Variation of sea ice extent in different regions of the Arctic Ocean

Sea ice in the Arctic has been reducing rapidly in the past half century due to global warming. This study analyzes the variations of sea ice extent in the entire Arctic Ocean and its sub regions. The results indicate that sea ice extent reduction during 1979-2013 is most significant in summer, following by that in autumn, winter and spring. In years with rich sea ice, sea ice extent anomaly with seasonal cycle removed changes with a period of 4-6 years. The year of 2003-2006 is the ice-rich period with diverse regional difference in this century. In years with poor sea ice, sea ice margin retreats further north in the Arctic. Sea ice in the Fram Strait changes in an opposite way to that in the entire Arctic. Sea ice coverage index in melting-freezing period is an critical indicator for sea ice changes, which shows an coincident change in the Arctic and sub regions. Since 2002, Region C2 in north of the Pacific sector contributes most to sea ice changes in the central Aarctic, followed by C1 and C3. Sea ice changes in different regions show three relationships. The correlation coefficient between sea ice coverage index of the Chukchi Sea and that of the East Siberian Sea is high, suggesting good consistency of ice variation. In the Atlantic sector, sea ice changes are coincided with each other between the Kara Sea and the Barents Sea as a result of warm inflow into the Kara Sea from the Barents Sea. Sea ice changes in the central Arctic are affected by surrounding seas.

MODIS-based Daily Lake Ice Extent and Coverage dataset for Tibetan Plateau

The Tibetan Plateau houses numerous lakes,the phenology and duration of lake ice in this region are sensitive to regional and global climate change,and as such are used as key indicators in climate change research,particularly in environment change comparison studies for the Earth three poles.However,due to its harsh natural environment and sparse population,there is a lack of conventional in situ measurement on lake ice phenology.The Moderate Resolution Imaging Spectroradiometer(MODIS)Normalized Difference Snow Index(NDSI)data,which can be traced back 20 years with a 500 m spatial resolution,were used to monitor lake ice for filling the observation gaps.Daily lake ice extent and coverage under clear-sky conditions was examined by employing the conventional SNOWMAP algorithm,and those under cloud cover conditions were re-determined using the temporal and spatial continuity of lake surface conditions through a series of steps.Through time series analysis of every single lake with size greater than 3 km2 in size,308 lakes within the Tibetan Plateau were identified as the effective records of lake ice extent and coverage to form the Daily Lake Ice Extent and Coverage dataset,including 216 lakes that can be further retrieved with four determinable lake ice parameters:Freeze-up Start(FUS),Freeze-up End(FUE),Break-up Start(BUS),and Break-up End(BUE),and 92 lakes with two parameters,FUS and BUE.Six lakes of different sizes and locations were selected for verification against the published datasets by passive microwave remote sensing.The lake ice phenology information obtained in this paper was highly consistent with that from passive microwave data at an average correlation coefficient of 0.91 and an RMSE value varying from 0.07 to 0.13.The present dataset is more effective at detecting lake ice parameters for smaller lakes than the coarse resolution passive microwave remote sensing observations.The published data are available in https://data.4tu.nl/repository/uuid:fdfd8c76-6b7c-4bbf-aec8-98ab199d9093 and http://www.sciencedb.cn/dataSet/handle/744.

Simulation of ice accumulation around bridge piers during river breakup periods using a discrete element model

During river breakup periods in winter or early spring, a large amount of ice floes of various sizes will be transported by flowing water. The presence of bridge piers in water alters velocity field. As a consequence, the transport process of ice floes around bridge piers will be influenced. It often causes the ice floe congestion around bridge piers. In the present study, the influences of the ice floe size and coverage ratio of ice floating on water surface on ice floe congestion have been examined. The influence of bridge pier layout on ice jam development has been assessed. Results showed that during river breakup period, the ice floe transport capacity around bridge pier decreased. With the presence of bridge piers, the critical coverage ratio of ice floating on water surface for the ice floe congestion depends on the ratio of the side length of ice floe to the pier spacing distance (a / Ln) and ice floe-length Froude number associated with the ice floe length (Fra). A discrete element model (DEM) has been developed to simulate the ice floe accumulating process around bridge piers. Simulation results agree well with those of experiments.