The project is aimed at developing an innovative retrieval framework to derive CH4 vertical profiles from satellite data, driven and validated by circulation modeling and known CH4 temporal trends. The methodology is based on Physics-Informed Neural Networks, which include equations that inform about the physical variability of the output parameter. The methodology will be tuned for and applied to IASI data, already extensively used to retrieve CH4 column abundances.

 eLTER EnRich-Bridging phases towards the Integrated European Long- Term Ecosystem, critical zone and socio-ecological Research Infrastructure

The Horizon Europe eLTER EnRich  aims at catalysing the eLTER ESFRI process towards a successful conclusion, transforming the eLTER Europe network in a Research Infrastructure (RI) aligned with the vision and role in the European system of RIs identified by ESFRI (European Strategy Forum on Research Infrastructures). 

The overall goal of this project is to identify the most effective mathematical models for describing the evolution of forest fires at different scales for application in a real-world scenario. To this end, the general objective will be pursued through the following specific objectives:
- Identification of a hierarchy of mathematical models of forest fires and study of their main mathematical properties.
- Numerical resolution of the proposed models, with emphasis on the multiscale aspects of the problem and computational speed.