Assimilating summer sea-ice concentration into a coupled ice–ocean model using a LSEIK filter

• Published in: Annals of Glaciology
• Main Authors: Yang, Qinghua, Loza, Svetlana N., Losch, Martin, Liu, Jiping, Zhang, Zhanghai, Nerger, Lars, Yang, Hu
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: INT GLACIOL SOC 2015
• Subjects: Arctic; Arctic Ocean; Annals of Glaciology; National Snow and Ice Data Center; Sea ice
• Online Access: https://epic.awi.de/id/eprint/35967/; https://epic.awi.de/id/eprint/35967/1/a69A740.pdf; http://www.igsoc.org/annals/56/69/a69A740.html; https://hdl.handle.net/10013/epic.43865; https://hdl.handle.net/10013/epic.43865.d001

The decrease in summer sea-ice extent in the Arctic Ocean opens shipping routes and creates potential for many marine operations. For these activities accurate predictions of sea-ice conditions are required to maintain marine safety. In an attempt at Arctic sea-ice prediction, the summer of 2010 is selected to implement an Arctic sea-ice data assimilation (DA) study. The DA system is based on a regional Arctic configuration of the Massachusetts Institute of Technology general circulation model (MITgcm) and a local singular evolutive interpolated Kalman (LSEIK) filter to assimilate Special Sensor Microwave Imager/Sounder (SSMIS) sea-ice concentration operational products from the US National Snow and Ice Data Center (NSIDC). Based on comparisons with both the assimilated NSIDC SSMIS concentration and concentration data from the Ocean and Sea Ice Satellite Application Facility, the forecasted sea-ice edge and concentration improve upon simulations without data assimilation. By the nature of the assimilation algorithm with multivariate covariance between ice concentration and thickness, sea-ice thickness fields are also updated, and the evaluation with in situ observation shows some improvement compared to the forecast without data assimilation.