Arctic sea ice extent has declined continuously for the past decade, owing partially to light absorption by black carbon (BC) and other impurities deposited on snow and the underlying pack. We present simulations for the contemporary period showing that the optical depth contributed by Arctic ice algal chlorophyll may be comparable during Boreal Spring to the corresponding values attributable to BC. The largest chlorophyll attenuation is obtained in the bottom layer, which supports pigment concentrations of about 300 to 1000 mg/m3 in the Bering Sea and Sea of Okhotsk. However, chlorophyll concentrations for the ice interior in regions north of 75° N and across the Canadian Archipelago are less than 0.1 micro g/m3. Freeboard and infiltration communities lead to intermediate levels of light removal. Since BC works its way downward from the atmospheric interface, there will be regions where it appropriates photosynthetic capability. Where ice thicknesses permit significant penetration through the pack column the ice algae may be crucial absorbers. We propose a continuous increase in relative chlorophyll activity and attenuation in the future, as biological activity becomes stronger in thin ice toward the center of the Arctic basin. A shift in relative importance of the two absorber types could occur as total BC mixing ratios are reduced because of environmental advocacy.
The sea-ice cover of the Arctic Ocean is an important element of the climate and ocean system in the Northern Hemisphere as it impacts albedo, atmospheric pressure regimes, CO2-exchange at the ocean/atmosphere interface as well as the North Atlantic freshwater budget and thermohaline circulation [1]. Due to global warming, the Arctic sea-ice cover is presently evolving at an unprecedent rate towards full melt during the summer season, driving the so-called "Arctic amplification" [2]. However, the Arctic sea-ice has also experienced large amplitude variations, from seasonal to orbital (Milankov…
Several environmental tipping points and self-reinforcing feedback loops are still disregarded within the frequently used climate models. Thus, existing climate models are not very representative for providing projections of the conditions after the actual environmental tipping points are triggered. In this contribution, we discuss the presence of the Arctic sea-ice loss tipping point and its influence on global warming. Our literature search and PIOMAS sea volume observation data based projection indicate the significant acceleration of the sea-ice loss (which leads to a year around and perma…
Arctic sea ice concentration is often coarsely observed and numerically computed despite its importance for polar climate system. In this work we present three machine-learning methods to recover the original high-resolution images from the coarse-grained low-resolution counterparts. The promising results indicate a possibility of extending the application to a broad range of geophysical variables.
The downward trend in Arctic sea ice extent is one of the most dramatic signals of climate change during recent decades. Comprehensive climate models have struggled to reproduce this, typically simulating a slower rate of sea ice retreat than has been observed. However, this bias has been widely noted to have decreased in models participating in the most recent phase of the Coupled Model Intercomparison Project (CMIP5) compared with the previous generation of models (CMIP3). Here we examine simulations from both CMIP3 and CMIP5. We find that simulated historical sea ice trends are influenced b…
The extent to which the ongoing decline in Arctic sea ice affects mid-latitude climate has received great attention and polarised opinions. The basic issue is whether the inter-annual variability in Arctic sea ice is the cause of, or the response to, variability in mid-latitude atmospheric circulation. A recent paper by Mori et al. (M19) claims to have reconciled previous conflicting studies by showing that a consistent mid-latitude climate response to inter-annual sea-ice anomalies can be identified in both the ERA-Interim reanalysis, taken as observations, and in an ensemble of atmosphere-on…
Sea ice motions play an important role in the polar climate system by transporting pollutants, heat, water and salt as well as changing the ice cover. Numerous physics-based models have been constructed to represent the sea ice dynamical interaction with the atmosphere and ocean. In this study, we propose a new data-driven deep-learning approach that utilizes a convolutional neural network (CNN) to model how Arctic sea ice moves in response to surface winds given its initial ice velocity and concentration a day earlier. Results show that CNN computes the sea ice response with a correlation of …
We study the response of the Lagrangian sea ice model neXtSIM to the uncertainty in the sea surface wind and sea ice cohesion. The ice mechanics in neXtSIM is based on a brittle-like rheological framework. The study considers short-term ensemble forecasts of the Arctic sea ice from January to April 2008. Ensembles are generated by perturbing the wind inputs and ice cohesion field both separately and jointly. The resulting uncertainty in the probabilistic forecasts is evaluated statistically based on the analysis of Lagrangian sea ice trajectories as sampled by virtual drifters seeded in the mo…
Here we evaluate the sea ice, surface air temperature, and sea-level-pressure from 31 of the models used in the Coupled Model Intercomparison Project Phase 6 (CMIP6) for their biases, trends, and variability, and compare them to the CMIP5 ensemble and the ERA5 reanalysis for the period 1979 to 2004. The principal purpose of this assessment is to provide an overview of the ability of the CMIP6 ensemble to represent the Arctic climate, and to see how this has changed since the last Phase of CMIP. Overall, we find a distinct improvement in the representation of the sea ice volume, but also in the…
A mechanism connecting ice algal ecodynamics with the buildup of organic macromolecules in brine channels is tested offline in a reduced model of pack geochemistry. Driver physical quantities are extracted from the global sea ice dynamics code CICE, including snow height, column thickness and internal temperature. The variables are averaged at the regional scale over ten Arctic biogeographic zones and treated as input matrices at four vertical habitat levels. Nutrient-light-salt limited ice algal growth is computed along with the associated grazing plus mortality. Vertical transport is diffusi…
This paper presents the first estimate of the seasonal cycle of ocean and sea ice net heat and freshwater (FW) fluxes around the boundary of the Arctic Ocean. The ocean transports are estimated primarily using 138 moored instruments deployed in September 2005 to August 2006 across the four main Arctic gateways: Davis, Fram and Bering Straits, and the Barents Sea Opening (BSO). Sea ice transports are estimated from a sea ice assimilation product. Monthly velocity fields are calculated with a box inverse model that enforces volume and salinity conservation. The resulting net ocean and sea ice he…
Predicting Arctic sea ice extent is a notoriously difficult forecasting problem, even for lead times as short as one month. Motivated by Arctic intraannual variability phenomena such as reemergence of sea surface temperature and sea ice anomalies, we use a prediction approach for sea ice anomalies based on analog forecasting. Traditional analog forecasting relies on identifying a single analog in a historical record, usually by minimizing Euclidean distance, and forming a forecast from the analog's historical trajectory. Here an ensemble of analogs are used to make forecasts, where the ensembl…
We study the seasonal changes in the thickness distribution of Arctic sea ice, $g(h)$, under climate forcing. Our analytical and numerical approach is based on a Fokker-Planck equation for $g(h)$ (Toppaladoddi \& Wettlaufer \emph{Phys. Rev. Lett.} {\bf 115}, 148501, 2015), in which the thermodynamic growth rates are determined using observed climatology. In particular, the Fokker-Planck equation is coupled to the observationally consistent thermodynamic model of Eisenman \& Wettlaufer (\emph{Proc. Natl. Acad. Sci. USA} {\bf 106}, pp. 28-32, 2009). We find that due to the combined effects of th…
We analyze the numerical solutions of a stochastic Arctic sea ice model with constant additive noise over a wide range of external heat-fluxes, $ΔF_0$, which correspond to greenhouse gas forcing. The variability that the stochasticity provides to the deterministic steady state solutions (perennial and seasonal ice states) is illustrated by examining both the stochastic paths and probability density functions (PDFs). The principal stochastic moments (standard deviation, mean and skewness) are calculated and compared with those determined from a stochastic perturbation theory described previousl…
Abrupt and irreversible winter Arctic sea-ice loss may occur under anthropogenic warming due to the collapse of a sea-ice equilibrium at a threshold value of CO$_2$, commonly referred to as a tipping point. Previous work has been unable to conclusively identify whether a tipping point in Arctic sea ice exists because fully-coupled climate models are too computationally expensive to run to equilibrium for many CO$_2$ values. Here, we explore the deviation of sea ice from its equilibrium state under realistic rates of CO$_2$ increase to demonstrate how a few time-dependent CO$_2$ experiments can…
In light of the rapid recent retreat of Arctic sea ice, the extreme weather events triggering the variability in Arctic ice cover has drawn increasing attention. A non-Gaussian $α$-stable Lévy process is thought to be an appropriate model to describe such extreme event. The maximal likely trajectory, based on the nonlocal Fokker-Planck equation, is applied to a nonautonomous Arctic sea ice system under $α$-stable Lévy noise. Two types of tipping times, the early-warning tipping time and the disaster-happening tipping time, are used to predict the critical time for the maximal likely transition…
Observations indicate that the Arctic sea ice cover is rapidly retreating while the Antarctic sea ice cover is steadily expanding. State-of-the-art climate models, by contrast, typically simulate a moderate decrease in both the Arctic and Antarctic sea ice covers. However, in each hemisphere there is a small subset of model simulations that have sea ice trends similar to the observations. Based on this, a number of recent studies have suggested that the models are consistent with the observations in each hemisphere when simulated internal climate variability is taken into account. Here we exam…
The importance of snow cover and ice extent in the Northern Hemisphere was recognized by various authors leading to a positive feedback of surface reflectivity on climate. In fact, the retreat of Arctic sea ice is accompanied by enhanced solar input in the Arctic region, i.e. a decrease of the terrestrial albedo. We have studied this effect for the past six decades and estimate the corresponding global warming in the northern hemisphere. A simple 1-dimensional model is used that includes the simultaneous increase of the greenhouse gases. Our results indicate that the latter directly cause a te…
The stochastic Arctic sea ice model described as a single periodic non-autonomous stochastic ordinary differential equation (ODE) is useful in explaining the seasonal variability of Arctic sea ice. However, to be nearer to realistic approximations we consider the inclusion of long-term forcing implying the effect of slowly-varying ocean or atmospheric low-frequencies. In this research, we rely on the equivalent Fokker-Planck equation instead of the stochastic ODE owing to the advantages of the Fokker-Planck equation in dealing with higher moments calculations. We include simple long-term forci…
We analyze the numerical solutions of a stochastic Arctic sea ice model with multiplicative noise over a wide range of external heat-fluxes, $ΔF_0$, which correspond to greenhouse gas forcing. When the noise is multiplicative, the noise-magnitude depends on the state-variable, and this will influence the statistical moments in a manner that differs from the additive case, which we analyzed in Part I of this study. The state variable describing the deterministic backbone of our model is the energy, $E(t)$, contained in the ice or the ocean and for a thorough comparison and contrast we choose th…
Wintertime Cross-correlational Structures between Sea Surface Temperature Anomaly and Atmospheric-and-Oceanic Fields in the East/Japan Sea Under Arctic Oscillation
Perhaps the most iconic feature of melting Arctic sea ice is the formation of distinctive, complex ponds on its surface during late spring. The evolution of melt ponds and their geometrical characteristics determines the albedo of sea ice, a key parameter in climate modeling. However, a theoretical understanding of this evolution, and predictions of geometrical features, have remained elusive. To address this fundamental problem in polar climate science, here we introduce a two dimensional random field Ising model for melt ponds. The ponds are identified as metastable states of the system, whe…
Understanding how sea ice melts is critical to climate projections. In the Arctic, melt ponds that develop on the surface of sea ice floes during the late spring and summer largely determine their albedo -- a key parameter in climate modeling. Here we explore the possibility of a conceptual sea ice climate model passing through a bifurcation point -- an irreversible critical threshold as the system warms, by incorporating geometric information about melt pond evolution. This study is based on a bifurcation analysis of the energy balance climate model with ice - albedo feedback as the key mecha…
The Arctic sea ice represents an important energy reservoir for the climate of the northern hemisphere. The shrinking of the polar ice in the past decades decreases the stored energy and raises serious concerns about future climate changes.[1-4] Model calculations of the present authors [5,6] suggest that half of the global warming during the past fifty years is directly related to the retreat of the sea ice, while the cause is not well understood, e.g. the role of surface pollution [7-10]. We have analysed the reported annual melting and freezing data of the northern sea ice in the years 1979…
As Arctic sea ice extent decreases with increasing greenhouse gases, there is a growing interest in whether there could be a bifurcation associated with its loss, and whether there is significant hysteresis associated with that bifurcation. A challenge in answering this question is that the bifurcation behavior of certain Arctic energy balance models have been shown to be sensitive to how ice-albedo feedback is parameterized. We analyze an Arctic energy balance model in the limit as a smoothing parameter associated with ice-albedo feedback tends to zero, which introduces a discontinuity bounda…
Climate change, amplified in the far north, has led to rapid sea ice decline in recent years. In the summer, melt ponds form on the surface of Arctic sea ice, significantly lowering the ice reflectivity (albedo) and thereby accelerating ice melt. Pond geometry controls the details of this crucial feedback; however, a reliable model of pond geometry does not currently exist. Here we show that a simple model of voids surrounding randomly sized and placed overlapping circles reproduces the essential features of pond patterns. The only two model parameters, characteristic circle radius and coverag…
The Arctic has warmed dramatically compared to the global average over the last few decades. During this same period, there have been strong cooling trends observed in the wintertime, near-surface air temperature over central Eurasia, a phenomenon known as Eurasian cooling. Many studies have suggested that the loss of sea ice, especially in the Barents and Kara Seas, is related to the cooling over Eurasia, although this connection and its possible mechanism is still a source of heated debate. Observations and reanalyses show a clear pattern of co-variability between Arctic sea ice and Eurasian…
Increased economic activity and research interest in the Arctic raise the need for better wave forecasts in the marginal ice zone (MIZ). Mathematical and numerical models of wave propagation in sea ice would benefit from more in situ data for validation. This study presents shipborne wave measurements from the MIZ where altimeter readings are corrected for ship motion to obtain estimated single point ocean surface elevation. From the combined measurements, we obtain significant wave height and zero up-crossing period, as well as one-dimensional wave spectra. In addition, we provide spectra and…
Black Carbon scavenging in liquid Arctic clouds: the role of size and mixing state
PSI Center for Energy and Environmental Sciences（瑞士保罗谢勒研究所能源与环境科学中心）；Asterisk Labs（星号实验室）；Department of Environmental Science, Stockholm University（斯德哥尔摩大学环境科学系）；Bolin Centre for Climate Research, Stockholm University（斯德哥尔摩大学博林气候研究中心）；STEP Srl（STEP有限公司）
As atmospheric models move to higher resolution and resolve smaller scales, the maximum modeled wind speed also tends to increase. Wave models tuned to coarser wind fields tend to overestimate the wave growth under strong winds. A recently developed semi-empirical parameterization of the Charnock parameter, which controls the roughness length over surface waves, substantially reduces the aerodynamic drag of waves in high winds (above a threshold of 30 m/s). Here we apply the formulation in a recent version of the wave model WAM (Cycle 4.7), which uses a modified version of the physics paramete…
It has been widely debated whether Arctic sea-ice loss can reach a tipping point beyond which a large sea-ice area disappears abruptly. The theory of dynamical systems predicts a slowing down when a system destabilises towards a tipping point. In simple stochastic systems this can result in increasing variance and autocorrelation, potentially yielding an early warning of an abrupt change. Here we aim to establish whether the loss of Arctic sea ice would follow these conceptual predictions, and which trends in sea ice variability can be expected from pre-industrial conditions toward an Arctic t…
Arctic teleconnection on climate and ozone pollution in the polar jet stream path of eastern US
The University of Sydney（悉尼大学）；Chennai Mathematical Institute（马德拉斯数学研究所）；AI 4 Water LTD（AI 4 Water有限公司）；Institute for Interdisciplinary Research（跨学科研究所）；School of Computational and Integrative Sciences, Jawaharlal Nehru University（贾瓦哈拉尔·尼赫鲁大学计算与综合科学学院）
In an effort to understand the dynamics of the Arctic sea-ice edge, we present a simple model of heat and mass transfer in the Fram Strait that reveals some fundamental mechanisms controlling sea-ice extent in the marginal seas and the depth and properties of the Arctic mixed layer. We identify and study key mechanisms relating to the sea-ice wedge described by Untersteiner, a boundary-layer structure near the ice edge, demonstrating how ice thickness and extent depend on ice-export rates, atmospheric forcing and the properties of incoming warm and salty Atlantic water in the West Spitsbergen …
The fluctuation statistics of the observed sea ice extent during the satellite era are compared with model output from CMIP5 models using a multi-fractal time series method. The two robust features of the observations are that on annual to bi-annual time scales the ice extent exhibits white noise structure and there is a decadal scale trend associated with the decay of the ice cover. It is shown that (i) there is a large inter-model variability in the time scales extracted from the models, (ii) none of the models exhibit the decadal time scales found in the satellite observations, (iii) {5} of…
Our ability to predict the future of Arctic sea ice is limited by ice's sensitivity to detailed surface conditions such as the distribution of snow and melt ponds. Snow on top of the ice decreases ice's thermal conductivity, increases its reflectivity (albedo), and provides a source of meltwater for melt ponds during summer that decrease the ice's albedo. In this paper, we develop a simple model of pre-melt snow topography that accurately describes snow cover of flat, undeformed Arctic sea ice on several study sites for which data was available. The model considers a surface that is a sum of r…
Research and experimental verification on low-frequency long-range sound propagation characteristics under ice-covered and range-dependent marine environment in the Arctic
Institute of Oceanography, Ministry of Natural Resources（自然资源部海洋研究所）；Institute of Acoustics, Chinese Academy of Sciences（中国科学院声学研究所）
High-resolution regional hindcasting of ocean and sea ice plays an important role in the assessment of shipping and operational risks in the Arctic Ocean. The ice-ocean model NEMO-LIM3 was modified to improve its simulation quality for appropriate spatio-temporal resolutions. A multigrid model setup with connected coarse- (14 km) and fine-resolution (5 km) model configurations was devised. These two configurations were implemented and run separately. The resulting computational cost was lower when compared to that of the built-in AGRIF nesting system. Ice and tracer boundary-condition schemes …
