Qinghua Yang

TL;DR: The polar regions have been attracting more and more attention in recent years, fueled by the perceptible impacts of anthropogenic climate change as mentioned in this paper, and it is argued that environmental prediction systems for the polar regions are less developed than elsewhere.

TL;DR: In this article, the impact of assimilating sea ice thickness data derived from ESA's Soil Moisture and Ocean Salinity (SMOS) satellite together with Special Sensor Microwave Imager/Sounder (SSMIS) sea ice concentration data of the National Snow and Ice Data Center (NSIDC) in a coupled sea ice-ocean model is examined.

TL;DR: In this article, the authors used a localized error subspace transform ensemble Kalman filter (LESTKF) to estimate the sea ice concentration and thickness in the National Centers for Environmental Prediction Climate Forecast System.

TL;DR: In this article, the authors focus on two challenges for implementing multivariate data assimilation systems for sea ice forecast, including the challenge of limited spatiotemporal coverage and large uncertainties of observations.