Co-Occurrence Probability Analysis of Sea Ice at Yingkou and Huludao Observation Stations of China

2017 ◽  
Author(s):  
Shanshan Tao ◽  
Zhifeng Wang ◽  
Ri Zhang ◽  
Sheng Dong
Keyword(s):  
Sea Ice ◽  
Probability Distributions ◽  
Joint Probability ◽  
Offshore Structures ◽  
Early Spring ◽  
Probability Analysis ◽  
Ice Thickness ◽  
Occurrence Probability ◽  
Sea Ice Thickness ◽  
Ice Conditions

Co-occurrence probability analysis of sea ice between adjacent areas is very helpful for the hazard prevention and protection strategy making of coastal and offshore engineering. Yingkou and Huludao with similar latitudes are located on the opposite sides of Liaodong Bay of China. Their sea ice conditions are both apparent in winter and early spring, so it is useful to study on the co-occurrence situations of sea ice conditions between these two areas. Based on the annual maximum sea ice thickness of Yingkou and Huludao observation stations, the co-occurrence probability analysis of sea ice thickness is conducted. The joint probability distributions of sea ice thickness between these adjacent areas are constructed by using univariate maximum entropy distributions and four bivariate copulas. Both marginal curve fittings are very well, and the model determined by Gumbel-Hougaard copula describes the bivariate sea ice thickness data best. Then different cases of co-occurrence probabilities of sea ice thickness between Yingkou and Huludao are presented, and they can provide references to the hazard protection of the coastal and offshore structures between these two areas.

Sea Ice Thickness Forecast Performance in the Barents Sea

2020 ◽  
Author(s):  
Laura Hume-Wright ◽  
Emma Fiedler ◽  
Nicolas Fournier ◽  
Joana Mendes ◽  
Ed Blockley ◽  
...  
Keyword(s):  
Sea Ice ◽  
Barents Sea ◽  
Forecast Model ◽  
The Arctic ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
Forecast Performance ◽  
In Situ Data ◽  
The Barents Sea ◽  
Ice Conditions

Abstract The presence of sea ice has a major impact on the safety, operability and efficiency of Arctic operations and navigation. While satellite-based sea ice charting is routinely used for tactical ice management, the marine sector does not yet make use of existing operational sea ice thickness forecasting. However, data products are now freely available from the Copernicus Marine Environment Monitoring Service (CMEMS). Arctic asset managers and vessels’ crews are generally not aware of such products, or these have so far suffered from insufficient accuracy, verification, resolution and adequate format, in order to be well integrated within their existing decision-making processes and systems. The objective of the EU H2020 project “Safe maritime operations under extreme conditions: The Arctic case” (SEDNA) is to improve the safety and efficiency of Arctic navigation. This paper presents a component focusing on the validation of an adaption of the 7-day sea ice thickness forecast from the UK Met Office Forecast Ocean Assimilation Model (FOAM). The experimental forecast model assimilates the CryoSat-2 satellite’s ice freeboard daily data. Forecast skill is evaluated against unique in-situ data from five moorings deployed between 2015 and 2018 by the Barents Sea Metocean and Ice Network (BASMIN) Joint Industry Project. The study shows that the existing FOAM forecasts produce adequate results in the Barents Sea. However, while studies have shown the assimilation of CryoSat-2 data is effective for thick sea ice conditions, this did not improve forecasts for the thinner sea ice conditions of the Barents Sea.

Methodology to Evaluate Sea Ice Loads for Seasonal Operations

2015 ◽  
Author(s):  
Jan Thijssen ◽  
Mark Fuglem
Keyword(s):  
Sea Ice ◽  
Offshore Structures ◽  
Ice Thickness ◽  
Safety Level ◽  
Site Specific ◽  
Design Load ◽  
Ice Load ◽  
Ice Conditions ◽  
Design Loads ◽  
Ice Loads

Offshore structures designed for operation in regions where sea ice is present will include a sea ice load component in their environmental loading assessment. Typically ice loads of interest are for 10−2, 10−3 or 10−4 annual probability of exceedance (APE) levels, with appropriate factoring to the required safety level. The ISO 19906 standard recommends methods to determine global sea ice loads on vertical structures, where crushing is the predominant failure mode. Fitted coefficients are proposed for both Arctic and Sub-Arctic (e.g. Baltic) conditions. With the extreme ice thickness expected at the site of interest, an annual global sea ice load can be derived deterministically. Although the simplicity of the proposed relation provides quick design load estimates, it lacks accuracy because the only dependencies are structure width, ice thickness and provided coefficients; no consideration is given to site-specific sea ice conditions and the corresponding exposure. Additionally, no term is provided for including ice management in the design load basis. This paper presents a probabilistic methodology to modify the deterministic ISO 19906 relations for determining global and local first-year sea ice loads on vertical structures. The presented methodology is based on the same ice pressure data as presented in ISO 19906, but accounts better for the influence of ice exposure, ice management and site-specific sea ice data. This is especially beneficial for ice load analyses of seasonal operations where exposure to sea ice is limited, and only thinner ice is encountered. Sea ice chart data can provide site-specific model inputs such as ice thickness estimates and partial concentrations, from which corresponding global load exceedance curves are generated. Example scenarios show dependencies of design loads on season length, structural geometry and sea ice conditions. Example results are also provided, showing dependency of design loads on the number of operation days after freeze-up, providing useful information for extending the drilling season of MODUs after freeze-up occurs.

scholarly journals Can we extend local sea-ice measurements to satellite scale? An example from the N-ICE2015 expedition

2017 ◽  
Vol 59 (76pt2) ◽  
pp. 163-172 ◽  
Author(s):  
Anja Rösel ◽  
Jennifer King ◽  
Anthony P. Doulgeris ◽  
Penelope M. Wagner ◽  
A. Malin Johansson ◽  
...  
Keyword(s):  
Sea Ice ◽  
Satellite Data ◽  
Arctic Sea Ice ◽  
Ice Thickness ◽  
Remotely Sensed Data ◽  
Sea Ice Thickness ◽  
In Situ Data ◽  
Ice Conditions ◽  
Area North

ABSTRACTKnowledge of Arctic sea-ice conditions is of great interest for Arctic residents, as well as for commercial usage, and to study the effects of climate change. Information gained from analysis of satellite data contributes to this understanding. In the course of using in situ data in combination with remotely sensed data, the question of how representative local scale measurements are of a wider region may arise. We compare in situ total sea-ice thickness measurements from the Norwegian young sea ICE expedition in the area north of Svalbard with airborne-derived total sea-ice thickness from electromagnetic soundings. A segmented and classified synthetic aperture radar (SAR) quad-pol ALOS-2 Palsar-2 satellite scene was grouped into three simplified ice classes. The area fractions of the three classes are: 11.2% ‘thin’, 74.4% ‘level’, and 14.4% ‘deformed’. The area fractions of the simplified classes from ground- and helicopter-based measurements are comparable with those achieved from the SAR data. Thus, this study shows that there is potential for a stepwise upscaling from in situ, to airborne, to satellite data, which allow us to assess whether in situ data collected are representative of a wider region as observed by satellites.

scholarly journals Variability of fast-ice thickness in Spitsbergen fjords

2006 ◽  
Vol 44 ◽  
pp. 231-239 ◽  
Author(s):  
Sebastian Gerland ◽  
Richard Hall
Keyword(s):  
Sea Ice ◽  
Early Spring ◽  
Ice Thickness ◽  
Western Coast ◽  
Total Thickness ◽  
Sea Ice Thickness ◽  
Svalbard Archipelago ◽  
Average Maximum ◽  
Before And After ◽  
Snow Thickness

AbstractDetailed measurements of Sea-ice thickness and Snow on Sea ice were recorded at different locations in fjords along the western coast of Spitsbergen, the largest island in the Svalbard archipelago, in 2004. Data corresponding to the ice Situation before and after melt onset were collected for Kongsfjorden and Van Mijenfjorden, while Hornsund was investigated once during early Spring. Profiles of total thickness (snow plus ice thickness) were measured, together with Some Snow-thickness measurements. Total thicknesses were measured with a portable electromagnetic instrument and at Selected Sites by drilling. The three fjords Show Some differences in measured thicknesses, connected to individual conditions. However, total thickness does not differ Substantially between the three fjords before melt onset. The modal total thickness for all three fjords before melt onset was 1.075 m, and the corresponding modal Snow thickness was 0.225 m (bin width 0.05 m). Long-term Kongsfjorden ice-thickness data Since 1997 Show that the maximum ice thickness varies Significantly interannually, as observed at other Arctic Sites. The average maximum ice thickness for Kongsfjorden was 0.71 m (years 1997–98, 2000 and 2002–05), and the respective average maximum Snow thickness was 0.22 m. In Kongsfjorden, 2004 was the year with highest maximum total thickness and Snow thickness relative to the other years.

scholarly journals Long-term variation of sea ice and its response to thermodynamic factors in the Northwest Passage of the Canadian Arctic Archipelago

2020 ◽  
Author(s):  
Xinyi Shen ◽  
Yu Zhang ◽  
Changsheng Chen ◽  
Song Hu
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
Ice Thickness ◽  
Sea Ice Concentration ◽  
Sea Ice Thickness ◽  
Northwest Passage ◽  
Arctic Sea ◽  
Ice Concentration ◽  
Ice Conditions ◽  
Thermodynamic Factors

Abstract. Sea ice conditions in the Canadian Arctic Archipelago (CAA) play a key role in the navigation of the Northwest Passage (NWP). Based on the observed and simulated sea ice concentration and thickness data, we studied the temporal and spatial characteristics of sea ice from 1979 to 2017 in the NWP of the CAA and evaluated the sea ice conditions along the southern and northern routes of the NWP. Against the background of the rapid retreat of Arctic sea ice, the 39-year observed sea ice concentration of the NWP exhibited a relatively large decreasing trend in summer and fall, while heavy sea ice conditions were maintained in winter and spring, with a slight increasing trend. Consistent with Arctic sea ice, the sea ice extent in the NWP displayed a decreasing trend of −2.34 %/10 a, with its minimum occurring in 2012. The sea ice thickness in most subregions of the NWP showed a decreasing trend, with the exception of Lancaster Sound. The decreasing trend of sea ice thickness in the NWP was estimated to −0.16 m/10 a. Based on the sea ice concentration and thickness, however, the sea ice conditions were heavier along the northern route than the southern route. This study considered both of these routes, and we selected and evaluated more specific pathways. The correlation results between the sea ice and atmospheric and oceanic thermodynamic factors in the NWP suggested that the thermodynamic factors had a greater impact on sea ice in the summer and fall, and the variations of sea ice concentration were more closely correlated with the thermodynamic factors than sea ice thickness. The sea surface temperature (SST) had a higher correlation with sea ice concentration than surface air temperature (SAT), while SAT exhibited a higher correlation with sea ice thickness than SST. The residual amount of sea ice concentration and thickness in the fall, associated with the fall SAT and SST, contributed to the formation of sea ice in the following winter and spring.

In-situ automatic observations of ice thickness of seas

2012 ◽  
Vol 19 (3) ◽  
pp. 583-592 ◽  
Author(s):  
Yinke Dou ◽  
Xiaomin Chang
Keyword(s):  
Sea Ice ◽  
New Technologies ◽  
Capacitive Sensor ◽  
Automatic Monitoring ◽  
Ice Thickness ◽  
In Situ Observation ◽  
Glacier Surface ◽  
Sea Ice Thickness ◽  
Surface Ice

Abstract Ice thickness is one of the most critical physical indicators in the ice science and engineering. It is therefore very necessary to develop in-situ automatic observation technologies of ice thickness. This paper proposes the principle of three new technologies of in-situ automatic observations of sea ice thickness and provides the findings of laboratory applications. The results show that the in-situ observation accuracy of the monitor apparatus based on the Magnetostrictive Delay Line (MDL) principle can reach ±2 mm, which has solved the “bottleneck” problem of restricting the fine development of a sea ice thermodynamic model, and the resistance accuracy of monitor apparatus with temperature gradient can reach the centimeter level and research the ice and snow substance balance by automatically measuring the glacier surface ice and snow change. The measurement accuracy of the capacitive sensor for ice thickness can also reach ±4 mm and the capacitive sensor is of the potential for automatic monitoring the water level under the ice and the ice formation and development process in water. Such three new technologies can meet different needs of fixed-point ice thickness observation and realize the simultaneous measurement in order to accurately judge the ice thickness.

Prévoir les variations saisonnières de la glace de mer arctique et leurs impacts sur le climat

2020 ◽  
pp. 024
Author(s):  
Rym Msadek ◽  
Gilles Garric ◽  
Sara Fleury ◽  
Florent Garnier ◽  
Lauriane Batté ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Region ◽  
Arctic Sea Ice ◽  
Climate Impacts ◽  
The Arctic ◽  
Recent Effort ◽  
Sea Ice Thickness ◽  
Arctic Sea ◽  
Ice Conditions ◽  
Upper Level

L'Arctique est la région du globe qui s'est réchauffée le plus vite au cours des trente dernières années, avec une augmentation de la température de surface environ deux fois plus rapide que pour la moyenne globale. Le déclin de la banquise arctique observé depuis le début de l'ère satellitaire et attribué principalement à l'augmentation de la concentration des gaz à effet de serre aurait joué un rôle important dans cette amplification des températures au pôle. Cette fonte importante des glaces arctiques, qui devrait s'accélérer dans les décennies à venir, pourrait modifier les vents en haute altitude et potentiellement avoir un impact sur le climat des moyennes latitudes. L'étendue de la banquise arctique varie considérablement d'une saison à l'autre, d'une année à l'autre, d'une décennie à l'autre. Améliorer notre capacité à prévoir ces variations nécessite de comprendre, observer et modéliser les interactions entre la banquise et les autres composantes du système Terre, telles que l'océan, l'atmosphère ou la biosphère, à différentes échelles de temps. La réalisation de prévisions saisonnières de la banquise arctique est très récente comparée aux prévisions du temps ou aux prévisions saisonnières de paramètres météorologiques (température, précipitation). Les résultats ayant émergé au cours des dix dernières années mettent en évidence l'importance des observations de l'épaisseur de la glace de mer pour prévoir l'évolution de la banquise estivale plusieurs mois à l'avance. Surface temperatures over the Arctic region have been increasing twice as fast as global mean temperatures, a phenomenon known as arctic amplification. One main contributor to this polar warming is the large decline of Arctic sea ice observed since the beginning of satellite observations, which has been attributed to the increase of greenhouse gases. The acceleration of Arctic sea ice loss that is projected for the coming decades could modify the upper level atmospheric circulation yielding climate impacts up to the mid-latitudes. There is considerable variability in the spatial extent of ice cover on seasonal, interannual and decadal time scales. Better understanding, observing and modelling the interactions between sea ice and the other components of the climate system is key for improved predictions of Arctic sea ice in the future. Running operational-like seasonal predictions of Arctic sea ice is a quite recent effort compared to weather predictions or seasonal predictions of atmospheric fields like temperature or precipitation. Recent results stress the importance of sea ice thickness observations to improve seasonal predictions of Arctic sea ice conditions during summer.

Assimilation of SMOS sea ice thickness in the regional ice prediction system

2021 ◽  
Vol 42 (12) ◽  
pp. 4583-4606
Author(s):  
Mukesh Gupta ◽  
Alain Caya ◽  
Mark Buehner
Keyword(s):  
Sea Ice ◽  
Ice Thickness ◽  
Prediction System ◽  
Sea Ice Thickness
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