Sea ice controls on Arctic water vapor content and transport: Discoveries from MOSAiC’s pan Arctic Water Isotope Network (AWIN)

2021 ◽  
Author(s):  
Ben Kopec ◽  
Martin Werner ◽  
Kyle Mattingly ◽  
Eric Klein ◽  
David Noone ◽  
...  
Keyword(s):  
Water Vapor ◽  
Sea Ice ◽  
Storm Track ◽  
Arctic Sea Ice ◽  
Storm Tracks ◽  
The Arctic ◽  
Arctic Seas ◽  
Arctic Water ◽  
Ocean Atmosphere ◽  
Water Isotope

<p>One of the key changes of the global climate system is the loss of Arctic sea ice, particularly through its impact on ocean-atmosphere interactions. Enhanced evaporation under open-water conditions is widespread from places and periods previously precluded by perennial sea ice cover, leading to an increase in vapor uptake across the Arctic. However, the response of ocean-atmosphere system to sea ice loss varies significantly over time and space. To quantify these variations, the Arctic Water Isotope Network (AWIN) has been established to make continuous water vapor isotope measurements (δD, δ<sup>18</sup>O, and d-excess) at seven land-based stations from Barrow, Alaska to Ny Alesund, Svalbard. This network has been supplemented by continuous mobile isotope data from the CiASOM project on the Polarstern ice-breaker throughout the MOSAiC “Arctic-drift” expedition. With this network, we comprehensively track water vapor from its source to sink, thereby demonstrating how it varies simultaneously across the entire Arctic Basin.</p><p>Here, we utilize AWIN measurements to specifically quantify how variations in sea ice extent and distribution affect moisture content, water vapor isotope traits, and transport along several critical storm tracks. By monitoring vapor isotopic changes in air masses advected from one site to another, we are able to track how much moisture is added along a given trajectory. We investigate several primary vapor transport pathways into the Arctic, including the North Atlantic/Greenland Sea, Baffin Bay, and the Bering Strait, and track the geochemical signature of this vapor as it transits along these well-established storm pathways into and within the Arctic. By quantifying isotopic changes between our sites we: 1) identify the distinct isotopic fingerprint of moisture sourced by evaporation from Arctic seas that is critically dependent on variable sea ice conditions, 2) detect moisture addition into critical storm tracks as they transit across the Arctic, and 3) determine the spatial variability of this enhanced Arctic-sourced evaporation and moisture. We find that for every major storm track observed, the Arctic Ocean and surrounding seas are significant sources of enhanced moisture uptake, acting within an amplified water cycle.</p>

MOSAiC’s Pan Arctic Water Isotope Network: Sea ice-water vapor isotope interactions and transport processes within, into and out of the Arctic

2020 ◽  
Author(s):  
Ben Kopec ◽  
Eric Klein ◽  
David Noone ◽  
Hannah Bailey ◽  
Kaisa-Riikka Mustonen ◽  
...  
Keyword(s):  
Water Vapor ◽  
Sea Ice ◽  
Arctic Basin ◽  
Hydrologic Cycle ◽  
The Arctic ◽  
Deuterium Excess ◽  
Arctic Water ◽  
Baffin Bay ◽  
Isotope Measurements ◽  
Water Isotope

<p>MOSAiC is a one of a kind, year-long study of the Arctic Basin’s behavior focused in large part on interactions between sea ice, atmospheric processes, ecosystem dynamics and oceanography, as well as connections between the Arctic and the mid-latitudes. Our MOSAiC project is focused on how the Arctic Basin’s water cycle behaves throughout the year, especially now that sea ice loss allows for a new source of moisture to the atmosphere during times when this basin was formerly frozen over. These massive changes in open water and corresponding fluxes in conjunction with significant shifts in atmospheric circulation, are altering how moisture is transported into, within, and out of the Arctic Basin. In order to help quantify these Arctic hydrologic cycle variations, we have established the AWIN (Arctic Water Isotope Network) that uses continuous water vapor isotope measurements (δD, δ<sup>18</sup>O, and deuterium excess) at eight land-based stations from Barrow in Alaska to Ny Alesund in Svalbard, as well as on board the Polarstern.</p><p>With a network of sites rather than a single station, we gain the significant advantage of being able to track water vapor and how it varies from site to site, allowing us to identify the sources of moisture, and how and where that moisture is transported into, within, and out of the Arctic. For this analysis, we focus on the first months of the expedition (October-December 2019) to closely examine cases of critical events including a major low-pressure system in mid-November that impacted much of the Arctic Ocean basin and three key repeating transport regimes – 1) transport into the Arctic from the North Atlantic via the Greenland Sea, 2) transport into the Arctic via Baffin Bay, and 3) transport out of the Arctic via the Greenland Sea, as well as transport within the Arctic during each of these regimes. For example, in the scenario of transport into the Arctic via Baffin Bay, at our site in Thule, Greenland, we see significant reductions in deuterium excess each time the southerly flow initiates, suggesting significant moisture evaporating from nearby in Baffin Bay. We then can track that moisture to another site to observe how much of that locally-sourced vapor is transported to a given downwind location, allowing us to quantify vapor fluxes and isotopic fractionation processes across the Arctic. By examining these scenarios under varying sea ice conditions and large-scale atmospheric circulation patterns, this circum-Arctic network of water isotope measurements is transforming our understanding of the Arctic hydrologic cycle during MOSAiC.</p>

scholarly journals Hydroclimatic Controls on the Isotopic (δ18 O, δ2 H, d-excess) Traits of Pan-Arctic Summer Rainfall Events

2021 ◽  
Vol 9 ◽  
Author(s):  
Moein Mellat ◽  
Hannah Bailey ◽  
Kaisa-Riikka Mustonen ◽  
Hannu Marttila ◽  
Eric S. Klein ◽  
...  
Keyword(s):  
Sea Ice ◽  
Water Cycle ◽  
Global Climate ◽  
Meteorological Data ◽  
Summer Rainfall ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Arctic Water ◽  
Ongoing Research ◽  
Air Masses

Arctic sea-ice loss is emblematic of an amplified Arctic water cycle and has critical feedback implications for global climate. Stable isotopes (δ18O, δ2H, d-excess) are valuable tracers for constraining water cycle and climate processes through space and time. Yet, the paucity of well-resolved Arctic isotope data preclude an empirically derived understanding of the hydrologic changes occurring today, in the deep (geologic) past, and in the future. To address this knowledge gap, the Pan-Arctic Precipitation Isotope Network (PAPIN) was established in 2018 to coordinate precipitation sampling at 19 stations across key tundra, subarctic, maritime, and continental climate zones. Here, we present a first assessment of rainfall samples collected in summer 2018 (n = 281) and combine new isotope and meteorological data with sea ice observations, reanalysis data, and model simulations. Data collectively establish a summer Arctic Meteoric Water Line where δ2H = 7.6⋅δ18O–1.8 (r2 = 0.96, p < 0.01). Mean amount-weighted δ18O, δ2H, and d-excess values were −12.3, −93.5, and 4.9‰, respectively, with the lowest summer mean δ18O value observed in northwest Greenland (−19.9‰) and the highest in Iceland (−7.3‰). Southern Alaska recorded the lowest mean d-excess (−8.2%) and northern Russia the highest (9.9‰). We identify a range of δ18O-temperature coefficients from 0.31‰/°C (Alaska) to 0.93‰/°C (Russia). The steepest regression slopes (>0.75‰/°C) were observed at continental sites, while statistically significant temperature relations were generally absent at coastal stations. Model outputs indicate that 68% of the summer precipitating air masses were transported into the Arctic from mid-latitudes and were characterized by relatively high δ18O values. Yet 32% of precipitation events, characterized by lower δ18O and high d-excess values, derived from northerly air masses transported from the Arctic Ocean and/or its marginal seas, highlighting key emergent oceanic moisture sources as sea ice cover declines. Resolving these processes across broader spatial-temporal scales is an ongoing research priority, and will be key to quantifying the past, present, and future feedbacks of an amplified Arctic water cycle on the global climate system.

Convolutional Neural Networks for Sea Ice Concentration Charting for Maritime Navigation in the Arctic

2021 ◽  
Author(s):  
Andreas Stokholm ◽  
Leif Pedersen ◽  
René Forsberg ◽  
Sine Hvidegaard
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Arctic Seas ◽  
Sea Ice Concentration ◽  
Data Set ◽  
Architecture Model ◽  
Radar Images ◽  
North East ◽  
Ice Concentration

<p>In recent years the Arctic has seen renewed political and economic interest, increased maritime traffic and desire for improved sea ice navigational tools. Despite a rise in digital technology, maps of sea ice concentration used for Arctic maritime operations are still today created by humans manually interpreting radar images. This process is slow with low map release frequency, uncertainties up to 20 % and discrepancies up to 60 %. Utilizing emerging AI Convolutional Neural Network (CNN) semantic image segmentation techniques to automate this process is drastically changing navigation in the Arctic seas, with better resolution, accuracy, release frequency and coverage. Automatic Arctic sea ice products may contribute to enabling the disruptive Northern Sea Route connecting North East Asia to Europe via the Arctic oceans.</p><p>The AI4Arctic/ASIP V2 data set, that combines 466 Sentinel-1 HH and HV SAR images from Greenland, Passive Microwave Radiometry from the AMSR2 instrument, and an equivalent sea ice concentration chart produced by ice analysts at the Danish Meteorological Institute, have been used to train a CNN U-Net Architecture model. The model shows robust capabilities in producing highly detailed sea ice concentration maps with open water, intermediate sea ice concentrations as well as full sea ice cover, which resemble those created by professional sea ice analysts. Often cited obstacles in automatic sea ice concentration models are wind-roughened sea ambiguities resembling sea ice. Final inference scenes show robustness towards such ambiguities.</p>

scholarly journals Impact of a Reduced Arctic Sea Ice Cover on Ocean and Atmospheric Properties

2012 ◽  
Vol 25 (1) ◽  
pp. 307-319 ◽  
Author(s):  
Jan Sedláček ◽  
Reto Knutti ◽  
Olivia Martius ◽  
Urs Beyerle
Keyword(s):  
Sea Ice ◽  
North Atlantic ◽  
Arctic Basin ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
Storm Tracks ◽  
The Arctic ◽  
The North ◽  
Arctic Sea ◽  
The North Atlantic

Abstract The Arctic sea ice cover declined over the last few decades and reached a record minimum in 2007, with a slight recovery thereafter. Inspired by this the authors investigate the response of atmospheric and oceanic properties to a 1-yr period of reduced sea ice cover. Two ensembles of equilibrium and transient simulations are produced with the Community Climate System Model. A sea ice change is induced through an albedo change of 1 yr. The sea ice area and thickness recover in both ensembles after 3 and 5 yr, respectively. The sea ice anomaly leads to changes in ocean temperature and salinity to a depth of about 200 m in the Arctic Basin. Further, the salinity and temperature changes in the surface layer trigger a “Great Salinity Anomaly” in the North Atlantic that takes roughly 8 yr to travel across the North Atlantic back to high latitudes. In the atmosphere the changes induced by the sea ice anomaly do not last as long as in the ocean. The response in the transient and equilibrium simulations, while similar overall, differs in specific regional and temporal details. The surface air temperature increases over the Arctic Basin and the anomaly extends through the whole atmospheric column, changing the geopotential height fields and thus the storm tracks. The patterns of warming and thus the position of the geopotential height changes vary in the two ensembles. While the equilibrium simulation shifts the storm tracks to the south over the eastern North Atlantic and Europe, the transient simulation shifts the storm tracks south over the western North Atlantic and North America. The authors propose that the overall reduction in sea ice cover is important for producing ocean anomalies; however, for atmospheric anomalies the regional location of the sea ice anomalies is more important. While observed trends in Arctic sea ice are large and exceed those simulated by comprehensive climate models, there is little evidence based on this particular model that the seasonal loss of sea ice (e.g., as occurred in 2007) would constitute a threshold after which the Arctic would exhibit nonlinear, irreversible, or strongly accelerated sea ice loss. Caution should be exerted when extrapolating short-term trends to future sea ice behavior.

scholarly journals Ocean–Atmosphere State Dependence of the Atmospheric Response to Arctic Sea Ice Loss

2017 ◽  
Vol 30 (5) ◽  
pp. 1537-1552 ◽  
Author(s):  
Joe M. Osborne ◽  
James A. Screen ◽  
Mat Collins
Keyword(s):  
Sea Ice ◽  
North Pacific ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
The North ◽  
Arctic Sea ◽  
Ocean Atmosphere ◽  
Arctic Sea Ice Loss ◽  
The North Pacific ◽  
Sst Anomalies

Abstract The Arctic is warming faster than the global average. This disproportionate warming—known as Arctic amplification—has caused significant local changes to the Arctic system and more uncertain remote changes across the Northern Hemisphere midlatitudes. Here, an atmospheric general circulation model (AGCM) is used to test the sensitivity of the atmospheric and surface response to Arctic sea ice loss to the phase of the Atlantic multidecadal oscillation (AMO), which varies on (multi-) decadal time scales. Four experiments are performed, combining low and high sea ice states with global sea surface temperature (SST) anomalies associated with opposite phases of the AMO. A trough–ridge–trough response to wintertime sea ice loss is seen in the Pacific–North American sector in the negative phase of the AMO. The authors propose that this is a consequence of an increased meridional temperature gradient in response to sea ice loss, just south of the climatological maximum, in the midlatitudes of the central North Pacific. This causes a southward shift in the North Pacific storm track, which strengthens the Aleutian low with circulation anomalies propagating into North America. While the climate response to sea ice loss is sensitive to AMO-related SST anomalies in the North Pacific, there is little sensitivity to larger-magnitude SST anomalies in the North Atlantic. With background ocean–atmosphere states persisting for a number of years, there is the potential to improve predictions of the impacts of Arctic sea ice loss on decadal time scales.

scholarly journals Alleviation of an arctic sea ice bias in a coupled model through modifications of the subgrid scale orographic parameterization

2020 ◽  
Author(s):  
Guillaume Gastineau ◽  
Francois Lott ◽  
Juliette Mignot ◽  
Frederic Hourdin
Keyword(s):  
Sea Ice ◽  
Northern Hemisphere ◽  
Storm Track ◽  
Coupled Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Subgrid Scale ◽  
Local Flow ◽  
Low Level ◽  
Arctic Sea

<p>In the IPSL-CM6A-LR model, the subgrid scale orography (SSO) parameterization imposes at low level a blocked flow drag opposed to the local flow and a lift that is perpendicular to the local flow. We suggest that their tuning impacts of the Arctic sea ice coverage and the large scale oceanic circulation in climate models. In forced atmospheric mode, increasing the blocking and reducing the lift leads to an equatorward shift of the Northern Hemisphere subtropical jet, and a reduction of the mid latitude eddy-driven jet. It improves the simulated variability, with a reduced storm-track, and increased blocking frequency over Greenland and Scandinavia. Second, it contributes to cool the polar low-troposphere in winter. We show that the reduction in eddy activity yields a reduction of the poleward heat fluxes in the low troposphere of the mid-latitudes and polar regions. <span>Transformed Eulerian Mean diagnostics also show that there is a reduction of the low-level eddy-driven subsidence in the polar region consistent with the simulated cooling.</span> The changes are amplified in the coupled model, as the eddy-driven jet shift further south. The low-troposphere polar cooling is further amplified by the temperature and albedo feedbacks in link with the Arctic sea-ice. This corrects the warm winter bias and the lack of sea-ice that were present over the Arctic without changing the SSO parameters. <span>This also impacts the ocean, with an equatorward shift of the Northern Hemisphere oceanic gyre, and a weakening of the AMOC. </span></p>

scholarly journals Marine Heatwaves in Siberian Arctic Seas and Adjacent Region

2021 ◽  
Vol 13 (21) ◽  
pp. 4436
Author(s):  
Elena Golubeva ◽  
Marina Kraineva ◽  
Gennady Platov ◽  
Dina Iakshina ◽  
Marina Tarkhanova
Keyword(s):  
Numerical Modeling ◽  
Sea Ice ◽  
Arctic Ocean ◽  
Northern Region ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Arctic Seas ◽  
Siberian Arctic ◽  
The Arctic Ocean ◽  
The Impact

We used a satellite-derived global daily sea surface temperature (SST) dataset with resolution 0.25 × 0.25∘ to analyze interannual changes in the Arctic Shelf seas from 2000 to 2020 and to reveal extreme events in SST distribution. Results show that the second decade of the 21st century for the Siberian Arctic seas turned significantly warmer than the first decade, and the increase in SST in the Arctic seas could be considered in terms of marine heatwaves. Analyzing the spatial distribution of heatwaves and their characteristics, we showed that from 2018 to 2020, the surface warming extended to the northern deep-water region of the Laptev Sea 75∘ to 81∘N. To reveal the most important forcing for the northward extension of the marine heatwaves, we used three-dimensional numerical modeling of the Arctic Ocean based on a sea-ice and ocean model forced by the NCEP/NCAR Reanalysis. The simulation of the Arctic Ocean variability from 2000 to 2020 showed marine heatwaves and their increasing intensity in the northern region of the Kara and Laptev seas, closely connected to the disappearance of ice cover. A series of numerical experiments on the sensitivity of the model showed that the main factors affecting the Arctic sea-ice loss and the formation of anomalous temperature north of the Siberian Arctic seas are equally the thermal and dynamic effects of the atmosphere. Numerical modeling allows us to examine the impact of other physical mechanisms as well. Among them were the state of the ocean and winter sea ice, the formation of fast ice polynias and riverine heat influx.

scholarly journals A fully coupled Arctic sea ice-ocean-atmosphere model (ArcIOAM v1.0) based on C-Coupler2: model description and preliminary results

2020 ◽  
Author(s):  
Shihe Ren ◽  
Xi Liang ◽  
Qizhen Sun ◽  
Hao Yu ◽  
L. Bruno Tremblay ◽  
...  
Keyword(s):  
Sea Ice ◽  
Coupled Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Model Description ◽  
Preliminary Results ◽  
Comparison Results ◽  
Arctic Sea ◽  
Ocean Atmosphere ◽  
Atmosphere Model

Abstract. The implementation of a new Arctic regional coupled sea ice-ocean-atmosphere model (ArcIOAM) and its preliminary results in the year of 2012 are presented in this paper. A newly developed coupler, C-Coupler2 (the Community Coupler 2), is used to couple the Arctic sea ice-oceanic configuration of the MITgcm (Massachusetts Institute of Technology general circulation model) with the Arctic atmospheric configuration of the Polar WRF (Weather Research and Forecasting) model. ArcIOAM is demonstrated with focus on seasonal simulation of the Arctic sea ice and ocean state in the year of 2012. The results obtained by ArcIOAM, along with the experiment of one-way coupling strategy, are compared with available observational data and reanalysis products. From the comparison, results obtained from two experiments both realistically capture the sea ice and oceanic variables in the Arctic region over a 1-year simulation period. The two-way coupled model has better performance in terms of sea ice extent, concentration, thickness and SST, especially in summer. This indicates that sea ice-ocean-atmosphere interaction takes a crucial role in controlling Arctic summertime sea ice distribution. The coupled model and documentation are available at  https://doi.org/10.5281/zenodo.3742692 (last access: 9 June 2020), and the source code is maintained at  https://github.com/cdmpbp123/Coupled_Atm_Ice_Oce (last access: 7 April 2020).

scholarly journals Rapid Arctic Sea Ice Loss on the Synoptic Time Scale and Related Atmospheric Circulation Anomalies

2020 ◽  
Vol 33 (5) ◽  
pp. 1597-1617 ◽  
Author(s):  
Zhuo Wang ◽  
John Walsh ◽  
Sarah Szymborski ◽  
Melinda Peng
Keyword(s):  
Water Vapor ◽  
Sea Ice ◽  
Time Scale ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Energy Propagation ◽  
Sea Ice Extent ◽  
Atmospheric Rivers ◽  
Downward Longwave Radiation ◽  
Wave Trains

AbstractLarge sea ice loss on the synoptic time scale is examined in various subregions in the Arctic as well as at the pan-Arctic scale. It is found that the frequency of large daily sea ice loss (LDSIL) days is significantly correlated with the September sea ice extent over the Beaufort–Chukchi–Siberian Seas, the Laptev–Kara Seas, the central Arctic, and the all-Arctic regions, indicating a link between the synoptic sea ice variability and the interannual variability of the annual minimum sea ice extent. A composite analysis reveals dipoles of anomalous cyclones and anticyclones associated with LDSIL days. Different from the well-known Arctic dipole pattern, the east–west dipoles are found over the corresponding regions of LDSIL in the Arctic marginal seas and are associated with the increasing occurrence of Rossby wave breaking and atmospheric rivers. The anticyclones of the dipoles are persistent and quasi-stationary, reminiscent of blocking. The anomalous poleward flow between the cyclone and the anticyclone enhances the poleward transport of heat and water vapor in the lower troposphere. Although enhanced downward shortwave radiation, associated with reduced cloud fraction, is found in some regions, it is not collocated with the regions of LDSIL. In contrast, enhanced downward longwave radiation owing to increasing column water vapor shows good spatial correspondence with LDSIL, indicating the importance of atmospheric rivers in LDSIL events. Lead/lag composites with respect to the onset of LDSIL episodes reveal precursor wave trains spanning the midlatitudes. The wave trains have predominantly zonal energy propagation in the midlatitudes and do not show a clear link to tropical or subtropical forcing.

Navigation in the Russian Arctic: Sea Ice Caused Difficulties and Accidents

2013 ◽  
Author(s):  
Nataliya Marchenko
Keyword(s):  
Sea Ice ◽  
Barents Sea ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Russian Arctic ◽  
Arctic Seas ◽  
The North ◽  
The Barents Sea ◽  
Arctic Sea ◽  
Ice Conditions

The 5 Russian Arctic Seas have common features, but differ significantly from each other in the sea ice regime and navigation specifics. Navigation in the Arctic is a big challenge, especially during the winter season. However, it is necessary, due to limited natural resources elsewhere on Earth that may be easier for exploitation. Therefore sea ice is an important issue for future development. We foresee that the Arctic may become ice free in summer as a result of global warming and even light yachts will be able to pass through the Eastern Passage. There have been several such examples in the last years. But sea ice is an inherent feature of Arctic Seas in winter, it is permanently immanent for the Central Arctic Basin. That is why it is important to get appropriate knowledge about sea ice properties and operations in ice conditions. Four seas, the Kara, Laptev, East Siberian, and Chukchi have been examined in the book “Russian Arctic Seas. Navigation Condition and Accidents”, Marchenko, 2012 [1]. The book is devoted to the eastern sector of the Arctic, with a description of the seas and accidents caused by heavy ice conditions. The traditional physical-geographical characteristics, information about the navigation conditions and the main sea routes and reports on accidents that occurred in the 20th century have reviewed. An additional investigation has been performed for more recent accidents and for the Barents Sea. Considerable attention has been paid to problems associated with sea ice caused by the present development of the Arctic. Sea ice can significantly affect shipping, drilling, and the construction and operation of platforms and handling terminals. Sea ice is present in the main part of the east Arctic Sea most of the year. The Barents Sea, which is strongly influenced and warmed by the North Atlantic Current, has a natural environment that is dramatically different from those of the other Arctic seas. The main difficulties with the Barents Sea are produced by icing and storms and in the north icebergs. The ice jet is the most dangerous phenomenon in the main straits along the Northern Sea Route and in Chukchi Seas. The accidents in the Arctic Sea have been classified, described and connected with weather and ice conditions. Behaviour of the crew is taken into consideration. The following types of the ice-induced accidents are distinguished: forced drift, forced overwintering, shipwreck, and serious damage to the hull in which the crew, sometimes with the help of other crews, could still save the ship. The main reasons for shipwrecks and damages are hits of ice floes (often in rather calm ice conditions), ice nipping (compression) and drift. Such investigation is important for safety in the Arctic.

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