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The surface morphology of lake ice remarkably changes under the combined influence of thermal and mechanical forces. However, research on the surface morphology of lake ice and its interaction with climate is scarce. A large-scale linear structure has repeatedly appeared on satellite images of Chagan Lake in recent years. The Geostationary Ocean Color Imager (GOCI), with a 1 h revisit, and Landsat 8 Operational Land Imager (OLI), with a spatial resolution of 30 m, provide the possibility for the study of hourly changes in the large-scale linear structure. We merged the Landsat and GOCI images, using an Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM), and extracted the lengths and angles of the linear structure. We monitored the hourly changes in the surface morphology during the cold season from 2018 to 2019. The average length of the linear structure in the completely frozen period was 21141.57±68.36 m. The average azimuth angle was 335.48±0.23 ∘ , nearly perpendicular to the domain wind in winter. Through two field investigations during the two recent cold seasons, we verified the linear structure as being ice fractures and ridges. The evolution of surface morphology is closely associated with air temperature, wind, and shoreline geometry. [ABSTRACT FROM AUTHOR]

The regional role and trends of freshwater ice are critical factors for aquatic ecosystems, climate variability, and human activities. The ice regime has been scarcely investigated in the Songhua River Basin of northeast China. Using daily ice records of 156 hydrological stations across the region, we examined the spatial variability in the river ice phenology and river ice thickness from 2010 to 2015 and explored the role of snow depth and air temperature on the ice thickness. The river ice phenology showed a latitudinal distribution and a changing direction from southeast to northwest. We identified two spatial clusters based on Moran's I spatial autocorrelation, and results showed that the completely frozen duration with high values clustered in the Xiao Hinggan Range and that with low values clustered in the Changbai Mountains at the 95 % confidence level. The maximum ice thickness over 125 cm was distributed along the ridge of the Da Hinggan Range and Changbai Mountains, and the maximum ice thickness occurred most often in February and March. In three subbasins of the Songhua River Basin, we developed six Bayesian regression models to predict ice thickness from air temperature and snow depth. The goodness of the fit (R2) for these regression models ranged from 0.80 to 0.95, and the root mean square errors ranged from 0.08 to 0.18 m. Results showed significant and positive correlations between snow cover and ice thickness when freshwater was completely frozen. Ice thickness was influenced by the cumulative air temperature of freezing through the heat loss of ice formation and decay instead of just air temperature. [ABSTRACT FROM AUTHOR]