Measurements of high-frequency acoustic scattering from sea ice over one season in the Chukchi Sea

AbstractA C-band sea-ice radar (SIR) network system was operated to monitor the sea-ice conditions off the Okhotsk Sea coast of northern Hokkaido, Japan, from 1969 to 2004. The system was based on three radar stations, which were capable of continuously monitoring the sea surface as far as 60 km offshore along a 250 km long coastal section. In 2004 the SIR system was closed down and a sea surface monitoring programme was commenced using high-frequency (HF) radar; this system provides information on surface currents in open-water conditions, while areas with ‘no signal’ can be identified as sea ice. The present study compares HF radar data with SIR data to evaluate their feasibility for sea-ice remote sensing. The period of overlapping data was 1.5 months. The results show that HF radar information can be utilized for ice-edge mapping although it cannot fully compensate for the loss of the SIR system. In particular, HF radar does not provide ice concentration, ice roughness and geometrical structures or ice kinematics. The probability of ice-edge detection by HF radar was 0.9 and the correlation of the ice-edge distance between the radars was 0.7.

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Distribution of Arctic and Pacific copepods and their habitat in the northern Bering Sea and Chukchi Sea

Biogeosciences Discussions ◽

10.5194/bgd-12-18661-2015 ◽

2015 ◽

Vol 12 (22) ◽

pp. 18661-18691 ◽

Cited By ~ 1

Author(s):

H. Sasaki ◽

K. Matsuno ◽

A. Fujiwara ◽

M. Onuka ◽

A. Yamaguchi ◽

...

Keyword(s):

Sea Ice ◽

Water Mass ◽

High Salinity ◽

Chukchi Sea ◽

Bottom Layer ◽

Sea Ice Extent ◽

High Salinity Water ◽

Explanatory Variables ◽

Northern Bering Sea ◽

Salinity Water

Abstract. The advection of warm Pacific water and the reduction of sea-ice extent in the western Arctic Ocean may influence the abundance and distribution of copepods, i.e., a key component in food webs. To understand the factors affecting abundance of copepods in the northern Bering Sea and Chukchi Sea, we constructed habitat models explaining the spatial patterns of the large and small Arctic copepods and the Pacific copepods, separately, using generalized additive models. Copepods were sampled by NORPAC net. Vertical profiles of density, temperature and salinity in the seawater were measured using CTD, and concentration of chlorophyll a in seawater was measured with a fluorometer. The timing of sea-ice retreat was determined using the satellite image. To quantify the structure of water masses, the magnitude of pycnocline and averaged density, temperature and salinity in upper and bottom layers were scored along three axes using principal component analysis (PCA). The structures of water masses indexed by the scores of PCAs were selected as explanatory variables in the best models. Large Arctic copepods were abundant in the water mass with high salinity water in bottom layer or with cold/low salinity water in upper layer and cold/high salinity water in bottom layer, and small Arctic copepods were abundant in the water mass with warm/saline water in upper layer and cold/high salinity water in bottom layers, while Pacific copepods were abundant in the water mass with warm/saline in upper layer and cold/high salinity water in bottom layer. All copepod groups were abundant in areas with deeper depth. Although chlorophyll a in upper and bottom layers were selected as explanatory variables in the best models, apparent trends were not observed. All copepod groups were abundant where the sea-ice retreated at earlier timing. Our study might indicate potential positive effects of the reduction of sea-ice extent on the distribution of all groups of copepods in the Arctic Ocean.

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Seasonal sea ice prediction based on regional indices

10.5194/tc-2018-151 ◽

2018 ◽

Author(s):

John E. Walsh ◽

J. Scott Stewart ◽

Florence Fetterer

Keyword(s):

Sea Ice ◽

Chukchi Sea ◽

Numerical Models ◽

Linear Trend ◽

Piecewise Linear ◽

Severity Index ◽

The Arctic ◽

Linear Quadratic ◽

Predictive Skill ◽

Arctic Ice

Abstract. Basic statistical metrics such as autocorrelations and across-region lag correlations of sea ice variations provide benchmarks for the assessments of forecast skill achieved by other methods such as more sophisticated statistical formulations, numerical models, and heuristic approaches. However, the strong negative trend of sea ice coverage in recent decades complicates the evaluation of statistical skill by inflating the correlation of interannual variations of pan-Arctic and regional ice extent. In this study we provide a quantitative evaluation of the contribution of the trend to the predictive skill of monthly and seasonal ice extent on the pan-Arctic and regional scales. We focus on the Beaufort Sea where the Barnett Severity Index provides a metric of historical variations in ice conditions over the summer shipping season. The variance about the trend line differs little among various methods of detrending (piecewise linear, quadratic, cubic, exponential). Application of the piecewise linear trend calculation indicates an acceleration of the trend during the 1990s in most of the Arctic subregions. The Barnett Severity Index as well as September pan-Arctic ice extent show significant statistical predictability out to several seasons when the data include the trend. However, this apparent skill largely vanishes when the data are detrended. No region shows significant correlation with the detrended September pan-Arctic ice extent at lead times greater than a month or two; the concurrent correlations are strongest with the East Siberian Sea. The Beaufort Sea’s ice extent as far back as July explains about 20 % of the variance of the Barnett Severity Index, which is primarily a September metric. The Chukchi Sea is the only other region showing a significant association with the Barnett Severity Index, although only at a lead time of a month or two.

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Discovery of the wreck of the Soviet steamer Chelyuskin on the bed of the Chukchi Sea

Polar Record ◽

10.1017/s0032247406216061 ◽

2007 ◽

Vol 43 (1) ◽

pp. 67-70 ◽

Cited By ~ 1

Author(s):

William Barr

Keyword(s):

Sea Ice ◽

Chukchi Sea ◽

Soviet Government ◽

Northern Sea Route ◽

The Pacific

In 1933, the steamer Chelyuskin sailed from Murmansk, east bound to attempt a transit of the Northern Sea Route to the Pacific, in order to demonstrate that such a transit could be achieved in one season. The vessel became beset in heavy ice in the Chukchi Sea, and after drifting with the ice for over two months, was crushed and sank on 13 February 1934. Apart from one fatality, her entire complement of 104 people was able to establish a camp on the sea ice. The Soviet government organised an impressive aerial evacuation, under which all were rescued. Following several unsuccessful attempts, the wreck was located on the bed of the Chukchi Sea by a Russian expedition, Chelyuskin-70, in mid-September 2006. Two small components of the ship's superstructure were recovered by divers and were sent to the ship's builders, Burmeister and Wein of Copenhagen, for identification.

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Arctic Intense Summer Storms and Their Impacts on Sea Ice—A Regional Climate Modeling Study

Atmosphere ◽

10.3390/atmos10040218 ◽

2019 ◽

Vol 10 (4) ◽

pp. 218 ◽

Cited By ~ 4

Author(s):

Alexander Semenov ◽

Xiangdong Zhang ◽

Annette Rinke ◽

Wolfgang Dorn ◽

Klaus Dethloff

Keyword(s):

Sea Ice ◽

Climate Model ◽

Chukchi Sea ◽

Regional Climate ◽

Turbulent Fluxes ◽

Heat Fluxes ◽

Shortwave Radiation ◽

Energy Budgets ◽

Sea Ice Concentration ◽

Storm Activity

Various temporal and spatial changes have manifested in Arctic storm activities, including the occurrence of the anomalously intense storms in the summers of 2012 and 2016, along with the amplified warming and rapidly decreased sea ice. To detect the variability of and changes in storm activity and understand its role in sea ice changes, we examined summer storm count and intensity year-by-year from ensemble hindcast simulations with an Arctic regional coupled climate model for the period of 1948–2008. The results indicated that the model realistically simulated the climatological spatial structure of the storm activity, characterized by the storm count and intensity. The simulated storm count captures the variability derived from the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP–NCAR) reanalysis, though the simulated one is higher than that in the reanalysis. This could be attributed to the higher resolution of the model that may better represent smaller and shallower cyclones. The composite analysis shows that intense storms tend to form a low-pressure pattern with centers over the Kara Sea and Chukchi Sea, respectively, generating cyclonic circulation over the North Atlantic and North Pacific Arctic Ocean. The former drives intensification of the transpolar drift and Fram Strait sea ice export, and the latter suppresses thick ice transport from the Canada Basin to the Beaufort–Chukchi Seas, in spite of an increase in sea ice transport to the East Siberian Sea. Associated with these changes in sea ice transport, sea ice concentration and thickness show large decreases in the Barents–Kara Seas and the Chukchi–East-Siberian Seas, respectively. Energy budgets analysis suggests that more numerous intense storms substantially decrease the downward net sea ice heat fluxes, including net radiative fluxes, turbulent fluxes, and oceanic heat fluxes, compared with that when a lower number of intense storms occur. The decrease in the heat fluxes could be attributable to an increased cloudiness and the resultant reduction of downward shortwave radiation, as well as a destabilized boundary layer induced increase in upward turbulent fluxes.

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