scholarly journals The effect of changing sea ice on nearshore wave climate trends along Alaska’s central Beaufort Sea coast

2021 ◽  
Author(s):  
Kees Nederhoff ◽  
Li Erikson ◽  
Anita Engelstad ◽  
Peter Bieniek ◽  
Jeremy Kasper
Keyword(s):  
Sea Ice ◽  
Recent Observation ◽  
Open Water ◽  
Beaufort Sea ◽  
Wave Climate ◽  
The Arctic ◽  
Wave Power ◽  
Time Period ◽  
Wave Heights ◽  
Sea Coast

Abstract. Diminishing sea ice is impacting the wave field across the Arctic region. Recent observation and model-based studies highlight the spatiotemporal influence of sea ice on offshore wave climatologies, but effects within the nearshore region are still poorly described. This study characterizes the wave climate in the central Beaufort Sea coast from 1979 to 2019 by utilizing a wave hindcast model that uses ERA5 winds, waves, and ice concentrations as input. The spectral wave model SWAN is calibrated and validated based on more than 10,000 in situ measurements collected over a 13-year time period across the region, with friction variations and empirical coefficients for newly implemented empirical ice formulations for the open water season. Model results and trends are analyzed over the 41-year time period using the non-parametric Mann-Kendall test, including an estimate of Sen’s slope. The model results show that the reduction of sea ice concentration correlates strongly with increases in average and extreme wave conditions. In particular, the open water season extended by ~96 days over the 41-year time period (~2.4 days/yr), resulting in a five-fold increase of the yearly cumulative wave power. Moreover, the open water season extends later into the year, resulting in relatively open-water conditions during fall storms with high wind speeds. The later freeze-up results in an increase of the annual offshore median wave heights of 1 % per year and an increase in the average number of rough wave days (defined as days when maximum wave heights exceed 2.5 m) from 1.5 in 1979 to 13.1 days in 2019. Trends in the nearshore areas deviate from the patterns offshore. Model results indicate a non-breaking depth-induced saturation limit for high wave heights in the shallow areas of Foggy Island Bay. Similar patterns are found for yearly cumulative wave power.

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>

Evaluation of PAZ satellite imagery for the assessment of intra-seasonal dynamics of permafrost coasts (Beaufort Sea, Canada)

2021 ◽  
Author(s):  
Carla Mora ◽  
Gonçalo Vieira ◽  
Pedro Pina ◽  
Dustin Whalen ◽  
Annett Bartsch
Keyword(s):  
High Resolution ◽  
Sea Ice ◽  
Tide Gauge ◽  
Beaufort Sea ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Coastal Monitoring ◽  
Horizon 2020 ◽  
Coastal Changes ◽  
Sea Coast

<p>Arctic permafrost coasts represent about 34% of the Earth’s coastline, with long sections affected by high erosion rates, increasingly threatening coastal communities. Year-round reduction in Arctic sea ice is forecasted and by the end of the 21st century, models indicate a decrease in sea ice area from 43 to 94% in September and from 8 to 34% in February (IPCC, 2014). An increase of the ice-free season leads to a longer exposure to wave action. Monitoring the Arctic coasts is limited by remoteness, climate harshness and difficulty of access for direct surveying, but also, when using satellite remote sensing, by frequent high cloudiness conditions and by illumination. In order to overcome these limitations, three sites at the Beaufort Sea Coast (Clarence lagoon, Hopper Island and Qikiqtaruk/Herschel Island) have been selected for monitoring using very high-resolution microwave X-band spotlight PAZ imagery from Hisdesat. Bluff top, thaw-slump headwalls and water lines were digitised from images acquired during the ice-free seasons of 2019 and 2020 at sub-monthly time-steps. The effects of coastal exposure on delineation accuracy in relation to satellite overpass geometry have been assessed and coastal changes have been quantified and compared to meteorological and tide-gauge data. The results show that PAZ imagery allow for monitoring and quantifying coastal changes at sub-monthly intervals and following the evolution of coastal features, such as small mud-flow fans and retrogressive thaw slumps. This shows that high resolution microwave imagery has a strong potential for significantly advancing coastal monitoring in remote Arctic areas. This research is part of project Nunataryuk funded under the European Union's Horizon 2020 Research and Innovation Programme (grant agreement no. 773421) and of Hisdesat project Coastal Monitoring for Permafrost Research in the Beaufort Sea Coast (Canada). </p>

scholarly journals Wave climate in the Arctic 1992–2014: seasonality and trends

2016 ◽  
Vol 10 (4) ◽  
pp. 1605-1629 ◽  
Author(s):  
Justin E. Stopa ◽  
Fabrice Ardhuin ◽  
Fanny Girard-Ardhuin
Keyword(s):  
Sea Ice ◽  
Wave Climate ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Altimeter Data ◽  
Data Set ◽  
Wave Hindcast ◽  
Wind Speeds ◽  
Ice Coverage ◽  
Wave Heights

Abstract. Over the past decade, the diminishing Arctic sea ice has impacted the wave field, which depends on the ice-free ocean and wind. This study characterizes the wave climate in the Arctic spanning 1992–2014 from a merged altimeter data set and a wave hindcast that uses CFSR winds and ice concentrations from satellites as input. The model performs well, verified by the altimeters, and is relatively consistent for climate studies. The wave seasonality and extremes are linked to the ice coverage, wind strength, and wind direction, creating distinct features in the wind seas and swells. The altimeters and model show that the reduction of sea ice coverage causes increasing wave heights instead of the wind. However, trends are convoluted by interannual climate oscillations like the North Atlantic Oscillation (NAO) and Pacific Decadal Oscillation. In the Nordic Greenland Sea the NAO influences the decreasing wind speeds and wave heights. Swells are becoming more prevalent and wind-sea steepness is declining. The satellite data show the sea ice minimum occurs later in fall when the wind speeds increase. This creates more favorable conditions for wave development. Therefore we expect the ice freeze-up in fall to be the most critical season in the Arctic and small changes in ice cover, wind speeds, and wave heights can have large impacts to the evolution of the sea ice throughout the year. It is inconclusive how important wave–ice processes are within the climate system, but selected events suggest the importance of waves within the marginal ice zone.

Segregation of Beaufort Sea beluga whales during the open-water season

2006 ◽  
Vol 84 (12) ◽  
pp. 1743-1751 ◽  
Author(s):  
L.L. Loseto ◽  
P. Richard ◽  
G.A. Stern ◽  
J. Orr ◽  
S.H. Ferguson
Keyword(s):  
Habitat Use ◽  
Sea Ice ◽  
Resource Selection ◽  
Open Water ◽  
Beaufort Sea ◽  
Reproductive Status ◽  
The Arctic ◽  
Habitat Segregation ◽  
Beluga Whales ◽  
Distance Analysis

Population segregation by habitat use occurs because energy requirements and survival strategies vary with age, sex, size, and reproductive stage. From late summer to early fall in 1993, 1995, and 1997, relative length (age), sex, and reproductive status of satellite-tagged beluga whales ( Delphinapterus leucas (Pallas, 1776)) in the eastern Beaufort Sea were tested for habitat segregation. We used (i) resource selection function models to evaluate how belugas used areas of varying sea ice concentration and shelf habitat and (ii) distance analysis to measure the selection of areas varying in distance to mainland and island coastlines. Resource selection functions and distance analysis established that habitat selection differed with length, sex, and reproductive status of whales: (i) females with calves and smaller males selected open-water habitats near the mainland; (ii) large males selected closed sea ice cover in and near the Arctic Archipelago; and (iii) smaller males and two females with calves (not newborn) selected habitat near the ice edge. The segregation of habitat use according to sex, age, and reproductive status relates to the different resources required at different life stages and may represent characteristics of beluga social structure. We discuss our results in the context of two common sexual segregation hypotheses and conclude that summer habitat segregation of belugas reflects differences in foraging ecology, risk of predation, and reproduction.

scholarly journals Retrieval of Summer Sea Ice Concentration in the Pacific Arctic Ocean from AMSR2 Observations and Numerical Weather Data Using Random Forest Regression

2021 ◽  
Vol 13 (12) ◽  
pp. 2283
Author(s):  
Hyangsun Han ◽  
Sungjae Lee ◽  
Hyun-Cheol Kim ◽  
Miae Kim
Keyword(s):  
Random Forest ◽  
Sea Ice ◽  
Arctic Ocean ◽  
Open Water ◽  
The Arctic ◽  
Atmospheric Effects ◽  
Sea Ice Concentration ◽  
Air Temperatures ◽  
The Pacific ◽  
Ice Concentration

The Arctic sea ice concentration (SIC) in summer is a key indicator of global climate change and important information for the development of a more economically valuable Northern Sea Route. Passive microwave (PM) sensors have provided information on the SIC since the 1970s by observing the brightness temperature (TB) of sea ice and open water. However, the SIC in the Arctic estimated by operational algorithms for PM observations is very inaccurate in summer because the TB values of sea ice and open water become similar due to atmospheric effects. In this study, we developed a summer SIC retrieval model for the Pacific Arctic Ocean using Advanced Microwave Scanning Radiometer 2 (AMSR2) observations and European Reanalysis Agency-5 (ERA-5) reanalysis fields based on Random Forest (RF) regression. SIC values computed from the ice/water maps generated from the Korean Multi-purpose Satellite-5 synthetic aperture radar images from July to September in 2015–2017 were used as a reference dataset. A total of 24 features including the TB values of AMSR2 channels, the ratios of TB values (the polarization ratio and the spectral gradient ratio (GR)), total columnar water vapor (TCWV), wind speed, air temperature at 2 m and 925 hPa, and the 30-day average of the air temperatures from the ERA-5 were used as the input variables for the RF model. The RF model showed greatly superior performance in retrieving summer SIC values in the Pacific Arctic Ocean to the Bootstrap (BT) and Arctic Radiation and Turbulence Interaction STudy (ARTIST) Sea Ice (ASI) algorithms under various atmospheric conditions. The root mean square error (RMSE) of the RF SIC values was 7.89% compared to the reference SIC values. The BT and ASI SIC values had three times greater values of RMSE (20.19% and 21.39%, respectively) than the RF SIC values. The air temperatures at 2 m and 925 hPa and their 30-day averages, which indicate the ice surface melting conditions, as well as the GR using the vertically polarized channels at 23 GHz and 18 GHz (GR(23V18V)), TCWV, and GR(36V18V), which accounts for atmospheric water content, were identified as the variables that contributed greatly to the RF model. These important variables allowed the RF model to retrieve unbiased and accurate SIC values by taking into account the changes in TB values of sea ice and open water caused by atmospheric effects.

scholarly journals Observations and Simulations of Meteorological Conditions over Arctic Thick Sea Ice in Late Winter during the Transarktika 2019 Expedition

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 174
Author(s):  
Günther Heinemann ◽  
Sascha Willmes ◽  
Lukas Schefczyk ◽  
Alexander Makshtas ◽  
Vasilii Kustov ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Open Water ◽  
The Arctic ◽  
Late Winter ◽  
Good Representation ◽  
Hourly Temperature ◽  
Ice Model

The parameterization of ocean/sea-ice/atmosphere interaction processes is a challenge for regional climate models (RCMs) of the Arctic, particularly for wintertime conditions, when small fractions of thin ice or open water cause strong modifications of the boundary layer. Thus, the treatment of sea ice and sub-grid flux parameterizations in RCMs is of crucial importance. However, verification data sets over sea ice for wintertime conditions are rare. In the present paper, data of the ship-based experiment Transarktika 2019 during the end of the Arctic winter for thick one-year ice conditions are presented. The data are used for the verification of the regional climate model COSMO-CLM (CCLM). In addition, Moderate Resolution Imaging Spectroradiometer (MODIS) data are used for the comparison of ice surface temperature (IST) simulations of the CCLM sea ice model. CCLM is used in a forecast mode (nested in ERA5) for the Norwegian and Barents Seas with 5 km resolution and is run with different configurations of the sea ice model and sub-grid flux parameterizations. The use of a new set of parameterizations yields improved results for the comparisons with in-situ data. Comparisons with MODIS IST allow for a verification over large areas and show also a good performance of CCLM. The comparison with twice-daily radiosonde ascents during Transarktika 2019, hourly microwave water vapor measurements of first 5 km in the atmosphere and hourly temperature profiler data show a very good representation of the temperature, humidity and wind structure of the whole troposphere for CCLM.

Eddy covariance flux measurements of momentum, heat and carbon dioxide in Hudson Bay at the onset of sea ice melt 

2021 ◽  
Author(s):  
Richard Sims ◽  
Brian Butterworth ◽  
Tim Papakyriakou ◽  
Mohamed Ahmed ◽  
Brent Else
Keyword(s):  
Carbon Dioxide ◽  
Gas Exchange ◽  
Sea Ice ◽  
Eddy Covariance ◽  
Open Water ◽  
The Arctic ◽  
Gas Transfer ◽  
Hudson Bay ◽  
Flux Measurements ◽  
Ice Fraction

<p>Remoteness and tough conditions have made the Arctic Ocean historically difficult to access; until recently this has resulted in an undersampling of trace gas and gas exchange measurements. The seasonal cycle of sea ice completely transforms the air sea interface and the dynamics of gas exchange. To make estimates of gas exchange in the presence of sea ice, sea ice fraction is frequently used to scale open water gas transfer parametrisations. It remains unclear whether this scaling is appropriate for all sea ice regions. Ship based eddy covariance measurements were made in Hudson Bay during the summer of 2018 from the icebreaker CCGS Amundsen. We will present fluxes of carbon dioxide (CO<sub>2</sub>), heat and momentum and will show how they change around the Hudson Bay polynya under varying sea ice conditions. We will explore how these fluxes change with wind speed and sea ice fraction. As freshwater stratification was encountered during the cruise, we will compare our measurements with other recent eddy covariance flux measurements made from icebreakers and also will compare our turbulent CO<sub>2 </sub>fluxes with bulk fluxes calculated using underway and surface bottle pCO<sub>2</sub> data. </p><p> </p>

Increasing Multiyear Sea Ice Loss in the Beaufort Sea: A New Export Pathway for the Diminishing Multiyear Ice Cover of the Arctic Ocean

2021 ◽  
Author(s):  
David Gareth Babb ◽  
Ryan J. Galley ◽  
Stephen E. L. Howell ◽  
Jack Christopher Landy ◽  
Julienne Christine Stroeve ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Beaufort Sea ◽  
Ice Cover ◽  
The Arctic ◽  
Export Pathway ◽  
The Arctic Ocean ◽  
Multiyear Ice

scholarly journals Inorganic carbon fluxes on the Mackenzie Shelf of the Beaufort Sea

2017 ◽  
Author(s):  
Jacoba Mol ◽  
Helmuth Thomas ◽  
Paul G. Myers ◽  
Xianmin Hu ◽  
Alfonso Mucci
Keyword(s):  
Sea Ice ◽  
Inorganic Carbon ◽  
Dissolved Inorganic Carbon ◽  
Beaufort Sea ◽  
Total Alkalinity ◽  
The Arctic ◽  
Surface Mixed Layer ◽  
Saturation State ◽  
Carbon Transfer ◽  
Mackenzie Shelf

Abstract. The Mackenzie Shelf in the southeastern Beaufort Sea is a region that has experienced large changes in the past several decades as warming, sea-ice loss, and increased river discharge have altered carbon cycling. Upwelling and downwelling events are common on the shelf, caused by strong, fluctuating along-shore winds, resulting in cross-shelf Ekman transport, and an alternating estuarine and anti-estuarine circulation. Downwelling carries inorganic carbon and other remineralization products off the shelf and into the deep basin for possible long-term storage in the world oceans. Upwelling carries dissolved inorganic carbon (DIC) and nutrient-rich waters from the Pacific-origin upper halocline layer (UHL) onto the shelf. Profiles of DIC and total alkalinity (TA) taken in August and September of 2014 are used to investigate the cycling of inorganic carbon on the Mackenzie Shelf. The along-shore transport of water and the cross-shelf transport of inorganic carbon are quantified using velocity field output from a simulation of the Arctic and Northern Hemisphere Atlantic (ANHA4) configuration of the Nucleus of European Modelling of the Ocean (NEMO) framework. A strong upwelling event prior to sampling on the Mackenzie Shelf is analyzed and the resulting influence on the carbonate system, including the saturation state of waters with respect to aragonite and pH, is investigated. TA and the oxygen isotope ratio of water (δ18O) are used to examine water-mass distributions in the study area and to investigate the influence of Pacific Water, Mackenzie River freshwater, and sea-ice melt on carbon dynamics and air-sea fluxes of carbon dioxide (CO2) in the surface mixed layer. Understanding carbon transfer in this seasonally dynamic environment is key to quantify the importance of Arctic shelf regions to the global carbon cycle and provide a basis for understanding how it will respond to the aforementioned climate-induced changes.

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