Changes in rural areas, such as depopulation, land abandonment and the loss of biodiversity, may proceed very slowly yet are often irreversible. Policymakers can steer these developments in order to reduce their negative impacts but this requires knowing whether current policy instruments are effective, who is benefiting from them and in what measure, what driving forces will be most influential and how they will affect people, planet, profits and land-use. To be truly useful, this knowledge must transcend siloed thinking and be the corollary of a joint effort uniting different actors under a common cause. PoliRur will provide this knowledge by combining several key activities needed to design effective place-based, human-centric and forward-looking rural policies. These include actionable research that takes place within an inclusive learning environment where rural populations, researchers and policymakers come together to address common problems; an evaluation exercise that uses text mining to assess the perceived effectiveness of past or planned policy interventions; and a foresight study that tries to glean the development trajectory of agriculture and its allied sectors until 2040 using several scenarios in which the evolution of rural populations occupies a central place. As a result of these activities, PoliRur will leave decision makers at different levels of government better equipped to tackle existing and emerging rural challenges, rural populations more empowered and rural areas more resilient.

Natural hazards, such as extreme weather events, are exacerbated by climate change. As a result, emergency responses are becoming more protracted, expensive, frequent, and stretching limited available resources. This is especially apparent in rapidly warming regions. MedEWSa addresses these challenges by providing novel solutions to ensure timely, precise, and actionable impact and finance forecasting, and early warning systems (EWS) that support the rapid deployment of first responders to vulnerable areas. Specifically, MedEWSa will deliver a sophisticated, comprehensive, and innovative pan-European–Mediterranean–African solution comprising a range of complementary services. Building on existing tools MedEWSa will develop a fully integrated impact-based multi-hazard EWS. This call contained five expected outcomes, all of which will be specifically addressed by MedEWSa. Led by WMO, MedEWSa will be an exemplar of the UN Secretary General’s March 2022 call to ensure that everyone on Earth is protected from extreme weather and climate-related hazards by EWS within the next five years. Through eight carefully selected pilot sites (areas in Europe, the southern Mediterranean, and Africa with a history of being impacted by natural hazards and extreme events with cascading effects), four twins will be created: ● Twin #1: Greece (Attica) – Ethiopia (National Parks): wildfires and extreme weather events (droughts, wind) ● Twin #2: Italy (Venice) – Egypt (Alexandria / Nile Delta): coastal floods and storm surges ● Twin #3: Slovakia (Kosice) – Georgia (Tbilisi): floods and landslides ● Twin #4: Spain (Catalonia) – Sweden (countrywide): heatwaves, droughts and wildfires. The twins will bridge areas with different climatic/physiographic conditions, yet subject to similar hazards, and are well positioned to deliver long-term bi-directional knowledge transfer. They will demonstrate the transferability and versatility of the tools developed in MedEWSa.

E2mC aims at demonstrating the technical and operational feasibility of the integration of social media analysis and crowdsourced information within both the Mapping and Early Warning Components of Copernicus Emergency Management Service (EMS). The Project will develop a prototype of a new EMS Service Component (Copernicus Witness), designed to exploit social media analysis and crowdsourcing capabilities to generate a new Product of the EMS Portfolio. The purpose of the new Copernicus Witness Service Component is to improve the timeliness and accuracy of geo-spatial information provided to Civil Protection authorities, on a 24/7 basis, during the overall crisis management cycle and, particularly, in the first hours immediately after the event. This will result in an early confirmation of alerts from running Early Warning Systems as well as first rapid impact assessment from the field. The technological enabler of the Copernicus Witness is the innovative and scalable Social&Crowd (S&C) Platform, developed by E2mC. Heterogeneous social media data streams (Twitter, Facebook, Instagram,… and different data: text, image, video, …) will be analysed and sparse crowdsourcing communities will be federated (crisis specific as Tomnod, HOT, SBTF and generic as Crowdcrafting, EpiCollect,…). Two demonstration loops will validate the usefulness of Copernicus Witness and the S&C Platform suitability to allow EC to evaluate possible Copernicus EMS evolution options. E2mC will perform demonstrations within realistic and operational scenarios designed by the Users involved within the Project (Civil Protection Authorities and Humanitarian Aid operators, including their volunteer teams) and by the current Copernicus EMS Operational Service Providers that are part of the E2mC Consortium. The involvement of social media and crowdsourcing communities will foster the engagement of a large number of people in supporting crisis management; many more citizens will become aware of Copernicus.

This project will build the WeatherGenerator – the world’s best generative Foundation Model of the Earth system – that will serve as a new Digital Twin for Destination Earth. The WeatherGenerator will be based on representation learning and create a general and versatile tool that models the dynamics of the Earth system based on a large variety of Earth system data. The WeatherGenerator will be task-independent and will improve results for a wide range of machine learning applications when compared to task specific machine learning tools. It will also be more resilient for climate applications when the underlying data distributions are changing, and it will lead to a significant reduction in computational costs and faster turnaround times. To achieve this, we will: (1) Collect and use the most important datasets of Earth system science including data from Digital Twins of Destination Earth, selected observations, analysis and reanalysis datasets, and output of conventional Earth system models. (2) Build the WeatherGenerator as a novel representation learning-based machine learning tool that exploits the full potential of Europe’s largest supercomputers. (3) Engage with the wider community via services and apply the WeatherGenerator for 22 selected applications that can be integrated into the Destination Earth framework. The applications include global and local predictions, local downscaling, data assimilation, model post-processing, and impact applications in the domains of renewable energy, water, health and food. The project consortium that will build the WeatherGenerator consists of experts in machine learning, supercomputing and Earth system sciences, and includes industry, SMEs, and leading operational weather centers. The WeatherGenerator will lead to key innovations in weather and climate science and machine learning to enable Europe to establish and defend leadership with respect to machine-learning based Earth system modelling.

The ultimate purpose of ANYWHERE is to empower exposed responder institutions and citizens to enhance their anticipation and pro-active capacity of response to face extreme and high-impact weather and climate events. This will be achieved through the operational implementation of cutting-edge innovative technology as the best way to enhance citizen's protection and saving lives. ANYWHERE proposes to implement a Pan-European multi-hazard platform providing a better identification of the expected weather-induced impacts and their location in time and space before they occur. This platform will support a faster analysis and anticipation of risks prior the event occurrence, an improved coordination of emergency reactions in the field and help to raise the self-preparedness of the population at risk. This significant step-ahead in the improvement of the pro-active capacity to provide adequate emergency responses is achievable capitalizing on the advanced forecasting methodologies and impact models made available by previous RTD projects, maximizing the uptake of their innovative potential not fully exploited up to now. The consortium is build upon a strong group of Coordinators of previous key EC projects in the related fields, together with 12 operational authorities and first responders institutions and 6 leading enterprises of the sector. The platform will be adapted to provide early warning products and locally customizable decision support services proactively targeted to the needs and requirements of the regional and local authorities, as well as public and private operators of critical infrastructures and networks. It will be implemented and demonstrated in 4 selected pilot sites to validate the prototype that will be transferred to the real operation. The market uptake will be ensured by the cooperation with a SME and Industry Collaborative Network, covering a wide range of sectors and stakeholders in Europe, and ultimately worldwide.