December to February season) and equinox (March to May and September to November), and the remaining 2% of the MSTIDs were observed during nighttime. The seasonal variation of the MSTID events was attributed to the source mechanisms generating them, the wind filtering and dissipation effects, and the local time dependency. The horizontal wavelengths of the MSTIDs were mostly concentrated between 500 and 800 km, with the mean value of 667 ± 131 km. The observed periods ranged from 30 to 45 min with the mean value of 36 ± 7 min. The observed horizontal phase speeds were distributed around 200 to 400 m/s, with the corresponding mean of 301 ± 75 m/s. The MSTIDs in the winter solstice and equinoctial months preferentially propagated northeastward and northwestward. Meanwhile, during the summer solstice, they propagated in all directions. The anisotropy of the propagation direction might be due to several reasons: the wind and dissipative filtering effects, ion drag effects, the primary source region, and the presence of the secondary or tertiary gravity waves in the thermosphere. Atmospheric gravity waves from strong convective sources might be the primary precursor for the observed equatorial MSTIDs. In all seasons, we noted that the MSTIDs propagating southeastward were probably excited by the likely gravity waves generated by the intertropical convergence zone (ITCZ).
Mapping Evapotranspiration of Agricultural Areas in Ghana
(Hindawi, 2021) Aidoo, K.; Klutse, N.A.B.; Asare, K.; Botchway, C.G.; Fosuhene, S.
Climate change is having an adverse effect on the environment especially in sub-Sahara Africa, where capacity for natural resource management such as water is very low. 'e scope of the effect on land use types have to be estimated to inform proper remedy. A combined estimation of transpiration and evaporation from plants and soil is critical to determine annual water requirement for different land use. Evapotranspiration (ET) is a major component in the world hydrological cycle, and understanding its spatial dimensions is critical in evaluating the effects it has on regional land use. A measure of this component is challenging due to variation in rainfall and environmental changes. 'e mapping evapotranspiration with high resolution and internalized cali bration (METRIC) method is employed to create evapotranspiration map for land use, using remotely sensed data by satellite, processed, and analyzed in ArcGIS. Normalized difference vegetation index (NDVI) was related to the availability of water for vegetation on different land use, and the results indicate a high evapotranspiration for vegetated land use with high NDVI than land use with low NDVI.
Mapping Evapotranspiration of Agricultural Areas in Ghana
(The Scientific World Journal, 2021) Aidoo, K.; Klutse, N.A.B.; Asare, K.; Botchway, C.G.; Fosuhene, S.
Climate change is having an adverse effect on the environment especially in sub-Sahara Africa, where capacity for natural resource management such as water is very low. 'e scope of the effect on land use types have to be estimated to inform proper remedy. A combined estimation of transpiration and evaporation from plants and soil is critical to determine annual water requirement for different land use. Evapotranspiration (ET) is a major component in the world hydrological cycle, and understanding its spatial dimensions is critical in evaluating the effects it has on regional land use. A measure of this component is challenging due to variation in rainfall and environmental changes. 'e mapping evapotranspiration with high resolution and internalized calibration (METRIC) method is employed to create evapotranspiration map for land use, using remotely sensed data by satellite, processed, and analyzed in ArcGIS. Normalized difference vegetation index (NDVI) was related to the availability of water for vegetation on different land use, and the results indicate a high evapotranspiration for vegetated land use with high NDVI than land use with low NDVI.
Modeling the spatial distribution of Global Solar Radiation (GSR) over Ghana using the ̊Angström-Prescott sunshine duration model
(Scientific African, 2019) Asilevi, P.J.; Quansah, E.; Amekudzi, L.K.; Annor, T.; Klutse, N.A.B.
Solar radiation is an important geological and meteorological parameter. In most developing countries, data is readily unavailable owing to lack of instrumentation and skilled personnel. In this study, Global solar radiation (GSR) over Ghana has been quantified using the Angström–Prescott ˚ sunshine model with sunshine duration data from 22 synoptic stations distributed across the country’s ecological zones. The simulated data was gridded at 10 km by 10 km, establishing the spatial distribution of solar radiation over the country. Comparison with satellite data showed good results with root mean square error (RMSE) values of 1–5 MJm−2day−1 and correlation coefficient of 60 - 66%. Meanwhile, the esti mated total GSR over the country was found to be 412.82 MJm−2day−1. The savanna zone had the maximum estimated total monthly mean GSR for the year, with the highest value of 20.76 MJm−2day−1 in Navrongo. The forest zone had the minimum estimated total annual mean GSR, with the lowest radiation level in Oda (17.11 MJm−2day−1). A maximum and minimum mean clearness index of 0.59 and 0.48 respectively are estimated, implying that about 53% of solar radiation at the top of the atmosphere reaches the study area after attenuation. The satellite data has a total monthly mean horizontal Global Solar irradiance of 366.62 MJm−2day−1. The study shows that the region is a potential field to harness and optimize solar energy for the operation of photovoltaic systems and solar collectors for industrial and domestic applications
Modeling the spatial distribution of Global Solar Radiation (GSR) over Ghana using the ˚Angström-Prescott sunshine duration model
(Scientific African, 2019-05-21) Klutse, N.A.B.; Asilevi, P.J.; Quansah, E.; Amekudzi, L.K.; Annor, T.
Solar radiation is an important geological and meteorological parameter. In most devel- oping countries, data is readily unavailable owing to lack of instrumentation and skilled personnel. In this study, Global solar radiation (GSR) over Ghana has been quantified us- ing the ˚Angström–Prescott sunshine model with sunshine duration data from 22 synoptic stations distributed across the country’s ecological zones. The simulated data was gridded at 10 km by 10 km, establishing the spatial distribution of solar radiation over the country. Comparison with satellite data showed good results with root mean square error (RMSE) values of 1–5 MJm −2 day −1 and correlation coefficient of 60 - 66%. Meanwhile, the esti- mated total GSR over the country was found to be 412.82 MJm −2 day −1 . The savanna zone had the maximum estimated total monthly mean GSR for the year, with the highest value of 20.76 MJm −2 day −1 in Navrongo. The forest zone had the minimum estimated total an- nual mean GSR, with the lowest radiation level in Oda (17.11 MJm −2 day −1 ). A maximum and minimum mean clearness index of 0.59 and 0.48 respectively are estimated, implying that about 53% of solar radiation at the top of the atmosphere reaches the study area after attenuation. The satellite data has a total monthly mean horizontal Global Solar irradiance of 366.62 MJm −2 day −1 . The study shows that the region is a potential field to harness and optimize solar energy for the operation of photovoltaic systems and solar collectors for industrial and domestic applications.
Modelling Cloud Cover Climatology over Tropical Climates in Ghana
(Atmosphere, 2022) Dogbey, F.; Asilevi, P.J.; Dzrobi, J.F.; Koffi, H.A.; Klutse, N.A.B.
Clouds play a crucial role in Earth’s climate system by modulating radiation fluxes via reflection and scattering, and thus the slightest variation in their spatial coverage significantly alters the climate response. Until now, due to the sparse distribution of advanced observation stations, large uncertainties in cloud climatology remain for many regions. Therefore, this paper estimates total cloud cover (TCC) by using sunshine duration measured in different tropical climates in Ghana. We used regression tests for each climate zone, coupled with bias correction by cumulative distribution function (CDF) matching, to develop the estimated TCC dataset from nonlinear empirical equations. It was found that the estimated percentage TCC, 20.8–84.7 3.5%, compared well with stationobserved TCC, 21.9–84.4 3.5%, with root mean square errors of 1.08–9.13 1.8% and correlation coefficients of 0.87–0.99 0.03. Overall, spatiotemporal characteristics were preserved, establishing that denser clouds tended to prevail mostly over the southern half of the forest-type climate during the June–September period. Moreover, the model and the observations show a non-normality, indicating a prevalence of above-average TCC over the study area. The results are useful for weather prediction and application in meteorology.
Nature of climate change-induced risks in semi-arid northwestern Ghana: Gauged observations, perceptions of smallholder farmers, and perspectives for livelihood adaptation
(Information Development, 2023) Lente, I.; Heve, W.K.; Owusu-Twum, M.Y.; Gordon, C.; Opoku, P.; Nukpezah, D.; Klutse, N.A.B.
Climate variability and impact have been an endemic challenge to smallholder farmers who largely depend on rainy weather for livelihoods in semi-arid north-western Ghana. Many households in semi arid regions exhibit low levels of adaptive capacity due to ineffective adaptation strategies and poor cop ing strategies. This study examined (1) trends in gauged rainfall and temperature data spanning the per iod from 1984 to 2014 and (2) smallholder farmers’ perceptions about yearly cyclical weather, and difficulties associated with climate change adaptations. The study adopted the participatory rural appraisal design using questionnaire, interviews and focus group discussions for collection of data for analysis. Estimated parameters partially supported that yearly temperatures are increasing, whereas annual rainfall is declining, although the latter is not significantly related to the former. Smallholder farm ers’ perceptions about changing weather conditions did not corroborate the observed declining annual rainfall trend. These farmers are faced with livelihood-affecting risks during either ‘prolonged dry per iods from October to May’ or ‘short annual rainy season from mid-May to September. Therefore, access to climate information and available climate adaptation strategies could improve farming activities and livelihoods of farmers in response to climate change.
Performance of CMIP6 HighResMIP on the Representation of Onset and Cessation of Seasonal Rainfall in Southern West Africa
(Atmosphere, 2022) Nkrumah, F.; Quagraine, K.A.; Quagraine, K.T.; Wainwright, C.; Quenum, G.M.L.D.; Amankwah, A.; Klutse, N.A.B.
Changes in rainfall onset and cessation dates are critical for improving decision making and adaptation strategies in numerous socio-economic sectors. An objective method of determining onset and cessation date is employed over Southern West Africa (SWA) in this study. The method is applied over 34 years of the quasi-global rainfall dataset from the Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) and five High Resolution Model Intercomparison Project (HighResMIP) model datasets under the Coupled Model Intercomparison Project Phase 6 (CMIP6) experiment. Generally, a strong agreement exists between CHIRPS and the HighResMIP models in capturing the behaviour of seasonal rainfall over SWA, with models able to capture the bimodal rainfall season. The ability of models in capturing onset and cessation dates as observed in CHIRPS shows the strength of these models in representing the short break between the two wet seasons that is otherwise known as the ‘Little Dry Season’. Patterns observed in the onset and cessation dates over the SWA region are consistent with the northward and southward displacement of the Intertropical Convergence Zone (ITCZ). The seasonal timing of the models shows good agreement with observations such that most mean onset/cessation dates agree within 26 days. While IPSLCM6A-ATM-HR, a model among the five HighResMIPs used in the study, best agrees with CHIRPS in representing onset and cessation dates during the unimodal rainfall season, no one model best agrees with CHIRPS during the bimodal season, with models outperforming each other in representing onset/cessation dates with little variation.
Potential impact of 1.5 °C and 2 °C global warming on consecutive dry and wet days over West Africa
(Environmental Research Letters, 2018) Klutse, N.A.B.; Ajayi, V.O.; Gbobaniyi, E.O.; Egbebiyi, T.S.; Kouadio, K.; Nkrumah, F.; Quagraine, K.A.; Olusegu, C.; Diasso, U.; Abiodun, B.J.; Lawal, K.; Nikulin, G.; Lennard, C.; Dosio, A.
We examine the impact of +1.5 ◦C and +2 ◦C global warming levels above pre-industrial levels on consecutive dry days (CDD) and consecutive wet days (CWD), two key indicators for extreme precipitation and seasonal drought. This is done using climate projections from a multi-model ensemble of 25 regional climate model (RCM) simulations. The RCMs take boundary conditions from ten global climate models (GCMs) under the RCP8.5 scenario. We define CDD as the maximum number of consecutive days with rainfall amount less than 1 mm and CWD as the maximum number of consecutive days with rainfall amount more than 1 mm. The differences in model representations of the change in CDD and CWD, at 1.5 ◦C and 2 ◦C global warming, and based on the control period 1971−2000 are reported. The models agree on a noticeable response to both 1.5 ◦C and 2 ◦C warming for each index. Enhanced warming results in a reduction in mean rainfall across the region. More than 80% of ensemble members agree that CDD will increase over the Guinea Coast, in tandem with a projected decrease in CWD at both 1.5 ◦C and 2 ◦C global warming levels. These projected changes may influence already fragile ecosystems and agriculture in the region, both of which are strongly affected by mean rainfall and the length of wet and dry periods.
Potential of the Coupled WRF/WRF-Hydro Modeling System for Flood Forecasting in the Ouémé River (West Africa)
(Water, 2022) Quenum, G.M.L.D.; Arnault, J.; Klutse, N.A.B.; Zhang, Z.; Kunstmann, H.; Oguntunde, P.G.
Since the beginning of the 2000s, most of the West-African countries, particularly Benin, have experienced an increased frequency of extreme flood events. In this study, we focus on the case of the Ouémé river basin in Benin. To investigate flood events in this basin for early warning, the coupled atmosphere–hydrology model system WRF-Hydro is used, and analyzed for the period 2008–2010. Such a coupled model allows exploration of the contribution of atmospheric components into the flood event, and its ability to simulate and predict accurate streamflow. The potential of WRF-Hydro to correctly simulate streamflow in the Ouémé river basin is assessed by forcing the model with operational analysis datasets from the European Centre for Medium-Range Weather Forecasts (ECMWF). Atmospheric and land surface processes are resolved at a spatial resolution of 5 km. The additional surface and subsurface water flow routing are computed at a resolution of 500 m. Key parameters of the hydrological module of WRF-Hydro are calibrated offline and tested online with the coupled WRF-Hydro. The uncertainty of atmospheric modeling on coupled results is assessed with the stochastic kinetic energy backscatter scheme (SKEBS). WRF-Hydro is able to simulate the discharge in the Ouémé river in offline and fully coupled modes with a Kling–Gupta efficiency (KGE) around 0.70 and 0.76, respectively. In the fully coupled mode, the model captures the flood event that occurred in 2010. A stochastic perturbation ensemble of ten members for three rain seasons shows that the coupled model performance in terms of KGE ranges from 0.14 to 0.79. Additionally, an assessment of the soil moisture has been developed. This ability to realistically reproduce observed discharge in the Ouémé river basin demonstrates the potential of the coupled WRF-Hydro modeling system for future flood forecasting applications