The Mediterranean and Sahel regions are among the most sensitive areas to climate change as demonstrated in many studies (IPCC, 2013). Increased rainfall variability and ET rates will compromise irrigation potential and expansion plans and increased competition and conflict over limited water resources. There are significant knowledge gaps and uncertainties about how much water will be available for a complete growing season, how much should be used for scheduling irrigation efficiently and extracted from these regions. More information regarding water use is necessary to improve agricultural planning and to manage water more efficiently at different scales: farm and catchment/irrigation district level. Over both regions, the temperature increase will cause higher evaporation and transpiration rates, decreasing soil moisture and increasing crop water requirements. The expected impact in rainfed agriculture is a decrease in yield due to heat and water stress and an increase in the likelihood of crop failure in rainfed crops for maize, millet and sorghum (Parkes et al. 2018). Ongoing changes in the socio-economic and environmental background of rainfed farmers combined with the expected population growth make timely and reliable information on rainfed crop yield and its spatial variability essential in decision-support for improving food security and livelihoods. To this end, both understanding of the long term changes (inter-annual variability) and short-term changes (intra-annual variability) are needed. Temperature and precipitation changing patterns will also increase hazards linked to environmental conditions such as droughts, floods or crop pests like locust swarms. ACCWA aims to develop the remote sensing based monitoring tools for agriculture and water and management that help risk guidance in a climate change context.

Travelling Ionospheric Disturbances (TIDs) constitute a specific type of space weather disturbance affecting the performance of critical space and ground infrastructure by disrupting operations and communications in multiple sectors. T-FORS aims at providing new models able to interpret a broad range of observations of the solar corona, the interplanetary medium, the magnetosphere, the ionosphere and the atmosphere, and to issue forecasts and warnings for TIDs several hours ahead. Machine Learning techniques are used to train the models based on existing databases developed in the frames of past Horizon 2020 projects, to estimate the occurrence probability of medium scale TIDs and to forecast the occurrence and propagation of large scale TIDs. Prototype services are developed based on specifications from the users' community and following harmonized standards and quality control similar to the best practices of meteorological services. On ground demonstration tests are organised, by aerospace and civil protection agencies, to validate the performance of the T-FORS prototype services. A comprehensive architectural concept is proposed, including the densification of ground instrument networks, and new space missions, and possible future adjustments in order to develop a real-time operational service fully compliant and complementary to the ESA Space Weather services.

Travelling Ionospheric Disturbances (TIDs) constitute a threat for operational systems for which the ionosphere is an essential part (i.e., radio systems) or for which the ionosphere is fundamentally a nuisance (i.e. GNSS based systems and applications). The overarching objective of TechTIDE is to design and test new viable TID impact mitigation strategies for the technologies affected by the TIDs and in close collaboration with operators of these technologies, to demonstrate the added value of the proposed mitigation techniques which are based on TechTIDE products. To achieve this main goal, it is necessary to address the following specific objectives: i. Improve understanding regarding the physical processes resulting in the formation of TIDs, and consequently to identify the drivers in the interplanetary medium, the magnetosphere and the atmosphere; ii. Define the impact of the TIDs on the space based navigation systems (mainly EGNOS services and N-RTK) and on ground-based HF communication and geolocation systems; iii. Develop improved methodologies, based on consortium partners’ algorithms, suitable to support for the first time the direct,real-time identification and tracking of TIDs over wide world regions; iv. Establish an operational system to issue warnings of the occurrence of TIDs over the region extending from Europe to South Africa, to estimate the parameters that specify the TID characteristics and the inferred perturbation, and provide all additional geophysical information to the users to help them assess the risks and to develop mitigation techniques, tailored to their applications; v. Work systematically with potential users to assess the functionality, reliability and efficiency of the TechTIDE services paving the way to its systematic exploitation from users and to its sustainable operation.

PITHIA-NRF aims at building a European distributed network that integrates observing facilities, data processing tools and prediction models dedicated to ionosphere, thermosphere and plasmasphere research. For the first time, PITHIA-NRF integrates on a European scale, and opens up, to all European researchers, key national and regional research infrastructures such as EISCAT, LOFAR, Ionosondes and Digisondes, GNSS receivers, Doppler sounding systems, riometers, and VLF receivers, ensuring optimal use and joint development. PITHIA-NRF is designed to provide organized access to experimental facilities, FAIR data, standardized data products, training and innovation services. Furthermore, PITHIA-NRF facilitates drastically research advances in the field of upper atmosphere and near-Earth space, through the integration of data collections from satellite missions (such as Cluster, DEMETER, Swarm and CHAMP) and results from key prediction models (such as IPIM-IRAP, MCM-SWAMI, SWIF and EUHFORIA) that can be accessed by scientific users for join exploitation with the data collected from the research infrastructures of the network. PITHIA-NRF paves the way for new observing technologies, and to standard-making processes for software and high-level data products that are tuned to meet the requirements of technologies concerned, linking best-in-class R&D facilities to provide seamless multi-technology services.