The contribution of weather forecast information to agriculture, water, and energy sectors in East and West Africa: A systematic review

Abstract

The provision of timely and precise weather information could reduce the vulnerability of people to climate change risks. In this study, we conduct a systematic review to synthesize the existing evidence on weather information services for the agriculture, water, and energy sectors of East and West Africa and identify priorities for future research. This systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement checklist. The review identified relevant peer-reviewed publications using ScienceDirect and Scopus databases for original research articles published in English from 2000 to 2022. After applying the eligibility criteria, 25 articles were included in the final review. The themes emerging from the articles were extracted, and a summary was provided to illustrate each theme. The review revealed that weather information studies focus more on the agriculture sector than energy production and water resource management. Users of weather information mainly accessed information related to rainfall and temperature, and the information was accessed mainly through radio, mobile phones, and television. Most of the information provided focused on generic meteorological forecasts instead of tailored impact-based forecasts. Only very few users can access, or benefit from the information produced due to poor communication and technical understanding of weather information. In addition, a lack of downscaled information, logistics, and trust hinders the uptake and use of climate information. Consequently, mainstreaming capacity-building of key stakeholders is required to promote effective adoption and strengthening of climate information services across East and West Africa.

Systematic Review Registration: [website], identifier [registration number].

Introduction

There has been a surge in climate change-induced extreme weather events such as floods, droughts, and storms in the past decade (2010—2020), particularly in tropical regions such as sub-Saharan Africa (Codjoe and Atiglo, 2020; Dube et al., 2021). The effects of such extreme events are more profound in Africa due to limited capacity to manage risks, weaker revenue capability, and lower institutional ability to upgrade infrastructure (Kayaga et al., 2013; Horne et al., 2018). Extreme events can result in the loss of human lives and livelihoods, decreased crop productivity, destruction of electricity distribution infrastructure, and interruption to water supplies (Connolly-Boutin and Smit, 2016; Curtis et al., 2017; Ife-Adediran and Aboyewa, 2020; Intergovernmental Panel on Climate Change, 2021).

One way to minimize the impact of extreme weather is by improving weather forecasting and better communication of weather warnings. The ability to provide timely and precise weather forecasts offers the potential to reduce the vulnerability of people to the impacts of extreme weather (Singh et al., 2018; Alley et al., 2019; Nost, 2019; Antwi-Agyei et al., 2021a). However, accurate forecasting of weather variables remains a major challenge for the scientific community (Mani and Mukherjee, 2016), especially in tropical regions. The need to safeguard lives and livelihoods from extreme weather events has made the provision of timely weather forecasts an essential adaptation initiative (Oyekale, 2015). Improving the weather forecast’s accuracy is crucial for people’s safety and protecting key economic sectors, including agriculture, aviation, water, energy, and emergency response (Parker et al., 2021). In addition, availability, accessibility, and usability of accurate weather information are key for climate-informed decision-making (Dinku et al., 2014; Mabe et al., 2014; Nkiaka et al., 2019). As weather forecasts become progressively more accurate and timelier, their use can inform climate change risk mitigation strategies. However, the benefits linked to these improvements will only be appreciated if the forecasts are used directly in management decisions (Blum and Miller, 2019).

There is an urgent need to assess the forecasting of high-impact weather in sub-Saharan Africa to minimize the devastating effects of extreme events on the economy and livelihoods (Woodhams et al., 2018; Carter et al., 2019). With improved warning systems, it is possible to reduce the extent of damage by improving the resilience of at-risk populations and reinforcing the preparedness of the population to cope with extreme events (Anaman et al., 2017). The production and use of improved weather information to deliver early warnings and adequately manage these extreme events are essential in societal preparedness against extreme weather events (Anaman et al., 2017).

Studies have highlighted the importance of weather and climate services in mitigating risks such as drought, flooding, and loss of lives and livelihoods (Mabe et al., 2014; Sena et al., 2014; Oyekale, 2015; Mittal, 2016; Guido et al., 2021; Kayaga et al., 2021). These studies have considered the effects of extreme weather events on agriculture, health, water, and energy sectors in South America, Asia, and Africa. Despite the plethora of information on climate services, the effect of observations of climate change on using weather forecasts has not been investigated in depth in East and West Africa regions (Seo, 2014; Nkiaka et al., 2019). Studies have not synthesized all of the evidence on the contribution of weather and climate information in Africa into a single study to enhance decision-making. The choice of East and West Africa was influenced by the geographic and socioeconomic characteristics, which make these regions most vulnerable to climate change. In addition, gaps remain between the production of climate services, its use in decision-making, and the societal benefits derived from climate services (Webber, 2019; Harvey et al., 2021).

This review focused on the agricultural, energy, and water resource sectors. These sectors are critically important as they contribute significantly to the gross domestic product (GDP) of the East and West Africa regions (Coers and Sanders, 2013; Food and Agriculture Organisation and African Development Bank, 2015; Nhemachena et al., 2018; Gashu et al., 2019) and are highly prone to climate variability and change (Cervigni et al., 2015; Butterfield et al., 2017).

With respect to water resources, many African countries encounter numerous difficulties in the acquisition of sustainable and sufficient quality water to meet the needs of a rapidly increasing population and socioeconomic development without compromising on safeguarding the essential ecosystems that water resources depend on (Global Water Partnership, 2015). Water scarcity in these two regions has risen due to climate change and other factors, with negative consequences projected at the river basin level (Yomo et al., 2019). It is predicted that water security will be significantly affected due to urbanization and rapid population growth in various continents (United Nations, 2019), as more water is required for domestic water supply, agriculture, and business. General Circulation Models (GCMs) in East Africa predict a 10–20% surge in rainfall and a shift in rainfall distribution. For example, in Uganda, the impact of climate change on seasonal rainfall is projected to be more significant compared to variations in annual rainfall (Kisakye and Van der Bruggen, 2018). In addition, rapid population growth, usage of agrochemicals, industrialization, urbanization, soil steepness, and land-use and cover changes threaten water quality (Mukanyandwi et al., 2018). Similarly, West Africa is dependent on rain-fed agriculture and already prone to extreme weather events such as floods and droughts. The region is projected to face a declining crop yield by 2050 if the large-scale water cycle changes already observed deteriorate (International Water Management Institute, 2022). An assessment of available water resources in Burkina Faso indicates that the country is heading toward water scarcity with ever-increasing demands for water. This situation could affect key sectors that are important for socioeconomic development, such as agriculture, and endanger the well-being of more than 340 million people in the region (WaterAid, 2021). However, water resource management and development have primarily paid less attention to the interdependence of the various uses of water—for agriculture, domestic, and industrial use and for maintaining the ecosystems and hydrological services. Inadequate data and information on the state of renewable water resources further worsen water planning and governance (Global Water Partnership, 2015).

The agriculture sector is the backbone of many African countries’ economies. The sector employs about 65–70% of the labor force, supports 90% of household livelihoods, and is responsible for about one-fourth of the continent’s gross domestic product (OECD/FAO, 2016; World Bank, 2016). The growth in the agriculture sector is more effective in easing poverty than growth in non-agricultural sectors (Mukasa et al., 2017). The agriculture sector is by nature subtle to climate conditions and is also prone to the impacts of climate change (Parker et al., 2019). In most African countries, agriculture is largely small scale and rain-fed, thus making it vulnerable to climate variability and change (Ochieng et al., 2016; Hlophe-Ginindza and Mpandeli, 2021). The economy and the livelihoods of many households in East and West Africa have become vulnerable to climate change owing to heavy dependence on rain-fed agriculture and natural resources (Ochieng et al., 2016; Sultan and Gaetani, 2016; Kalai et al., 2017). Due to climate change, observed and projected disruptions in precipitation patterns are likely to reduce growing seasons and negatively affect crop yield (Guido et al., 2020). The agriculture sector is predominated by smallholder farmers with limited access to the resources and technology needed to cope with the impacts of extreme events (Abdul-Razak and Kruse, 2017). To cope with the devastating effects of climate change on food production, farmers have been adopting new farming technologies and practices. These practices include improved management systems such as introducing microcatchments, crop cover, crop rotations, ridges, planting trees, improved pastures, and innovative technologies such as shorter cycle varieties, improved seeds, and drought-tolerant varieties (Kristjanson et al., 2012; Anuga and Gordon, 2016). East and West Africa are key producers of the African continent’s food; therefore, strengthening the resilience of the agricultural system to climate change is crucial to reducing poverty (SDG1) and averting hunger (SDG 2) (FAO, 2015).

The review also focused on the energy sector of East and West Africa. The economy and energy systems of East Africa are extremely reliant on natural resources and thus very prone to current and projected effects of climate change (Ddamulira, 2016). The region’s present energy state is marked by a high reliance on biofuels in rural areas. While biofuels are renewable clean energy options, their use remains traditional, with major environmental and health consequences (Waindi and Khalid, 2011). Heavy system losses also harm the electricity sector in East Africa. This is owing to a high reliance on hydropower for electricity generation. However, the climate in the region has an impact on this reliance since the occurrence of severe drought results in significant losses in electricity output (Waindi and Khalid, 2011). This results in widespread power rationing which has negative impacts on the socioeconomic livelihoods of the people across space and time. The West African region is similarly faced with the realities of energy vulnerability, system unreliability, and fuel price volatility. Energy poverty (lack of access to modern energy services) and its effects on local economies and social development are projected to remain the predominant challenge through 2030 (Merem et al., 2017). The potential impacts of climate change on the energy sector could include substantial stress on the production, distribution, and utilization of energy. This may lead to increased use of fossil fuels or reinforced infrastructure, and increasing greenhouse gas (GHG) emissions, for instance, reduced efficiency of power stations, reduction in renewable energy resources, or increased risks of storm damage to coastal infrastructure (Cronin et al., 2018). These would undermine all of the achievements made in the energy sector.

Methods

The systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (Liberati et al., 2009).

Eligibility criteria

We excluded studies that were conducted in other regions, focused on sectors other than those of interest, and considered outcomes not relevant to this study. In addition, papers were excluded if they were not published in English or published before 2000. Reviews, book sections, opinions, letters to the editor, and papers reporting only mathematical models were excluded from this review.

Information sources and search strategy

The review targeted peer-reviewed articles published in English from January 2000 to January 2022. The year 2000 marked a surge of pilot-scale studies with African farmers ensuing the much-publicized 1997/1998 El Nino (Hansen et al., 2011). Articles were searched from two major databases, ScienceDirect and Scopus, due to their broad coverage and quality of content. The search terms included search strings such as (“weather forecast” OR “weather information” OR “weather service”) AND (“Agriculture” OR “water resource” OR “energy”) AND (“Africa”). Furthermore, we manually searched the reference list of selected articles for articles pertinent to the study but were not captured during The electronic search. Supplementary Table S1 shows the search strategy and results of the various databases.

Study selection

Articles obtained using the search terms were exported into the EndNote reference manager (version X20), and duplicates were removed. Two reviewers (TPA and PA-A) independently screened titles and abstracts of the articles retrieved from the electronic databases and hand searches. Articles that failed to meet the inclusion criteria were excluded. We then downloaded the full-text articles and reviewed them for inclusion. At this stage, studies were excluded for reasons (Supplementary Table S2). Any disagreements in the screening and selection of articles were resolved by dialogue and involvement of a third reviewer.

Data extraction and analysis

A data-extraction form was designed and piloted to gather information according to the focus of the study. The form captured information on the author’s name and year of publication, the title of the article, country and region, sector, weather information accessed, whether the information helped make decisions, and key barriers to the uptake of climate information. Regarding data analysis, descriptive statistics were used to present information on study countries and the medium of receiving weather and climate information. Included studies were analyzed using thematic analysis. The themes emerging from the articles were extracted, and a summary was provided to illustrate each theme. These themes include information accessed, user decision-making, and key barriers. Quality assessment of the included papers was not done due to the heterogeneity of the papers.

Results

Search results

Using the search terms, 38,636 and 348 articles were retrieved from ScienceDirect and Scopus databases, respectively. Fourteen (14) additional papers were obtained through random Google search and manual screening of the reference lists of included studies. After removing duplicates, 35,349 records were retained. The titles and abstracts were then screened to obtain 52 records to be included for full-text assessment. Twenty-seven (27) articles were excluded for reasons (Supplementary Table S2), while 25 articles fully met the inclusion criteria (Figure 1).

FIGURE 1

Study setting

Of the 25 included studies, 20 reported findings from only West Africa, four from East Africa, and one article reported findings from East and West Africa. These studies were conducted in 11 countries across East and West Africa, with the majority of the studies reporting findings from Ghana (n = 9), followed by Burkina Faso and Senegal (n = 5), Kenya and Tanzania (n = 3), Benin, Ethiopia, Niger and Uganda (n = 2), and Mali and Nigeria (n = 1) (Figure 2). All of the 25 studies focused on the agriculture sector (Table 1).

FIGURE 2

Information accessed

Twenty-one studies reported on different types of weather information accessed by users. Most of the weather and climate information provided focused on generic meteorological forecasts instead of a tailored impact-based forecast. Though all of the included studies focused on agriculture, the information accessed by users differed based on whether they were into animal husbandry or crop farming. The majority of the studies reported that for users in crop farming, the climate information needed or accessed was related to rainfall and temperature, such as the onset of rains, rainfall distribution and amount, end of rains, the intensity of the dry season, dry spells, and the speed of winds during the rainy season (Rasmussen et al., 2015; Amegnaglo et al., 2017; Diouf et al., 2019; Radeny et al., 2019; Bacci et al., 2020; Partey et al., 2020; Antwi-Agyei et al., 2021c). Some studies reported that pastoralists needed or accessed extra information such as the outbreak of livestock and crop pests/diseases (Oyekale, 2015) and the availability of grazing resources (Rasmussen et al., 2015). However, four studies did not mention the specific type of weather information needed by users. For example, Chiputwa et al. (2022) reported that users needed or accessed information on daily forecasts, early warning system (EWS), and seasonal forecasts, while Wamalwa et al. (2016) reported that users had access to agro-weather and climate information. In addition, disaster forecasts such as flooding, wind and windstorms, dry/wet spells, and drought were reported by eight studies (Rasmussen et al., 2015; Amegnaglo et al., 2017; Ouedraogo et al., 2018; Diouf et al., 2019; Radeny et al., 2019; Bacci et al., 2020; Antwi-Agyei et al., 2021c; Ouedraogo et al., 2021) (Table 2).

The medium through which weather and climate information was received was also assessed. The most common means of accessing climate information included radio, mobile phone (text messages and voice calls), television, and extension officers (Figure 3).

FIGURE 3

User’s decision-making

Decisions made due to the access to weather and climate information ranged from land preparation to harvesting time. One study reported that most of the respondents who received the information used it to make decisions such as preparing farmlands, selecting crop varieties, varying cropping patterns, and harvesting time (Antwi-Agyei et al., 2021c). Furthermore, farmers who received seasonal, daily, and early warning systems (EWS) made significantly more farm management decisions and had a higher yield of crops than non-users of weather and climate information services (Chiputwa et al., 2022) (Table 3). In the fisheries sector, climate information helped fishers postpone their activities on the sea or go to sea while using their life jacket (Ouedraogo et al., 2018). However, the proportion of fishers who used weather information in decision-making was low. Of those who had access to weather and climate information, only a few utilized the information to decide on various activities (Oyekale, 2015; Nyang’au et al., 2021). In some instances, users combined indigenous and scientific forecasts. Though they acknowledge the limitations in using indigenous forecasts, they considered it better for decision-making than the scientific forecast provided by the state agency responsible for the forecast (Nyadzi et al., 2018) (Table 3).

Key barriers to the uptake of weather information

The production and delivery of weather information is not an assurance that the information will automatically inform decision-making because barriers can hinder the use of information. In the studies reviewed, 18 studies reported barriers to the uptake and use of weather information in East and West Africa. The four key barriers reported include; poor communication and understanding of weather information (n = 12), lack of downscaled information (n = 8), lack of logistics (n = 5) and lack of trust (n = 4). Other barriers include meteorological information not tailored to meet the information needs of vulnerable group decision-makers at the sub-national level and the belief in indigenous knowledge (Table 4). One study reported that the inability to comprehend how anthropogenic activities contribute to climate change impeded the uptake of seasonal climate forecasts (Ebhuoma and Simatele, 2019). Regarding logistics and training, the inability to interpret climate information and convert it into actions affected the user’s ability to use the information in decision-making (Partey et al., 2020).

Discussion

This study reviewed and assessed literature for evidence on the uptake, use and adoption of weather and climate information in the Agriculture, Water and Energy sectors in East and West Africa. The review revealed many research gaps and highlighted significant findings for policy-making.

Our review showed that studies on weather information services had focused predominantly on West Africa than East Africa. The dominance of studies in West Africa, especially Ghana, could be attributed to the region’s vulnerability to climate risks (Karambiri et al., 2011; Sultan and Gaetani, 2016; Akinsanola and Zhou, 2019). Most of the studies were conducted in rural communities without focusing on users in urban communities. Future studies are needed to identify the weather and climate information needs of urban users (especially farmers) and evaluate the influence of the information on users’ ability to make informed decisions. Further studies are also needed to identify the type of weather and climate information needed by users in sectors such as fisheries, energy, and water resources.

Regarding the type of weather information accessed by users, our results revealed that the information accessed differs even within a specific sector. Most farmers were more interested in accessing rainfall (such as the likely amount and distribution of rainfall) and temperature (such as the intensity of the dry season) forecasts. The findings are consistent with other results from South Africa, Europe, and Asia (Lebel, 2013; Mudombi and Nhamo, 2014; Shackleton et al., 2015), highlighting rainfall and temperature information as crucial information needed by users to manage climate risks. Many households in East and West Africa regions rely on agro-based livelihoods that are extremely vulnerable to the adverse impacts of climate change. Forecast on rainfall and temperature helps farmers to plan what to plant and when to do it. In addition, it helps them put measures in place to reduce the devastating impacts of extreme events on their livelihoods. However, most of the information received by users was a daily forecast instead of a seasonal forecast. This is in agreement with the findings of Baffour-Ata et al. (2022) who observed that few farmers received seasonal forecasts. They attributed this to the possibility of farmers encountering a digital divide (i.e., a gap between demographics and regions with access to modern information and communications technology and those that do not or have restricted access) in the access to seasonal forecasts. It is also important to stress the space–time relevance of seasonal forecasts to the needs of decision-makers. This has often been attributed to the greater uncertainty and probabilistic information associated with seasonal forecasts provided by national meteorological agencies (see Antwi-Agyei et al., 2021c). There is a need to build the capacity of meteorological agencies in the provision of accurate seasonal forecasts to aid decision-making. The availability of seasonal forecasts could provide advanced early warning of rainfall variability and help users plan ahead of time (Young et al., 2020).

The review further showed that few studies reported on impact-based forecasts such as drought, windstorms, and floods. Impact-based forecasts bridge the gap between forecasts and possible impacts of impending hazards [World Meteorological Organisation (WMO), 2015]. The provision of an impact-based forecast helps farmers to act before disasters in order to minimize the effects of weather and climate hazards on their livelihoods. The medium of communicating weather and climate information is important as it ensures users access the required information to make the right decisions. Our review revealed that the key media for communicating weather and climate information included radio, mobile phones, and television. Findings are consistent with other studies (Ajani, 2014; Coulier et al., 2018; Sikhondze, 2020; Henriksson et al., 2021), reporting radio as the most preferred medium of receiving weather and climate information. However, in rural areas that do not have electricity, farmers have to purchase batteries to enable them to operate their radios, and this places an extra financial burden on them. This could discourage farmers from using radios, thus denying them access to weather and climate information. Therefore, policymakers should prioritize extending electricity to rural farming communities or providing them with alternative effective means of accessing weather and climate information.

The significance of weather and climate information depends on mainly the ability to produce information that is usable and delivered in ways that can be incorporated into decision-making processes (Singh et al., 2018). The review showed that users who had access to weather and climate information used it to make several decisions related to land preparation, crop variety selection, varying cropping patterns, and harvesting time. Farmers also made key farm management decisions such as the application of fertilizers and pesticides, irrigation, and drying of crops based on weather and seasonal forecasts (Antwi-Agyei et al., 2021c). The decisions often lead to a significant increase in crop yields and farmer income and welfare. However, the review also highlights that few users utilized the information accessed. One fundamental gap identified is that most of the included studies did not have a comparison group (who did not use weather and climate information) in their analysis, making it difficult to assess the impact of using the information in decision-making.

The production and delivery of weather and climate service do not necessarily warrant that the information will be used or is even helpful for decision-making (Nkiaka et al., 2019). Our review revealed several challenges confronting the uptake, use, and adoption of weather and climate information. Key among them include poor communication and understanding of weather and climate information, lack of downscaled information, and lack of logistics. These findings support the findings of other studies in Europe, North America, and South Africa (Bolson et al., 2013; Bruno Soares and Dessai, 2016; Singh et al., 2018), where farmers and other users of weather and climate information identified barriers that prevented them from making better decisions using weather and climate information. Other studies have documented similar challenges affecting the use of climate and weather information for the implementation of climate-smart agricultural practices in Ghana (Antwi-Agyei et al., 2022). These barriers, if not addressed, could erode the efforts made in the provision of weather and climate information to aid farmers in planning their farming activities and also build their resilience to climate change. The review noted that there is a need to integrate scientific and indigenous knowledge to ensure locally appropriate framing of communications and use of weather and climate information services. Studies on cost–benefit analysis of the reliance on indigenous knowledge and scientific weather and climate information are needed. Further studies are required to explore the effectiveness of integrating indigenous knowledge of climate information into scientific weather and climate information to increase the uptake, use, and adoption of weather and climate information.

The use of weather and climate information in the agriculture sector could present some synergies and trade-offs in other sectors such as the energy and water resource sectors. For instance, cultivating plants that require low water will reduce water withdrawal for irrigation. In addition, the use of solar-powered pumps, promotion of microirrigation, and other forms of farming, such as hydroponics, would address the trade-offs associated with increasing food production (Mpandeli et al., 2018). Weather and climate information services can play a substantial role in guiding nexus-related decision-making (Conway et al., 2015). Unfortunately, studies on weather and climate information have not explored the synergies and trade-offs between the water–energy–food (WEF) nexus. Implementing measures that enhance the synergies and reduce the trade-offs between the WEF nexus is crucial in attenuating the devastating impacts of climate change on livelihoods (Mpandeli et al., 2018).

Conclusion and policy implications

This review reveals that studies on weather and climate information have to date focused more on West Africa than East African countries. The uptake, use, and adoption of climate information helped users to take key decisions to reduce the impact of extreme weather events. However, few studies reported on the impact-based forecast, and few users could access or benefit from the information produced due to poor communication and understanding of weather and climate information, lack of downscaled information, lack of logistics and trust, etc. These challenges, if not addressed, may regress the achievements made in the provision of weather and climate information. Therefore, sustainable efforts should be made to address these challenges through practical training and capacity building of end-users. This will facilitate the creation of awareness and understanding of climate information to help mitigate the impacts of stern climate events on livelihoods.

There is a need for weather and climate information that is easily accessible, understandable, and tailored to meet the needs of users. Weather and climate information delivery should be a key factor in policy discussions at all levels to improve climate risk management. Investors and governments could also increase their revenue base by expanding and diversifying technology in the delivery of impact-based forecasts specific to key sectors of the economy. Future studies are required to evaluate the production of the impact-based forecast, its performance, uncertainties, and how it translates into farmers’ decision-making.

References

• 1

  Abdul-RazakM.KruseS. (2017). The adaptive capacity of smallholder farmers to climate change in the Northern Region of Ghana. Clim. Risk Manag.17, 104–122. 10.1016/j.crm.2017.06.001

  • CrossRef
  • Google Scholar

• 2

  AjaniE. N. (2014). Promoting the use of information and communication technologies (ICTs) for agricultural transformation in sub-saharan Africa: Implications for policy. J. Agric. Food Inf.15, 42–53. 10.1080/10496505.2013.858049

  • CrossRef
  • Google Scholar

• 3

  AkinsanolaA. A.ZhouW. (2019). Projections of West African summer monsoon rainfall extremes from two CORDEX models. Clim. Dyn.52, 2017–2028. 10.1007/s00382-018-4238-8

  • CrossRef
  • Google Scholar

• 4

  AlleyR. B.EmanuelK. A.ZhangF. (2019). Advances in weather prediction. Science363, 342–344. 10.1126/science.aav7274

  • CrossRef
  • Google Scholar

• 5

  AmegnagloC. J.AnamanK. A.Mensah-BonsuA.OnumahE. E.Amoussouga GeroF. (2017). Contingent valuation study of the benefits of seasonal climate forecasts for maize farmers in the Republic of Benin, West Africa. Clim. Serv.6, 1–11. 10.1016/j.cliser.2017.06.007

  • CrossRef
  • Google Scholar

• 6

  AnamanK. A.QuayeR.AmankwahE. (2017). Evaluation of public weather services by users in the formal services sector in Accra, Ghana. Mod. Econ.08, 921–945. 10.4236/me.2017.87065

  • CrossRef
  • Google Scholar

• 7

  Antwi-AgyeiP.DougillA. J.Doku-MarfoJ.AbaidooR. C. (2021a). Understanding climate services for enhancing resilient agricultural systems in Anglophone West Africa: The case of Ghana. Clim. Serv.22, 100218. 10.1016/j.cliser.2021.100218

  • CrossRef
  • Google Scholar

• 8

  Antwi-AgyeiP.AmanorK.HogarhJ. N.DougillA. J. (2021b). Predictors of access to and willingness to pay for climate information services in north-eastern Ghana: A gendered perspective. Environ. Dev.37, 100580. 10.1016/j.envdev.2020.100580

  • CrossRef
  • Google Scholar

• 9

  Antwi-AgyeiP.DougillA. J.AbaidooR. C. (2021c). Opportunities and barriers for using climate information for building resilient agricultural systems in Sudan savannah agro-ecological zone of north-eastern Ghana. Clim. Serv.22, 100226. 10.1016/j.cliser.2021.100226

  • CrossRef
  • Google Scholar

• 10

  Antwi-AgyeiP.AbaloE. M.DougillA. J.Baffour-AtaF. (2022). Motivations, enablers and barriers to the adoption of climate-smart agricultural practices by smallholder farmers: Evidence from the transitional and savannah agroecological zones of Ghana. Reg. Sustain.2 (4), 375–386. 10.1016/j.regsus.2022.01.005

  • CrossRef
  • Google Scholar

• 11

  AnugaS. W.GordonC. (2016). Adoption of climate-smart weather practices among smallholder food crop farmers in the Techiman municipal: Implication for crop yield. Res. J. Agric. Environ. Manag.5, 279–286.

  • Google Scholar

• 12

  BacciM.BaouaY. O.TarchianiV. (2020). Agrometeorological forecast for smallholder farmers: A powerful tool for weather-informed crops management in the sahel. Sustain. Switz.12, 3246. 10.3390/su12083246

  • CrossRef
  • Google Scholar

• 13

  Baffour-AtaF.Antwi-AgyeiP.NkiakaE.DougillA. J.AnningA. K.KwakyeS. O. (2022). Climate information services available to farming households in northern region, Ghana. Weather, Clim. Soc.14, 467–480. 10.1175/wcas-d-21-0075.1

  • CrossRef
  • Google Scholar

• 14

  BlumA. G.MillerA. (2019). Opportunities for forecast-informed water resources management in the United States. Bull. Am. Meteorological Soc.100, 2087–2090. 10.1175/bams-d-18-0313.1

  • CrossRef
  • Google Scholar

• 15

  BolsonJ.MartinezC.BreuerN.SrivastavaP.KnoxP. (2013). Climate information use among southeast US water managers: Beyond barriers and toward opportunities. Reg. Environ. Change13, 141–151. 10.1007/s10113-013-0463-1

  • CrossRef
  • Google Scholar

• 16

  Bruno SoaresM.DessaiS. (2016). Barriers and enablers to the use of seasonal climate forecasts amongst organisations in Europe. Clim. Change137, 89–103. 10.1007/s10584-016-1671-8

  • CrossRef
  • Google Scholar

• 17

  ButterfieldR.Coll BesaM.BurmeisterH.BlairK.KavonicJ.BharwaniS.et al (2017). Inspiring climate action in african cities: Practical options for resilient pathways. FRACTAL Working Paper 4. Oxford, United Kingdom: Stockholm Environment Institute Oxford Centre.

  • Google Scholar

• 18

  CarterS.SteynorA.VincentK.VismanE.WaagsaetherK. (2019). Co-production of African weather and climate services. Second edition. Manual, Cape Town: Future Climate for Africa and Weather and Climate Information Services for Africa. Available from: https://futureclimateafrica.org/coproduction-manual.

  • Google Scholar

• 19

  CervigniR.LidenR.NeumannJ. E.StrzepekK. M. (2015). Enhancing the climate resilience of africa's infrastructure: The power and water sectors. Washington, DC: World Bank Publications.

  • Google Scholar

• 20

  ChiputwaB.Blundo-CantoG.StewardP.AndrieuN.NdiayeO. (2022). Co-Production, uptake of weather and climate services, and welfare impacts on farmers in Senegal: A panel data approach. Agric. Syst.195, 103309. 10.1016/j.agsy.2021.103309

  • CrossRef
  • Google Scholar

• 21

  CodjoeS. N. A.AtigloD. Y. (2020). The implications of extreme weather events for attaining the sustainable development goals in sub-Saharan Africa. Front. Clim.2, 18. 10.3389/fclim.2020.592658

  • CrossRef
  • Google Scholar

• 22

  CoersR.SandersM. (2013). The energy–GDP nexus; addressing an old question with new methods. Energy Econ.36, 708–715. 10.1016/j.eneco.2012.11.015

  • CrossRef
  • Google Scholar

• 23

  Connolly-BoutinL.SmitB. (2016). Climate change, food security, and livelihoods in sub-Saharan Africa. Reg. Environ. Change16, 385–399. 10.1007/s10113-015-0761-x

  • CrossRef
  • Google Scholar

• 24

  ConwayD.van GarderenE. A.DeryngD.DorlingS.KruegerT.LandmanW.et al (2015). Climate and southern Africa's water–energy–food nexus. Nat. Clim. Change5, 837–846. 10.1038/nclimate2735

  • CrossRef
  • Google Scholar

• 25

  CoulierM.CarterA.DuongT. M.LeT. T.LuuG. T. T.MadsenE. J. (2018). Actionability of climate services in southeast Asia: Findings from ACIS baseline surveys in vietnam, Lao PDR and Cambodia.

  • Google Scholar

• 26

  CroninJ.AnandarajahG.DessensO. (2018). Climate change impacts on the energy system: A review of trends and gaps. Clim. Change151, 79–93. 10.1007/s10584-018-2265-4

  • CrossRef
  • Google Scholar

• 27

  CurtisS.FairA.WistowJ.ValD. V.OvenK. (2017). Impact of extreme weather events and climate change for health and social care systems. Environ. Health16, 128. 10.1186/s12940-017-0324-3

  • CrossRef
  • Google Scholar

• 28

  DdamuliraR. (2016). Climate change and energy in East Africa. Development59, 257–262. 10.1057/s41301-017-0101-1

  • CrossRef
  • Google Scholar

• 29

  DinkuT.BlockP.SharoffJ.HailemariamK.OsgoodD.del CorralJ.et al (2014). Bridging critical gaps in climate services and applications in Africa. Earth Perspect.1, 15–13. 10.1186/2194-6434-1-15

  • CrossRef
  • Google Scholar

• 30

  DioufN. S.OuedraogoI.ZougmoréR. B.OuedraogoM.ParteyS. T.GumucioT. (2019). Factors influencing gendered access to climate information services for farming in Senegal. Gend. Technol. Dev.23, 93–110. 10.1080/09718524.2019.1649790

  • CrossRef
  • Google Scholar

• 31

  DubeK.NhamoG.ChikodziD. (2021). Flooding trends and their impacts on coastal communities of Western Cape Province, South Africa. GeoJournal, 1–16. 10.1007/s10708-021-10460-z

  • CrossRef
  • Google Scholar

• 32

  EbhuomaE. E.SimateleD. M. (2019). ‘We know our terrain’: Indigenous knowledge preferred to scientific systems of weather forecasting in the delta state of Nigeria. Clim. Dev.11, 112–123. 10.1080/17565529.2017.1374239

  • CrossRef
  • Google Scholar

• 33

  FAO (2015). Regional overview of food insecurity: African food security prospects brighter than ever. Ghana: FAO Accra.

  • Google Scholar

• 34

  Food and Agriculture Organization and African Development Bank (2015). Agricultural growth in West Africa: Market and policy drivers. Rome: FAO and the African Development Bank.

  • Google Scholar

• 35

  GashuD.DemmentM. W.StoeckerB. J. (2019). Challenges and opportunities to the African agriculture and food system. Afr. J. Food Agric. Nutr. Dev.19, 14190–14217. 10.18697/ajfand.84.blfb2000

  • CrossRef
  • Google Scholar

• 36

  Global Water Partnership (2015). Integrated water resources management in eastern Africa: Coping with 'complex' hydrology. Retrieved from: https://www.gwp.org/globalassets/global/toolbox/publications/technical-focus-papers/p1238_gwp_tfp_ea_121015_web.pdf (Acessed on February 24, 2022.

  • Google Scholar

• 37

  GuidoZ.ZimmerA.LopusS.HannahC.GowerD.WaldmanK.et al (2020). Farmer forecasts: Impacts of seasonal rainfall expectations on agricultural decision-making in Sub-Saharan Africa. Clim. Risk Manag.30, 100247. 10.1016/j.crm.2020.100247

  • CrossRef
  • Google Scholar

• 38

  GuidoZ.LopusS.WaldmanK.HannahC.ZimmerA.KrellN.et al (2021). Perceived links between climate change and weather forecast accuracy: New barriers to tools for agricultural decision-making. Clim. Change168, 9–20. 10.1007/s10584-021-03207-9

  • CrossRef
  • Google Scholar

• 39

  HansenJ. W.MasonS. J.SunL.TallA. (2011). Review of seasonal climate forecasting for agriculture in sub-Saharan Africa. Exp. Agric.47, 205–240. 10.1017/s0014479710000876

  • CrossRef
  • Google Scholar

• 40

  HarveyB.HuangY.-S.AraujoJ.VincentK.RouxJ.-P.RouhaudE.et al (2021). Mobilizing climate information for decision-making in Africa: Contrasting user-centered and knowledge-centered approaches. Front. Clim.2, 589282. 10.3389/fclim.2020.589282

  • CrossRef
  • Google Scholar

• 41

  HenrikssonR.VincentK.ArcherE.JewittG. (2021). Understanding gender differences in availability, accessibility and use of climate information among smallholder farmers in Malawi. Clim. Dev.13, 503–514. 10.1080/17565529.2020.1806777

  • CrossRef
  • Google Scholar

• 42

  Hlophe-GinindzaS. N.MpandeliN. (2021). The role of small-scale farmers in ensuring food security in Africa. Afr: Food Secur.

  • Google Scholar

• 43

  HorneJ.TortajadaC.HarringtonL. (2018). Achieving the sustainable development goals: Improving water services in cities affected by extreme weather events. Int. J. Water Resour. Dev.34, 475–489. 10.1080/07900627.2018.1464902

  • CrossRef
  • Google Scholar

• 44

  Ife-AdediranO. O.AboyewaO. B. (2020). “Climate change resistant energy sources for global adaptation,” in African handbook of climate change adaptation, 1–12.

  • Google Scholar

• 45

  Intergovernmental Panel on Climate Change (IPCC) (2021). “Summary for policymakers,” in Climate change 2021: The physical science basis. Contribution of working group I to the sixth assessment report of the intergovernmental Panel on climate change. Editors Masson-DelmotteV.ZhaiP.PiraniA.ConnorsS. L.PéanC.BergerS.et al (Cambridge University Press). In Press.

  • Google Scholar

• 46

  International Water Management Institute (2022). Putting water at the heart of sustainable development in West Africa. Retrieved from: https://www.iwmi.cgiar.org/2021/12/putting-water-at-the-heart-of-sustainable-development-in-west-africa/ (Accessed on March 2, 2022.

  • Google Scholar

• 47

  KalaiK.DevaraniL.KoyuB.LaitonjamN. (2017). Reviewing the impact of climate change on agriculture and farm households through gender lens. Asian J. Agricult. Extens., Econom. Sociol.21 (3), 1–8. 10.9734/AJAEES/2017/37591

  • CrossRef
  • Google Scholar

• 48

  KarambiriH.García GalianoS. G.GiraldoJ. D.YacoubaH.IbrahimB.BarbierB.et al (2011). Assessing the impact of climate variability and climate change on runoff in West Africa: The case of Senegal and nakambe river basins. Atmos. Sci. Lett.12, 109–115. 10.1002/asl.317

  • CrossRef
  • Google Scholar

• 49

  KayagaS. M.AmankwaaE. F.GoughK. V.WilbyR. L.AbarikeM. A.CodjoeS. N.et al (2021). Cities and extreme weather events: Impacts of flooding and extreme heat on water and electricity services in Ghana. Environ. Urbanization33, 131–150. 10.1177/0956247820952030

  • CrossRef
  • Google Scholar

• 50

  KayagaS.MugabiJ.KingdomW. (2013). Evaluating the institutional sustainability of an urban water utility: A conceptual framework and research directions. Util. Policy27, 15–27. 10.1016/j.jup.2013.08.001

  • CrossRef
  • Google Scholar

• 51

  KisakyeV.Van der BruggenB. (2018). Effects of climate change on water savings and water security from rainwater harvesting systems. Resour. Conservation Recycl.138, 49–63. 10.1016/j.resconrec.2018.07.009

  • CrossRef
  • Google Scholar

• 52

  KristjansonP.NeufeldtH.GassnerA.MangoJ.KyazzeF. B.DestaS.et al (2012). Are food insecure smallholder households making changes in their farming practices? Evidence from East Africa. Food Secur.4, 381–397. 10.1007/s12571-012-0194-z

  • CrossRef
  • Google Scholar

• 53

  LebelL. (2013). Local knowledge and adaptation to climate change in natural resource-based societies of the Asia-Pacific. Mitig. Adapt. Strateg. Glob. Chang.18, 1057–1076. 10.1007/s11027-012-9407-1

  • CrossRef
  • Google Scholar

• 54

  LiberatiA.AltmanD. G.TetzlaffJ.MulrowC.GøtzscheP. C.IoannidisJ. P.et al (2009). The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: Explanation and elaboration. J. Clin. Epidemiol.62, e1–e34. 10.1016/j.jclinepi.2009.06.006

  • CrossRef
  • Google Scholar

• 55

  MabeF. N.NketiahP.DarkoD. (2014). Farmers’ willingness to pay for weather forecast information in Savelugu-Nanton municipality of the northern region. Russ. J. Agric. Socioecon. Sci.36, 34–44. 10.18551/rjoas.2014-12.05

  • CrossRef
  • Google Scholar

• 56

  ManiJ. K.MukherjeeD. (2016). Accuracy of weather forecast for hill zone of West Bengal for better agriculture management practices. Indian J. Res.5, 325–328.

  • Google Scholar

• 57

  MeremE. C.TwumasiY.WesleyJ.IsokpehiP.ShengeM.FageirS.et al (2017). Regional assessment of energy trends in West Africa using GIS. Int. J. Energy Eng.7, 1–27. 10.5923/j.ijee.20170701.01

  • CrossRef
  • Google Scholar

• 58

  MittalS. (2016). Role of mobile phone-enabled climate information services in gender-inclusive agriculture. Gend. Technol. Dev.20, 200–217. 10.1177/0971852416639772

  • CrossRef
  • Google Scholar

• 59

  MpandeliS.NaidooD.MabhaudhiT.NhemachenaC.NhamoL.LiphadziS.et al (2018). Climate change adaptation through the water-energy-food nexus in southern Africa. Int. J. Environ. Res. Public Health15, 2306. 10.3390/ijerph15102306

  • CrossRef
  • Google Scholar

• 60

  MudombiS.NhamoG. (2014). Access to weather forecasting and early warning information by communal farmers in seke and murewa districts, Zimbabwe. J. Hum. Ecol.48, 357–366. 10.1080/09709274.2014.11906805

  • CrossRef
  • Google Scholar

• 61

  MukanyandwiV.NahayoL.HakorimanaE.GasiraboA.OtgonS. (2018). Review on water resources management and key threats in Rwanda, East Africa. J. Water Secur.4, 1–8. 10.15544/jws.2018.003

  • CrossRef
  • Google Scholar

• 62

  MukasaA. N.WoldemichaelA. D.SalamiA. O.SimpasaA. M. (2017). Africa’s agricultural transformation: Identifying priority areas and overcoming challenges. Afr. Econ. Brief.8, 1–16.

  • Google Scholar

• 63

  NaabF. Z.AbubakariZ.AhmedA. (2019). The role of climate services in agricultural productivity in Ghana: The perspectives of farmers and institutions. Clim. Serv.13, 24–32. 10.1016/j.cliser.2019.01.007

  • CrossRef
  • Google Scholar

• 64

  NhemachenaC.MatchayaG.NhemachenaC. R.KaruaiheS.MucharaB.NhlengethwaS. (2018). Measuring baseline agriculture-related sustainable development goals index for southern Africa. Sustainability10, 849. 10.3390/su10030849

  • CrossRef
  • Google Scholar

• 65

  NkiakaE.TaylorA.DougillA. J.Antwi-AgyeiP.FournierN.BosireE. N.et al (2019). Identifying user needs for weather and climate services to enhance resilience to climate shocks in sub-Saharan Africa. Environ. Res. Lett.14, 123003. 10.1088/1748-9326/ab4dfe

  • CrossRef
  • Google Scholar

• 66

  NostE. (2019). Climate services for whom? The political economics of contextualizing climate data in Louisiana’s coastal master plan. Clim. Change157, 27–42. 10.1007/s10584-019-02383-z

  • CrossRef
  • Google Scholar

• 67

  NyadziE.NyamekyeA. B.WernersS. E.BiesbroekR. G.DewulfA.SlobbeE. V.et al (2018). Diagnosing the potential of hydro-climatic information services to support rice farming in northern Ghana. NJAS Wageningen J. Life Sci.86-87, 51–63. 10.1016/j.njas.2018.07.002

  • CrossRef
  • Google Scholar

• 68

  NyamboB.ChengulaF. (2017). Dissemination of agricultural weather forecasts under weather and climate variability: A case of the smallholder farmers in moshi rural district, Tanzania.

  • Google Scholar

• 69

  Nyang'auJ. O.MohamedJ. H.MangoN.MakateC.WangeciA. N. (2021). Smallholder farmers’ perception of climate change and adoption of climate smart agriculture practices in Masaba South Sub-county, Kisii, Kenya. Heliyon7, e06789. 10.1016/j.heliyon.2021.e06789

  • CrossRef
  • Google Scholar

• 70

  OchiengJ.KirimiL.MathengeM. (2016). Effects of climate variability and change on agricultural production: The case of small scale farmers in Kenya. NJAS Wageningen J. Life Sci.77, 71–78. 10.1016/j.njas.2016.03.005

  • CrossRef
  • Google Scholar

• 71

  OECD/FAO (2016). OECD-FAO agricultural outlook 2016-2025. Paris: OECD Publishing.

  • Google Scholar

• 72

  OuedraogoI.DioufN. S.AbloukaG.ZougmoréR. B.WhitbreadA. (2021). Utility and triggers in uptake of agricultural weather and climate information services in Senegal, West Africa. Atmosphere12, 1515. 10.3390/atmos12111515

  • CrossRef
  • Google Scholar

• 73

  OuedraogoI.DioufN. S.OuédraogoM.NdiayeO.ZougmoréR. B. (2018). Closing the gap between climate information producers and users: Assessment of needs and uptake in Senegal. Climate6, 13. 10.3390/cli6010013

  • CrossRef
  • Google Scholar

• 74

  OyekaleA. S. (2015). Access to risk mitigating weather forecasts and changes in farming operations in East and West Africa: Evidence from a baseline survey. Sustainability7, 14599–14617. 10.3390/su71114599

  • CrossRef
  • Google Scholar

• 75

  ParkerL.BourgoinC.Martinez-ValleA.LäderachP. (2019). Vulnerability of the agricultural sector to climate change: The development of a pan-tropical Climate Risk Vulnerability Assessment to inform sub-national decision making. PloS one14, e0213641. 10.1371/journal.pone.0213641

  • CrossRef
  • Google Scholar

• 76

  ParkerD. J.BlythA. M.WoolnoughS. J.DougillA. J.BainC. L.de ConingE.et al (2021). The african SWIFT project: Growing science capability to bring about a revolution in weather prediction. Bull. Am. Meteorological Soc.103 (2), E349–E369.

  • Google Scholar

• 77

  ParteyS. T.DakorahA. D.ZougmoréR. B.OuédraogoM.NyasimiM.NikoiG. K.et al (2020). Gender and climate risk management: Evidence of climate information use in Ghana. Clim. Change158, 61–75. 10.1007/s10584-018-2239-6

  • CrossRef
  • Google Scholar

• 78

  RadenyM.DesalegnA.MubiruD.KyazzeF.MahooH.RechaJ.et al (2019). Indigenous knowledge for seasonal weather and climate forecasting across East Africa. Clim. Change156, 509–526. 10.1007/s10584-019-02476-9

  • CrossRef
  • Google Scholar

• 79

  RasmussenL. V.MertzO.RasmussenK.NietoH. (2015). Improving how meteorological information is used by pastoralists through adequate communication tools. J. Arid Environ.121, 52–58. 10.1016/j.jaridenv.2015.05.001

  • CrossRef
  • Google Scholar

• 80

  SanfoS.SalackS.SaleyI. A.DakuE. K.WorouN. O.SavadogoA.et al (2022). Effects of customized climate services on land and labor productivity in Burkina Faso and Ghana. Clim. Serv.25, 100280. 10.1016/j.cliser.2021.100280

  • CrossRef
  • Google Scholar

• 81

  SarkuR.van SlobbeE.TermeerK.ChudaskaR.SiwaleA.DewulfA. (2021). Tracing hybridity in the provision of ICT-enabled agricultural weather information services in Ghana. J. Agric. Food Inf.22, 1–31. 10.1080/10496505.2021.1874388

  • CrossRef
  • Google Scholar

• 82

  SarkuR.Van SlobbeE.TermeerK.Kranjac-BerisavljevicG.DewulfA. (2022). Usability of weather information services for decision-making in farming: Evidence from the Ada East District, Ghana. Clim. Serv.25, 100275. 10.1016/j.cliser.2021.100275

  • CrossRef
  • Google Scholar

• 83

  SenaA.BarcellosC.FreitasC.CorvalanC. (2014). Managing the health impacts of drought in Brazil. Int. J. Environ. Res. Public Health11, 10737–10751. 10.3390/ijerph111010737

  • CrossRef
  • Google Scholar

• 84

  SeoS. N. (2014). Evaluation of the Agro-Ecological Zone methods for the study of climate change with micro farming decisions in sub-Saharan Africa. Eur. J. Agron.52, 157–165. 10.1016/j.eja.2013.09.014

  • CrossRef
  • Google Scholar

• 85

  ShackletonS.ZiervogelG.SalluS.GillT.TschakertP. (2015). Why is socially-just climate change adaptation in sub-saharan Africa so challenging? A review of barriers identified from empirical cases. WIREs Clim. Change6, 321–344. 10.1002/wcc.335

  • CrossRef
  • Google Scholar

• 86

  SikhondzeW. B. (2020). Farmer perception of the effectiveness of the extension service in communicating climate change information, kingdom of Swaziland. Open Access Libr. J.7, 1–12. 10.4236/oalib.1106394

  • CrossRef
  • Google Scholar

• 87

  SinghC.DaronJ.BazazA.ZiervogelG.SpearD.KrishnaswamyJ.et al (2018). The utility of weather and climate information for adaptation decision-making: Current uses and future prospects in Africa and India. Clim. Dev.10, 389–405. 10.1080/17565529.2017.1318744

  • CrossRef
  • Google Scholar

• 88

  SultanB.GaetaniM. (2016). Agriculture in West Africa in the twenty-first century: Climate change and impacts scenarios, and potential for adaptation. Front. Plant Sci.7, 1262. 10.3389/fpls.2016.01262

  • CrossRef
  • Google Scholar

• 89

  TallA. (2010). Climate forecasting to serve communities in West Africa. Procedia Environ. Sci.1, 421–431. 10.1016/j.proenv.2010.09.030

  • CrossRef
  • Google Scholar

• 90

  TarchianiV.CoulibalyH.BakiG.SiaC.BurroneS.NikiemaP. M.et al (2021). Access, uptake, use and impacts of agrometeorological services in sahelian rural areas: The case of Burkina Faso. Agronomy11, 431. 10.3390/agronomy11122431

  • CrossRef
  • Google Scholar

• 91

  United Nations (2019). World population prospects 2019. Vol (ST/ESA/SE. A/424). New York, United States: Department of Economic and Social Affairs: Population Division.

  • Google Scholar

• 92

  WaindiI. O.KhalidA. (2011). Renewable energy in East Africa: An introductory evaluation using a systems approach to assess alternatives to providing electricity. J. Afr. Bus.12, 387–418. 10.1080/15228916.2011.621854

  • CrossRef
  • Google Scholar

• 93

  WamalwaI. W.MburuB. K.Mang’uriuD. G. (2016). Agro climate and weather information dissemination and its influence on adoption of climate smart practices among small scale farmers of Kisii country, Kenya. J. Biol. Agric. Healthc.6, 14–23.

  • Google Scholar

• 94

  WaterAid (2021). Climate change and water security in West Africa - Niger and Burkina Faso. Retrieved from: https://washmatters.wateraid.org/publications/water-security-address-climate-change-west-africa-niger-burkina-faso (Accessed on March 2, 2022.

  • Google Scholar

• 95

  WebberS. (2019). Putting climate services in contexts: Advancing multi-disciplinary understandings: Introduction to the special issue. Clim. Change157, 1–8. 10.1007/s10584-019-02600-9

  • CrossRef
  • Google Scholar

• 96

  WoodhamsB. J.BirchC. E.MarshamJ. H.BainC. L.RobertsN. M.BoydD. F. (2018). What is the added value of a convection-permitting model for forecasting extreme rainfall over tropical East Africa?Mon. Weather Rev.146, 2757–2780. 10.1175/mwr-d-17-0396.1

  • CrossRef
  • Google Scholar

• 97

  World Bank (2016). CPIA Africa - assessing africa's policies and institutions: 2015 CPIA results for Africa. Washington DC: World Bank Group.

  • Google Scholar

• 98

  World Meteorological Organisation [WMO] (2015). WMO guidelines on multi-hazard impact-based forecast and warning services. WMO Doc.1150, 34. Available from: https://library.wmo.int/doc_num.php?explnum_id=7901.

  • Google Scholar

• 99

  YegbemeyR. N.AloukoutouA. M.AïhountonG. B. (2021). The impact of short message services (SMS) weather forecasts on cost, yield and income in maize production. Afr. Development/Afrique Développement46, 163–188.

  • Google Scholar

• 100

  YomoM.MouradK. A.GnazouM. D. (2019). Examining water security in the challenging environment in Togo, West Africa. Water11, 231. 10.3390/w11020231

  • CrossRef
  • Google Scholar

• 101

  YoungM.HeinrichV.BlackE.AsfawD. (2020). Optimal spatial scales for seasonal forecasts over Africa. Environ. Res. Lett.15, 094023. 10.1088/1748-9326/ab94e9

  • CrossRef
  • Google Scholar

• 102

  ZongoB.DiarraA.BarbierB.ZoromM.YacoubaH.DogotT. (2016). Farmers' perception and willingness to pay for climate information in Burkina Faso. J. Agric. Sci. Tor.8, 175–187. 10.5539/jas.v8n1p175

  • CrossRef
  • Google Scholar