scholarly journals Long-Term Ice Conditions in Yingkou, a Coastal Region Northeast of the Bohai Sea, between 1951/1952 and 2017/2018: Modeling and Observations

2022 ◽  
Vol 14 (1) ◽  
pp. 182
Author(s):  
Yuxian Ma ◽  
Bin Cheng ◽  
Ning Xu ◽  
Shuai Yuan ◽  
Honghua Shi ◽  
...  
Keyword(s):  
Sea Ice ◽  
Air Temperature ◽  
Large Scale ◽  
Bohai Sea ◽  
Coastal Region ◽  
Ice Thickness ◽  
Climate Indices ◽  
Clear Trend ◽  
The Bohai Sea ◽  
Ice Conditions

Bohai Sea ice creates obstacles for maritime navigation and offshore activities. A better understanding of ice conditions is valuable for sea-ice management. The evolution of 67 years of seasonal ice thickness in a coastal region (Yingkou) in the Northeast Bohai Sea was simulated by using a snow/ice thermodynamic model, using local weather-station data. The model was first validated by using seasonal ice observations from field campaigns and a coastal radar (the season of 2017/2018). The model simulated seasonal ice evolution well, particularly ice growth. We found that the winter seasonal mean air temperature in Yingkou increased by 0.33 °C/decade slightly higher than air temperature increase (0.27 °C/decade) around Bohai Sea. The decreasing wind-speed trend (0.05 m/s perdecade) was a lot weaker than that averaged (0.3 m/s per decade) between the early 1970s and 2010s around the entire Bohai Sea. The multi-decadal ice-mass balance revealed decreasing trends of the maximum and average ice thickness of 2.6 and 0.8 cm/decade, respectively. The length of the ice season was shortened by 3.7 days/decade, and ice breakup dates were advanced by 2.3 days/decade. All trends were statistically significant. The modeled seasonal maximum ice thickness is highly correlated (0.83, p < 0.001) with the Bohai Sea Ice Index (BoSI) used to quantify the severity of the Bohai Sea ice condition. The freezing-up date, however, showed a large interannual variation without a clear trend. The simulations indicated that Bohai ice thickness has grown continuously thinner since 1951/1952. The time to reach 0.15 m level ice was delayed from 3 January to 21 January, and the ending time advanced from 6 March to 19 February. There was a significant weakening of ice conditions in the 1990s, followed by some recovery in 2000s. The relationship between large-scale climate indices and ice condition suggested that the AO and NAO are strongly correlated with interannual changes in sea-ice thickness in the Yingkou region.

Sea ice thickness analyses for the Bohai Sea using MODIS thermal infrared imagery

2016 ◽  
Vol 35 (7) ◽  
pp. 96-104 ◽  
Author(s):  
Tao Zeng ◽  
Lijian Shi ◽  
Makynen Marko ◽  
Bin Cheng ◽  
Juhong Zou ◽  
...  
Keyword(s):  
Sea Ice ◽  
Bohai Sea ◽  
Thermal Infrared ◽  
Ice Thickness ◽  
Infrared Imagery ◽  
Sea Ice Thickness ◽  
The Bohai Sea ◽  
Thermal Infrared Imagery

Using remote sensing to estimate sea ice thickness in the Bohai Sea, China based on ice type

2009 ◽  
Vol 30 (17) ◽  
pp. 4539-4552 ◽  
Author(s):  
Li Ning ◽  
Feng Xie ◽  
Wei Gu ◽  
Yingjun Xu ◽  
Shuqing Huang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Sea Ice ◽  
Bohai Sea ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
The Bohai Sea

scholarly journals Sea Ice Extent Detection in the Bohai Sea Using Sentinel-3 OLCI Data

2019 ◽  
Vol 11 (20) ◽  
pp. 2436 ◽  
Author(s):  
Hua Su ◽  
Bowen Ji ◽  
Yunpeng Wang
Keyword(s):  
Sea Ice ◽  
Bohai Sea ◽  
Regional Climate ◽  
Regional Climate Change ◽  
The Novel ◽  
Sea Ice Extent ◽  
Important Indicator ◽  
The Bohai Sea ◽  
Information Index ◽  
Ice Conditions

Sea ice distribution is an important indicator of ice conditions and regional climate change in the Bohai Sea (China). In this study, we monitored the spatiotemporal distribution of the Bohai Sea ice in the winter of 2017–2018 by developing sea ice information indexes using 300 m resolution Sentinel-3 Ocean and Land Color Instrument (OLCI) images. We assessed and validated the index performance using Sentinel-2 MultiSpectral Instrument (MSI) images with higher spatial resolution. The results indicate that the proposed Normalized Difference Sea Ice Information Index (NDSIIIOLCI), which is based on OLCI Bands 20 and 21, can be used to rapidly and effectively detect sea ice but is somewhat affected by the turbidity of the seawater in the southern Bohai Sea. The novel Enhanced Normalized Difference Sea Ice Information Index (ENDSIIIOLCI), which builds on NDSIIIOLCI by also considering OLCI Bands 12 and 16, can monitor sea ice more accurately and effectively than NDSIIIOLCI and suffers less from interference from turbidity. The spatiotemporal evolution of the Bohai Sea ice in the winter of 2017–2018 was successfully monitored by ENDSIIIOLCI. The results show that this sea ice information index based on OLCI data can effectively extract sea ice extent for sediment-laden water and is well suited for monitoring the evolution of Bohai Sea ice in winter.

Estimation of sea ice thickness in the Bohai Sea using a combination of VIS/NIR and SAR images

2015 ◽  
Vol 52 (2) ◽  
pp. 115-130 ◽  
Author(s):  
Chengyu Liu ◽  
Jinlong Chao ◽  
Wei Gu ◽  
Yingjun Xu ◽  
Feng Xie
Keyword(s):  
Sea Ice ◽  
Bohai Sea ◽  
Ice Thickness ◽  
Sar Images ◽  
Sea Ice Thickness ◽  
The Bohai Sea

scholarly journals Monitoring the Characteristics of the Bohai Sea Ice Using High-Resolution Geostationary Ocean Color Imager (GOCI) Data

2019 ◽  
Vol 11 (3) ◽  
pp. 777 ◽  
Author(s):  
Yu Yan ◽  
Kaiyue Huang ◽  
Dongdong Shao ◽  
Yingjun Xu ◽  
Wei Gu
Keyword(s):  
High Resolution ◽  
Sea Ice ◽  
Spatial Resolution ◽  
Temporal Resolution ◽  
Bohai Sea ◽  
Ocean Color ◽  
High Temporal Resolution ◽  
The Bohai Sea ◽  
Ice Conditions ◽  
Ice Disaster

Satellite remote sensing data, such as moderate resolution imaging spectroradiometers (MODIS) and advanced very high-resolution radiometers (AVHRR), are being widely used to monitor sea ice conditions and their variability in the Bohai Sea, the southernmost frozen sea in the Northern Hemisphere. Monitoring the characteristics of the Bohai Sea ice can provide crucial information for ice disaster prevention for marine transportation, oil field operation, and regional climate change studies. Although these satellite data cover the study area with fairly high spatial resolution, their typically limited cloudless images pose serious restrictions for continuous observation of short-term dynamics, such as sub-seasonal changes. In this study, high spatiotemporal resolution (500 m and eight images per day) geostationary ocean color imager (GOCI) data with a high proportion of cloud-free images were used to monitor the characteristics of the Bohai Sea ice, including area and thickness. An object-based feature extraction method and an albedo-based thickness inversion model were used for estimating sea ice area and thickness, respectively. To demonstrate the efficacy of the new dataset, a total of 68 GOCI images were selected to analyze the evolution of sea ice area and thickness during the winter of 2012–2013 with severe sea ice conditions. The extracted sea ice area was validated using Landsat Thematic Mapper (TM) data with higher spatial resolution, and the estimated sea ice thickness was found to be consistent with in situ observation results. The entire sea ice freezing–melting processes, including the key events such as the day with the maximum ice area and the first and last days of the frozen season, were better resolved by the high temporal-resolution GOCI data compared with MODIS or AVHRR data. Both characteristics were found to be closely correlated with cumulative freezing/melting degree days. Our study demonstrates the applicability of the GOCI data as an improved dataset for studying the Bohai Sea ice, particularly for purposes that require high temporal resolution data, such as sea ice disaster monitoring.

scholarly journals The MOSAiC Drift: Ice conditions from space and comparison with previous years

2021 ◽  
Author(s):  
Thomas Krumpen ◽  
Luisa von Albedyll ◽  
Helge F. Goessling ◽  
Stefan Hendricks ◽  
Bennet Juhls ◽  
...  
Keyword(s):  
Sea Ice ◽  
Large Scale ◽  
Ice Thickness ◽  
Sea Ice Concentration ◽  
Melt Ponds ◽  
Ice Concentration ◽  
Ice Conditions ◽  
Snow Thickness ◽  
Lead Activity

Abstract. We combine satellite data products to provide a first and general overview of the sea-ice conditions along the MOSAiC drift and a comparison with previous years. We find that the MOSAiC drift was around 25 % faster than the climatological mean drift, as a consequence of large-scale low-pressure anomalies prevailing around the Barents-Kara-Laptev Sea region between January and March. In winter (October–April), satellite observations show that the sea-ice in the vicinity of the Central Observatory (CO) was rather thin compared to the previous years along the same trajectory. Unlike ice thickness, satellite-derived sea-ice concentration, lead frequency, and snow thickness during winter month were close to the long-term mean with little variability. With the onset of spring and decreasing distance to Fram Strait, variability in ice concentration and lead activity increased. In addition, frequency and strength of deformation events (divergence and shear) were higher during summer than during winter. Overall, we find that sea-ice conditions observed close (~ 5 km) to the CO are representative for the wider (50 km and 100 km) surroundings. An exception is the ice thickness: Here we find that sea-ice near the CO (50 km radius) was 4 % thinner than sea-ice within a 100 km radius. Moreover, satellite acquisitions indicate that the formation of large melt ponds began earlier on the MOSAiC floe than on neighbouring floes.

Sign in / Sign up

Export Citation Format

Share Document