ROADMAP investigates the influence of North Atlantic and North Pacific ocean surface variability on the extratropical atmospheric circulation, with a focus on high-impact weather and climate extremes under present-day and future climate conditions. Specifically, ROADMAP will address: • impacts of a changing ocean circulation on sea surface temperature (SST) • future of western boundary currents and their extensions, such as the Gulfstream • extratropical ocean-atmosphere interactions controlling jet streams, cyclones, blocking and their links to weather and climate extremes • impacts of tropical SST anomalies (e.g. El Nino) on the extratropical atmospheric circulation • role of the SST and Arctic sea ice for driving impact-relevant atmospheric extremes such as heat waves including compound weather extremes • intensity and frequency of Mediterranean mesoscale cyclones (Medicanes) • interactions between oceanic and atmospheric modes of variability ROADMAP will exploit the wealth of model simulations recently produced in other international (EU and worldwide) research activities. Additionally, ROADMAP will conduct dedicated experiments employing cutting-edge numerical techniques based on data assimilation and interactive ensemble modelling. Analyses will be based on advanced dynamical and statistical methods as well as novel machine learning techniques designed to infer complex, non-linear relationships. ROADMAP applies a multi-model approach, crucial for assessing uncertainties. Results will be disseminated to the scientific, stakeholder and climate service community as well the general public. The consortium encompasses leading climate research institutions from seven European countries, including universities as well as institutions providing (national) meteorological and climate services. ROADMAP will continue a long-standing history of successful international collaboration between its partners.

The purpose of the proposal put together by the Climate JPI and the Water JPI is to “enable collaboration between national research and innovation funding members to address together the protection of cultural heritage in Europe and beyond. With this purpose, both JPIs will support the implementation of multi-annual joint activities that will focus on the better understanding of, and the identification of best available adaptation solutions in response to hydroclimatic extreme events”. The Consortium established by both JPIs gathers today 16 organisations including programme owners (funding agencies from Belgium, France, Georgia, Italy, Malta, UK, Kenya, Portugal and Romania), research performing organisations/ academia, foundations and private companies. The following operational objectives have been laid out by the Consortium: - Enhance cross-sector collaborations and strategic coordination between water, climate and cultural heritage. - Launch and monitor joint activities to measure progress towards widening. - Address potential barriers for collaboration. - Evaluate the impacts of those joint activities on widening policies as well as EU and international policy frameworks, notably the EU Green Deal and the Sustainable Development Goals (SDGs). - Implement joint activities enabling the market, regulatory and societal uptake of results. The project will be structured around 6 work packages (WP) looking at the coordination of activities (WP1), the identification of relevant gaps in the fields of cultural heritage, water and climate (WP2), the launch of joint activities, the TAP instrument (Thematic Annual Programming; WP3), communication and dissemination of project results (WP4), the analysis of impacts of proposed actions on EU widening strategies (WP5), and the implementation of specific tools to enable the social, regulatory and market uptake of proposed innovations stemming from joint activities (WP6).

Contrails and aviation-induced cloudiness effects on climate change show large uncertainties since they are subject to meteorological, regional, and seasonal variations. Indeed, under some specific circumstances, aircraft can generate anthropogenic cirrus with cooling. Thus, the need for research into contrails and aviation-induced cloudiness and its associated uncertainties to be considered in aviation climate mitigation actions becomes unquestionable. We will blend cutting-edge AI techniques (deep learning) and climate science with application to the aviation domain, aiming at closing (at least partially) de existing gap in terms of understanding aviation-induced climate impact. The overall purpose of E-CONTRAIL project is to develop artificial neural networks (leveraging remote sensing detection methods) for the prediction of the climate impact derived from contrails and aviation-induced cloudiness, contributing, thus, to a better understanding of the non-CO2 impact of aviation on global warming and reducing their associated uncertainties as essential steps towards green aviation. Specifically, the objectives of E-CONTRAIL are: O-1 to develop remote sensing algorithms for the detection of contrails and aviation-induced cloudiness. O-2 to quantify the radiative forcing of ice clouds based on remote sensing and radiative transfer methods. O-3 to use of deep learning architectures to generate AI models capable of predicting the radiative forcing of contrails based on data-archive numerical weather forecasts and historical traffic O-4 to assess the climate impact and develop a visualization tool in a dashboard Upon successful achievement of the objectives described above, we ambition to provide aviation stakeholders with an early and accurate (thus, reducing the associated uncertainty) prediction of those volumes of airspace with the conditions for large global warming impact due to contrails and aviation-induced cloudiness.

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.

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.