March webinar presented by Yue Ying, research scientist from NERSC, (Norway) and chaired by Alberto Carassi, leader of SASIP WP4 from the University of Bologna (Italy).

Sea ice linear kinematic features, such as leads and ridges, play an important role in daily sea ice forecasts. The neXtSIM model developed in SASIP allows faithful representation of these features in forecasts. The WP4 team have been developing a data assimilation software, called NEDAS, to assimilate additional observations of these features derived from high-resolution SAR images and improve the forecasts. In this webinar, Yue Ying will describe the issues they had encountered in feature-based assimilation for both the Lagrangian and the Direct-Galerkin versions of neXtSIM, and report on preliminary assessment of the forecast performance of the new assimilation software.

Whatch the recording :