Controls on Arctic Sea Ice from First-Year and Multiyear Ice Survivability

2011 ◽  
Vol 24 (9) ◽  
pp. 2378-2390 ◽  
Author(s):  
Kyle C. Armour ◽  
Cecilia M. Bitz ◽  
LuAnne Thompson ◽  
Elizabeth C. Hunke
Keyword(s):  
Sea Ice ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
Climate Forcing ◽  
Reduced Model ◽  
First Year ◽  
Arctic Sea ◽  
Multiyear Ice ◽  
Area And Volume

Abstract Recent observations of Arctic sea ice show that the decrease in summer ice cover over the last few decades has occurred in conjunction with a significant loss of multiyear ice. The transition to an Arctic that is populated by thinner, first-year sea ice has important implications for future trends in area and volume. Here, a reduced model for Arctic sea ice is developed. This model is used to investigate how the survivability of first-year and multiyear ice controls the mean state, variability, and trends in ice area and volume. A hindcast with a global dynamic–thermodynamic sea ice model that traces first-year and multiyear ice is used to estimate the survivability of each ice type. These estimates of survivability, in concert with the reduced model, yield persistence time scales of September area and volume anomalies and the characteristics of the sensitivity of sea ice to climate forcing that compare well with a fully coupled climate model. The September area is found to be nearly in equilibrium with climate forcing at all times, and therefore the observed decline in summer sea ice cover is a clear indication of a changing climate. Keeping an account of first-year and multiyear ice area within global climate models offers a powerful way to evaluate those models with observations, and could help to constrain projections of sea ice decline in a warming climate.

scholarly journals Observation-based selection of climate models projects Arctic ice-free summers around 2035

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
David Docquier ◽  
Torben Koenigk
Keyword(s):  
Model Selection ◽  
Sea Ice ◽  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
The Arctic ◽  
Arctic Sea ◽  
Area And Volume

AbstractArctic sea ice has been retreating at an accelerating pace over the past decades. Model projections show that the Arctic Ocean could be almost ice free in summer by the middle of this century. However, the uncertainties related to these projections are relatively large. Here we use 33 global climate models from the Coupled Model Intercomparison Project 6 (CMIP6) and select models that best capture the observed Arctic sea-ice area and volume and northward ocean heat transport to refine model projections of Arctic sea ice. This model selection leads to lower Arctic sea-ice area and volume relative to the multi-model mean without model selection and summer ice-free conditions could occur as early as around 2035. These results highlight a potential underestimation of future Arctic sea-ice loss when including all CMIP6 models.

scholarly journals How Climate Model Complexity Influences Sea Ice Stability

2015 ◽  
Vol 28 (10) ◽  
pp. 3998-4014 ◽  
Author(s):  
Till J. W. Wagner ◽  
Ian Eisenman
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
Model Complexity ◽  
The Arctic ◽  
Arctic Sea ◽  
The Stability ◽  
Low Order

Abstract Record lows in Arctic sea ice extent have been making frequent headlines in recent years. The change in albedo when sea ice is replaced by open water introduces a nonlinearity that has sparked an ongoing debate about the stability of the Arctic sea ice cover and the possibility of Arctic “tipping points.” Previous studies identified instabilities for a shrinking ice cover in two types of idealized climate models: (i) annual-mean latitudinally varying diffusive energy balance models (EBMs) and (ii) seasonally varying single-column models (SCMs). The instabilities in these low-order models stand in contrast with results from comprehensive global climate models (GCMs), which typically do not simulate any such instability. To help bridge the gap between low-order models and GCMs, an idealized model is developed that includes both latitudinal and seasonal variations. The model reduces to a standard EBM or SCM as limiting cases in the parameter space, thus reconciling the two previous lines of research. It is found that the stability of the ice cover vastly increases with the inclusion of spatial communication via meridional heat transport or a seasonal cycle in solar forcing, being most stable when both are included. If the associated parameters are set to values that correspond to the current climate, the ice retreat is reversible and there is no instability when the climate is warmed. The two parameters have to be reduced by at least a factor of 3 for instability to occur. This implies that the sea ice cover may be substantially more stable than has been suggested in previous idealized modeling studies.

scholarly journals Refinement of future Arctic sea-ice projections

2021 ◽  
Author(s):  
David Docquier ◽  
Torben Koenigk
Keyword(s):  
Model Selection ◽  
Sea Ice ◽  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
The Arctic ◽  
Arctic Sea ◽  
Area And Volume

Abstract Arctic sea ice has been retreating at unprecedented pace over the past decades. Model projections show that the Arctic Ocean could be almost ice free in summer by the middle of this century. However, the uncertainties related to these projections are relatively large. Here we use 33 global climate models from the Coupled Model Intercomparison Project 6 (CMIP6) in order to reduce these uncertainties. We select the models that best capture the observed Arctic sea-ice area and volume and northward ocean heat transport to refine model projections of Arctic sea ice. This model selection leads to smaller Arctic sea-ice area and volume relative to the multi-model mean without model selection and summer ice-free conditions could occur as early as around 2035. These results highlight a potential underestimation of the future Arctic sea-ice loss when including all models.

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 Sub-kilometre scale distribution of snow depth on Arctic sea ice from Soviet drifting stations

2021 ◽  
Author(s):  
Robbie Mallett ◽  
Julienne Stroeve ◽  
Michel Tsamados ◽  
Rosemary Willatt ◽  
Thomas Newman ◽  
...  
Keyword(s):  
Sea Ice ◽  
Snow Depth ◽  
Arctic Sea Ice ◽  
First Year ◽  
Sea Ice Thickness ◽  
Arctic Sea ◽  
Ice Field ◽  
The Mean ◽  
Ice Impacts ◽  
Multiyear Ice

The sub-kilometre scale distribution of snow depth on Arctic sea ice impacts atmosphere-ice fluxes of heat and light, and is of importance for satellite estimates of sea ice thickness from both radar and lidar altimeters. While information about the mean of this distribution is increasingly available from modelling and remote sensing, the full distribution cannot yet be resolved. We analyse 33539 snow depth measurements from 499 transects taken at Soviet drifting stations between 1955 and 1991 and derive a simple statistical distribution for snow depth over multi-year ice as a function of only the mean snow depth. We then evaluate this snow depth distribution against snow depth transects that span first-year ice to multiyear ice from the MOSAiC, SHEBA and AMSR-Ice field campaigns. Because the distribution can be generated using only the mean snow depth, it can be used in the downscaling of several existing snow depth products for use in flux modelling and altimetry studies.

scholarly journals Observations of Sea Ice Melt from Operation IceBridge Imagery

2019 ◽  
Author(s):  
Nicholas C. Wright ◽  
Chris M. Polashenski ◽  
Scott T. McMichael ◽  
Ross A. Beyer
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
First Year ◽  
Ice Melt ◽  
Melt Pond ◽  
Ice Surface ◽  
Optical Images ◽  
Arctic Sea ◽  
Ice Floes ◽  
Multiyear Ice

Abstract. The summer albedo of Arctic sea ice is heavily dependent on the fraction and color of melt ponds that form on the ice surface. This work presents a new dataset of sea ice surface fractions along Operation IceBridge (OIB) flight tracks derived from the Digital Mapping System optical imagery set. This dataset was created by deploying version 2 of the Open Source Sea-ice Processing (OSSP) algorithm to NASA’s Advanced Supercomputing Pleiades System. These new surface fraction results are then analyzed to investigate the behavior of meltwater on first-year ice in comparison to multiyear ice. Observations herein show that first-year ice does not ubiquitously have a higher melt pond fraction than multiyear ice under the same forcing conditions, contrary to established knowledge in the sea ice community. We discover and document a larger possible spread of pond fractions on first year ice leading to both high and low pond coverage, in contrast to the uniform melt evolution that has been previously observed on multiyear ice floes. We also present a selection of optical images that captures both the typical and atypical ice types, as observed from the OIB dataset. We hope to demonstrate the power of this new dataset and to encourage future collaborative efforts to utilize the OIB data to explore the behavior of melt pond formation Arctic sea ice.

scholarly journals Variability of Arctic Sea Ice (1979–2016)

Water ◽  
2018 ◽  
Vol 11 (1) ◽  
pp. 23 ◽  
Author(s):  
Zhankai Wu ◽  
Xingdong Wang
Keyword(s):  
Sea Ice ◽  
Data Center ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
First Year ◽  
Concentration Data ◽  
Sea Ice Concentration ◽  
Arctic Sea ◽  
Ice Concentration ◽  
Multiyear Ice

This study is based on the daily sea ice concentration data from the National Snow and Ice Data Center (NSIDC; Cooperative Institute for Research in Environmental Sciences (CIRES), Boulder, CO, USA) from 1979 to 2016. The Arctic sea ice is analyzed from the total sea ice area, first year ice extent, multiyear ice area, and the variability of sea ice concentration in different ranges. The results show that the total sea ice area decreased by 0.0453 × 106 km2·year−1 (−0.55%/year) between 1979 and 2016, and the variability of the sea ice area from 1997 to 2016 is significantly larger than that from 1979 to 1996. The first-year ice extent increased by 0.0199 × 106 km2·year−1 (0.36%/year) from 1997 to 2016. The multiyear ice area decreased by 0.0711 × 106 km2·year−1 (−0.66%/year) from 1979 to 2016, of which in the last 20 years is about 30.8% less than in 1979–1996. In terms of concentration, we have focused on comparing 1979–1996 and 1997–2016 in different ranges. Sea ice concentration between 0.9–1 accounted for about 39.57% from 1979 to 1996, while from 1997–2016, it accounted for only 27.75%. However, the sea ice of concentration between 0.15–0.4 exhibits no significant trend changes.

scholarly journals Observations of sea ice melt from Operation IceBridge imagery

2020 ◽  
Vol 14 (10) ◽  
pp. 3523-3536
Author(s):  
Nicholas C. Wright ◽  
Chris M. Polashenski ◽  
Scott T. McMichael ◽  
Ross A. Beyer
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
First Year ◽  
Ice Melt ◽  
Melt Pond ◽  
Ice Surface ◽  
Optical Images ◽  
Arctic Sea ◽  
Ice Floes ◽  
Multiyear Ice

Abstract. The summer albedo of Arctic sea ice is heavily dependent on the fraction and color of melt ponds that form on the ice surface. This work presents a new dataset of sea ice surface fractions along Operation IceBridge (OIB) flight tracks derived from the Digital Mapping System optical imagery set. This dataset was created by deploying version 2 of the Open Source Sea-ice Processing (OSSP) algorithm to NASA's Advanced Supercomputing Pleiades System. These new surface fraction results are then analyzed to investigate the behavior of meltwater on first-year ice in comparison to multiyear ice. Observations herein show that first-year ice does not ubiquitously have a higher melt pond fraction than multiyear ice under the same forcing conditions, contrary to established knowledge in the sea ice community. We discover and document a larger possible spread of pond fractions on first-year ice leading to both high and low pond coverage, in contrast to the uniform melt evolution that has been previously observed on multiyear ice floes. We also present a selection of optical images that capture both the typical and atypical ice types, as observed from the OIB dataset. The derived OIB data presented here will be key to explore the behavior of melt pond formation Arctic sea ice.

scholarly journals Polar cod in jeopardy under the retreating Arctic sea ice

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Mats Brockstedt Olsen Huserbråten ◽  
Elena Eriksen ◽  
Harald Gjøsæter ◽  
Frode Vikebø
Keyword(s):  
Sea Ice ◽  
Barents Sea ◽  
Keystone Species ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
Biophysical Model ◽  
The Arctic ◽  
Polar Cod ◽  
Arctic Sea ◽  
Shelf Sea

Abstract The Arctic amplification of global warming is causing the Arctic-Atlantic ice edge to retreat at unprecedented rates. Here we show how variability and change in sea ice cover in the Barents Sea, the largest shelf sea of the Arctic, affect the population dynamics of a keystone species of the ice-associated food web, the polar cod (Boreogadus saida). The data-driven biophysical model of polar cod early life stages assembled here predicts a strong mechanistic link between survival and variation in ice cover and temperature, suggesting imminent recruitment collapse should the observed ice-reduction and heating continue. Backtracking of drifting eggs and larvae from observations also demonstrates a northward retreat of one of two clearly defined spawning assemblages, possibly in response to warming. With annual to decadal ice-predictions under development the mechanistic physical-biological links presented here represent a powerful tool for making long-term predictions for the propagation of polar cod stocks.

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