Abstract

In the global climate system, the Arctic ocean plays an important role especially illuminated by the recent warming and changes. Although hampered by the sparseness of the concerned, the ocean and sea ice states have been constructed and become an invaluable resource for understanding the potential relations among the dynamics variables in the past. However, recent inter-comparison studies suggest a large spread within the ensembles of the reanalyses. Based on the HYCOM and the ensemble Kalman filter, a coupled ocean and sea-ice data assimilation system using 100 members has been operationally implemented focusing on the Arctic forecast since 2008. In this study, the quantitative assessment of this reanalysis compares to both assimilated and unassimilated observations available, and presents the strengths and weakness of this system for potential users.

Presenter Profile

In 2008, he received a doctorate degree in fluid mechanics from the Institute of Atmospheric Physics, Chinese Academy of Sciences. After graduation, he stayed and worked as an associate research fellow for 2011-2014 years. Since March 2014, he has been working on the research center of environmental and remote sensing in Norway. In the study of ocean numerical models and data assimilation methods for a long time, the optimization of the collection of Argo temperature salt profile in the HYCOM model was optimized, and the sea ice thickness observation was improved in the ocean sea ice coupling model. More than ten SCI papers were published and then adopted by several commercial marine systems. At present, in the European ocean forecasting service project (Copernicus), it is one of the many years of analysis product experts responsible for Arctic sea sea ice reanalysis. Part II: report title: SAR sea ice geophysical parameters interpretation of the typical scene of the north and South Pole: Zhu Tingting, Wuhan University, National Key Laboratory of Surveying and Mapping Information Engineering: July 1, 2018 (Sunday) at 10:30 to 11:30 place: the Southern Building of the Meng min Wei science and technology building, S818: synthetic aperture radar technology pass It is an important data source for sea ice remote sensing monitoring to obtain the scattering information of various types of sea ice in a coherent way. Because the dynamic changes and deformation of the polar sea ice have greatly increased the difficulty of remote sensing, how to improve the interpretation ability of the SAR sea ice scene is a hot issue in the current sea ice remote sensing. In view of the deformation caused by sea ice dynamic environment, this paper presents a systematic multi scale sea ice parameter description and inversion framework from sea ice density - sea ice classification - sea ice deformation characteristics.