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Abstract: Scientifically sound decisions in sustainable water management are usually based on hydrological modeling which can only be accomplished by meteorological driving information. Especially in regions with weak infrastructure this task is hampered by limited hydro-meteorological information in sufficient spatial and temporal resolution. We investigated three approaches to provide required meteorological fields driving the distributed hydrological model: the results of the mesoscale meteorological model MM5 which are available near real time, the TRMM product 3B42 available with approximately one month delay, and station data available with a delay of one year or more. The study site is the White Volta catchment in the semi-arid environment of West Africa. The results for 2004 show that the meteorological model is able to provide meteorological input data for near real time water balance estimations. In this study the TRMM product does not improve the simulation results. Besides missing important meteorological data, also gridded information on land surface properties (albedo, LAI, etc.) is usually difficult to obtain, albeit it is an essential input for distributed hydrological models. This information is commonly taken from “static” tables depending on the land use. Satellite remote sensing provides worldwide spatially detailed information on land surface properties which is particularly suitable for large regions in remote settings. Therefore the MODIS products for albedo and LAI were processed to annual time series including the identification and replacement of low quality observations by interpolation. The impact using MODIS data on the spatial distribution of water balance variables occurs mainly on local scale. The hydrological simulations using MODIS LAI and albedo values result in higher annual evapotranspiration and lower total discharge sums for 2004. Altogether it is concluded that hydrological decision support systems in regions with weak infrastructure can benefit significantly from the integration of atmospheric modeling and satellite-derived land surface data. [Copyright &y& Elsevier]

The number of solar power plants has increased in West Africa in recent years. Reliable reanalysis data and short-term forecasting of solar irradiance from numerical weather prediction models could provide an economic advantage for the planning and operation of solar power plants, especially in data-poor regions such as West Africa. This study presents a detailed assessment of different shortwave (SW) radiation schemes from the Weather Research and Forecasting (WRF) Model option Solar (WRF-Solar), with appropriate configurations for different atmospheric conditions in Ghana and the southern part of Burkina Faso. We applied two 1-way nested domains (D1 = 15 km and D2 = 3 km) to investigate four different SW schemes, namely, the Community Atmosphere Model, Dudhia, RRTMG, Goddard, and RRTMG without aerosol and with aerosol inputs (RRTMG_AERO). The simulation results were validated using hourly measurements from different automatic weather stations established in the study region in recent years. The results show that the RRTMG_AERO_D01 generally outperforms the other SW radiation schemes to simulate global horizontal irradiance under all-sky condition [RMSE = 235 W m−2 (19%); MAE = 172 W m−2 (14%)] and also under cloudy skies. Moreover, RRTMG_AERO_D01 shows the best performance on a seasonal scale. Both the RRTMG_AERO and Dudhia experiments indicate a good performance under clear skies. However, the sensitivity study of different SW radiation schemes in the WRF-Solar model suggests that RRTMG_AERO gives better results. Therefore, it is recommended that it be used for solar irradiance forecasts over Ghana and the southern part of Burkina Faso. [ABSTRACT FROM AUTHOR]

Classification of atmospheric circulation patterns (CP) is a common tool for downscaling rainfall, but it is rarely used for West Africa. In this study, a two‐step classification procedure is proposed for this region, which is applied from 1989 to 2010 for the Sudan‐Sahel zone (Central Burkina Faso) with a focus on heavy rainfall. The approach is based on a classification of large‐scale atmospheric CPs (e.g., Saharan Heat Low) of the West African Monsoon using a fuzzy rule‐based method to describe the seasonal rainfall variability. The wettest CPs are further classified using meso‐scale monsoon patterns to better describe the daily rainfall variability during the monsoon period. A comprehensive predictor screening for the seasonal classification indicates that the best performing predictor variables (e.g., surface pressure, meridional moisture fluxes) are closely related to the main processes of the West African Monsoon. In the second classification step, the stream function at 700 hPa for identifying troughs and ridges of tropical waves shows the highest performance, providing an added value to the overall performance of the classification. Thus, the new approach can better distinguish between dry and wet CPs during the rainy season. Moreover, CPs are identified that are of high relevance for daily heavy rainfall in the study area. The two wettest CPs caused roughly half of the extremes on about 6.5% of days. Both wettest patterns are characterized by an intensified Saharan Heat Low and a cyclonic rotation near the study area, indicating a tropical wave trough. Since the classification can be used to condition other statistical approaches used in climate sciences and other disciplines, the presented classification approach opens many different applications for the West African Monsoon region. [ABSTRACT FROM AUTHOR]

Estimates of global horizontal irradiance (GHI) from reanalysis and satellite-based data are the most important information for the design and monitoring of PV systems in Africa, but their quality is unknown due to the lack of in situ measurements. In this study, we evaluate the performance of hourly GHI from state-of-the-art reanalysis and satellite-based products (ERA5, MERRA-2, CAMS, and SARAH-2) with 37 quality-controlled in situ measurements from novel meteorological networks established in Burkina Faso and Ghana under different weather conditions for the year 2020. The effects of clouds and aerosols are also considered in the analysis by using common performance measures for the main quality attributes and a new overall performance value for the joint assessment. The results show that satellite data performs better than reanalysis data under different atmospheric conditions. Nevertheless, both data sources exhibit significant bias of more than 150 W/m2 in terms of RMSE under cloudy skies compared to clear skies. The new measure of overall performance clearly shows that the hourly GHI derived from CAMS and SARAH-2 could serve as viable alternative data for assessing solar energy in the different climatic zones of West Africa. [ABSTRACT FROM AUTHOR]

In sub-Saharan Africa, with its high rainfall variability and limited irrigation options, the crop planting date is a crucial tactical decision for farmers and therefore a major concern in agricultural decision making. To support decision making in rainfed agriculture, a new approach has been developed to optimize crop planting date. The General Large-Area Model for Annual Crops (GLAM) has been used for the first time to simulate maize yields in West Africa. It is used in combination with fuzzy logic rules to give more flexibility in crop planting date computation when compared with binary logic methods. A genetic algorithm is applied to calibrate the crop model and to optimize the planting dates at the end. The process for optimizing planting dates results in an ensemble of optimized planting rules. This principle of ensemble members leads to a time window of optimized planting dates for a single year and thereby potentially increases the willingness of farmers to adopt this approach. The optimized planting date (OPD) approach is compared with two well-established methods in sub-Saharan Africa. The results suggest earlier planting dates across Burkina Faso, ranging from 10 to 20 days for the northern and central part and less than 10 days for the southern part. With respect to the potential yields, the OPD approach indicates that an average increase in maize potential yield of around 20% could be obtained in water-limited regions in Burkina Faso. The implementation of the presented approach in agricultural decision support is expected to have the potential to improve agricultural risk management in these regions dominated by rainfed agriculture and characterized by high rainfall variability. [ABSTRACT FROM AUTHOR]

Abstract: Savannahs are highly dynamic ecosystems but many of their properties and the related balances of energy, carbon, nitrogen, and water are still poorly understood. A particular scientific issue is the quantification of trace gases emitted from the soil of savannah ecosystems and their interaction with regional and global climate and air chemistry. Therefore it is important to develop and evaluate land-surface models that on the one hand represent vegetation and soil dynamics and on the other hand provide energy and water fluxes in a temporal resolution suitable for the application in climate/air chemistry models. In this paper, we present a consistent coupling between a common land-surface model (OSU) and a widely used biogeochemical model (DNDC) that is a first step for a full coupling of climate/air chemistry and biogeochemical processes. For consistency reasons, both models are linked to a general physiologically based plant model to provide the physical boundary conditions as well as the carbon and nitrogen in- and output variables. Evaluation is carried out with measurements of soil temperature, latent heat flux, soil water content, and soil emission data from two vegetation periods collected at a natural grassland site in Bontioli Nature Reserve, Burkina Faso (Africa). The results demonstrate that simulations of biogeochemical processes based on soil environmental conditions, calculated either with the land-surface model or with the unchanged biogeochemical model, do not differ significantly from each other. The OSU model simulates more realistic day-to-day variation of soil temperature as DNDC but the sensitivity of the biogeochemical simulation to this variation is small. In contrast, the sensitivity to differences in soil water content is high, but simulation results of both models are very similar on the daily scale and hardly depend on spatial soil resolution. [Copyright &y& Elsevier]

West Africa's Sudanian savannas are one of Africa's high-potential "bread baskets", where surplus food (e.g. millet, sorghum, cowpea and livestock) is being produced. These ecosystems currently undergo pronounced land use changes and will likely face shorter rainy seasons with more extreme rainfall and droughts in the future. This could have serious impacts on the vegetation and its carbon dioxide (CO2) exchange with potentially increasing CO2 emissions accelerating climate warming. Understanding how the CO2 fluxes in this area respond to land use changes and environmental fluctuations, in particular rain events, is essential to design sustainable land use strategies. However, this understanding is hampered by a limited data availability. In this study, we monitored net ecosystem exchange (NEE) of CO2, rainfall and other weather and vegetation parameters during four years (2013-2016) at three savanna sites in southern Burkina Faso and northern Ghana. To this end, a monitoring network of three eddy-covariance stations and nine automatic weather stations was established. The three savannas were characterized by different vegetation due to different land use: i) woody and nearly pristine, ii) a mixture of cropland and grassland and iii) grassland under intensive grazing. Other site characteristics such as climate, soil, or topography chosen were as similar as possible. The impact of rain events on CO2 exchange for these three contrasting ecosystems was analyzed for single rain events (short-term) and on a yearly time scale (long-term). We found that the pristine savanna site was a prominent sink of CO2 (-864 to 605 g CO2 m-2 y-1) while the two degraded sites were net CO2 sources (118 to 605 g CO2 m-2 y-1) with a complex relation with annual rainfall amounts. The NEE responses to single rain events revealed that daytime rain systematically decreased the sink strengths at all sites, which might be associated with decreased light availability. At the degraded sites, additional factors increasing CO2 losses were rain duration and dry spell length. The observed patterns of immediate CO2 flux responses to rainfall at differently used savannas indicate strong internal feedbacks between vegetation and land use changes and raise the question whether the CO2 sink potentials might be overestimated with possible implications for global CO2 budgets. Our findings also suggest that carbon sequestration needs to be taken into account when designing sustainable land-use strategies. [ABSTRACT FROM AUTHOR]

Large-scale experimental sites for studying Critical Zone processes are relatively rare for savannas. However, they are essential for a better understanding of environmental changes and their impacts on ecosystem functioning and services. This study gives an overview of a novel field observatory which was established for mesoscale watersheds in the Sudan Savanna near the border of Burkina Faso and Ghana as part of the WASCAL (West African Science Service Centre on Climate Change and Adapted Land Use) programme. The study area is characterized by severe land cover changes due to a strongly increasing demand of agricultural land. The observatory is designed for long-term measurements of selected eco-hydrological processes in fine temporal resolution focusing on land-atmosphere exchange processes. It consists of a network of automatic weather stations, agro-meteorological stations, eddy covariance towers and various hydrological measurement devices, which are complemented by long-term historical measurements from national meteorological and hydrological networks. A unique component of the observatory is a micrometeorological experiment using the eddy covariance towers which is conducted since the initiation of the observatory in 2013. The experiment was implemented at three contrasting sites with different vegetation cover and contrasting land use practices (pristine savanna, mixture of cropland, degraded grassland) to investigate the impact of land use changes on water, energy, and CO2 fluxes. Moreover, the datasets of the new observatory are the basis of various field, data analysis and modelling studies conducted by other disciplines (i.e. agriculture, biology, ecology, remote sensing) in this region and are made available via a new database, the WASCAL Data Discovery Portal. The new large-scale field experiment also forms an excellent platform for future field campaigns and long-term experimental sites and can be used as foundation for an observatory that addresses key processes and components of the Critical Zone. In this presentation we give a detailed overview about the new field observatory with its different components and its advantages and drawbacks in comparison to other large-scale experimental sites for savanna ecosystems (e.g. AMMA catch observatory). In addition, recent outcomes from the long-term micro-meteorological field experiment are shown. Finally, the current challenges and future perspectives are addressed for operating this type of observatory in this region. [ABSTRACT FROM AUTHOR]