11 research outputs found
Afrique : comment les drones de livraison pourraient transformer les prévisions météo
No full texthttps://theconversation.com/afrique-comment-les-drones-de-livraison-pourraient-transformer-les-previsions-meteo-251285Alors que les données météo manquent cruellement en Afrique, une idée fait son chemin. Celle d'utiliser les drones, de plus en plus nombreux dans les ciels du continent pour livrer par exemple des médicaments. Car ces derniers peuvent fournir également de nombreuses données météo
Afrique : comment les drones de livraison pourraient transformer les prévisions météo
No full textAlors que les données météo manquent cruellement en Afrique, une idée fait son chemin. Celle d'utiliser les drones, de plus en plus nombreux dans les ciels du continent pour livrer par exemple des médicaments. Car ces derniers peuvent fournir également de nombreuses données météo
Multiscale Characteristics of West African Summer Monsoon Precipitation Derived from UCadMet Network Observations
No full textInternational audienceSince 2012 a joint Université Cheikh Anta Diop de Dakar and Universidad Complutense de Madrid meteorological observation network (UCadMet) has been in place in the city of Dakar (Senegal). During the last years, the observation and data storage systems have been considerably improved. Last summer of 2022, a laser disdrometer was installed providing detailed information on the size and speed of precipitation with a time resolution of one minute. Observations from several tipping bucket rain gauges are available also at the same site. Summer 2022 has been anomalously rainy in West Africa, with large precipitation events during the African monsoon season, which seems to be enhanced by a La Niña situation in the Pacific. These events have proven to be particularly suitable for evaluating the performance of the installed observing systems and for drawing some conclusions about the characteristics of monsoon precipitation in this region not only at different time scales, but also across scales (from 1 min to season). Commonly used rain rate together with drop size distribution are used to access information on rainfall microphysics. This analysis allows the design of future lines of action considering climate change, for which large precipitation events are expected to become more frequent
Rainy day funds? How men and women adapt to heavy rainfall shocks and the role of cash transfers in Mali
No full textWeather shocks can affect men and women differently, due in part to differences in their adaptive capacities. We merge weather data with survey data from a randomized control trial of a cash transfer program in Mali to describe how men and women cope with weather shocks and the role of cash transfer programs in supporting adaptive responses. We find that heavy rainfall reduces household’s consumption but that the cash transfer program mitigates these impacts, primarily by allowing households to draw down both men’s and women’s savings, increasing the value of livestock and farming assets held jointly by men and women, and facilitating a reallocation of men’s and women’s labor to livestock production and women’s labor to domestic work
Performance of dry and wet spells combined with remote sensing indicators for crop yield prediction in Senegal
No full textStudying the relationship between potential high-impact precipitation and crop yields can help us understand the impact of the intensification of the hydrological cycle on agricultural production. The objective of this study is to analyse the contribution of intra seasonal rainfall indicators, namely dry and wet spells, for predicting millet yields at regional scale in Senegal using multiple linear regression. Using dry and wet spells with traditional indicators i.e. proxies of crop biomass and cumulated rainfall, hereafter called remote sensing indicators (NDVI, SPI3, WSI and RG), we analysed the ability of dry and wet spells alone or combined with these remote sensing indicators to provide intraseasonal forecasts covering the period 1991–2010. We analysed all 12 regions producing millet and found that results vary strongly between regions and also during the season, as a function of the dekad of prediction. At the spatial scale, the strongest performing combinations include the dry spell indicators DSC20 and DSxl in the peanut basin. While in the south of the country, the combination of wet period indicators WS1 or WSC5 with the RG is fairly reliable. Focussing on Thies, our best region in the groundnut basin, we showed that dry and wet spells indicators can explain up to 80% of yield variations, alone or in combination with remote sensing indicators. Regarding the timing of prediction, millet yield can be forecast as early as July with an accuracy of 40% of the mean yield but the best forecast is obtained in early September, at the peak of crop development (accuracy of 100 kg/ha i.e. 20% of the mean yield). Although, the estimated yields show biases over some years identified as extremely deficient or in oversupply in terms of agricultural yields.JRC.D.5 - Food Securit
Regionalization of the Onset and Offset of the Rainy Season in Senegal Using Kohonen Self-Organizing Maps
No full textInternational audienceThis study explores the spatiotemporal variability of the onset, end, and duration of the rainy season in Senegal. These phenological parameters, crucial for agricultural planning in West Africa, exhibit high interannual and spatial variability linked to precipitation. The objective is to detect and spatially classify these indices across Senegal using different approaches. Daily precipitation data and ERA5 reanalyses from 1981 to 2018 were utilized. The employed method enables the detection of key dates. Subsequently, the Kohonen algorithm spatially classifies these indices on topological maps. The results indicate a meridional gradient of the onset, progressively later from the southeast to the northwest, whereas the end follows a north–south gradient. The duration varies from 45 days in the north to 150 days in the south. The use of self-organizing maps allows for classifying the onset, end, and duration of the season into four zones for the onset and end, and three zones for the duration of the season. They highlight the interannual irregularity of transitions, with both early and late years. The dynamic analysis underscores the complex influence of atmospheric circulation fields, notably emphasizing the importance of low-level monsoon flux. These findings have tangible implications for improving seasonal forecasts and agricultural activity planning in Senegal. They provide information on the onset, end, and duration classes for each specific zone, which can be valuable for planning crops adapted to each region
Performance of dry and wet spells combined with remote sensing indicators for crop yield prediction in Senegal
No full textStudying the relationship between potential high-impact precipitation and crop yields can help us understand the impact of the intensification of the hydrological cycle on agricultural production. The objective of this study is to analyse the contribution of intra seasonal rainfall indicators, namely dry and wet spells, for predicting millet yields at regional scale in Senegal using multiple linear regression. Using dry and wet spells with traditional indicators i.e. proxies of crop biomass and cumulated rainfall, hereafter called remote sensing indicators (NDVI, SPI3, WSI and RG), we analysed the ability of dry and wet spells alone or combined with these remote sensing indicators to provide intraseasonal forecasts covering the period 1991–2010. We analysed all 12 regions producing millet and found that results vary strongly between regions and also during the season, as a function of the dekad of prediction. At the spatial scale, the strongest performing combinations include the dry spell indicators DSC20 and DSxl in the peanut basin. While in the south of the country, the combination of wet period indicators WS1 or WSC5 with the RG is fairly reliable. Focussing on Thies, our best region in the groundnut basin, we showed that dry and wet spells indicators can explain up to 80% of yield variations, alone or in combination with remote sensing indicators. Regarding the timing of prediction, millet yield can be forecast as early as July with an accuracy of 40% of the mean yield but the best forecast is obtained in early September, at the peak of crop development (accuracy of 100 kg/ha i.e. 20% of the mean yield). Although, the estimated yields show biases over some years identified as extremely deficient or in oversupply in terms of agricultural yields
Case Study of Coastal Fog Events in Senegal Using LIDAR Ceilometer
No full textThis study aims to examine the atmospheric conditions characterising fog phenomena on the Senegalese coast focusing on two specific instances that occurred on April 3 and April 30, 2023. These events were detected by the LIDAR Ceilometer installed at LPAOSF/ESP/UCAD and confirmed on the METARs of the meteorological stations at Dakar and Diass airports. The LIDAR's backscatter signal showed that the fog of April 3 started around midnight with a vertical extension at 100 m altitude and dissipated around 10 a.m. The April 30 event characterized by a good vertical extension from the surface up to 300 m above sea level, was triggered just after 2 a.m. and lasted around 3 hours. The results showed that a decrease in temperature, accompanied by an increase in humidity and light wind, is favorable for the triggering and persistence of fog. Sea Level Pressure (SLP) anomaly fields show two distinct configurations. The April 3 event was characterized by a zonal dipole of SLP anomalies between the Sahara and the northern Senegalese coast, while the April 30 event was characterized by a meridional dipole between the Sahara and the Gulf of Guinea area as far as the equatorial Atlantic. A weakening of the pressure around the study area was observed in both cases, allowing moisture advection to favor the onset of fog. The hovmoller diagrams of relative humidity and wind show that a good vertical extension of humidity associated with a westerly wind in the lower layers plays an important role in the formation and persistence of fog. The presence of dry air associated with a weak easterly wind in the middle layers could explain the low vertical extension of the fog on April 3. A strong wind in the lower layers would be responsible for the premature dissipation of the April 30 fog
Predictability of Intra-Seasonal Descriptors of Rainy Season over Senegal Using Global SST Patterns
No full textSeasonal forecasting of the rainfall characteristics in Sahel is of crucial interest in determining crop variability in these countries. This study aims to provide further characterization of nine rainfall metrics over Senegal (Onset, cessation, LRS, CDD, CDD7, CDD15, NR90p, NR95p, NR99p) and their response to global SST patterns from 1981 to 2018. The Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) dataset and the Hadley Centre Global Sea Ice and Sea Surface Temperature (HadISST) were used. The results showed strong spatio-temporal variability with a pronounced south–north gradient for all metrics. The earliest onset was observed in the south of the country from 4 July and the latest onset in the north from 9 August. Since 2012, a new regime is observed with an increase in both long dry spells and extreme wet events. Furthermore, SST forcing has shown that the North tropical Atlantic and the East Equatorial Pacific are better able to explain the interannual variability of the intraseasonal descriptors. However, the prediction of metrics is earlier for the most remote basin (Pacific) compared to the most local basin (Atlantic). These results have implications for the seasonal forecasting of Sahel’s intraseasonal variability based on SST predictors, as significant predictability is found far from the beginning of the season
