scholarly journals Wave climate and storm activity in the Kara sea

2020 ◽  
Author(s):  
Stanislav Myslenkov ◽  
Vladimir Platonov ◽  
Alexander Kislov ◽  
Ksenia Silvestrova ◽  
Igor Medvedev
Keyword(s):  
Interannual Variability ◽  
Pareto Distribution ◽  
Ice Cover ◽  
Wave Climate ◽  
Kara Sea ◽  
The Arctic ◽  
Storm Activity ◽  
Storm Waves ◽  
Ice Conditions

Abstract. Recurrence of extreme wind waves in the Kara Sea strongly influences the Arctic climate change. The paper presents the analysis of wave climate and storm activity in the Kara Sea based on the results of numerical modeling. A third-generation wave model WaveWatchIII is used to reconstruct wind wave fields on an unstructured grid with a spatial resolution of 15–20 km for the period from 1979 to 2017. The mean and maximum wave heights, wavelengths and periods are calculated. The maximum significant wave height (SWH) for the whole period amounts to 9.9 m. The average long-term SWH for the ice-free period does not exceed 1.3 m. The seasonal variability of the wave parameters is analyzed. The interannual variability of storm waves recurrence with different thresholds (from 3 to 7 m) was calculated. A significant linear trend shows an increase in the storm wave frequency for the period from 1979 to 2017. A double growth in the reccurence was observed for cases with an SWH more than 3–5 m from 1979 to 2017. The local maximum of the storm waves more than 3–4 m was observed in 1995, and the minimum in 1998. The maximum value (four cases) of the number of storms with an SWH threshold 7 m is registered in 2016. The frequency of wind speeds and ice conditions contributing to the storm waves formation were analyzed. It is shown that trends in the storm activity of the Kara Sea are primarily regulated by the ice. If the ice cover decreases in the southern part of the sea that leads to the increase of the number of events only with SWH threshold more than 3–4 m. If in the entire sea the ice cover decreases that leads already to increase of the extreme storms. The frequency of strong and long-term winds has high interannual variability and a weak positive trend. The analysis of distribution functions of the storm events with an SWH more than 3 m was carried out. Six different sectors of the Kara Sea were analyzed to reveal spatial differences. A comparison of the different distribution laws showed that the Pareto distribution is in the best agreement with the data. Up to 99 % of the points are described by this distribution. However, the extreme events with an SWH more than 6–7 m deviate from the distribution, and their probability is approximately twice as less as that predicted by the Pareto distribution. Presumably, this deviation is caused by the combined impact of rare wind speed frequencies and anomalies of the sea ice conditions.

scholarly journals Thirty-Nine-Year Wave Hindcast, Storm Activity, and Probability Analysis of Storm Waves in the Kara Sea, Russia

Water ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 648
Author(s):  
Stanislav Myslenkov ◽  
Vladimir Platonov ◽  
Alexander Kislov ◽  
Ksenia Silvestrova ◽  
Igor Medvedev
Keyword(s):  
Climate Change ◽  
Pareto Distribution ◽  
Linear Trend ◽  
Wind Waves ◽  
Kara Sea ◽  
The Arctic ◽  
Storm Events ◽  
Storm Activity ◽  
Significant Linear Trend ◽  
The Impact

The recurrence of extreme wind waves in the Kara Sea strongly influences the Arctic climate change. The period 2000–2010 is characterized by significant climate warming, a reduction of the sea ice in the Arctic. The main motivation of this research to assess the impact of climate change on storm activity over the past 39 years in the Kara Sea. The paper presents the analysis of wave climate and storm activity in the Kara Sea based on the results of numerical modeling. A wave model WAVEWATCH III is used to reconstruct wind wave fields for the period from 1979 to 2017. The maximum significant wave height (SWH) for the whole period amounts to 9.9 m. The average long-term SWH for the ice-free period does not exceed 1.3 m. A significant linear trend shows an increase in the storm wave frequency for the period from 1979 to 2017. It is shown that trends in the storm activity of the Kara Sea are primarily regulated by the ice. Analysis of the extreme storm events showed that the Pareto distribution is in the best agreement with the data. However, the extreme events with an SWH more than 6‒7 m deviate from the Pareto distribution.

scholarly journals Variability of ice conditions of the Bering sea and assessment of the possibility of their modelling

2019 ◽  
Vol 59 (6) ◽  
pp. 920-927
Author(s):  
V. V. Plotnikov ◽  
N. M. Vakulskaya ◽  
V. A. Dubina
Keyword(s):  
Sea Ice ◽  
Interannual Variability ◽  
Bering Sea ◽  
Ice Cover ◽  
Practical Application ◽  
Seasonal And Interannual Variability ◽  
Proposed Model ◽  
Ice Conditions ◽  
The Bering Sea

Various aspects of seasonal and interannual variability of the sea ice cover are estimated on the basis of all available the Bering Sea ice data from 1960 to 2017. The possibility of long-term and superlong-term modeling of the ice cover is investigated. Results of tests are given, and a conclusion about prospects of the proposed model and an opportunity of its practical application is done.

scholarly journals Seasonal and interannual changes of ice massifs in East Siberian sea

2018 ◽  
Vol 64 (3) ◽  
pp. 229-240 ◽  
Author(s):  
A. V. Yulin ◽  
M. V. Sharatunova ◽  
E. A. Pavlova ◽  
V. V. Ivanov
Keyword(s):  
Interannual Variability ◽  
20Th Century ◽  
Autonomous Navigation ◽  
Ice Cover ◽  
Cold Period ◽  
Main Difficulty ◽  
East Siberian Sea ◽  
Climatic Period ◽  
Fast Decrease ◽  
Ice Conditions

The paper considers the seasonal and interannual variability of the Novosibirsky and Ayonsky ice massifs of the East Siberian Sea, which represent the main difficulty for navigation during summer.Analysis of ice conditions showed the tendency towards the onset of a new climatic period - “relative warming”. This is consistent with the regional quasi-periodic 30-year alternations beetween the “relatively cold” and “relatively warm” climatic periods identified in the AARI.We have compared ice conditions of the “relatively cold” period of 1958–1987 and the “relatively warm” period of 1988–2017. Since the end of the 1980s the ice massifs began to decrease more intensively with the onset of break up some 10–20 days earlier.In general, the drift ice area during  summer has decreased by 15–20 % in the western part of the sea and by 20–30 % in eastern one. The fast decrease of close floatingice in the East Siberian Sea observed in the last decades resulted in increase of the possibilities of autonomous navigation.The latest works containing the analysis of in conditions of the East Siberian Sea belong to the 90s of last century. In these works ice conditions of the period of the 40–80s of the 20th century were considered. During this period, the background of the ice cover extent was high. As a result, the usage of the average values of ice massifs areas calculated on all observations series (since 1946), is not informative for characterizing ice conditions during separately taken periods.

scholarly journals Wave Climate from Spectra and Its Connections with Local and Remote Wind Climate

2019 ◽  
Vol 49 (2) ◽  
pp. 543-559 ◽  
Author(s):  
Haoyu Jiang ◽  
Lin Mu
Keyword(s):  
Wind Field ◽  
Wave Climate ◽  
The Arctic ◽  
Target Point ◽  
Wave Spectra ◽  
Basin Scale ◽  
Long Term Trends ◽  
Wind Climate ◽  
Climate Systems

AbstractWind-generated waves can propagate over large distances. Therefore, wave spectra from a fixed point can record information about air–sea interactions in distant areas. In this study, the spectral wave climate for a point in the tropical eastern Pacific Ocean is computed. Several well-defined wave climate systems are observed in the mean wave spectrum. Significant seasonal cycling, long-term trends, and correlations with the Southern Oscillation, the Arctic Oscillation, and the Antarctic Oscillation are observed in the local wave spectra, showing abundant climatic information. Projections of wind vectors on the directions pointing to the target location are used to connect the spectral wave climate and basin-scale wind climate, because significant correlations are observed between the wave spectra and the wind projections of both local and remote wind systems. The origins of all the identified wave climate systems, including the westerlies and the trade winds in both hemispheres, are clearly shown in wind projection maps. Some of these origins are thousands of kilometers away from the target point, demonstrating the validity of this connection. Comparisons are made between wave spectra and the corresponding local and remote wind fields with respect to seasonal and interannual variability and long-term trends. The results show that each frequency and direction of ocean wave spectra at a certain location can be approximately linked to the wind field for a geographical area, implying that it is feasible to reconstruct spectral wave climates from observational wind field data and monitor wind climates from observational wave spectra geographically far away.

Growth of Wave Height with Retreating Ice Cover in the Arctic

2020 ◽  
Author(s):  
Changlong Guan ◽  
Jingkai Li
Keyword(s):  
Arctic Ocean ◽  
Surface Waves ◽  
Wave Height ◽  
Open Water ◽  
Ice Cover ◽  
Wave Climate ◽  
Least Square ◽  
The Arctic ◽  
The Arctic Ocean ◽  
Wave Heights

<p>For the Arctic surface waves, one of the most uncontroversial viewpoints is that their escalation in the past few years is mainly caused by the ice extent reduction. Ice retreat enlarges the open water area, i.e., the effective fetch, and thus allows more wind input energy and available distance for wave evolution. This knowledge has been supported by a few previous studies on the Arctic waves which analyzed the correlation between time-series variations in wave height and ice coverage. However, from the perspective of space, the detailed relationship between retreating ice cover and increasing surface waves is not well studied. Hence, we performed such a study for the whole Arctic and its subregions, which will be helpful for a better understanding of the wave climate and for forecasting waves in the Arctic Ocean.</p><p>Wave data are produced by twelve-year (2007-2018) hindcasts of summer melt seasons (May-Sept.) and numerical tests with WAVEWATCH III. When a viscoelastic wave-ice model and a spherical multiple-cell grid are applied, simulated wave heights agree with available buoy data and previous research. After the validations, simulated significant wave heights over twelve-year summer melt seasons are used to demonstrate the detailed relationship between the escalation of wave height and reduction of ice extent for the whole Arctic and seven subregions. Through least square regression, we find that the mean wave height in the Arctic Ocean will increase by 0.071m (10<sup>6</sup>km<sup>2</sup>)<sup>-1</sup> when the ice extent is smaller than 9.4×10<sup>6</sup>km<sup>2</sup>, and roughly 51% is contributed by the enlarged fetch. By analyzing the nondimensional wave energy and comparing the simulated wave height with Wilson IV, we prove the swell is widespread during the summertime in the current Arctic Ocean. Furthermore, we also display the variations in probabilities of occurrence of large waves as ice-edge retreats in seven subregions. Assuming that an ice free period occurs in the Arctic in September, the model results show that the simulated mean wave height is approximately 1.6m and the large waves occur much more frequently, which mean that the growth rate of wave height will be higher if the minimum ice extent keeps reducing in the future.</p>

scholarly journals Analysis of dynamics for anomalies of the ice cover in the Okhotsk Sea in the period from 1882 to 2015

2016 ◽  
Vol 185 (2) ◽  
pp. 228-239
Author(s):  
Vladimir M. Pishchalnik ◽  
Valery A. Romanyuk ◽  
Igor G. Minervin ◽  
Alevtina S. Batuhtina
Keyword(s):  
Time Series ◽  
Air Temperature ◽  
Regime Shift ◽  
Ice Cover ◽  
Satellite Observations ◽  
Okhotsk Sea ◽  
Ice Conditions ◽  
The Mean ◽  
Analysis Of Dynamics

The time-series for the ice cover dynamics in the Okhotsk Sea in the period from 1882 to 2015 are reconstructed on the base of shipboard, airborne, and satellite observations and measurements of the air temperature at the coastal meteorological stations. Abnormality of the ice conditions is estimated relative to the “climate norm” determined as the mean seasonal variation for the 1961-1990. Long-term variability of the ice cover is analyzed. Its regime shift with change of trend is revealed in the late 1970s - early 1980s that corresponds to the regime shift of the air temperature variability in the northern hemisphere.

scholarly journals Wave Climate Associated With Changing Water Level and Ice Cover in Lake Michigan

2021 ◽  
Vol 8 ◽  
Author(s):  
Chenfu Huang ◽  
Longhuan Zhu ◽  
Gangfeng Ma ◽  
Guy A. Meadows ◽  
Pengfei Xue
Keyword(s):  
Climate Change ◽  
Water Level ◽  
Lake Michigan ◽  
Linear Trend ◽  
Ice Cover ◽  
Wave Climate ◽  
Water Levels ◽  
Regional Warming ◽  
Model Simulations

Detailed knowledge of wave climate change is essential for understanding coastal geomorphological processes, ecosystem resilience, the design of offshore and coastal engineering structures and aquaculture systems. In Lake Michigan, the in-situ wave observations suitable for long-term analysis are limited to two offshore MetOcean buoys. Since this distribution is inadequate to fully represent spatial patterns of wave climate across the lake, a series of high-resolution SWAN model simulations were performed for the analysis of long-term wave climate change for the entirety of Lake Michigan from 1979 to 2020. Model results were validated against observations from two offshore buoys and 16 coastal buoys. Linear regression analysis of significant wave height (Hs) (mean, 90th percentile, and 99th percentile) across the entire lake using this 42-year simulation suggests that there is no simple linear trend of long-term changes of Hs for the majority (>90%) of the lake. To address the inadequacy of linear trend analysis used in previous studies, a 10-year trailing moving mean was applied to the Hs statistics to remove seasonal and annual variability, focusing on identifying long-term wave climate change. Model results reveal the regime shifts of Hs that correspond to long-term lake water level changes. Specifically, downward trends of Hs were found in the decade of 1990–2000; low Hs during 2000–2010 coincident with low lake levels; and upward trends of Hs were found during 2010–2020 along with rising water levels. The coherent pattern between the wave climate and the water level was hypothesized to result from changing storm frequency and intensity crossing the lake basin, which influences both waves (instantly through increased wind stress on the surface) and water levels (following, with a lag through precipitation and runoff). Hence, recent water level increases and wave growth were likely associated with increased storminess observed in the Great Lakes. With regional warming, the decrease in ice cover in Lake Michigan (particularly in the northernmost region of the lake) favored the wave growth in the winter due to increased surface wind stress, wind fetch, and wave transmission. Model simulations suggest that the basin-wide Hs can increase significantly during the winter season with projected regional warming and associated decreases in winter ice cover. The recent increases in wave height and water level, along with warming climate and ice reduction, may yield increasing coastal damages such as accelerating coastal erosion.

The impact of denying sea ice information on the predictability of atmospheric processes over the Arctic and at mid-latitude regions

2020 ◽  
Author(s):  
Leandro Ponsoni ◽  
Daniela Flocco ◽  
François Massonnet ◽  
Steve Delhaye ◽  
Ed Hawkins ◽  
...  
Keyword(s):  
Sea Ice ◽  
General Circulation ◽  
Model Comparison ◽  
General Circulation Models ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Atmospheric Processes ◽  
Ice Conditions ◽  
The Impact

<p>In this work, we make use of an inter-model comparison and of a perfect model approach, in which model outputs are used as true reference states, to assess the impact that denying sea ice information has on the prediction of atmospheric processes, both over the Arctic and at mid-latitude regions. To do so, two long-term control runs (longer than 250 years) were generated with two state-of-the-art General Circulation Models (GCM), namely EC-Earth and HadGEM. From these two reference states, we have identified three different years in which the Arctic sea ice volume (SIV) was (i) maximum, (ii) minimum and (iii) a representative case for the mean state. By departing from each of these three dates (not necessarily the same for the two models), we generated a set of experiments in which the control runs are restarted both from original and climatological sea ice conditions. Here, climatological sea ice conditions are estimated as the time-average of sea ice parameters from the respective long-term control runs. The experiments are 1-year long and all of them start in January when ice is still thin, snow depth is small, air-ocean temperatures contrast the most and, therefore, the heat conductive flux in sea ice (at the surface) is nearly maximum. To robustly separate the response to degrading the initial sea ice state from background internal variability, each of the two counterfactual experiments (reference and climatological) consists of 50 ensembles members. Threstatedese ensembles are generated by adding small random perturbations to the sea surface temperature (EC-Earth) or to the air temperature (HadGEM) fields. Preliminary results reinforce the importance of having the right sea ice state for improving the (sub-)seasonal prediction of atmospheric parameters (e.g., 2m-temperature and geopotential) and circulation (e.g., Westerlies and Jet Stream) not only over the Arctic, but also at mid-latitude regions.</p>

Landfast ice zoning from SAR imagery

2020 ◽  
Author(s):  
Valeria Selyuzhenok ◽  
Denis Demchev ◽  
Thomas Krumpen
Keyword(s):  
Time Series ◽  
Sea Ice ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Ice Drift ◽  
Landfast Ice ◽  
Sea Ice Drift ◽  
Ice Conditions ◽  
Sar Imagery

<p>Landfast sea ice is a dominant sea ice feature of the Arctic coastal region. As a part of Arctic sea ice cover, landfast ice is an important part of coastal ecosystem, it provides functions as a climate regulator and platform for human activity. Recent changes in sea ice conditions in the Arctic have also affected landfast ice regime. At the same time, industrial interest in the Arctic shelf seas continue to increase. Knowledge on local landfast ice conditions are required to ensure safety of on ice operations and accurate forecasting.  In order to obtain a comprehensive information on landfast ice state we use a time series of wide swath SAR imagery.  An automatic sea ice tracking algorithm was applied to the sequential SAR images during the development stage of landfast ice cover. The analysis of resultant time series of sea ice drift allows to classify homogeneous sea ice drift fields and timing of their attachment to the landfast ice. In addition, the drift data allows to locate areas of formation of grounded sea ice accumulation called stamukha. This information сan be useful for local landfast ice stability assessment. The study is supported by the Russian Foundation for Basic Research (RFBR) grant 19-35-60033.</p>

Dynamic–Thermodynamic Sea Ice Model: Ridging and Its Application to Climate Study and Navigation

2005 ◽  
Vol 18 (18) ◽  
pp. 3840-3855 ◽  
Author(s):  
Sergey V. Shoutilin ◽  
Alexander P. Makshtas ◽  
Motoyoshi Ikeda ◽  
Alexey V. Marchenko ◽  
Roman V. Bekryaev
Keyword(s):  
Sea Ice ◽  
Arctic Basin ◽  
Circulation Pattern ◽  
Ice Cover ◽  
The Arctic ◽  
Partial Recovery ◽  
Pacific Side ◽  
Pattern Production ◽  
Ice Model

Abstract A dynamic–thermodynamic sea ice model with the ocean mixed layer forced by atmospheric data is used to investigate spatial and long-term variability of the sea ice cover in the Arctic basin. The model satisfactorily reproduces the averaged main characteristics of the sea ice and its extent in the Arctic Basin, as well as its decrease in the early 1990s. Employment of the average ridge shape for describing the ridging allows the authors to suggest that it occurs in winter and varies from year to year by a factor of 2, depending on an atmospheric circulation pattern. Production and horizontal movement of ridges are the focus in this paper, as they show the importance of interannual variability of the Arctic ice cover. The observed thinning in the 1990s is a result of reduction in ridge formation on the Pacific side during the cyclonic phase of the Arctic Oscillation. The model yields a partial recovery of sea ice cover in the last few years of the twentieth century. In addition to the sea ice cover and average thickness compared with satellite data, the ridge amount is verified with observations taken in the vicinity of the Russian coast. The model results are useful to estimate long-term variability of the probability of ridge-free navigation in different parts of the Arctic Ocean, including the Northern Sea Route area.

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