Search Results (12)

Ethiopian pastoralist communities are facing a recurrent drought crisis that significantly affects the availability of water and pasture resources for communities dependent on livestock. The increasing intensity, duration and frequency of droughts in the pastoral community in Ethiopia have drawn the attention of multiple stakeholders and increased stakeholder debates on the role of early warning systems (EWSs) for anticipatory action to build climate resilience in the pastoral community. The Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT), in collaboration with various partners, has developed an interactive web-based digital EWS to provide near real-time information on water and pasture conditions in pastoral and agro-pastoral regions of Ethiopia. In this study, a stakeholder analysis was conducted to identify key stakeholders, understand stakeholder needs, and facilitate collaboration towards sustaining the EWS. The stakeholder analysis revealed the roles and information needs of key actors engaged in livestock water and pasture monitoring and early warning systems aimed at improving the pastoral communities’ resilience. The analysis showed a pressing need for access to real-time information on water and pasture availability and seasonal climate forecasts by local communities for effective and optimal resources management. Local and national governments need similar data for evidence-based decision-making in resource allocation and policy development. International and non-governmental organizations (INGOs) require the same information for efficient humanitarian responses and targeted development interventions. The private sector seeks insights into market dynamics to better align production strategies with community needs. An EWS serves as a vital tool for development partners, facilitating improved planning, coordination, and impact assessment. It also emphasizes the importance of proactive collaboration among stakeholders, including local communities, government bodies, INGOs, and academic and research institutions. Enhanced communication strategies, such as partnerships with local media, are essential for timely information dissemination. Ultimately, sustained collaboration and adaptive strategies are crucial for optimizing the impact of an EWS towards improving the livelihoods and resilience of pastoral communities amid climate variability. Full article

Drought is one of the most challenging disasters that impact the natural and cultural ecosystems across the world, especially in the climate dependent sectors of arid and semi-arid areas. The aim of this article is to share the experiences gained and enhance the readers’ awareness on the status of drought and process of the early warning systems (EWS) in south India. Drought status of three agroecologically different states is included in this article, such as Kerala, Tamil Nadu and Telangana. As far as Tamil Nadu is concerned, Karur, Thuthukudi, Krishnagiri, Namakkal, Trichy and Thirunelveli districts are water scarce compared to other districts in the state. The districts such as Wayanad, Thiruvananthapuram, Idukki and Palakkad in Kerala have received lesser rainfall compared to the other parts of the state during the period 1981 to 2019. In Telangana, the mandals such as Nagarkurnool, Jogulamba-Gadwal, Wanaparthy, Mahabubnagar Nalgonda and Yedadri are frequently hit by dry spells and droughts. As a case study, weather early warning dissemination, carried out at Parambikulam Aliyar basin, Coimbatore, Tamil Nadu, during Khariff and Rabi seasons, using IMDs medium and extended range forecast is also elaborated in particular in the article. As far as the accuracy of forecast is concerned, probability of false detection (false alarm rate) was found to be 0.81 for Khariff and 0.30 for Rabi season, indicating the need for better performance in the accuracy of dry spell early warning, disaster preparedness and response. In-spite of this, access to early warning has supported the farmers during harvest and land preparation with a utility score of 72% and 59%, respectively. In Parambikulam Aliyar basin, remote sensing products such as MODIS-NDVI, NDWI and TWI was also used to identify the real-time progression of monthly vegetative condition for Kharif and Rabi seasons. NDVI values were used to monitor the district level vegetation condition and compared it with the drought year 2016, the difference in area under barren land was 76% less during Khariff, 2021 and 44% during Rabi, 2021.This study is a compilation of lessons learned from different states and the existing knowledge and practice in early warnings, and recommends the need for a holistic approach in drought and dry spell monitoring along with better accuracy and dissemination to minimize climate-related shocks in agriculture. Full article

In Niger (a fully Sahelian country), the use of climate information is one of the early warning strategies (EWSs) for reducing socio-economic vulnerabilities in farmer communities. It helps farmers to better anticipate risks and choose timely alternative options that can allow them to generate more profit. This study assesses the impacts of the use of climate information and services that benefit end-users. Individual surveys and focus groups were conducted with a sample of 368 people in eight communes in Southwestern Niger. The survey was conducted within the framework of the ANADIA project implemented by the National Meteorological Direction (NMD) of Niger. The survey aims to identify different types of climate services received by communities and evaluates the major benefits gained from their use. Mostly, the communities received climate (73.6%) and weather (99%) information on rainfall, temperature, dust, wind, clouds, and air humidity. Few producers in the area (10%) received information on seasonal forecasts of the agrometeorological characteristics of the rainy season. The information is not widely disseminated in the villages during the roving seminars conducted by the NMD. For most people, this information is highly relevant to their needs because of its practical advice for options to be deployed to mitigate disasters for agriculture, livestock, health, water resources, and food security. In those communities, 82% of farmers have (at least once) changed their routine practices as a result of the advice and awareness received according to the climate information. The information received enables farmers (64.4%) to adjust their investments according to the profile of the upcoming rainfall season. The use of climate information and related advice led to an increase of about 64 bunches (equivalent to 10 bags of 100 kg) in annual millet production, representing an income increase of about 73,000 FCFA from an average farmland of 3 ha per farmer. In addition, the use of climate information helps to reduce the risks of floods and droughts, which often cause massive losses to crop production, animal and human life, infrastructure, materials, and goods. It has also enabled communities to effectively manage seeds and animal foods and to plan social events, departures and returns to rural exodus. These analyses confirm that the use of climate information serves as an EWS that contributes to increasing the resilience of local populations in the Sahel. Full article

Climate change is often linked with record-breaking heavy or poor rainfall events, unprecedented storms, extreme day and night time temperatures, etc. It may have a marked impact on climate-sensitive sectors and associated livelihoods. Block-level weather forecasting is a new-fangled dimension of agrometeorological services (AAS) in the country and is getting popularized as a climate-smart farming strategy. Studies on the economic impact of these microlevel advisories are uncommon. Agromet advisory services (AAS) play a critical role as an early warning service and preparedness among the maize farmers in the Parambikulam–Aliyar Basin, as this area still needs to widen and deepen its AWS network to reach the village level. In this article, the responses of the maize farmers of Parambikulam–Aliyar Basin on AAS were analyzed. AAS were provided to early and late Rabi farmers during the year 2020–2022. An automatic weather station was installed at the farmers’ field to understand the real-time weather. Forecast data from the India Meteorological Department (IMD) were used to provide agromet advisory services. Therefore, the present study deserves special focus. Social media and other ICT tools were used for AAS dissemination purposes. A crop simulation model (CSM), DSSAT4.7cereal maize, was used for assessing maize yield in the present scenario and under the elevated GHGs scenario under climate change. Our findings suggest that the AAS significantly supported the farmers in sustaining production. The AAS were helpful for the farmers during the dry spells in the late samba (2021–2022) to provide critical irrigation and during heavy rainfall events at the events of harvest during early and late Rabi (2021–22). Published research articles on the verification of weather forecasts from South India are scanty. This article also tries to understand the reliability of forecasts. Findings from the verification suggest that rainfall represented a fairly good forecast for the season, though erratic, with an accuracy score or HI score of 0.77 and an HK score of 0.60, and the probability of detection (PoD) of hits was found to be 0.91. Verification shows that the forecasted relative humidity observed showed a fairly good correlation, with an R² value of 0.52. These findings suggest that enhancing model forecast accuracy can enhance the reliability and utility of AAS as a climate-smart adaptation option. This study recommends that AAS can act as a valuable input to alleviate the impacts of hydrometeorological disasters on maize crop production in the basin. There is a huge demand for quality weather forecasts with respect to accuracy, resolution, and lead time, which is increasing across the country. Externally funded research studies such as ours are an added advantage to bridge the gap in AAS dissemination to a great extent. Full article

This study integrated local and scientific knowledge to assess the impacts of climate change and variability on food security in West Pokot County, Kenya from 1980–2012. It characterized rainfall and temperature from 1980–2011 and the phenology of agricultural vegetation, assessed land use and land cover (LULC) changes, and surveyed local knowledge and perceptions of the relationships between climate change and variability, land use decisions, and food (in)security. The 124 respondents were aware of long-term changes in their environment, with 68% strongly believing that climate has become more variable. The majority of the respondents (88%) reported declining rainfall and rising temperatures, with respondents in the lowland areas reporting shortened growing seasons that affected food production. Meteorological data for 1980–2011 confirmed high inter-annual rainfall variability around the mean value of 973.4 mm/yr but with no notable trend. Temperature data showed an increasing trend between 1980 and 2012 with lowlands and highlands showing changes of +1.25 °C and +1.29 °C, respectively. Land use and land cover changes between 1984 and 2010 showed cropland area increased by +4176% (+33,138 ha), while grassland and forest areas declined by –49% (–96,988 ha) and –38% (–65,010 ha), respectively. These area changes illustrate human-mediated responses to the rainfall variability, such as increased stocking after good rainfall years and crop area expansion. The mean Normalized Difference Vegetation Index (NDVI) values ranged from 0.36–0.54 within a year, peaking in May and September. For weather-related planning, respondents relied on radio (64%) and traditional forecasters (26%) as predominant information sources. Supporting continuous climate change monitoring, intensified early warning systems, and disseminating relevant information to farmers could help farmers adopt appropriate adaptation strategies. Full article

Weather and climate information services (WCIS) are gaining recognition among scientists and governments as an essential adaptation tool for agriculture, especially in the drylands of Africa. In Senegal, the widespread production and dissemination of WCIS was initiated in 2015 to cover the agricultural, pastoral and fishing sectors. This paper analyzes the types of decisions made by WCIS users, their preferences and level of satisfaction, and explores the triggers of agricultural WCIS adoption. We collected data during the onset and cessation of the rainy seasons to understand the utility and reliability of WCIS by farmers across all stages of the growing season. Data were analyzed using descriptive statistics. A binary logistic regression was tested to understand the socio-economic triggers in uptake of WCIS. Results showed that rainfall forecast is the most preferred WCIS (49% of the respondents) followed by extreme wind forecast. At the beginning of the rainy season, nearly 80% of the respondents have chosen the sowing date and about 60% have chosen crop varieties based on disseminated WCIS. In the middle of the growing season, about 70% of the respondents used WCIS to decide on fertilizer application dates. Results also showed that age and level of education, being trained on WCIS use, membership to farmers’ organizations, owning a radio have a significant effect on WCIS-based decision-making. These factors are essential for triggering the uptake of WCIS, and therefore are required to improve the implementation of existing weather climate services in Africa. Full article

Smallholder farmers in Ethiopia are vulnerable to climate change impacts due to their low adaptive capacity and dependence on rainfed agriculture. Thus, a successful weather forecast system may bring significant economic and social value to the community. The main objectives of this study were to identify the key information exchange agents, understand the information flow path, rank the relative importance of the different information dissemination pathways, and determine weather forecast adoption. We conducted a household survey in five villages of Rim Kebele in Bahir Dar area and found that farmers communicate with four main agents with regard to information exchange. We developed an agent-based model to learn the adoption rates of weather forecast information. Agriculture extension agents were found to be the most influential members of the community. Farmers’ communicating with neighboring village farmers showed higher adoption. Our results show at least twice that improvements in communication network attain higher adoption rates. Radio has also demonstrated positive uptake of information. We also found that forecast accuracy of 70% is sufficient to achieve high adoption rates. Our findings might help decision-makers recognize critical information flow pathways and their relative importance, and identify barriers to disseminating weather forecast information in the community. Full article

Geo-Kompsat-2A (Geostationary-Korean Multi-Purpose SATtellite-2A, GK2A), a new generation of Korean geostationary meteorological satellite, carry state-of-the-art optical sensors with significantly higher radiometric, spectral, and spatial resolution than the Communication, Ocean, and Meteorological Satellite (COMS) previously available in the geostationary orbit. The new Advanced Meteorological Imager (AMI) on GK2A has 16 observation channels, and its spatial resolution is 0.5 or 1 km for visible channels and 2 km for near-infrared and infrared channels. These advantages, when combined with shortened revisit times (around 10 min for full disk and 2 min for sectored regions), provide new levels of capacity for the identification and tracking of rapidly changing weather phenomena and for the derivation of quantitative products. These improvements will bring about unprecedented levels of performance in nowcasting services and short-range weather forecasting systems. Imagery from the satellites is distributed and disseminated to users via multiple paths, including internet services and satellite broadcasting services. In post-launch performance validation, infrared channel calibration is accurate to within 0.2 K with no significant diurnal variation using an approach developed under the Global Space-based Inter-Calibration System framework. Visible and near infrared channels showed unexpected seasonal variations of approximately 5 to 10% using the ray matching method and lunar calibration. Image navigation was accurate to within requirements, 42 µrad (1.5 km), and channel-to-channel registration was also validated. This paper describes the features of the GK2A AMI, GK2A ground segment, and data distribution. Early performance results of AMI during the commissioning period are presented to demonstrate the capabilities and applications of the sensor. Full article

This paper describes a quasi-operational regional air quality forecasting system for the contiguous United States (CONUS) developed at the National Center for Atmospheric Research (NCAR) to support air quality decision-making, field campaign planning, early identification of model errors and biases, and support the atmospheric science community in their research. This system aims to complement the operational air quality forecasts produced by the National Oceanic and Atmospheric Administration (NOAA), not to replace them. A publicly available information dissemination system has been established that displays various air quality products, including a near-real-time evaluation of the model forecasts. Here, we report the performance of our air quality forecasting system in simulating meteorology and fine particulate matter (PM_2.5) for the first year after our system started, i.e., 1 June 2019 to 31 May 2020. Our system shows excellent skill in capturing hourly to daily variations in temperature, surface pressure, relative humidity, water vapor mixing ratios, and wind direction but shows relatively larger errors in wind speed. The model also captures the seasonal cycle of surface PM_2.5 very well in different regions and for different types of sites (urban, suburban, and rural) in the CONUS with a mean bias smaller than 1 µg m⁻³. The skill of the air quality forecasts remains fairly stable between the first and second days of the forecasts. Our air quality forecast products are publicly available at a NCAR webpage. We invite the community to use our forecasting products for their research, as input for urban scale (<4 km), air quality forecasts, or the co-development of customized products, just to name a few applications. Full article

Agriculture production in Nigerien rural areas mainly depends on weather variability. Weather forecasts produced by national or international bodies have very limited dissemination in rural areas and even if broadcast by local radio, they remain generic and limited to short-term information. According to several experiences in West Africa, weather and climate services (WCSs) have great potential to support farmers’ decision making. The challenge is to reach local communities with tailored information about the future weather to support strategic and tactical crop management decisions. WCSs, in West Africa, are mainly based on short-range weather forecasts and seasonal climate forecasts, while medium-range weather forecasts, even if potentially very useful for crop management, are rarely produced. This paper presents the results of a pilot initiative in Niger to reach farming communities with 10-day forecasts from the National Oceanic and Atmospheric Administration—Global Forecast System (NOAA-GFS) produced by the National Centers for Environmental Prediction (NCEP). After the implementation of the download and treatment chain, the Niger National Meteorological Directorate can provide 10-day agrometeorological forecasts to the agricultural extension services in eight rural municipalities. Exploiting the users’ evaluation of the forecasts, an analysis of usability and overall performance of the service is described. The results demonstrate that, even in rural and remote areas, agrometeorological forecasts are valued as powerful and useful information for decision-making processes. The service can be implemented at low cost with effective technologies making it affordable and sustainable even in developing countries. Nonetheless, the service’s effectiveness depends on several aspects mainly related to the way information is communicated to the public. Full article

Climate information is recognized as a powerful tool to reduce the effect of climate risk and uncertainty on crop production and increase the resilience and the adaptive capacity of farmers in semi-arid zones. This paper estimates farmers’ willingness to pay (WTP) for climate information within cowpea and sesame value chains in Northern Burkina Faso. The study used the contingent valuation method for a monetary valuation of farmers’ preferences for climate information. Data were collected using a structured questionnaire from 170 farmers. The study found that 63% of respondents were willing to pay for climate information services (CIS) such as seasonal climate forecast (SCF), decadal climate information (10-DCI), daily climate information (1-DCI) and agro-advisories. The predicted value for the WTP was XOF 3496 for SCF, XOF 1066 for 10-DCI, XOF 1985 for 1-DCI and XOF 1628 for agro-advisories. The study also showed that several socioeconomic and motivation factors have greater influence on farmers’ WTP for CIS. These included the gender, age, education of the farm head and the awareness of farm head to climate information. The outcomes of this paper should support policy makers to better design an efficient mechanism for the dissemination of climate information to improve the adaptive capacity of farmers to climate risks in Burkina Faso. Full article

Smallholder farmers in East Africa need information and knowledge on appropriate climate-smart agriculture (CSA) practices, technologies, and institutional innovations in order to effectively adapt to changing climatic conditions and cope with climate variability. This paper assesses farmer adoption of climate-smart agricultural practices and innovation after being exposed to Farms of the Future Approach (FotF). First; we explore and assess the various CSA technologies and practices; including institutional innovations farmers are adopting. Second; we identify and document farmer learning and dissemination pathways that can enhance adoption of CSA technologies and practices. Third; we identify existing institutions that enhance adoption of CSA practices. We use household survey data, complemented by qualitative information from focus group discussions and key informant interviews. The results show farmers are adopting a variety of CSA technologies, practices, and institutional innovations to after participating in the FotF approach with use of improved crop varieties, agroforestry, and scientific weather forecast information cited as the main practices. To minimize their risks and reduce vulnerabilities, farmers are diversifying and integrating five to 10 CSA practices in one season. Matengo pits, SACCOs, and efficient energy stoves were adopted by very few farmers due to their high initial investment costs and unsuitability to the area. Ninety-eight percent of farmers reported that they receive agricultural information orally from a variety of sources including government extension workers, seed companies, researchers, traditional experts, neighbors, radio agricultural shows, religious groups, farmer groups, and family members. Lastly, farmers reported that the FotF approach is a useful tool that enabled them to interact with other farmers and learn new CSA practices and innovations. Suggested improvements to make on the FotF included include longer trip duration, increased number of farmer participants, and gender balance and age considerations to include youth. Full article