scholarly journals Impact of Winter Ural Blocking on Arctic Sea Ice: Short-Time Variability

2018 ◽  
Vol 31 (6) ◽  
pp. 2267-2282 ◽  
Author(s):  
Xiaodan Chen ◽  
Dehai Luo ◽  
Steven B. Feldstein ◽  
Sukyoung Lee
Keyword(s):  
Heat Flux ◽  
Sea Ice ◽  
Sensible Heat Flux ◽  
Reanalysis Data ◽  
Arctic Sea Ice ◽  
Time Variability ◽  
Sea Ice Concentration ◽  
Arctic Sea ◽  
Barents And Kara Seas ◽  
The Impact

Using daily reanalysis data from 1979 to 2015, this paper examines the impact of winter Ural blocking (UB) on winter Arctic sea ice concentration (SIC) change over the Barents and Kara Seas (BKS). A case study of the sea ice variability in the BKS in the 2015/16 and 2016/17 winters is first presented to establish a link between the BKS sea ice variability and UB events. Then the UB events are classified into quasi-stationary (QUB), westward-shifting (WUB), and eastward-shifting (EUB) UB types. It is found that the frequency of the QUB events increases significantly during 1999–2015, whereas the WUB events show a decreasing frequency trend during 1979–2015. Moreover, it is shown that the variation of the BKS-SIC is related to downward infrared radiation (IR) and surface sensible and latent heat flux changes due to different zonal movements of the UB. Calculations show that the downward IR is the main driver of the BKS-SIC decline for QUB events, while the downward IR and surface sensible heat flux make comparable contributions to the BKS-SIC variation for WUB and EUB events. The SIC decline peak lags the QUB and EUB peaks by about 3 days, though QUB and EUB require lesser prior SIC. The QUB gives rise to the largest SIC decline likely because of its longer persistence, whereas the BKS-SIC decline is relatively weak for the EUB. The WUB is found to cause a SIC decline during its growth phase and an increase during its decay phase. Thus, the zonal movement of the UB has an important impact on the SIC variability in BKS.

scholarly journals A Nonlinear Theory of Atmospheric Blocking: An Application to Greenland Blocking Changes Linked to Winter Arctic Sea Ice Loss

2019 ◽  
Vol 77 (2) ◽  
pp. 723-751 ◽  
Author(s):  
Wenqi Zhang ◽  
Dehai Luo
Keyword(s):  
Sea Ice ◽  
Phase Speed ◽  
Arctic Sea Ice ◽  
Atmospheric Blocking ◽  
Energy Dispersion ◽  
Sea Ice Concentration ◽  
Zonal Scale ◽  
The North ◽  
Arctic Sea ◽  
The Impact

Abstract In this paper, the impact of winter Arctic sea ice concentration (SIC) decline over Baffin Bay, Davis Strait, and Labrador Sea (BDL) on Greenland blocking (GB) is first examined. It is found that the GB has a longer duration, a more notable westward movement, and a larger zonal scale in the low SIC winter than in the high SIC winter. In particular, the decay of GB may become slower than its growth in the low SIC winter, but the reverse is seen in the high SIC winter. The GB in the low SIC winter can have a more important impact on cold anomalies over North American midlatitudes than in the high SIC winter because of its slower decay and stronger retrogression. The influence of large BDL SIC loss on the GB mainly through reduced meridional potential vorticity gradient (PVy) related to reduced zonal winds over the North Atlantic mid- to high latitudes (NAMH) due to BDL warming is further examined by using the nonlinear phase speed and energy dispersion speed formula of blocking based on a nonlinear wave packet theory of atmospheric blocking. In this theory, the preexisting synoptic-scale eddies rather than the eddy straining or deformation is important for the blocking intensification and maintenance, which contradicts the eddy straining theory of Shutts. It is revealed from this theoretical model that under weaker NAMH zonal wind conditions the energy dispersion speed of GB may become smaller due to weaker PVy during its decaying phase than during the blocking growing phase, in addition to the GB having larger negative phase speed and stronger nonlinearity. The opposite is true when the PVy is larger. Thus, under a large SIC loss condition the GB shows notable retrogression, large zonal scales, and a long lifetime, which has a slower decay than its growth.

scholarly journals Evidence for an increasing role of ocean heat in Arctic winter sea ice growth

2021 ◽  
pp. 1-42
Author(s):  
Robert Ricker ◽  
Frank Kauker ◽  
Axel Schweiger ◽  
Stefan Hendricks ◽  
Jinlun Zhang ◽  
...  
Keyword(s):  
Sea Ice ◽  
Reanalysis Data ◽  
Arctic Sea Ice ◽  
Satellite Observations ◽  
The Arctic ◽  
Ice Growth ◽  
Marginal Seas ◽  
Air Temperatures ◽  
Barents And Kara Seas ◽  
The Impact

AbstractWe investigate how sea ice decline in summer and warmer ocean and surface temperatures in winter affect sea ice growth in the Arctic. Sea ice volume changes are estimated from satellite observations during winter from 2002 to 2019 and partitioned into thermodynamic growth and dynamic volume change. Both components are compared to validated sea ice-ocean models forced by reanalysis data to extend observations back to 1980 and to understand the mechanisms that cause the observed trends and variability. We find that a negative feedback driven by the increasing sea ice retreat in summer yields increasing thermodynamic ice growth during winter in the Arctic marginal seas eastward from the Laptev Sea to the Beaufort Sea. However, in the Barents and Kara Seas, this feedback seems to be overpowered by the impact of increasing oceanic heat flux and air temperatures, resulting in negative trends in thermodynamic ice growth of -2 km3month-1yr-1 on average over 2002-2019 derived from satellite observations.

scholarly journals Improving Met Office seasonal predictions of Arctic sea ice using assimilation of CryoSat-2 thickness

2018 ◽  
Vol 12 (11) ◽  
pp. 3419-3438 ◽  
Author(s):  
Edward W. Blockley ◽  
K. Andrew Peterson
Keyword(s):  
Sea Ice ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
Ice Thickness ◽  
Forecast Errors ◽  
Sea Ice Concentration ◽  
Sea Ice Thickness ◽  
Near Surface ◽  
Arctic Sea ◽  
The Impact

Abstract. Interest in seasonal predictions of Arctic sea ice has been increasing in recent years owing, primarily, to the sharp reduction in Arctic sea-ice cover observed over the last few decades, a decline that is projected to continue. The prospect of increased human industrial activity in the region, as well as scientific interest in the predictability of sea ice, provides important motivation for understanding, and improving, the skill of Arctic predictions. Several operational forecasting centres now routinely produce seasonal predictions of sea-ice cover using coupled atmosphere–ocean–sea-ice models. Although assimilation of sea-ice concentration into these systems is commonplace, sea-ice thickness observations, being much less mature, are typically not assimilated. However, many studies suggest that initialization of winter sea-ice thickness could lead to improved prediction of Arctic summer sea ice. Here, for the first time, we directly assess the impact of winter sea-ice thickness initialization on the skill of summer seasonal predictions by assimilating CryoSat-2 thickness data into the Met Office's coupled seasonal prediction system (GloSea). We show a significant improvement in predictive skill of Arctic sea-ice extent and ice-edge location for forecasts of September Arctic sea ice made from the beginning of the melt season. The improvements in sea-ice cover lead to further improvement of near-surface air temperature and pressure fields across the region. A clear relationship between modelled winter thickness biases and summer extent errors is identified which supports the theory that Arctic winter thickness provides some predictive capability for summer ice extent, and further highlights the importance that modelled winter thickness biases can have on the evolution of forecast errors through the melt season.

scholarly journals Seasonal cycle and long-term trend of solar energy fluxes through Arctic sea ice

2014 ◽  
Vol 8 (6) ◽  
pp. 2219-2233 ◽  
Author(s):  
S. Arndt ◽  
M. Nicolaus
Keyword(s):  
Sea Ice ◽  
Open Water ◽  
Ice Cover ◽  
Reanalysis Data ◽  
Arctic Sea Ice ◽  
Light Transmittance ◽  
First Year ◽  
Sea Ice Concentration ◽  
Solar Heat ◽  
Arctic Sea

Abstract. Arctic sea ice has not only decreased in volume during the last decades, but has also changed in its physical properties towards a thinner and more seasonal ice cover. These changes strongly impact the energy budget, and might affect the ice-associated ecosystems. In this study, we quantify solar shortwave fluxes through sea ice for the entire Arctic during all seasons. To focus on sea-ice-related processes, we exclude fluxes through open water, scaling linearly with sea ice concentration. We present a new parameterization of light transmittance through sea ice for all seasons as a function of variable sea ice properties. The maximum monthly mean solar heat flux under the ice of 30 × 105 Jm−2 occurs in June, enough heat to melt 0.3 m of sea ice. Furthermore, our results suggest that 96% of the annual solar heat input through sea ice occurs during only a 4-month period from May to August. Applying the new parameterization to remote sensing and reanalysis data from 1979 to 2011, we find an increase in transmitted light of 1.5% yr−1 for all regions. This corresponds to an increase in potential sea ice bottom melt of 63% over the 33-year study period. Sensitivity studies reveal that the results depend strongly on the timing of melt onset and the correct classification of ice types. Assuming 2 weeks earlier melt onset, the annual transmitted solar radiation to the upper ocean increases by 20%. Continuing the observed transition from a mixed multi-year/first-year sea ice cover to a seasonal ice cover results in an increase in light transmittance by an additional 18%.

scholarly journals A Variational Method for Computation of Sensible Heat Flux over the Arctic Sea Ice

2009 ◽  
Vol 26 (4) ◽  
pp. 838-845 ◽  
Author(s):  
Zuohao Cao ◽  
Jianmin Ma
Keyword(s):  
Heat Flux ◽  
Variational Method ◽  
Sea Ice ◽  
Variational Approach ◽  
Sensible Heat Flux ◽  
Arctic Sea Ice ◽  
Eddy Correlation ◽  
The Arctic ◽  
Sensible Heat ◽  
Arctic Sea

Abstract In this study, a variational approach was employed to compute surface sensible heat flux over the Arctic sea ice. Because the variational approach is able to take into account information from the Monin–Obukhov similarity theory (MOST) as well as the observed meteorological information, it is expected to improve the pure MOST-based approach in computation of sensible heat flux. Verifications using the direct eddy-correlation measurements over the Arctic sea ice during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment period of 1997/98 show that the variational method yields good agreement between the computed and the measured sensible heat fluxes. The variational method is also shown to be more accurate than the traditional MOST method in the computation of sensible heat flux over the Arctic sea ice.

scholarly journals Uncertainties in Arctic Sea Ice Thickness Associated with Different Atmospheric Reanalysis Datasets Using the CICE5 Model

Atmosphere ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 361
Author(s):  
Su-Bong Lee ◽  
Baek-Min Kim ◽  
Jinro Ukita ◽  
Joong-Bae Ahn
Keyword(s):  
Sea Ice ◽  
Arctic Region ◽  
Reanalysis Data ◽  
Arctic Sea Ice ◽  
Heat Fluxes ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
Sea Ice Extent ◽  
Ice Volume ◽  
Arctic Sea

Reanalysis data are known to have relatively large uncertainties in the polar region than at lower latitudes. In this study, we used a single sea-ice model (Los Alamos’ CICE5) and three sets of reanalysis data to quantify the sensitivities of simulated Arctic sea ice area and volume to perturbed atmospheric forcings. The simulated sea ice area and thickness thus volume were clearly sensitive to the selection of atmospheric reanalysis data. Among the forcing variables, changes in radiative and sensible/latent heat fluxes caused significant amounts of sensitivities. Differences in sea-ice concentration and thickness were primarily caused by differences in downward shortwave and longwave radiations. 2-m air temperature also has a significant influence on year-to-year variability of the sea ice volume. Differences in precipitation affected the sea ice volume by causing changes in the insulation effect of snow-cover on sea ice. The diversity of sea ice extent and thickness responses due to uncertainties in atmospheric variables highlights the need to carefully evaluate reanalysis data over the Arctic region.

scholarly journals Comparison of Arctic Sea Ice Concentrations from the NASA Team, ASI, and VASIA2 Algorithms with Summer and Winter Ship Data

2019 ◽  
Vol 11 (21) ◽  
pp. 2481 ◽  
Author(s):  
Tatiana Alekseeva ◽  
Vasiliy Tikhonov ◽  
Sergei Frolov ◽  
Irina Repina ◽  
Mikhael Raev ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
Interaction Study ◽  
Sea Ice Concentration ◽  
Ice Melt ◽  
Antarctic Sea Ice ◽  
Arctic Sea ◽  
Ice Concentration ◽  
Satellite Microwave ◽  
The Impact

The paper presents a comparison of sea ice concentration (SIC) derived from satellite microwave radiometry data and dedicated ship observations. For the purpose, the NASA Team (NT), Arctic Radiation and Turbulence Interaction Study (ARTIST) Sea Ice (ASI), and Variation Arctic/Antarctic Sea Ice Algorithm 2 (VASIA2) algorithms were used as well as the database of visual ice observations accumulated in the course of 15 Arctic expeditions. The comparison was performed in line with the SIC gradation (in tenths) into very open (1–3), open (4–6), close (7–8), very close and compact (9–10,10) ice, separately for summer and winter seasons. On average, in summer NT underestimates SIC by 0.4 tenth as compared to ship observations, while ASI and VASIA2 by 0.3 tenth. All three algorithms overestimate total SIC in regions of very open ice and underestimate it in regions of close, very close, and compact ice. The maximum average errors are typical of open ice regions that are most common in marginal ice zones. In winter, NT and ASI also underestimate SIC on average by 0.4 and 0.8 tenths, respectively, while VASIA2, on the contrary, overestimates by 0.2 tenth against the ship data, however, for open and close ice the average errors are significantly higher than in summer. In the paper, we also estimate the impact of ice melt stage and presence of new ice and nilas on SIC derived from NT, ASI, and VASIA2.

scholarly journals Seasonal cycle of solar energy fluxes through Arctic sea ice

2014 ◽  
Vol 8 (3) ◽  
pp. 2923-2956
Author(s):  
S. Arndt ◽  
M. Nicolaus
Keyword(s):  
Heat Flux ◽  
Sea Ice ◽  
Light Transmission ◽  
Reanalysis Data ◽  
Arctic Sea Ice ◽  
Light Transmittance ◽  
The Arctic ◽  
Energy Fluxes ◽  
Solar Heat ◽  
Arctic Sea

Abstract. Arctic sea ice has not only decreased considerably during the last decades, but also changed its physical properties towards a thinner and more seasonal cover. These changes strongly impact the energy budget and might affect the ice-associated ecosystem of the Arctic. But until now, it is not possible to quantify shortwave energy fluxes through sea ice sufficiently well over large regions and during different seasons. Here, we present a new parameterization of light transmittance through sea ice for all seasons as a function of variable sea ice properties. The annual maximum solar heat flux of 30 × 105 J m−2 occurs in June, then also matching the under ice ocean heat flux. Furthermore, our results suggest that 96% of the total annual solar heat input occurs from May to August, during four months only. Applying the new parameterization on remote sensing and reanalysis data from 1979 to 2011, we find an increase in light transmission of 1.5% a−1 for all regions. Sensitivity studies reveal that the results strongly depend on the timing of melt onset and the correct classification of ice types. Hence, these parameters are of great importance for quantifying under-ice radiation fluxes and the uncertainty of this parameterization. Assuming a two weeks earlier melt onset, the annual budget increases by 20%. Continuing the observed transition from Arctic multi- to first year sea ice could increase light transmittance by another 18%. Furthermore, the increase in light transmission directly contributes to an increase in internal and bottom melt of sea ice, resulting in a positive transmittance-melt feedback process.

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