2019-2020 mechanisms of fresh water release from the Beaufort Gyre region of the Arctic Ocean

2021 ◽  
Author(s):  
Andrey Proshutinsky ◽  
Richard Krishfield ◽  
Mary-Louise Timmermans ◽  
Isabela Le Bras ◽  
John Toole ◽  
...  
Keyword(s):  
Sea Ice ◽  
Sea Level ◽  
Fresh Water ◽  
Ocean Circulation ◽  
Atmospheric Pressure ◽  
Water Layer ◽  
The Arctic ◽  
Water Release ◽  
Sea Ice Concentration ◽  
Beaufort Gyre

<p>From September 2019 to September 2020, the sea-level atmospheric pressure over the Beaufort Gyre region (BGR) was reduced relative to climatology and a well pronounced cyclonic circulation forcing of sea ice and ocean lasted more than eight months. This resulted in the following: increased sea ice area in 2020 relative to 2019; periodic reversals of sea ice drift from anticyclonic to cyclonic; the formation of an unusual donut-shaped sea ice cover pattern (in August-September 2020); upwelling in the central BGR with a reduction of freshwater content by ~1000 km<sup>3</sup>; downwelling along the periphery of the BGR; changes in the intensity and trajectories of freshwater fluxes from the Mackenzie river and Bering Strait and fresh water contributions to the BGR freshwater content; unusual warming of the Pacific water layer in the northern BGR; and biogeochemical changes driven by ocean circulation and water mass redistribution. Numerical modeling is used to better understand the causes and consequences of the observed changes. Sea-level atmospheric pressure from NCAR/NCEP reanalysis, sea ice concentration and ice motion from NSIDC, altimetry based sea surface heights from Technical University of Denmark, and hydrographic data from the Beaufort Gyre project and USCGC Healy expeditions are used in the study.</p>

Causes and consequences of Southern Ocean change: the IPCC SROCC assessment

2020 ◽  
Author(s):  
Michael Meredith ◽  
Martin Sommerkorn ◽  
Sandra Cassotta ◽  
Chris Derksen ◽  
Alexey Ekaykin ◽  
...  
Keyword(s):  
Southern Ocean ◽  
Sea Ice ◽  
Sea Level ◽  
Ocean Circulation ◽  
Global Climate ◽  
Ice Sheets ◽  
The Arctic ◽  
Polar Regions ◽  
Ice Shelves

<p>Climate change in the polar regions exerts a profound influence both locally and over all of our planet.  Physical and ecosystem changes influence societies and economies, via factors that include food provision, transport and access to non-renewable resources.  Sea level, global climate and potentially mid-latitude weather are influenced by the changing polar regions, through coupled feedback processes, sea ice changes and the melting of snow and land-based ice sheets and glaciers.</p><p>Reflecting this importance, the IPCC Special Report on the Ocean and Cryosphere in a Changing Climate (SROCC) features a chapter highlighting past, ongoing and future change in the polar regions, the impacts of these changes, and the possible options for response.  The role of the polar oceans, both in determining the changes and impacts in the polar regions and in structuring the global influence, is an important component of this chapter.</p><p>With emphasis on the Southern Ocean and through comparison with the Arctic, this talk will outline key findings from the polar regions chapter of SROCC. It will synthesise the latest information on the rates, patterns and causes of changes in sea ice, ocean circulation and properties. It will assess cryospheric driving of ocean change from ice sheets, ice shelves and glaciers, and the role of the oceans in determining the past and future evolutions of polar land-based ice. The implications of these changes for climate, ecosystems, sea level and the global system will be outlined.</p>

scholarly journals On large-scale shifts in the Arctic Ocean and sea-ice conditions during 1979−98

2001 ◽  
Vol 33 ◽  
pp. 545-550 ◽  
Author(s):  
W. Maslowski ◽  
D. C. Marble ◽  
W. Walczowski ◽  
A. J. Semtner
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Fresh Water ◽  
Ocean Circulation ◽  
Large Scale ◽  
Atlantic Water ◽  
The Arctic ◽  
Upper Ocean ◽  
Recent Climate ◽  
The Arctic Ocean

AbstractResults from a regional model of the Arctic Ocean and sea ice forced with realistic atmospheric data are analyzed to understand recent climate variability in the region. The primary simulation uses daily-averaged 1979 atmospheric fields repeated for 20 years and then continues with interannual forcing derived from the European Centre for Medium-range Weather Forecasts for 1979−98. An eastward shift in the ice-ocean circulation, fresh-water distribution and Atlantic Water extent has been determined by comparing conditions between the early 1980s and 1990s. A new trend is modeled in the late 1990s, and has a tendency to return the large-scale sea-ice and upper ocean conditions to their state in the early 1980s. Both the sea-ice and the upper ocean circulation as well as fresh-water export from the Russian shelves and Atlantic Water recirculation within the Eurasian Basin indicate that the Arctic climate is undergoing another shift. This suggests an oscillatory behavior of the Arctic Ocean system. Interannual atmospheric variability appears to be the main and sufficient driver of simulated changes. The ice cover acts as an effective dynamic medium for vorticity transfer from the atmosphere into the ocean.

Sea ice changes in the Chukchi Sea over the Industrial Era based on biomarkers

2021 ◽  
Author(s):  
Youcheng Bai ◽  
Marie-Alexandrine Sicre ◽  
Jian Ren ◽  
Bassem Jalali ◽  
Hongliang Li ◽  
...  
Keyword(s):  
Sea Ice ◽  
Ocean Circulation ◽  
Chukchi Sea ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
Sea Ice Extent ◽  
Decadal Scale ◽  
Ice Concentration ◽  
Spring Sea Ice ◽  
Shelf Region

<p>High-resolution palaeo-climate records documenting sea ice extent over the Industrial Era is an important source of information to fully understand the emergence and magnitude of on-going changes and better predict future climate evolution of the Arctic Ocean. In this study, source-specific highly branched isoprenoids (HBIs) and phytosterols were measured in multicores retrieved from the Chukchi shelf region to document the history of seasonal sea ice in this area since the beginning of the Industrial Era. HBIs at the end of the 19th century (AD 1865-1875) point to a retreat of the sea ice edge and rapid return to colder conditions. After 1920-1930 AD, proxy records indicate a steady sea ice retreat reaching a maximum in the 1990s. Sympagic biomarker IP<sub>25</sub> and HBI II were generally low during negative Arctic Oscillation (AO) (i.e., before 1920s) while higher values were found during positive AO, in particular in the 1990s. Our data also suggest a role of remote ocean circulation features.</p><p>Among existing indices for semi-quantitative of sea ice concentration, the H-Print % sea ice index seems to generally perform less than so-called phytoplankton marker-IP<sub>25</sub> (PIP<sub>25</sub>) index to estimate spring sea ice concentration (SpSIC). However, P<sub>B</sub>IP<sub>25</sub>-derived SpSIC better reproduce decadal scale variability and the long-term sea ice decline since the mid-20th century. Our results also highlight the lack of data for improving the PIP<sub>25</sub> and their relationship to sea ice.</p>

scholarly journals Sea Ice Concentration Products over Polar Regions with Chinese FY3C/MWRI Data

2021 ◽  
Vol 13 (11) ◽  
pp. 2174
Author(s):  
Lijian Shi ◽  
Sen Liu ◽  
Yingni Shi ◽  
Xue Ao ◽  
Bin Zou ◽  
...  
Keyword(s):  
Time Series ◽  
Sea Ice ◽  
Ocean Circulation ◽  
The Arctic ◽  
Retrieval Algorithm ◽  
Atmospheric Effects ◽  
Observation Data ◽  
Long Time Series ◽  
Ice Concentration ◽  
Long Time

Polar sea ice affects atmospheric and ocean circulation and plays an important role in global climate change. Long time series sea ice concentrations (SIC) are an important parameter for climate research. This study presents an SIC retrieval algorithm based on brightness temperature (Tb) data from the FY3C Microwave Radiation Imager (MWRI) over the polar region. With the Tb data of Special Sensor Microwave Imager/Sounder (SSMIS) as a reference, monthly calibration models were established based on time–space matching and linear regression. After calibration, the correlation between the Tb of F17/SSMIS and FY3C/MWRI at different channels was improved. Then, SIC products over the Arctic and Antarctic in 2016–2019 were retrieved with the NASA team (NT) method. Atmospheric effects were reduced using two weather filters and a sea ice mask. A minimum ice concentration array used in the procedure reduced the land-to-ocean spillover effect. Compared with the SIC product of National Snow and Ice Data Center (NSIDC), the average relative difference of sea ice extent of the Arctic and Antarctic was found to be acceptable, with values of −0.27 ± 1.85 and 0.53 ± 1.50, respectively. To decrease the SIC error with fixed tie points (FTPs), the SIC was retrieved by the NT method with dynamic tie points (DTPs) based on the original Tb of FY3C/MWRI. The different SIC products were evaluated with ship observation data, synthetic aperture radar (SAR) sea ice cover products, and the Round Robin Data Package (RRDP). In comparison with the ship observation data, the SIC bias of FY3C with DTP is 4% and is much better than that of FY3C with FTP (9%). Evaluation results with SAR SIC data and closed ice data from RRDP show a similar trend between FY3C SIC with FTPs and FY3C SIC with DTPs. Using DTPs to present the Tb seasonal change of different types of sea ice improved the SIC accuracy, especially for the sea ice melting season. This study lays a foundation for the release of long time series operational SIC products with Chinese FY3 series satellites.

scholarly journals Sea Ice Concentration and Sea Ice Extent Mapping with L-Band Microwave Radiometry and GNSS-R Data from the FFSCat Mission Using Neural Networks

2021 ◽  
Vol 13 (6) ◽  
pp. 1139
Author(s):  
David Llaveria ◽  
Juan Francesc Munoz-Martin ◽  
Christoph Herbert ◽  
Miriam Pablos ◽  
Hyuk Park ◽  
...  
Keyword(s):  
Sea Ice ◽  
Microwave Radiometer ◽  
Cost Effective ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
Sea Ice Extent ◽  
Neural Network Approach ◽  
Ice Concentration ◽  
L Band ◽  
Moderate Cost

CubeSat-based Earth Observation missions have emerged in recent times, achieving scientifically valuable data at a moderate cost. FSSCat is a two 6U CubeSats mission, winner of the ESA S3 challenge and overall winner of the 2017 Copernicus Masters Competition, that was launched in September 2020. The first satellite, 3Cat-5/A, carries the FMPL-2 instrument, an L-band microwave radiometer and a GNSS-Reflectometer. This work presents a neural network approach for retrieving sea ice concentration and sea ice extent maps on the Arctic and the Antarctic oceans using FMPL-2 data. The results from the first months of operations are presented and analyzed, and the quality of the retrieved maps is assessed by comparing them with other existing sea ice concentration maps. As compared to OSI SAF products, the overall accuracy for the sea ice extent maps is greater than 97% using MWR data, and up to 99% when using combined GNSS-R and MWR data. In the case of Sea ice concentration, the absolute errors are lower than 5%, with MWR and lower than 3% combining it with the GNSS-R. The total extent area computed using this methodology is close, with 2.5% difference, to those computed by other well consolidated algorithms, such as OSI SAF or NSIDC. The approach presented for estimating sea ice extent and concentration maps is a cost-effective alternative, and using a constellation of CubeSats, it can be further improved.

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 On the Link between Arctic Sea Ice Decline and the Freshwater Content of the Beaufort Gyre: Insights from a Simple Process Model

2014 ◽  
Vol 27 (21) ◽  
pp. 8170-8184 ◽  
Author(s):  
Peter E. D. Davis ◽  
Camille Lique ◽  
Helen L. Johnson
Keyword(s):  
Sea Ice ◽  
Momentum Transfer ◽  
Momentum Flux ◽  
Process Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Simple Process ◽  
Beaufort Gyre ◽  
Arctic Sea ◽  
The Arctic Ocean

Abstract Recent satellite and hydrographic observations have shown that the rate of freshwater accumulation in the Beaufort Gyre of the Arctic Ocean has accelerated over the past decade. This acceleration has coincided with the dramatic decline observed in Arctic sea ice cover, which is expected to modify the efficiency of momentum transfer into the upper ocean. Here, a simple process model is used to investigate the dynamical response of the Beaufort Gyre to the changing efficiency of momentum transfer, and its link with the enhanced accumulation of freshwater. A linear relationship is found between the annual mean momentum flux and the amount of freshwater accumulated in the Beaufort Gyre. In the model, both the response time scale and the total quantity of freshwater accumulated are determined by a balance between Ekman pumping and an eddy-induced volume flux toward the boundary, highlighting the importance of eddies in the adjustment of the Arctic Ocean to a change in forcing. When the seasonal cycle in the efficiency of momentum transfer is modified (but the annual mean momentum flux is held constant), it has no effect on the accumulation of freshwater, although it does impact the timing and amplitude of the annual cycle in Beaufort Gyre freshwater content. This suggests that the decline in Arctic sea ice cover may have an impact on the magnitude and seasonality of the freshwater export into the North Atlantic.

Sea ice protists in arctic marine sedaDNA records: origins, diversity, and vertical export of DNA from the sea surface to the seafloor 

2021 ◽  
Author(s):  
Sara Harðardóttir ◽  
Connie Lovejoy ◽  
Marit-Solveig Seidenkrantz ◽  
Sofia Ribeiro
Keyword(s):  
Sea Ice ◽  
Ocean Circulation ◽  
Ancient Dna ◽  
Genetic Material ◽  
Amplicon Sequencing ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Gene Copy ◽  
Marine Biodiversity ◽  
Vertical Export

<p>Arctic sea ice is declining at an unprecedented pace as the Arctic Ocean heads towards ice-free summers within the next few decades. Because of the role of sea ice in the Earth System such as ocean circulation and ecosystem functioning, reconstructing its past variability is of great importance providing insight into past climate patterns and future climate scenarios. Today, much of our knowledge of past sea-ice variability derives from a relatively few microfossil and biogeochemical tracers, which have limitations, such as preservation biases and low taxonomic resolution. Marine sedimentary ancient DNA (marine <em>seda</em>DNA) has the potential to capture more of the arctic marine biodiversity compared to other approaches. However, little is known about how well past communities are represented in marine <em>seda</em>DNA. The transport and fate of DNA derived from sea-ice associated organisms, from surface waters to the seafloor and its eventual incorporation into marine sediment records is poorly understood.  Here, we present results from a study applying a combination of methods to examine modern and ancient DNA to material collected along the Northeast Greenland Shelf. We characterized the vertical export of genetic material by amplicon sequencing the hyper-variable V4 region of the 18S rDNA at three water depths, in surface sediments, and in a dated sediment core.  The amplicon sequencing approach, as currently applied, includes some limitations for quantitative reconstructions of past changes such as primer competition, PCR errors, and variation of gene copy numbers across different taxa. For these reasons we quantified amplicons from a single species, the circum-polar sea ice dinoflagellate <em>Polarella glacialis</em> in the marine <em>seda</em>DNA, using digital droplet PCR. The results will increase our understanding on the taphonomy of DNA in sea ice environments, how sedimentation differs among taxonomic groups, and provide indications to potentially useful marine <em>seda</em>DNA-based proxies for climate and environmental reconstructions.</p>

scholarly journals Recent Sea Ice Decline Did Not Significantly Increase the Total Liquid Freshwater Content of the Arctic Ocean

2018 ◽  
Vol 32 (1) ◽  
pp. 15-32 ◽  
Author(s):  
Qiang Wang ◽  
Claudia Wekerle ◽  
Sergey Danilov ◽  
Dmitry Sidorenko ◽  
Nikolay Koldunov ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Sea Ice ◽  
Arctic Ocean ◽  
Ocean Circulation ◽  
General Circulation ◽  
The Arctic ◽  
Sea Ice Decline ◽  
The Arctic Ocean ◽  
Eurasian Basin ◽  
The Impact

Abstract The freshwater stored in the Arctic Ocean is an important component of the global climate system. Currently the Arctic liquid freshwater content (FWC) has reached a record high since the beginning of the last century. In this study we use numerical simulations to investigate the impact of sea ice decline on the Arctic liquid FWC and its spatial distribution. The global unstructured-mesh ocean general circulation model Finite Element Sea Ice–Ocean Model (FESOM) with 4.5-km horizontal resolution in the Arctic region is applied. The simulations show that sea ice decline increases the FWC by freshening the ocean through sea ice meltwater and modifies upper ocean circulation at the same time. The two effects together significantly increase the freshwater stored in the Amerasian basin and reduce its amount in the Eurasian basin. The salinification of the upper Eurasian basin is mainly caused by the reduction in the proportion of Pacific Water and the increase in that of Atlantic Water (AW). Consequently, the sea ice decline did not significantly contribute to the observed rapid increase in the Arctic total liquid FWC. However, the changes in the Arctic freshwater spatial distribution indicate that the influence of sea ice decline on the ocean environment is remarkable. Sea ice decline increases the amount of Barents Sea branch AW in the upper Arctic Ocean, thus reducing its supply to the deeper Arctic layers. This study suggests that all the dynamical processes sensitive to sea ice decline should be taken into account when understanding and predicting Arctic changes.

scholarly journals Stationary Wave Interference and Its Relation to Tropical Convection and Arctic Warming

2016 ◽  
Vol 29 (4) ◽  
pp. 1369-1389 ◽  
Author(s):  
Michael Goss ◽  
Steven B. Feldstein ◽  
Sukyoung Lee
Keyword(s):  
Sea Ice ◽  
Stationary Wave ◽  
Warm Pool ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Boreal Winter ◽  
Destructive Interference ◽  
Constructive Interference ◽  
Sea Ice Concentration ◽  
Stratospheric Polar Vortex

Abstract The interference between transient eddies and climatological stationary eddies in the Northern Hemisphere is investigated. The amplitude and sign of the interference is represented by the stationary wave index (SWI), which is calculated by projecting the daily 300-hPa streamfunction anomaly field onto the 300-hPa climatological stationary wave. ERA-Interim data for the years 1979 to 2013 are used. The amplitude of the interference peaks during boreal winter. The evolution of outgoing longwave radiation, Arctic temperature, 300-hPa streamfunction, 10-hPa zonal wind, Arctic sea ice concentration, and the Arctic Oscillation (AO) index are examined for days of large SWI values during the winter. Constructive interference during winter tends to occur about one week after enhanced warm pool convection and is followed by an increase in Arctic surface air temperature along with a reduction of sea ice in the Barents and Kara Seas. The warming of the Arctic does occur without prior warm pool convection, but it is enhanced and prolonged when constructive interference occurs in concert with enhanced warm pool convection. This is followed two weeks later by a weakening of the stratospheric polar vortex and a decline of the AO. All of these associations are reversed in the case of destructive interference. Potential climate change implications are briefly discussed.

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