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It is expected that global climate change will increase the probability of extreme hydrometeorological events like droughts and floods. In order to adapt to this changing climate and to maintain basic water-, power-, and food supply, especially water-scarse regions require reliable knowledge about the available freshwater resources and potential extreme events during the next season. However, the headwaters of semi-arid catchments are often characterized by complex terrain and strong topographic gradients. To predict seasonal extreme events in such regions, hydrological models require high-resolution forecasts of precipitation and temperature. A 35 km horizontal resolution of the latest global seasonal forecast products is not suited for regional hydrological applications in such catchments. Therefore, it is mandatory to improve the spatial resolution of the hydrometeorological information to better represent the regional conditions in river basins with complex terrain. In particular, if such information is used as driving data in a one-way coupled model chain with subsequent hydrological models, a high-resolution and high-quality meteorological input is a key factor.In this study, we demonstrate the concept of achieving this improved and regionalized meteorological input. For eight river basins in semi-arid regions like Iran, Brazil, Sudan, and West-Africa, we perform a dynamical downscaling of the global atmospheric fields with the use of the Weather Research and Forecasting (WRF) model. The best possible regionalization of the global fields is identified by testing up to 32 parameterization combinations of the WRF model for different representations of subgrid-scale convection, cloud microphysics, radiation physics and boundary layer physics for each individual region. For these configuration runs we use ERA-Interim re-analyses which also serve as the initialization for the latest seasonal predictions of the European Centre for Medium-Range Weather Forecasts (ECMWF SEAS5) re-forecasts. Five consecutive years for each of the 32 parameterization combinations are simulated and their performance is analyzed with the use of local station data for identifying an optimized model setup for each region. Preliminary results already indicate that this identified configuration does not only depend on the performance of the modeled meteorological information, but also on the required computation time that strongly differs between the individual configurations. With this optimized WRF setup for each region, we finally downscale the global SEAS5 forecasts and thereby provide the regionalized input for the subsequent hydrological model systems. Our study is the first step towards an one-way coupled model chain that finally allows to provide high-resolution hydrometeorological and hydrological forecasts for the next season. In the end, this derived information has the potential to significantly improve the regional water management, especially in semi-arid regions and in the context of extreme events like e.g. droughts. [ABSTRACT FROM AUTHOR]

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]