scholarly journals Is it ‘boom times’ for baleen whales in the Pacific Arctic region?

2016 ◽  
Vol 12 (9) ◽  
pp. 20160251 ◽  
Author(s):  
Sue E. Moore
Keyword(s):  
Sea Ice ◽  
Marine Ecosystem ◽  
Late Summer ◽  
Arctic Region ◽  
Open Water ◽  
Bowhead Whale ◽  
The Arctic ◽  
Ecosystem Structure ◽  
Baleen Whales ◽  
The Pacific

The marine ecosystem in the Pacific Arctic region has experienced dramatic transformation, most obvious by the loss of sea ice volume (75%), late-summer areal extent (50%) and change in phenology (four to six weeks longer open-water period). This alteration has resulted in an opening of habitat for subarctic species of baleen whales, many of which are recovering in number from severe depletions from commercial whaling in the nineteenth and twentieth centuries. Specifically, humpback, fin and minke whales ( Megaptera novaeangliae , Balaenoptera physalus and Balaenoptera acutorostrata ) are now regularly reported during summer and autumn in the southern Chukchi Sea. These predators of zooplankton and forage fishes join the seasonally resident grey whale ( Eschrichtius robustus ) and the arctic-endemic bowhead whale ( Balaena mysticetus ) in the expanding open-ocean habitat of the Pacific Arctic. Questions arising include: (i) what changes in whale-prey production and delivery mechanisms have accompanied the loss of sea ice, and (ii) how are these five baleen whale species partitioning the expanding ice-free habitat? While there has been no programme of research specifically focused on these questions, an examination of seasonal occurrence, foraging plasticity and (for bowhead whales) body condition suggests that the current state of Pacific Arctic marine ecosystem may be ‘boom times’ for baleen whales. These favourable conditions may be moderated, however, by future shifts in ecosystem structure and/or negative impacts to cetaceans related to increased commercial activities in the region.

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 Record high Pacific Arctic seawater temperatures and delayed sea ice advance in response to episodic atmospheric blocking

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Tsubasa Kodaira ◽  
Takuji Waseda ◽  
Takehiko Nose ◽  
Jun Inoue
Keyword(s):  
Sea Ice ◽  
Arctic Region ◽  
Arctic Sea Ice ◽  
Sea Surface ◽  
The Arctic ◽  
Atmospheric Blocking ◽  
Sea Ice Extent ◽  
The Pacific ◽  
Arctic Sea ◽  
Highly Correlated

AbstractArctic sea ice is rapidly decreasing during the recent period of global warming. One of the significant factors of the Arctic sea ice loss is oceanic heat transport from lower latitudes. For months of sea ice formation, the variations in the sea surface temperature over the Pacific Arctic region were highly correlated with the Pacific Decadal Oscillation (PDO). However, the seasonal sea surface temperatures recorded their highest values in autumn 2018 when the PDO index was neutral. It is shown that the anomalous warm seawater was a rapid ocean response to the southerly winds associated with episodic atmospheric blocking over the Bering Sea in September 2018. This warm seawater was directly observed by the R/V Mirai Arctic Expedition in November 2018 to significantly delay the southward sea ice advance. If the atmospheric blocking forms during the PDO positive phase in the future, the annual maximum Arctic sea ice extent could be dramatically reduced.

Record high Pacific Arctic seawater temperatures and delayed sea ice advance in response to episodic atmospheric blocking

2021 ◽  
Author(s):  
Tsubasa Kodaira ◽  
Takuji Waseda ◽  
Takehiko Nose ◽  
Jun Inoue
Keyword(s):  
Sea Ice ◽  
Arctic Region ◽  
Arctic Sea Ice ◽  
Sea Surface ◽  
The Arctic ◽  
Atmospheric Blocking ◽  
Sea Ice Extent ◽  
The Pacific ◽  
Arctic Sea ◽  
Highly Correlated

<p>Arctic sea ice is rapidly decreasing during the recent period of global warming. One of the significant factors of the Arctic sea ice loss is oceanic heat transport from lower latitudes. For months of sea ice formation, the variations in the sea surface temperature over the Pacific Arctic region were highly correlated with the Pacific Decadal Oscillation (PDO). However, the seasonal sea surface temperatures recorded their highest values in autumn 2018 when the PDO index was neutral. It is shown that the anomalous warm seawater was a rapid ocean response to the southerly winds associated with episodic atmospheric blocking over the Bering Sea in September 2018. This warm seawater was directly observed by the R/V Mirai Arctic Expedition in November 2018 to significantly delay the southward sea ice advance. If the atmospheric blocking forms during the PDO positive phase in the future, the annual maximum Arctic sea ice extent could be dramatically reduced.</p>

scholarly journals Spring partitioning of Disko Bay, West Greenland, by Arctic and Subarctic baleen whales

2012 ◽  
Vol 69 (7) ◽  
pp. 1226-1233 ◽  
Author(s):  
Kristin L. Laidre ◽  
Mads Peter Heide-Jørgensen
Keyword(s):  
Climate Change ◽  
Sea Ice ◽  
Satellite Telemetry ◽  
Open Water ◽  
The Arctic ◽  
Interspecies Interactions ◽  
Baleen Whales ◽  
West Greenland ◽  
Bowhead Whales ◽  
Departure Date

Abstract Laidre, K. L., and Heide-Jørgensen, M. P. 2012. Spring partitioning of Disko Bay, West Greenland, by Arctic and Subarctic baleen whales. – ICES Journal of Marine Science, 69: . Movements of co-occurring bowhead (Balaena mysticetus) and humpback (Megaptera novaeangliae) whales in Disko Bay, West Greenland, were examined using satellite telemetry. Data on movements, habitat use, and phenology were collected from tagged 49 bowheads and 44 humpbacks during the transition from sea-ice breakup to open water between 2008 and 2010. Bowhead whales began their northward spring migration around 27 May (median day-of-the-year departure date = 147, interquartile range 141–153) and were distributed broadly in northern and central Disko Bay in water depths between 100 and 400 m. Humpback whales arrived in Disko Bay no later than 2 June and were located in shallow water (<100 m) along the coasts of the mainland or Disko Island. Trends in departure date from Disko Bay were significant for bowhead whales (∼15 d later, p < 0.001) between two periods: 2001–2006 and 2008–2010. Many species are predicted to arrive earlier in the Arctic and to expand their range northwards with reduced sea ice and increasing temperatures under climate change. Quantifying the spatial and temporal relationships between co-occurring Arctic and Subarctic top predators allows for baseline insight to be gained on how climate change might alter interspecies interactions.

scholarly journals Trends, abrupt shifts and interannual variability of the Arctic Wintertime Seasonal Sea Ice from 1979 to 2019

2020 ◽  
pp. 1-13
Author(s):  
Guanghua Hao ◽  
Jie Su ◽  
Timo Vihma ◽  
Fei Huang
Keyword(s):  
Time Series ◽  
Sea Ice ◽  
Large Scale ◽  
Open Water ◽  
The Arctic ◽  
Atlantic Sector ◽  
Near Surface ◽  
The Pacific ◽  
Pressure Anomaly ◽  
Abrupt Shifts

Abstract The Arctic winter seasonal sea ice (WSSI) concentration from 1979 to 2019 is derived from passive microwave data. Based on Empirical Orthogonal Function (EOF) analysis, the WSSI time series includes regionally different trends, abrupt shifts and interannual variations. The time series of the first EOF mode (PC1) mainly represents the WSSI trend, which is characterized by an increase, particularly in the Pacific sector. PC1 confirms two abrupt shifts in WSSI in 1989 and 2007, with a variance of 31%. After 2007, the large-scale atmospheric circulation anomaly shows a strengthened wavenumber 3 structure at high latitudes associated with a mid-tropospheric low-pressure anomaly in central and western Siberia and a high-pressure anomaly in eastern Siberia in summer and autumn. These patterns have promoted the increased transport of moist static energy to the central Arctic and contributed to increased near-surface air temperatures that may enhance ice melting in summer and reduce ice growth in autumn and winter. The changes in ice melt and growth have had opposite effects in the Pacific and Atlantic sectors: WSSI has increased in the Pacific sector due to the replacement of multi-year ice by WSSI, and decreased in the Atlantic sector due to the replacement of WSSI by open water.

Causality and Evolution of Summer Polynyas off the Coast of Northern Greenland

2020 ◽  
Author(s):  
Younjoo Lee ◽  
Wieslaw Maslowski ◽  
Robert Osinski ◽  
Jaclyn Clement Kinney ◽  
Anthony Craig ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Model ◽  
National Laboratory ◽  
Arctic Region ◽  
Open Water ◽  
Horizontal Resolution ◽  
The Arctic ◽  
Northern Coast ◽  
Infiltration Capacity ◽  
Land Hydrology

&lt;p&gt;The summer polynya along the northern coast of Greenland has been observed only six months later after the winter polynya in 2018, which has prompted concerns about the stability of some of the thickest sea-ice in the Arctic region. This study combines retrospective remotely sensed sea-ice measurements with results from the Regional Arctic System Model (RASM) to examine the causes, effect, and evolution of open-water areas/polynyas in the region.&lt;/p&gt;&lt;p&gt;RASM is a limited-domain, fully-coupled climate model, consisting of the atmosphere (Weather Research and Forecasting, WRF3.7), ocean (Los Alamos National Laboratory Parallel Ocean Program, POP2), sea-ice (Community Sea Ice Model, CICE5), land hydrology (Variable Infiltration Capacity, VIC4) and streamflow routing (RVIC) components. The ocean and sea-ice models are configured with the horizontal resolution of 1/12-degree with 45 vertical levels and 5 sea-ice thickness categories, respectively. The atmosphere and land hydrology components are set up on a 50-km grid with 40-vertical levels and 3-soil layers, respectively. The Climate Forecast System Reanalysis (CFSR) and version 2 (CFSv2) output are used as boundary conditions for dynamic downscaling.&lt;/p&gt;&lt;p&gt;Analysis of the sea-ice conditions off the coast of northern Greenland revealed that RASM, in agreement with satellite measurements, has simulated five summer polynya events, i.e. in August of 1984, 1985, 2002, 2004 and 2018, over the 39-year period (1980-2018). All these events were primarily dynamically forced, with the thermodynamic forcing playing the secondary, yet still important role. While the thermodynamically driven sea-ice melting exhibited a relatively little year-to-year variability, between 87 km&lt;sup&gt;3&lt;/sup&gt; and 115 km&lt;sup&gt;3&lt;/sup&gt;, its relative contribution to the total sea-ice loss increased by 2.5 times, from 16% in 1984 to 40% in 2018. This implies that with continuing thinning of sea-ice, increasingly less mechanical forcing may be required to generate and maintain a polynya or open water north of Greenland in summers to come. &amp;#160;&lt;/p&gt;

Investigations of past climate and sea-ice variability in the fjord area by Station Nord, eastern North Greenland

1969 ◽  
Vol 35 ◽  
pp. 67-70 ◽  
Author(s):  
Niels Nørgaard-Pedersen ◽  
Sofia Ribeiro ◽  
Naja Mikkelsen ◽  
Audrey Limoges ◽  
Marit-Solveig Seidenkrantz
Keyword(s):  
Sea Ice ◽  
Outer Part ◽  
Late Summer ◽  
Field Work ◽  
The Arctic ◽  
Research Station ◽  
Fjord System ◽  
Sea Bottom ◽  
Satellite Radar ◽  
North Greenland

The marine record of the Independence–Danmark fjord system extending out to the Wandel Hav in eastern North Greenland (Fig. 1A) is little known due to the almost perennial sea-ice cover, which makes the region inaccessible for research vessels (Nørgaard-Pedersen et al. 2008), and only a few depth measurements have been conducted in the area. In 2015, the Villum Research Station, a new logistic base for scientific investigations, was opened at Station Nord. In contrast to the early exploration of the region, it is now possible to observe and track the seasonal character and changes of ice in the fjord system and the Arctic Ocean through remote sensing by satellite radar systems. Satellite data going back to the early 1980s show that the outer part of the Independence–Danmark fjord system is characterised by perennial sea ice whereas both the southern part of the fjord system and an area 20–30 km west of Station Nord are partly ice free during late summer (Fig. 1B). Hence, marine-orientated field work can be conducted from the sea ice using snow mobiles, and by drilling through the ice to reach the underlying water and sea bottom.

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.

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.

Co-producing Sea-Ice Predictions with Stakeholders Using Simulation

2021 ◽  
Keyword(s):  
Sea Ice ◽  
Local Community ◽  
Economic Value ◽  
Arctic Region ◽  
Production Model ◽  
The Arctic ◽  
Simulation Game ◽  
Climate Services ◽  
Diverse Range ◽  
Uncertainty Information

Abstract Forecasts of sea-ice evolution in the Arctic region for several months ahead can be of considerable socio-economic value for a diverse range of marine sectors and for local community supply logistics. However, subseasonal-to-seasonal (S2S) forecasts represent a significant technical challenge, while translating user needs into scientifically manageable procedures and robust user confidence requires collaboration among a range of stakeholders. We developed and tested a novel, transdisciplinary co-production approach that combined socio-economic scenarios and participatory, research-driven simulation-gaming to test a new S2S sea-ice forecast system with experienced mariners in the cruise tourism sector. Our custom-developed computerized simulation-game ICEWISE integrated sea-ice parameters, forecast technology and human factors, as a participatory environment for stakeholder engagement. We explored the value of applications-relevant S2S sea-ice prediction and linked uncertainty information. Results suggest that the usefulness of S2S services is currently most evident in schedule-dependent sectors but expected to increase due to anticipated changes in the physical environment and continued growth in Arctic operations. Reliable communication of uncertainty information in sea-ice forecasts must be demonstrated and trialed before users gain confidence in emerging services and technologies. Mariners’ own intuition, experience, and familiarity with forecast service provider reputation impact the extent to which sea-ice information may reduce uncertainties and risks for Arctic mariners. Our insights into the performance of the combined foresight/simulation co-production model in brokering knowledge across a range of domains demonstrates promise. We conclude with an overview of the potential contributions from S2S sea-ice predictions and from experiential co-production models to the development of decision-driven and science-informed climate services.

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