ISOBAR aims at the provision of a service- and AI-based Network Operations Plan, by integrating enhanced convective weather forecasts for predicting imbalances between capacity and demand and exploiting AI to select mitigation measures at local and network level in a collaborative ATFCM operations paradigm. To achieve this vision, four objectives are set: a) Reinforce collaborative ATFCM processes at pre-tactical and tactical levels into the LTM (local) and Network Management (network) roles integrating dynamic weather cells. b) Characterisation of demand and capacity imbalances at pre-tactical level [-1D, -30min] depending on the input of probabilistic weather cells by using applied AI methods and ATM and weather data integration. c) User-driven mitigation plan considering AUs priorities (and fluctuations in demand based on weather forecasts) and predicted effectiveness of ATFCM regulations, considering flow constraints and network effects. d) Develop an operational and technical roadmap for the integr

The project ?Knowledge and climate services from an African observation and Data research Infrastructure? aims to provide concepts for developing the best available science and science-based services in Africa that are needed to sharpen our common action on climate change as outlined in the Paris Agreement and the UN Sustainable Development Goals, in particular SDG 13 ?Take urgent action to combat climate change and its impacts?. The concepts we want to provide aim at improving the knowledge base on climate change in Africa and developing the tools to combat the negative consequences of it. This basic objective shall be achieved by a consortium that combines partners from Africa and Europe but also combines diverse experiences, backgrounds and viewpoints. The common goal is to provide a comprehensive concept that supports the important societal role of research outlined above by co-designing research capacities for climate change observation with societal demands and expectations, in our case called ?climate services? and to pave the way for their implementation. The specific objectives of the proposed project are: ? A comprehensive design for a pan-African climate observation system developed on the basis of climate services as guiding design principle. This shall be rooted in a comprehensive documentation of past and existing observing capability, contrasted with scientifically justified requirements to identify the gaps. ? A broad information network as basis for a successful and sustainable cooperation that connects infrastructure operators, scientists, data and knowledge users, a community of practice in climate services, agencies and funding bodies. This will be achieved by a dense networking and knowledge exchange approach connecting to all important players on the global, continental, national, and local level. ? A solid strategy for implementation and usage in close connection to future actors and users.

In this project the problem of analysing and quantifying the effects of meteorological uncertainty in Trajectory Based Operations is addressed. In particular, two problems are considered: 1) trajectory planning and 2) sector demand analysis, both at the pre-tactical level (up to three hours before departure) and tactical level (during the flight). In each problem two types of meteorological uncertainty are considered: wind uncertainty and convective zones (including individual storm cells). Weather predictions will be based on Ensemble Prediction Systems and Nowcasts. At the trajectory scale, the main objective is to assess and improve the predictability of efficient 4D trajectories when weather uncertainty is taken into account. To reach this goal, a methodology based on the use of stochastic optimal control algorithms will be explored for robust trajectory planning at the pre-tactical level. At the tactical level, various tactics will be investigated to avoid storms by using a Monte-Carlo method. At the sector scale, the main objective is to analyse the impact of the previously developed trajectory planning on sector demand. To achieve this objective, a methodology will be developed to measure the uncertainty of sector demand (probabilistic sector loading) based on the uncertainty of the individual trajectories. This analysis will also provide an understanding of how weather uncertainty propagates from the trajectory scale to the sector scale. All the solutions proposed in this project will be evaluated and assessed using an advanced air traffic simulator. This project is fully aligned with the call, where the following objectives are stated: “to enhance meteorological capabilities and their integration into ATM planning processes for improving ATM efficiency” and “to develop 4D trajectories that are optimised to take account of all environmental considerations”.