Atmospheric and oceanic drivers of regional Arctic winter sea-ice variability in present and future climates

Author(s):  
Jakob Dörr ◽  
Marius Årthun ◽  
Tor Eldevik ◽  
Erica Madonna

<p>The recent retreat of Arctic sea ice area is overlaid by strong internal variability on all timescales. In winter, sea ice retreat and variability are currently dominated by the Barents Sea, primarily driven by variable ocean heat transport from the Atlantic. Climate models from the latest intercomparison project CMIP6 project that the future loss of winter Arctic sea ice spreads throughout the Arctic Ocean and, hence, that other regions of the Arctic Ocean will see increased sea-ice variability. It is, however, not known how the influence of ocean heat transport will change, and to what extent and in which regions other drivers, such as atmospheric circulation or river runoff into the Arctic Ocean, will become important. Using a combination of observations and simulations from the Community Earth System Model Large Ensemble (CESM-LE), we analyze and contrast the present and future regional drivers of the variability of the winter Arctic sea ice cover. We find that for the recent past, both observations and CESM-LE show that sea ice variability in the Atlantic and Pacific sector of the Arctic Ocean is influenced by ocean heat transport through the Barents Sea and Bering Strait, respectively. The two dominant modes of large-scale atmospheric variability – the Arctic Oscillation and the Pacific North American pattern – are only weakly related to recent regional sea ice variability. However, atmospheric circulation anomalies associated with regional sea ice variability show distinct patterns for the Atlantic and Pacific sectors consistent with heat and humidity transport from lower latitudes. In the future, under a high emission scenario, CESM-LE projects a gradual expansion of the footprint of the Pacific and Atlantic inflows, covering the whole Arctic Ocean by 2050-2079. This study highlights the combined importance of future Atlantification and Pacification of the Arctic Ocean and improves our understanding of internal climate variability which essential in order to predict future sea ice changes under anthropogenic warming.   </p><p> </p>

2019 ◽  
Vol 32 (5) ◽  
pp. 1461-1482 ◽  
Author(s):  
Lejiang Yu ◽  
Shiyuan Zhong ◽  
Mingyu Zhou ◽  
Donald H. Lenschow ◽  
Bo Sun

Abstract The sharp decline of Arctic sea ice in recent decades has captured the attention of the climate science community. A majority of climate analyses performed to date have used monthly or seasonal data. Here, however, we analyze daily sea ice data for 1979–2016 using the self-organizing map (SOM) method to further examine and quantify the contributions of atmospheric circulation changes to the melt-season Arctic sea ice variability. Our results reveal two main variability modes: the Pacific sector mode and the Barents and Kara Seas mode, which together explain about two-thirds of the melt-season Arctic sea ice variability and more than 40% of its trend for the study period. The change in the frequencies of the two modes appears to be associated with the phase shift of the Pacific decadal oscillation (PDO) and the Atlantic multidecadal oscillation (AMO). The PDO and AMO trigger anomalous atmospheric circulations, in particular, the Greenland high and the North Atlantic Oscillation and anomalous warm and cold air advections into the Arctic Ocean. The changes in surface air temperature, lower-atmosphere moisture, and downwelling longwave radiation associated with the advection are consistent with the melt-season sea ice anomalies observed in various regions of the Arctic Ocean. These results help better understand the predictability of Arctic sea ice on multiple (synoptic, intraseasonal, and interannual) time scales.


2009 ◽  
Vol 22 (1) ◽  
pp. 165-176 ◽  
Author(s):  
R. W. Lindsay ◽  
J. Zhang ◽  
A. Schweiger ◽  
M. Steele ◽  
H. Stern

Abstract The minimum of Arctic sea ice extent in the summer of 2007 was unprecedented in the historical record. A coupled ice–ocean model is used to determine the state of the ice and ocean over the past 29 yr to investigate the causes of this ice extent minimum within a historical perspective. It is found that even though the 2007 ice extent was strongly anomalous, the loss in total ice mass was not. Rather, the 2007 ice mass loss is largely consistent with a steady decrease in ice thickness that began in 1987. Since then, the simulated mean September ice thickness within the Arctic Ocean has declined from 3.7 to 2.6 m at a rate of −0.57 m decade−1. Both the area coverage of thin ice at the beginning of the melt season and the total volume of ice lost in the summer have been steadily increasing. The combined impact of these two trends caused a large reduction in the September mean ice concentration in the Arctic Ocean. This created conditions during the summer of 2007 that allowed persistent winds to push the remaining ice from the Pacific side to the Atlantic side of the basin and more than usual into the Greenland Sea. This exposed large areas of open water, resulting in the record ice extent anomaly.


2020 ◽  
Vol 47 (3) ◽  
Author(s):  
Qiang Wang ◽  
Claudia Wekerle ◽  
Xuezhu Wang ◽  
Sergey Danilov ◽  
Nikolay Koldunov ◽  
...  

2014 ◽  
Vol 44 (5) ◽  
pp. 1329-1353 ◽  
Author(s):  
Michel Tsamados ◽  
Daniel L. Feltham ◽  
David Schroeder ◽  
Daniela Flocco ◽  
Sinead L. Farrell ◽  
...  

Abstract Over Arctic sea ice, pressure ridges and floe and melt pond edges all introduce discrete obstructions to the flow of air or water past the ice and are a source of form drag. In current climate models form drag is only accounted for by tuning the air–ice and ice–ocean drag coefficients, that is, by effectively altering the roughness length in a surface drag parameterization. The existing approach of the skin drag parameter tuning is poorly constrained by observations and fails to describe correctly the physics associated with the air–ice and ocean–ice drag. Here, the authors combine recent theoretical developments to deduce the total neutral form drag coefficients from properties of the ice cover such as ice concentration, vertical extent and area of the ridges, freeboard and floe draft, and the size of floes and melt ponds. The drag coefficients are incorporated into the Los Alamos Sea Ice Model (CICE) and show the influence of the new drag parameterization on the motion and state of the ice cover, with the most noticeable being a depletion of sea ice over the west boundary of the Arctic Ocean and over the Beaufort Sea. The new parameterization allows the drag coefficients to be coupled to the sea ice state and therefore to evolve spatially and temporally. It is found that the range of values predicted for the drag coefficients agree with the range of values measured in several regions of the Arctic. Finally, the implications of the new form drag formulation for the spinup or spindown of the Arctic Ocean are discussed.


2020 ◽  
Vol 117 (42) ◽  
pp. 26069-26075
Author(s):  
Anne de Vernal ◽  
Claude Hillaire-Marcel ◽  
Cynthia Le Duc ◽  
Philippe Roberge ◽  
Camille Brice ◽  
...  

The impact of the ongoing anthropogenic warming on the Arctic Ocean sea ice is ascertained and closely monitored. However, its long-term fate remains an open question as its natural variability on centennial to millennial timescales is not well documented. Here, we use marine sedimentary records to reconstruct Arctic sea-ice fluctuations. Cores collected along the Lomonosov Ridge that extends across the Arctic Ocean from northern Greenland to the Laptev Sea were radiocarbon dated and analyzed for their micropaleontological and palynological contents, both bearing information on the past sea-ice cover. Results demonstrate that multiyear pack ice remained a robust feature of the western and central Lomonosov Ridge and that perennial sea ice remained present throughout the present interglacial, even during the climate optimum of the middle Holocene that globally peaked ∼6,500 y ago. In contradistinction, the southeastern Lomonosov Ridge area experienced seasonally sea-ice-free conditions, at least, sporadically, until about 4,000 y ago. They were marked by relatively high phytoplanktonic productivity and organic carbon fluxes at the seafloor resulting in low biogenic carbonate preservation. These results point to contrasted west–east surface ocean conditions in the Arctic Ocean, not unlike those of the Arctic dipole linked to the recent loss of Arctic sea ice. Hence, our data suggest that seasonally ice-free conditions in the southeastern Arctic Ocean with a dominant Arctic dipolar pattern, may be a recurrent feature under “warm world” climate.


2019 ◽  
Vol 32 (8) ◽  
pp. 2381-2395
Author(s):  
Evelien Dekker ◽  
Richard Bintanja ◽  
Camiel Severijns

AbstractWith Arctic summer sea ice potentially disappearing halfway through this century, the surface albedo and insulating effects of Arctic sea ice will decrease considerably. The ongoing Arctic sea ice retreat also affects the strength of the Planck, lapse rate, cloud, and surface albedo feedbacks together with changes in the heat exchange between the ocean and the atmosphere, but their combined effect on climate sensitivity has not been quantified. This study presents an estimate of all Arctic sea ice related climate feedbacks combined. We use a new method to keep Arctic sea ice at its present-day (PD) distribution under a changing climate in a 50-yr CO2 doubling simulation, using a fully coupled global climate model (EC-Earth, version 2.3). We nudge the Arctic Ocean to the (monthly dependent) year 2000 mean temperature and minimum salinity fields on a mask representing PD sea ice cover. We are able to preserve about 95% of the PD mean March and 77% of the September PD Arctic sea ice extent by applying this method. Using simulations with and without nudging, we estimate the climate response associated with Arctic sea ice changes. The Arctic sea ice feedback globally equals 0.28 ± 0.15 W m−2 K−1. The total sea ice feedback thus amplifies the climate response for a doubling of CO2, in line with earlier findings. Our estimate of the Arctic sea ice feedback agrees reasonably well with earlier CMIP5 global climate feedback estimates and shows that the Arctic sea ice exerts a considerable effect on the Arctic and global climate sensitivity.


2020 ◽  
Author(s):  
Georgi Laukert ◽  
Dorothea Bauch ◽  
Ilka Peeken ◽  
Thomas Krumpen ◽  
Kirstin Werner ◽  
...  

<p>The lifetime and thickness of Arctic sea ice have markedly decreased in the recent past. This affects Arctic marine ecosystems and the biological pump, given that sea ice acts as platform and transport medium of marine and atmospheric nutrients. At the same time sea ice reduces light penetration to the Arctic Ocean and restricts ocean/atmosphere exchange. In order to understand the ongoing changes and their implications, reconstructions of source regions and drift trajectories of Arctic sea ice are imperative. Automated ice tracking approaches based on satellite-derived sea-ice motion products (e.g. ICETrack) currently perform well in dense ice fields, but provide limited information at the ice edge or in poorly ice-covered areas. Radiogenic neodymium (Nd) isotopes (ε<sub>Nd</sub>) have the potential to serve as a chemical tracer of sea-ice provenance and thus may provide information beyond what can be expected from satellite-based assessments. This potential results from pronounced ε<sub>Nd</sub> differences between the distinct marine and riverine sources, which feed the surface waters of the different sea-ice formation regions. We present the first dissolved (< 0.45 µm) Nd isotope and concentration data obtained from optically clean Arctic first- and multi-year sea ice (ice cores) collected from different ice floes across the Fram Strait during the RV POLARSTERN cruise PS85 in 2014. Our data confirm the preservation of the seawater ε<sub>Nd</sub>signatures in sea ice despite low Nd concentrations (on average ~ 6 pmol/kg) resulting from efficient brine rejection. The large range in ε<sub>Nd</sub> signatures (~ -10 to -30) mirrors that of surface waters in various parts of the Arctic Ocean, indicating that differences between ice floes but also between various sections in an individual ice core reflect the origin and evolution of the sea ice over time. Most ice cores have ε<sub>Nd</sub> signatures of around -10, suggesting that the sea ice was formed in well-mixed waters in the central Arctic Ocean and transported directly to the Fram Strait via the Transpolar Drift. Some ice cores, however, also revealed highly unradiogenic signatures (ε<sub>Nd</sub> < ~ -15) in their youngest (bottom) sections, which we attribute to incorporation of meltwater from Greenland into newly grown sea ice layers. Our new approach facilitates the reconstruction of the origin and spatiotemporal evolution of isolated sea-ice floes in the future Arctic.</p>


2016 ◽  
Vol 12 (11) ◽  
pp. 20160223 ◽  
Author(s):  
Mati Kahru ◽  
Zhongping Lee ◽  
B. Greg Mitchell ◽  
Cynthia D. Nevison

The influence of decreasing Arctic sea ice on net primary production (NPP) in the Arctic Ocean has been considered in multiple publications but is not well constrained owing to the potentially large errors in satellite algorithms. In particular, the Arctic Ocean is rich in coloured dissolved organic matter (CDOM) that interferes in the detection of chlorophyll a concentration of the standard algorithm, which is the primary input to NPP models. We used the quasi-analytic algorithm (Lee et al . 2002 Appl. Opti. 41 , 5755−5772. ( doi:10.1364/AO.41.005755 )) that separates absorption by phytoplankton from absorption by CDOM and detrital matter. We merged satellite data from multiple satellite sensors and created a 19 year time series (1997–2015) of NPP. During this period, both the estimated annual total and the summer monthly maximum pan-Arctic NPP increased by about 47%. Positive monthly anomalies in NPP are highly correlated with positive anomalies in open water area during the summer months. Following the earlier ice retreat, the start of the high-productivity season has become earlier, e.g. at a mean rate of −3.0 d yr −1 in the northern Barents Sea, and the length of the high-productivity period has increased from 15 days in 1998 to 62 days in 2015. While in some areas, the termination of the productive season has been extended, owing to delayed ice formation, the termination has also become earlier in other areas, likely owing to limited nutrients.


2020 ◽  
Author(s):  
Lejiang Yu ◽  
Sharon Zhong

<p>The sharp decline of Arctic sea ice in recent decades has captured the attention of the climate science<br>community. A majority of climate analyses performed to date have used monthly or seasonal data. Here,<br>however, we analyze daily sea ice data for 1979–2016 using the self-organizing map (SOM) method to further<br>examine and quantify the contributions of atmospheric circulation changes to the melt-season Arctic sea ice<br>variability. Our results reveal two main variability modes: the Pacific sector mode and the Barents and Kara<br>Seas mode, which together explain about two-thirds of the melt-season Arctic sea ice variability and more<br>than 40% of its trend for the study period. The change in the frequencies of the two modes appears to be<br>associated with the phase shift of the Pacific decadal oscillation (PDO) and the Atlantic multidecadal oscillation<br>(AMO). The PDO and AMO trigger anomalous atmospheric circulations, in particular, the<br>Greenland high and the North Atlantic Oscillation and anomalous warm and cold air advections into the<br>Arctic Ocean. The changes in surface air temperature, lower-atmosphere moisture, and downwelling longwave<br>radiation associated with the advection are consistent with the melt-season sea ice anomalies observed<br>in various regions of the Arctic Ocean. These results help better understand the predictability of Arctic sea ice<br>on multiple (synoptic, intraseasonal, and interannual) time scales.</p>


2020 ◽  
Author(s):  
Louise Sime ◽  
Masa Kageyama ◽  
Marie Sicard ◽  
Maria-Vittoria Guarino ◽  
Anne de Vernal ◽  
...  

<p>The Last interglacial (LIG) is a period with increased summer insolation at high northern latitudes, which results in strong changes in the terrestrial and marine cryosphere. Understanding the mechanisms for this response via climate modelling and comparing the models’ representation of climate reconstructions is one of the objectives set up by the Paleoclimate Modelling Intercomparison Project for its contribution to the sixth phase of the Coupled Model Intercomparison Project. Here we analyse the results from 12 climate models in terms of Arctic sea ice. The mean pre-industrial to LIG reduction in minimum sea ice area (SIA) reaches 59% (multi-model mean LIG area is 2.21 mill. km2, compared to 5.85 mill. km2 for the PI), and the range of model results for LIG minimum sea ice area (from 0.02 to 5.65 mill. km2) is larger than for PI (from 4.10 to 8.30 mill. km2). On the other hand there is little change for the maximum sea ice area (which is 12 mill. km2 for both the PI and the LIG, with a standard deviation of 1.04 mill. km2 for PI and 1.21 mill. km2 for LIG). To evaluate the model results we synthesize LIG sea ice data from marine cores collected in the Arctic Ocean, Nordic Seas and northern North Atlantic. South of 78<sup>o</sup>N, in the Atlantic and Nordic seas, the LIG was seasonally ice-free. North of 78<sup>o</sup>N there are some discrepancies between sea ice reconstructions based on dinocysts/foraminifers/ostracods and IP25: some sites have both seasonal and perennial interpretations based on the same core, but different indicators. Because of the conflicting interpretations it is not possible for any one model to match every data point in our data synthesis, or say whether the Arctic was seasonally ice-free. Drivers for the inter-model differences are: different phasing of the up and down short-wave anomalies over the Arctic ocean, associated with differences in model albedo; possible cloud property differences, in terms of optical depth; LIG ocean circulation changes which occur for some, but not all, LIG simulations. Finally we note that inter-comparisons between the LIG simulations, and simulations with moderate CO2 increase (during the transition to high CO2 levels), may yield insight into likely 21C Arctic sea ice changes using these LIG simulations.</p>


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