Data assimilation (DA) combines models with observations, in the most accurate and computationally efficient way. It enables and improves operational forecasts, forcing a meteorological model towards the real atmospheric behavior. DA methods can be very different, according to the type of available data, model complexity, final objectives and constraints, such as operational timing and finite computing resources. Nowadays, the increasing amount of quasi real-time data magnifies the DA value in weather forecasts but also the computational challenge, while upgrading predictions at different spatial and time scales is of paramount importance to increase resilience in the context of climate change. The ESA Earth Explorer 9 FORUM mission (scheduled for 2027) will provide unprecedented spectral data in the whole Far-Infrared range, i.e. precise information on the Earth energy budget, cirrus contribution, water vapor and green-house gases. In the PNRR SRT-EMM research infrastructure, the assessment of FORUM data in weather forecast will be developed, both versus and in synergy with other main available observations (e.g. IASI-NG). Fast radiative transfer codes will be used to build the observation operator, as required to compare model variables with FORUM (synthetic) data in the DA process. Variational and Kalman-filter based DA techniques will be applied to multiscale atmospheric codes in order to assess the impact at different scales and in different future operational scenarios.

• Master’s degree in one of the following disciplines: physics, engineering, mathematics, computer science, or related natural sciences• Basic experience in developing and running numerical codes• Basic knowledge of atmospheric physics and radiative transfer processes• Knowledge of at least one programming languages among Fortran, C++, Python, Matlab• Knowledge of the operating systems Linux and Windows or MacOS • Ability to work within a team• Attention to detail and organizational skills• Excellent interpersonal and communication skills

The team consists of researchers from CNR and LaMMA (consortium between CNR and the Tuscany regional administration), supported by professors of the Universities of Florence and Bologna, already cooperating in the context of projects and academic courses and theses.The PhD student will thus learn from CNR and academic experts as well as from the operational group of LaMMA (operational meteorological service of Tuscany). The overall accessible expertise will cover weather modeling, data assimilation, radiative transfer, operational forecasts, dynamical systems, machine learning, developed also thanks to European framework programs and European and Italian Space Agencies ones.