A1D4.7

Lead Beneficiary: NOVELTIS

Beneficiaries involved: KU Leuven, Uoulu, IEEA, DTU

Due Date: end of the project

Goal

The objectives are to provide soteria consortium with expertise on data assimilation by producing a state of the art report and by providing a few partners with support to tentative of data assimilation prototyping. The delivery D4.7 will correspond to three reports: a report on data assimilation methods, a report on data assimilation tools and a report on results of data assimilation prototyping.

Progress so far

NOVELTIS achieved the report on Data Assimilation methods that are widely used in geosciences. This report presents the two main families of assimilation schemes: variationnal and sequential methods. NOVELTIS achieved the report on data assimilation tools that have been already developed by several research teams in the oceanography and the meteorology forecasting framework. This report has similar architecture than the data assimilation schemes report but, it focuses on software packages. These reports were diffused to the SOTERIA consortium in draft versions. These versions may evolve to take into account for partners’ feedbacks. Final versions will be delivered at the date due for the delivery D4.7.

NOVELTIS acheived to collect partners expectations on data assimilation and initiated data assimilation prototyping with a few partners:

• At a first step we achieved the clarification with KU Leuven and works were engaged on the improvement of solar wind forecast by developing data assimilation with a MHD model. Uoulu is also involved in this activity for solar magnetic field modelling.

• At a second step, we initiated clarification of works with IEEA during the WP4 workshop of September. The idea is to use the GPS data to improve forecasts of the ionosphere scintillation model GISM developed by IEEA.

• Finally, works were also engaged with DTU on the improvement of Field Aligned Currents (FACs) modelling by using magnetic observations produced by Low Earth Orbiters like CHAMP. The mathematical features of the model were identified and a method was defined to improve FAC estimation. The relevance of this method is under assessment and the implementation should follow.

List of the people involved in this deliverable: NOVELTIS - François Crespon, Chafih Skandrani, Julien Lamouroux, and Eric Jeansou; KU Leuven - Giovanni Lapenta, Lapo Bettarini, Marina Skender, and Maria Elena Innocenti; DTU - Susanne Vennerstrom; U Oulu - Kalevi Mursula and Ilpo Virtanen; IEEA - Yannick Beniguel