scholarly journals Time-Dependent Variations in the Arctic’s Surface Albedo Feedback and the Link to Seasonality in Sea Ice

2017 ◽  
Vol 30 (1) ◽  
pp. 393-410 ◽  
Author(s):  
Olivier Andry ◽  
Richard Bintanja ◽  
Wilco Hazeleger
Keyword(s):  
Sea Ice ◽  
Surface Albedo ◽  
Kernel Method ◽  
Ice Cover ◽  
Temporal Variations ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Dominant Factor ◽  
Strong Impact ◽  
Albedo Feedback

The Arctic is warming 2 to 3 times faster than the global average. Arctic sea ice cover is very sensitive to this warming and has reached historic minima in late summer in recent years (e.g., 2007 and 2012). Considering that the Arctic Ocean is mainly ice covered and that the albedo of sea ice is very high compared to that of open water, any change in sea ice cover will have a strong impact on the climate response through the radiative surface albedo feedback. Since sea ice area is projected to shrink considerably, this feedback will likely vary considerably in time. Feedbacks are usually evaluated as being constant in time, even though feedbacks and climate sensitivity depend on the climate state. Here the authors assess and quantify these temporal changes in the strength of the surface albedo feedback in response to global warming. Analyses unequivocally demonstrate that the strength of the surface albedo feedback exhibits considerable temporal variations. Specifically, the strength of the surface albedo feedback in the Arctic, evaluated for simulations of the future climate (CMIP5 RCP8.5) using a kernel method, shows a distinct peak around the year 2100. This maximum is found to be linked to increased seasonality in sea ice cover when sea ice recedes, in which sea ice retreat during spring turns out to be the dominant factor affecting the strength of the annual surface albedo feedback in the Arctic. Hence, changes in sea ice seasonality and the associated fluctuations in surface albedo feedback strength will exert a time-varying effect on Arctic amplification during the projected warming over the next century.

scholarly journals A Stochastic Dynamical Model of Arctic Sea Ice

2017 ◽  
Vol 30 (13) ◽  
pp. 5119-5140 ◽  
Author(s):  
Woosok Moon ◽  
J. S. Wettlaufer
Keyword(s):  
Sea Ice ◽  
Multiplicative Noise ◽  
Numerical Solutions ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Radiative Loss ◽  
Albedo Feedback ◽  
Wide Range ◽  
Arctic Sea

The noise forcing underlying the variability in the Arctic ice cover has a wide range of principally unknown origins. For this reason, the analytical and numerical solutions of a stochastic Arctic sea ice model are analyzed with both additive and multiplicative noise over a wide range of external heat fluxes Δ F0, corresponding to greenhouse gas forcing. The stochastic variability fundamentally influences the nature of the deterministic steady-state solutions corresponding to perennial and seasonal ice and ice-free states. Thus, the results are particularly relevant for the interpretation of the state of the system as the ice cover thins with Δ F0, allowing a thorough examination of the differing effects of additive versus multiplicative noise. In the perennial ice regime, the principal stochastic moments are calculated and compared to those determined from a stochastic perturbation theory described previously. As Δ F0 increases, the competing contributions to the variability of the destabilizing sea ice–albedo feedback and the stabilizing longwave radiative loss are examined in detail. At the end of summer the variability of the stochastic paths shows a clear maximum, which is due to the combination of the increasing influence of the albedo feedback and an associated “memory effect,” in which fluctuations accumulate from early spring to late summer. This is counterbalanced by the stabilization of the ice cover resulting from the longwave loss of energy from the ice surface, which is enhanced during winter, thereby focusing the stochastic paths and decreasing the variability. Finally, common examples in stochastic dynamics with multiplicative noise are discussed wherein the choice of the stochastic calculus (Itô or Stratonovich) is not necessarily determinable a priori from observations alone, which is why both calculi are treated on equal footing herein.

scholarly journals Regional variability in sea ice melt in a changing Arctic

2015 ◽  
Vol 373 (2045) ◽  
pp. 20140165 ◽  
Author(s):  
Donald K. Perovich ◽  
Jacqueline A. Richter-Menge
Keyword(s):  
Sea Ice ◽  
Temporal Trends ◽  
Beaufort Sea ◽  
Ice Cover ◽  
Temporal Variations ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Regional Variability ◽  
The Mean ◽  
Surface Melt

In recent years, the Arctic sea ice cover has undergone a precipitous decline in summer extent. The sea ice mass balance integrates heat and provides insight on atmospheric and oceanic forcing. The amount of surface melt and bottom melt that occurs during the summer melt season was measured at 41 sites over the time period 1957 to 2014. There are large regional and temporal variations in both surface and bottom melting. Combined surface and bottom melt ranged from 16 to 294 cm, with a mean of 101 cm. The mean ice equivalent surface melt was 48 cm and the mean bottom melt was 53 cm. On average, surface melting decreases moving northward from the Beaufort Sea towards the North Pole; however interannual differences in atmospheric forcing can overwhelm the influence of latitude. Substantial increases in bottom melting are a major contributor to ice losses in the Beaufort Sea, due to decreases in ice concentration. In the central Arctic, surface and bottom melting demonstrate interannual variability, but show no strong temporal trends from 2000 to 2014. This suggests that under current conditions, summer melting in the central Arctic is not large enough to completely remove the sea ice cover.

scholarly journals The Effect of Atmospheric Transmissivity on Model and Observational Estimates of the Sea Ice Albedo Feedback

2020 ◽  
Vol 33 (13) ◽  
pp. 5743-5765
Author(s):  
Aaron Donohoe ◽  
Ed Blanchard-Wrigglesworth ◽  
Axel Schweiger ◽  
Philip J. Rasch
Keyword(s):  
Sea Ice ◽  
Surface Albedo ◽  
Climate Models ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Surface Temperature Change ◽  
Feedback Parameter ◽  
Radiative Fluxes ◽  
Albedo Feedback ◽  
Concentration Changes

AbstractThe sea ice-albedo feedback (SIAF) is the product of the ice sensitivity (IS), that is, how much the surface albedo in sea ice regions changes as the planet warms, and the radiative sensitivity (RS), that is, how much the top-of-atmosphere radiation changes as the surface albedo changes. We demonstrate that the RS calculated from radiative kernels in climate models is reproduced from calculations using the “approximate partial radiative perturbation” method that uses the climatological radiative fluxes at the top of the atmosphere and the assumption that the atmosphere is isotropic to shortwave radiation. This method facilitates the comparison of RS from satellite-based estimates of climatological radiative fluxes with RS estimates across a full suite of coupled climate models and, thus, allows model evaluation of a quantity important in characterizing the climate impact of sea ice concentration changes. The satellite-based RS is within the model range of RS that differs by a factor of 2 across climate models in both the Arctic and Southern Ocean. Observed trends in Arctic sea ice are used to estimate IS, which, in conjunction with the satellite-based RS, yields an SIAF of 0.16 ± 0.04 W m−2 K−1. This Arctic SIAF estimate suggests a modest amplification of future global surface temperature change by approximately 14% relative to a climate system with no SIAF. We calculate the global albedo feedback in climate models using model-specific RS and IS and find a model mean feedback parameter of 0.37 W m−2 K−1, which is 40% larger than the IPCC AR5 estimate based on using RS calculated from radiative kernel calculations in a single climate model.

scholarly journals Retrieval of Snow Depth over Arctic Sea Ice Using a Deep Neural Network

2019 ◽  
Vol 11 (23) ◽  
pp. 2864 ◽  
Author(s):  
Jiping Liu ◽  
Yuanyuan Zhang ◽  
Xiao Cheng ◽  
Yongyun Hu
Keyword(s):  
Neural Network ◽  
Sea Ice ◽  
Snow Depth ◽  
Deep Neural Network ◽  
Arctic Basin ◽  
Temporal Variations ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Thickness ◽  
Arctic Sea

The accurate knowledge of spatial and temporal variations of snow depth over sea ice in the Arctic basin is important for understanding the Arctic energy budget and retrieving sea ice thickness from satellite altimetry. In this study, we develop and validate a new method for retrieving snow depth over Arctic sea ice from brightness temperatures at different frequencies measured by passive microwave radiometers. We construct an ensemble-based deep neural network and use snow depth measured by sea ice mass balance buoys to train the network. First, the accuracy of the retrieved snow depth is validated with observations. The results show the derived snow depth is in good agreement with the observations, in terms of correlation, bias, root mean square error, and probability distribution. Our ensemble-based deep neural network can be used to extend the snow depth retrieval from first-year sea ice (FYI) to multi-year sea ice (MYI), as well as during the melting period. Second, the consistency and discrepancy of snow depth in the Arctic basin between our retrieval using the ensemble-based deep neural network and two other available retrievals using the empirical regression are examined. The results suggest that our snow depth retrieval outperforms these data sets.

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.

scholarly journals Low-frequency bursts of horizontally polarized waves in the Arctic sea-ice cover

2011 ◽  
Vol 57 (202) ◽  
pp. 231-237 ◽  
Author(s):  
David Marsan ◽  
Jérôme Weiss ◽  
Jean-Philippe Métaxian ◽  
Jacques Grangeon ◽  
Pierre-François Roux ◽  
...  
Keyword(s):  
Sea Ice ◽  
Regional Scale ◽  
Low Frequency ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Strong Activity ◽  
Temporal Sampling ◽  
Polarized Waves ◽  
Arctic Sea

AbstractWe report the detection of bursts of low-frequency waves, typically f = 0.025 Hz, on horizontal channels of broadband seismometers deployed on the Arctic sea-ice cover during the DAMOCLES (Developing Arctic Modeling and Observing Capabilities for Long-term Environmental Studies) experiment in spring 2007. These bursts have amplitudes well above the ambient ice swell and a lower frequency content. Their typical duration is of the order of minutes. They occur at irregular times, with periods of relative quietness alternating with periods of strong activity. A significant correlation between the rate of burst occurrences and the ice-cover deformation at the ∼400 km scale centered on the seismic network suggests that these bursts are caused by remote, episodic deformation involving shearing across regional-scale leads. This observation opens the possibility of complementing satellite measurements of ice-cover deformation, by providing a much more precise temporal sampling, hence a better characterization of the processes involved during these deformation events.

scholarly journals Late-Twentieth-Century Simulation of Arctic Sea Ice and Ocean Properties in the CCSM4

2012 ◽  
Vol 25 (5) ◽  
pp. 1431-1452 ◽  
Author(s):  
Alexandra Jahn ◽  
Kara Sterling ◽  
Marika M. Holland ◽  
Jennifer E. Kay ◽  
James A. Maslanik ◽  
...  
Keyword(s):  
Twentieth Century ◽  
Sea Ice ◽  
Internal Variability ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Motion Field ◽  
Sea Ice Extent ◽  
Arctic Sea ◽  
Ensemble Mean

To establish how well the new Community Climate System Model, version 4 (CCSM4) simulates the properties of the Arctic sea ice and ocean, results from six CCSM4 twentieth-century ensemble simulations are compared here with the available data. It is found that the CCSM4 simulations capture most of the important climatological features of the Arctic sea ice and ocean state well, among them the sea ice thickness distribution, fraction of multiyear sea ice, and sea ice edge. The strongest bias exists in the simulated spring-to-fall sea ice motion field, the location of the Beaufort Gyre, and the temperature of the deep Arctic Ocean (below 250 m), which are caused by deficiencies in the simulation of the Arctic sea level pressure field and the lack of deep-water formation on the Arctic shelves. The observed decrease in the sea ice extent and the multiyear ice cover is well captured by the CCSM4. It is important to note, however, that the temporal evolution of the simulated Arctic sea ice cover over the satellite era is strongly influenced by internal variability. For example, while one ensemble member shows an even larger decrease in the sea ice extent over 1981–2005 than that observed, two ensemble members show no statistically significant trend over the same period. It is therefore important to compare the observed sea ice extent trend not just with the ensemble mean or a multimodel ensemble mean, but also with individual ensemble members, because of the strong imprint of internal variability on these relatively short trends.

scholarly journals Importance of open-water ice growth and ice concentration evolution: a study based on FESOM-ECHAM6

2015 ◽  
Vol 6 (2) ◽  
pp. 2137-2179
Author(s):  
X. Shi ◽  
G. Lohmann
Keyword(s):  
Sea Ice ◽  
Surface Albedo ◽  
Global Climate Model ◽  
Open Water ◽  
Arctic Sea Ice ◽  
Meridional Overturning Circulation ◽  
The Arctic ◽  
Water Ice ◽  
Ice Growth ◽  
Ice Concentration

Abstract. A newly developed global climate model FESOM-ECHAM6 with an unstructured mesh and high resolution is applied to investigate to what degree the area-thickness distribution of new ice formed in open water affects the ice and ocean properties. A sensitivity experiment is performed which reduces the horizontal-to-vertical aspect ratio of open-water ice growth. The resulting decrease in the Arctic winter sea-ice concentration strongly reduces the surface albedo, enhances the ocean heat release to the atmosphere, and increases the sea-ice production. Furthermore, our simulations show a positive feedback mechanism among the Arctic sea ice, the Atlantic Meridional Overturning Circulation (AMOC), and the surface air temperature in the Arctic, as the sea ice transport affects the freshwater budget in regions of deep water formation. A warming over Europe, Asia and North America, associated with a negative anomaly of Sea Level Pressure (SLP) over the Arctic (positive phase of the Arctic Oscillation (AO)), is also simulated by the model. For the Southern Ocean, the most pronounced change is a warming along the Antarctic Circumpolar Current (ACC), especially for the Pacific sector. Additionally, a series of sensitivity tests are performed using an idealized 1-D thermodynamic model to further investigate the influence of the open-water ice growth, which reveals similar results in terms of the change of sea ice and ocean temperature. In reality, the distribution of new ice on open water relies on many uncertain parameters, for example, surface albedo, wind speed and ocean currents. Knowledge of the detailed processes is currently too crude for those processes to be implemented realistically into models. Our sensitivity experiments indicate a pronounced uncertainty related to open-water sea ice growth which could significantly affect the climate system.

scholarly journals Recent advances in understanding the Arctic climate system state and change from a sea ice perspective: a review

2014 ◽  
Vol 14 (7) ◽  
pp. 10929-10999 ◽  
Author(s):  
R. Döscher ◽  
T. Vihma ◽  
E. Maksimovich
Keyword(s):  
Global Warming ◽  
Sea Ice ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
Climate System ◽  
Arctic Climate ◽  
The Arctic ◽  
Atlantic Sector ◽  
Sea Ice Decline ◽  
Arctic Sea

Abstract. The Arctic sea ice is the central and essential component of the Arctic climate system. The depletion and areal decline of the Arctic sea ice cover, observed since the 1970's, have accelerated after the millennium shift. While a relationship to global warming is evident and is underpinned statistically, the mechanisms connected to the sea ice reduction are to be explored in detail. Sea ice erodes both from the top and from the bottom. Atmosphere, sea ice and ocean processes interact in non-linear ways on various scales. Feedback mechanisms lead to an Arctic amplification of the global warming system. The amplification is both supported by the ice depletion and is at the same time accelerating the ice reduction. Knowledge of the mechanisms connected to the sea ice decline has grown during the 1990's and has deepened when the acceleration became clear in the early 2000's. Record summer sea ice extents in 2002, 2005, 2007 and 2012 provided additional information on the mechanisms. This article reviews recent progress in understanding of the sea ice decline. Processes are revisited from an atmospheric, ocean and sea ice perspective. There is strong evidence for decisive atmospheric changes being the major driver of sea ice change. Feedbacks due to reduced ice concentration, surface albedo and thickness allow for additional local atmosphere and ocean influences and self-supporting feedbacks. Large scale ocean influences on the Arctic Ocean hydrology and circulation are highly evident. Northward heat fluxes in the ocean are clearly impacting the ice margins, especially in the Atlantic sector of the Arctic. Only little indication exists for a direct decisive influence of the warming ocean on the overall sea ice cover, due to an isolating layer of cold and fresh water underneath the sea ice.

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