WorldWideScience

Sample records for modeling sea ice

  1. Modelling sea ice dynamics

    Science.gov (United States)

    Murawski, Jens; Kleine, Eckhard

    2017-04-01

    Sea ice remains one of the frontiers of ocean modelling and is of vital importance for the correct forecasts of the northern oceans. At large scale, it is commonly considered a continuous medium whose dynamics is modelled in terms of continuum mechanics. Its specifics are a matter of constitutive behaviour which may be characterised as rigid-plastic. The new developed sea ice dynamic module bases on general principles and follows a systematic approach to the problem. Both drift field and stress field are modelled by a variational property. Rigidity is treated by Lagrangian relaxation. Thus one is led to a sensible numerical method. Modelling fast ice remains to be a challenge. It is understood that ridging and the formation of grounded ice keels plays a role in the process. The ice dynamic model includes a parameterisation of the stress associated with grounded ice keels. Shear against the grounded bottom contact might lead to plastic deformation and the loss of integrity. The numerical scheme involves a potentially large system of linear equations which is solved by pre-conditioned iteration. The entire algorithm consists of several components which result from decomposing the problem. The algorithm has been implemented and tested in practice.

  2. Multiscale Models of Melting Arctic Sea Ice

    Science.gov (United States)

    2014-09-30

    1 Multiscale Models of Melting Arctic Sea Ice Kenneth M. Golden University of Utah, Department of Mathematics phone: (801) 581-6851...feedback has played a major role in the recent declines of the summer Arctic sea ice pack. However, understanding the evolution of melt ponds and sea...Models of Melting Arctic Sea Ice 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER

  3. CICE, The Los Alamos Sea Ice Model

    Energy Technology Data Exchange (ETDEWEB)

    2017-05-12

    The Los Alamos sea ice model (CICE) is the result of an effort to develop a computationally efficient sea ice component for a fully coupled atmosphere–land–ocean–ice global climate model. It was originally designed to be compatible with the Parallel Ocean Program (POP), an ocean circulation model developed at Los Alamos National Laboratory for use on massively parallel computers. CICE has several interacting components: a vertical thermodynamic model that computes local growth rates of snow and ice due to vertical conductive, radiative and turbulent fluxes, along with snowfall; an elastic-viscous-plastic model of ice dynamics, which predicts the velocity field of the ice pack based on a model of the material strength of the ice; an incremental remapping transport model that describes horizontal advection of the areal concentration, ice and snow volume and other state variables; and a ridging parameterization that transfers ice among thickness categories based on energetic balances and rates of strain. It also includes a biogeochemical model that describes evolution of the ice ecosystem. The CICE sea ice model is used for climate research as one component of complex global earth system models that include atmosphere, land, ocean and biogeochemistry components. It is also used for operational sea ice forecasting in the polar regions and in numerical weather prediction models.

  4. Sea ice biogeochemistry: a guide for modellers.

    Directory of Open Access Journals (Sweden)

    Letizia Tedesco

    Full Text Available Sea ice is a fundamental component of the climate system and plays a key role in polar trophic food webs. Nonetheless sea ice biogeochemical dynamics at large temporal and spatial scales are still rarely described. Numerical models may potentially contribute integrating among sparse observations, but available models of sea ice biogeochemistry are still scarce, whether their relevance for properly describing the current and future state of the polar oceans has been recently addressed. A general methodology to develop a sea ice biogeochemical model is presented, deriving it from an existing validated model application by extension of generic pelagic biogeochemistry model parameterizations. The described methodology is flexible and considers different levels of ecosystem complexity and vertical representation, while adopting a strategy of coupling that ensures mass conservation. We show how to apply this methodology step by step by building an intermediate complexity model from a published realistic application and applying it to analyze theoretically a typical season of first-year sea ice in the Arctic, the one currently needing the most urgent understanding. The aim is to (1 introduce sea ice biogeochemistry and address its relevance to ocean modelers of polar regions, supporting them in adding a new sea ice component to their modelling framework for a more adequate representation of the sea ice-covered ocean ecosystem as a whole, and (2 extend our knowledge on the relevant controlling factors of sea ice algal production, showing that beyond the light and nutrient availability, the duration of the sea ice season may play a key-role shaping the algal production during the on going and upcoming projected changes.

  5. Sea Ice Biogeochemistry: A Guide for Modellers

    Science.gov (United States)

    Tedesco, Letizia; Vichi, Marcello

    2014-01-01

    Sea ice is a fundamental component of the climate system and plays a key role in polar trophic food webs. Nonetheless sea ice biogeochemical dynamics at large temporal and spatial scales are still rarely described. Numerical models may potentially contribute integrating among sparse observations, but available models of sea ice biogeochemistry are still scarce, whether their relevance for properly describing the current and future state of the polar oceans has been recently addressed. A general methodology to develop a sea ice biogeochemical model is presented, deriving it from an existing validated model application by extension of generic pelagic biogeochemistry model parameterizations. The described methodology is flexible and considers different levels of ecosystem complexity and vertical representation, while adopting a strategy of coupling that ensures mass conservation. We show how to apply this methodology step by step by building an intermediate complexity model from a published realistic application and applying it to analyze theoretically a typical season of first-year sea ice in the Arctic, the one currently needing the most urgent understanding. The aim is to (1) introduce sea ice biogeochemistry and address its relevance to ocean modelers of polar regions, supporting them in adding a new sea ice component to their modelling framework for a more adequate representation of the sea ice-covered ocean ecosystem as a whole, and (2) extend our knowledge on the relevant controlling factors of sea ice algal production, showing that beyond the light and nutrient availability, the duration of the sea ice season may play a key-role shaping the algal production during the on going and upcoming projected changes. PMID:24586604

  6. Sea ice biogeochemistry: a guide for modellers.

    Science.gov (United States)

    Tedesco, Letizia; Vichi, Marcello

    2014-01-01

    Sea ice is a fundamental component of the climate system and plays a key role in polar trophic food webs. Nonetheless sea ice biogeochemical dynamics at large temporal and spatial scales are still rarely described. Numerical models may potentially contribute integrating among sparse observations, but available models of sea ice biogeochemistry are still scarce, whether their relevance for properly describing the current and future state of the polar oceans has been recently addressed. A general methodology to develop a sea ice biogeochemical model is presented, deriving it from an existing validated model application by extension of generic pelagic biogeochemistry model parameterizations. The described methodology is flexible and considers different levels of ecosystem complexity and vertical representation, while adopting a strategy of coupling that ensures mass conservation. We show how to apply this methodology step by step by building an intermediate complexity model from a published realistic application and applying it to analyze theoretically a typical season of first-year sea ice in the Arctic, the one currently needing the most urgent understanding. The aim is to (1) introduce sea ice biogeochemistry and address its relevance to ocean modelers of polar regions, supporting them in adding a new sea ice component to their modelling framework for a more adequate representation of the sea ice-covered ocean ecosystem as a whole, and (2) extend our knowledge on the relevant controlling factors of sea ice algal production, showing that beyond the light and nutrient availability, the duration of the sea ice season may play a key-role shaping the algal production during the on going and upcoming projected changes.

  7. A toy model of sea ice growth

    Science.gov (United States)

    Thorndike, Alan S.

    1992-01-01

    My purpose here is to present a simplified treatment of the growth of sea ice. By ignoring many details, it is possible to obtain several results that help to clarify the ways in which the sea ice cover will respond to climate change. Three models are discussed. The first deals with the growth of sea ice during the cold season. The second describes the cycle of growth and melting for perennial ice. The third model extends the second to account for the possibility that the ice melts away entirely in the summer. In each case, the objective is to understand what physical processes are most important, what ice properties determine the ice behavior, and to which climate variables the system is most sensitive.

  8. Stress and deformation characteristics of sea ice in a high resolution numerical sea ice model.

    Science.gov (United States)

    Heorton, Harry; Feltham, Daniel; Tsamados, Michel

    2017-04-01

    The drift and deformation of sea ice floating on the polar oceans is due to the applied wind and ocean currents. The deformations of sea ice over ocean basin length scales have observable patterns; cracks and leads in satellite images and within the velocity fields generated from floe tracking. In a climate sea ice model the deformation of sea ice over ocean basin length scales is modelled using a rheology that represents the relationship between stresses and deformation within the sea ice cover. Here we investigate the link between observable deformation characteristics and the underlying internal sea ice stresses and force balance using the Los Alamos numerical sea ice climate model. In order to mimic laboratory experiments on the deformation of small cubes of sea ice we have developed an idealised square domain that tests the model response at spatial resolutions of up to 500m. We use the Elastic Anisotropic Plastic and Elastic Viscous Plastic rheologies, comparing their stability over varying resolutions and time scales. Sea ice within the domain is forced by idealised winds in order to compare the confinement of wind stresses and internal sea ice stresses. We document the characteristic deformation patterns of convergent, divergent and rotating stress states.

  9. Grease ice in basin-scale sea-ice ocean models

    OpenAIRE

    Lars H. Smedsrud; Martin, Torge

    2015-01-01

    The first stage of sea-ice formation is often grease ice, a mixture of sea water and frazil ice crystals. Over time, grease ice typically congeals first to pancake ice floes and then to a solid sea-ice cover. Grease ice is commonly not explicitly simulated in basin-scale sea-ice ocean models, though it affects oceanic heat loss and ice growth and is expected to play a greater role in a more seasonally icecovered Arctic Ocean. We present an approach to simulate the grease-ice layer with, as ba...

  10. A sea ice model for the marginal ice zone with an application to the Greenland Sea

    DEFF Research Database (Denmark)

    Pedersen, Leif Toudal; Coon, Max D.

    2004-01-01

    A model is presented that describes the formation, transport, and desalinization of frazil and pancake ice as it is formed in marginal seas. This model uses as input the total ice concentration evaluated from Special Sensor Microwave Imager and wind speed and direction. The model calculates...... the areal concentration, thickness, volume concentration, and salinity of frazil ice as well as the areal concentration, thickness, and salinity of pancakes. A simple parameterization for the Odden region of the Greenland Sea is presented. The model is run for the winter of 1996-1997. There are direct...... observations of the thickness and salinity of pancakes and the volume concentration of frazil ice to compare with the model. The model results compare very well with the measured data. This new ice model can be tuned to work in marginal seas elsewhere to calculate ice thickness, motion, and brine rejection...

  11. High resolution modelling of the decreasing Arctic sea ice

    DEFF Research Database (Denmark)

    Madsen, K. S.; Rasmussen, T. A. S.; Blüthgen, Jonas

    2012-01-01

    , and secondly oceanic oil drift in ice affected conditions. Both investigations are made with the coupled ocean - sea ice model HYCOM-CICE at 10 km resolution, which is also used operationally at DMI and allows detailed studies of sea ice build-up, drift and melt. To investigate the sea ice decrease of the last......The Arctic sea ice cover has been rapidly decreasing and thinning over the last decade, with minimum ice extent in 2007 and almost as low extent in 2011. This study investigates two aspects of the decreasing ice cover; first the large scale thinning and changing dynamics of the polar sea ice...... decade, we have performed a reanalysis simulation of the years 1990-2011, forced with ERA Interim atmospheric data. Thus, the simulation includes both the period before the recent sea ice decrease and the full period of decrease up till today. We will present our model results of the thinning...

  12. High resolution modelling of the decreasing Arctic sea ice

    DEFF Research Database (Denmark)

    Madsen, K. S.; Rasmussen, T. A. S.; Blüthgen, Jonas

    2012-01-01

    The Arctic sea ice cover has been rapidly decreasing and thinning over the last decade, with minimum ice extent in 2007 and almost as low extent in 2011. This study investigates two aspects of the decreasing ice cover; first the large scale thinning and changing dynamics of the polar sea ice......, and secondly oceanic oil drift in ice affected conditions. Both investigations are made with the coupled ocean - sea ice model HYCOM-CICE at 10 km resolution, which is also used operationally at DMI and allows detailed studies of sea ice build-up, drift and melt. To investigate the sea ice decrease of the last...... and changing dynamics and discuss how they relate to satellite observations. The relation to the upper ocean heat content is also investigated. The decreasing sea ice has opened up for increased ship traffic and oil exploration in the polar oceans. To avoid damage on the pristine Arctic ecosystem...

  13. Model resolution influence on simulated sea ice decline

    Directory of Open Access Journals (Sweden)

    J. O. Sewall

    2008-10-01

    Full Text Available Satellite observations and model predictions of recent and future Arctic sea ice decline have raised concerns over the timing and potential impacts of a seasonally ice-free Arctic Ocean. Model predictions of seasonally ice-free Arctic conditions are, however, highly variable. Here I present results from fourteen climate system models from the World Climate Research Programme's (WCRP's Coupled Model Intercomparison Project phase 3 (CMIP3 multi-model dataset that indicate modeled Arctic sea ice sensitivity to increased atmospheric CO2 forcing is strongly correlated with ice/ocean model horizontal resolution. Based on coupled model analyses and ice only simulations with the Los Alamos National Lab sea ice model (CICE, the correlation between declining Arctic sea ice cover and ice/ocean model resolution appears to depend largely on ocean model resolution and its influence on ocean heat transport into the Arctic basin. The correlation between model resolution, northward ocean heat transport, and the degree of Arctic ice loss is independent of ice model physics and complexity. This not only illustrates one difficulty in using numerical models to accurately predict the timing and magnitude of Arctic sea ice decline under increasing atmospheric greenhouse gas forcing, but also highlights one area where improved simulation (of northward ocean heat transport could greatly decrease the uncertainties associated with predictions of future Arctic sea ice cover.

  14. A network model for electrical transport in sea ice

    Energy Technology Data Exchange (ETDEWEB)

    Zhu, J., E-mail: zhu@math.utah.ed [University of Utah, Department of Mathematics, 155 S 1400 E RM 233, Salt Lake City, UT 84112-0090 (United States); Golden, K.M., E-mail: golden@math.utah.ed [University of Utah, Department of Mathematics, 155 S 1400 E RM 233, Salt Lake City, UT 84112-0090 (United States); Gully, A., E-mail: gully@math.utah.ed [University of Utah, Department of Mathematics, 155 S 1400 E RM 233, Salt Lake City, UT 84112-0090 (United States); Sampson, C., E-mail: christian.sampson@gmail.co [University of Utah, Department of Mathematics, 155 S 1400 E RM 233, Salt Lake City, UT 84112-0090 (United States)

    2010-07-15

    Monitoring the thickness of sea ice is an important tool in assessing the impact of global warming on Earth's polar regions, and most methods of measuring ice thickness depend on detailed knowledge of its electrical properties. We develop a network model for the electrical conductivity of sea ice, which incorporates statistical measurements of the brine microstructure. The numerical simulations are in close agreement with direct measurements we made in Antarctica on the vertical conductivity of first year sea ice.

  15. Reducing uncertainty in high-resolution sea ice models.

    Energy Technology Data Exchange (ETDEWEB)

    Peterson, Kara J.; Bochev, Pavel Blagoveston

    2013-07-01

    Arctic sea ice is an important component of the global climate system, reflecting a significant amount of solar radiation, insulating the ocean from the atmosphere and influencing ocean circulation by modifying the salinity of the upper ocean. The thickness and extent of Arctic sea ice have shown a significant decline in recent decades with implications for global climate as well as regional geopolitics. Increasing interest in exploration as well as climate feedback effects make predictive mathematical modeling of sea ice a task of tremendous practical import. Satellite data obtained over the last few decades have provided a wealth of information on sea ice motion and deformation. The data clearly show that ice deformation is focused along narrow linear features and this type of deformation is not well-represented in existing models. To improve sea ice dynamics we have incorporated an anisotropic rheology into the Los Alamos National Laboratory global sea ice model, CICE. Sensitivity analyses were performed using the Design Analysis Kit for Optimization and Terascale Applications (DAKOTA) to determine the impact of material parameters on sea ice response functions. Two material strength parameters that exhibited the most significant impact on responses were further analyzed to evaluate their influence on quantitative comparisons between model output and data. The sensitivity analysis along with ten year model runs indicate that while the anisotropic rheology provides some benefit in velocity predictions, additional improvements are required to make this material model a viable alternative for global sea ice simulations.

  16. Land-ice modeling for sea-level prediction

    Energy Technology Data Exchange (ETDEWEB)

    Lipscomb, William H [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2010-06-11

    There has been major progress in ice sheet modeling since IPCC AR4. We will soon have efficient higherorder ice sheet models that can run at ",1 km resolution for entire ice sheets, either standalone or coupled to GeMs. These models should significantly reduce uncertainties in sea-level predictions. However, the least certain and potentially greatest contributions to 21st century sea-level rise may come from ice-ocean interactions, especially in West Antarctica. This is a coupled modeling problem that requires collaboration among ice, ocean and atmosphere modelers.

  17. Analysis of Sea Ice Cover Sensitivity in Global Climate Model

    Directory of Open Access Journals (Sweden)

    V. P. Parhomenko

    2014-01-01

    Full Text Available The paper presents joint calculations using a 3D atmospheric general circulation model, an ocean model, and a sea ice evolution model. The purpose of the work is to analyze a seasonal and annual evolution of sea ice, long-term variability of a model ice cover, and its sensitivity to some parameters of model as well to define atmosphere-ice-ocean interaction.Results of 100 years simulations of Arctic basin sea ice evolution are analyzed. There are significant (about 0.5 m inter-annual fluctuations of an ice cover.The ice - atmosphere sensible heat flux reduced by 10% leads to the growth of average sea ice thickness within the limits of 0.05 m – 0.1 m. However in separate spatial points the thickness decreases up to 0.5 m. An analysis of the seasonably changing average ice thickness with decreasing, as compared to the basic variant by 0.05 of clear sea ice albedo and that of snow shows the ice thickness reduction in a range from 0.2 m up to 0.6 m, and the change maximum falls for the summer season of intensive melting. The spatial distribution of ice thickness changes shows, that on the large part of the Arctic Ocean there was a reduction of ice thickness down to 1 m. However, there is also an area of some increase of the ice layer basically in a range up to 0.2 m (Beaufort Sea. The 0.05 decrease of sea ice snow albedo leads to reduction of average ice thickness approximately by 0.2 m, and this value slightly depends on a season. In the following experiment the ocean – ice thermal interaction influence on the ice cover is estimated. It is carried out by increase of a heat flux from ocean to the bottom surface of sea ice by 2 W/sq. m in comparison with base variant. The analysis demonstrates, that the average ice thickness reduces in a range from 0.2 m to 0.35 m. There are small seasonal changes of this value.The numerical experiments results have shown, that an ice cover and its seasonal evolution rather strongly depend on varied parameters

  18. Quantifying uncertainty and sensitivity in sea ice models

    Energy Technology Data Exchange (ETDEWEB)

    Urrego Blanco, Jorge Rolando [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Hunke, Elizabeth Clare [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Urban, Nathan Mark [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-07-15

    The Los Alamos Sea Ice model has a number of input parameters for which accurate values are not always well established. We conduct a variance-based sensitivity analysis of hemispheric sea ice properties to 39 input parameters. The method accounts for non-linear and non-additive effects in the model.

  19. What sea-ice biogeochemical modellers need from observers

    Directory of Open Access Journals (Sweden)

    Nadja Steiner

    2016-02-01

    Full Text Available Abstract Numerical models can be a powerful tool helping to understand the role biogeochemical processes play in local and global systems and how this role may be altered in a changing climate. With respect to sea-ice biogeochemical models, our knowledge is severely limited by our poor confidence in numerical model parameterisations representing those processes. Improving model parameterisations requires communication between observers and modellers to guide model development and improve the acquisition and presentation of observations. In addition to more observations, modellers need conceptual and quantitative descriptions of the processes controlling, for example: primary production and diversity of algal functional types in sea ice, ice algal growth, release from sea ice, heterotrophic remineralisation, transfer and emission of gases (e.g., DMS, CH4, BrO, incorporation of seawater components in growing sea ice (including Fe, organic and inorganic carbon, and major salts and subsequent release; CO2 dynamics (including CaCO3 precipitation, flushing and supply of nutrients to sea-ice ecosystems; and radiative transfer through sea ice. These issues can be addressed by focused observations, as well as controlled laboratory and field experiments that target specific processes. The guidelines provided here should help modellers and observers improve the integration of measurements and modelling efforts and advance toward the common goal of understanding biogeochemical processes in sea ice and their current and future impacts on environmental systems.

  20. Sensitivity of open-water ice growth and ice concentration evolution in a coupled atmosphere-ocean-sea ice model

    Science.gov (United States)

    Shi, Xiaoxu; Lohmann, Gerrit

    2017-09-01

    A coupled atmosphere-ocean-sea ice model is applied to investigate to what degree the area-thickness distribution of new ice formed in open water affects the ice and ocean properties. Two sensitivity experiments are performed which modify the horizontal-to-vertical aspect ratio of open-water ice growth. The resulting changes in the Arctic sea-ice concentration strongly affect the surface albedo, the ocean heat release to the atmosphere, and the sea-ice production. The changes are further amplified through 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 Fram Strait sea ice import influences the freshwater budget in the North Atlantic Ocean. Anomalies in sea-ice transport lead to changes in sea surface properties of the North Atlantic and the strength of AMOC. For the Southern Ocean, the most pronounced change is a warming along the Antarctic Circumpolar Current (ACC), owing to the interhemispheric bipolar seasaw linked to AMOC weakening. Another insight of this study lies on the improvement of our climate model. The ocean component FESOM is a newly developed ocean-sea ice model with an unstructured mesh and multi-resolution. We find that the subpolar sea-ice boundary in the Northern Hemisphere can be improved by tuning the process of open-water ice growth, which strongly influences the sea ice concentration in the marginal ice zone, the North Atlantic circulation, salinity and Arctic sea ice volume. Since the distribution of new ice on open water relies on many uncertain parameters and the knowledge of the detailed processes is currently too crude, it is a challenge to implement the processes realistically into models. Based on our sensitivity experiments, we conclude a pronounced uncertainty related to open-water sea ice growth which could significantly affect the climate system sensitivity.

  1. Smoluchowski coagulation models of sea ice thickness distribution dynamics

    Science.gov (United States)

    Godlovitch, D.; Illner, R.; Monahan, A.

    2011-12-01

    Sea ice thickness distributions display a ubiquitous exponential decrease with thickness. This tail characterizes the range of ice thickness produced by mechanical redistribution of ice through the process of ridging, rafting, and shearing. We investigate how well the thickness distribution can be simulated by representing mechanical redistribution as a generalized stacking process. Such processes are naturally described by a well-studied class of models known as Smoluchowski Coagulation Models (SCMs), which describe the dynamics of a population of fixed-mass "particles" which combine in pairs to form a "particle" with the combined mass of the constituent pair at a rate which depends on the mass of the interacting particles. Like observed sea ice thickness distributions, the mass distribution of the populations generated by SCMs has an exponential or quasi-exponential form. We use SCMs to model sea ice, identifying mass-increasing particle combinations with thickness-increasing ice redistribution processes. Our model couples an SCM component with a thermodynamic component and generates qualitatively accurate thickness distributions with a variety of rate kernels. Our results suggest that the exponential tail of the sea ice thickness distribution arises from the nature of the ridging process, rather than specific physical properties of sea ice or the spatial arrangement of floes, and that the relative strengths of the dynamic and thermodynamic processes are key in accurately simulating the rate at which the sea ice thickness tail drops off with thickness.

  2. Model resolution influence on simulated sea ice decline

    OpenAIRE

    Sewall, J.O.

    2008-01-01

    Satellite observations and model predictions of recent and future Arctic sea ice decline have raised concerns over the timing and potential impacts of a seasonally ice-free Arctic Ocean. Model predictions of seasonally ice-free Arctic conditions are, however, highly variable. Here I present results from fourteen climate system models from the World Climate Research Programme's (WCRP's) Coupled Model Intercomparison Project phase 3 (CMIP3) multi-model dataset that indicate modeled Ar...

  3. Sensitivity of sea ice and ocean simulations to sea ice salinity in a coupled global climate model

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    The impacts of the spatiotemporal variations of sea ice salinity on sea ice and ocean characteristics have not been studied in detail, as the existing climate models neglect or misrepresent this process. To address this issue, this paper formulated a parameterization with more realistic sea ice salinity budget, and examined the sensitivity of sea ice and ocean simulations to the ice salinity variations and associated salt flux into the ocean using a coupled global climate model. Results show that the inclusion of such a parameterization leads to an increase and thickening of sea ice in the Eurasian Arctic and within the ice pack in the Antarctic circumpolar region, and a weakening of the North Atlantic Deep Water and a strengthening of the Antarctic Bottom Water. The atmospheric responses associated with the ice changes were also discussed.

  4. Modeling the summertime evolution of sea-ice melt ponds

    DEFF Research Database (Denmark)

    Lüthje, Mikael; Feltham, D.L.; Taylor, P.D.;

    2006-01-01

    We present a mathematical model describing the summer melting of sea ice. We simulate the evolution of melt ponds and determine area coverage and total surface ablation. The model predictions are tested for sensitivity to the melt rate of unponded ice, enhanced melt rate beneath the melt ponds......, vertical seepage, and horizontal permeability. The model is initialized with surface topographies derived from laser altimetry corresponding to first-year sea ice and multiyear sea ice. We predict that there are large differences in the depth of melt ponds and the area of coverage between the two types...... of ice. We also find that the vertical seepage rate and the melt rate of unponded ice are important in determining the total surface ablation and area covered by melt ponds....

  5. Modeling the summertime evolution of sea-ice melt ponds

    DEFF Research Database (Denmark)

    Lüthje, Mikael; Feltham, D.L.; Taylor, P.D.

    2006-01-01

    We present a mathematical model describing the summer melting of sea ice. We simulate the evolution of melt ponds and determine area coverage and total surface ablation. The model predictions are tested for sensitivity to the melt rate of unponded ice, enhanced melt rate beneath the melt ponds......, vertical seepage, and horizontal permeability. The model is initialized with surface topographies derived from laser altimetry corresponding to first-year sea ice and multiyear sea ice. We predict that there are large differences in the depth of melt ponds and the area of coverage between the two types...... of ice. We also find that the vertical seepage rate and the melt rate of unponded ice are important in determining the total surface ablation and area covered by melt ponds....

  6. On the assimilation of ice velocity and concentration data into large-scale sea ice models

    Directory of Open Access Journals (Sweden)

    V. Dulière

    2007-03-01

    Full Text Available Data assimilation into sea ice models designed for climate studies has started about 15 years ago. In most of the studies conducted so far, it is assumed that the improvement brought by the assimilation is straightforward. However, some studies suggest this might not be true. In order to elucidate this question and to find an appropriate way to further assimilate sea ice concentration and velocity observations into a global sea ice-ocean model, we analyze here results from a number of twin experiments (i.e. experiments in which the assimilated data are model outputs carried out with a simplified model of the Arctic sea ice pack. Our objective is to determine to what degree the assimilation of ice velocity and/or concentration data improves the global performance of the model and, more specifically, reduces the error in the computed ice thickness. A simple optimal interpolation scheme is used, and outputs from a control run and from perturbed experiments without and with data assimilation are thoroughly compared. Our results indicate that, under certain conditions depending on the assimilation weights and the type of model error, the assimilation of ice velocity data enhances the model performance. The assimilation of ice concentration data can also help in improving the model behavior, but it has to be handled with care because of the strong connection between ice concentration and ice thickness.

    This study is preliminary study towards real observation data assimilation into NEMOLIM, a global sea ice-ocean model.

  7. Modelling sea ice formation in the Terra Nova Bay polynya

    Science.gov (United States)

    Sansiviero, M.; Morales Maqueda, M. Á.; Fusco, G.; Aulicino, G.; Flocco, D.; Budillon, G.

    2017-02-01

    Antarctic sea ice is constantly exported from the shore by strong near surface winds that open leads and large polynyas in the pack ice. The latter, known as wind-driven polynyas, are responsible for significant water mass modification due to the high salt flux into the ocean associated with enhanced ice growth. In this article, we focus on the wind-driven Terra Nova Bay (TNB) polynya, in the western Ross Sea. Brine rejected during sea ice formation processes that occur in the TNB polynya densifies the water column leading to the formation of the most characteristic water mass of the Ross Sea, the High Salinity Shelf Water (HSSW). This water mass, in turn, takes part in the formation of Antarctic Bottom Water (AABW), the densest water mass of the world ocean, which plays a major role in the global meridional overturning circulation, thus affecting the global climate system. A simple coupled sea ice-ocean model has been developed to simulate the seasonal cycle of sea ice formation and export within a polynya. The sea ice model accounts for both thermal and mechanical ice processes. The oceanic circulation is described by a one-and-a-half layer, reduced gravity model. The domain resolution is 1 km × 1 km, which is sufficient to represent the salient features of the coastline geometry, notably the Drygalski Ice Tongue. The model is forced by a combination of Era Interim reanalysis and in-situ data from automatic weather stations, and also by a climatological oceanic dataset developed from in situ hydrographic observations. The sensitivity of the polynya to the atmospheric forcing is well reproduced by the model when atmospheric in situ measurements are combined with reanalysis data. Merging the two datasets allows us to capture in detail the strength and the spatial distribution of the katabatic winds that often drive the opening of the polynya. The model resolves fairly accurately the sea ice drift and sea ice production rates in the TNB polynya, leading to

  8. Sea-ice deformation in a coupled ocean-sea-ice model and in satellite remote sensing data

    Science.gov (United States)

    Spreen, Gunnar; Kwok, Ron; Menemenlis, Dimitris; Nguyen, An T.

    2017-07-01

    A realistic representation of sea-ice deformation in models is important for accurate simulation of the sea-ice mass balance. Simulated sea-ice deformation from numerical simulations with 4.5, 9, and 18 km horizontal grid spacing and a viscous-plastic (VP) sea-ice rheology are compared with synthetic aperture radar (SAR) satellite observations (RGPS, RADARSAT Geophysical Processor System) for the time period 1996-2008. All three simulations can reproduce the large-scale ice deformation patterns, but small-scale sea-ice deformations and linear kinematic features (LKFs) are not adequately reproduced. The mean sea-ice total deformation rate is about 40 % lower in all model solutions than in the satellite observations, especially in the seasonal sea-ice zone. A decrease in model grid spacing, however, produces a higher density and more localized ice deformation features. The 4.5 km simulation produces some linear kinematic features, but not with the right frequency. The dependence on length scale and probability density functions (PDFs) of absolute divergence and shear for all three model solutions show a power-law scaling behavior similar to RGPS observations, contrary to what was found in some previous studies. Overall, the 4.5 km simulation produces the most realistic divergence, vorticity, and shear when compared with RGPS data. This study provides an evaluation of high and coarse-resolution viscous-plastic sea-ice simulations based on spatial distribution, time series, and power-law scaling metrics.

  9. A modified discrete element model for sea ice dynamics

    Institute of Scientific and Technical Information of China (English)

    LI Baohui; LI Hai; LIU Yu; WANG Anliang; JI Shunying

    2014-01-01

    Considering the discontinuous characteristics of sea ice on various scales, a modified discrete element mod-el (DEM) for sea ice dynamics is developed based on the granular material rheology. In this modified DEM, a soft sea ice particle element is introduced as a self-adjustive particle size function. Each ice particle can be treated as an assembly of ice floes, with its concentration and thickness changing to variable sizes un-der the conservation of mass. In this model, the contact forces among ice particles are calculated using a viscous-elastic-plastic model, while the maximum shear forces are described with the Mohr-Coulomb fric-tion law. With this modified DEM, the ice flow dynamics is simulated under the drags of wind and current in a channel of various widths. The thicknesses, concentrations and velocities of ice particles are obtained, and then reasonable dynamic process is analyzed. The sea ice dynamic process is also simulated in a vortex wind field. Taking the influence of thermodynamics into account, this modified DEM will be improved in the future work.

  10. Sea Ice

    Science.gov (United States)

    Perovich, D.; Gerland, S.; Hendricks, S.; Meier, Walter N.; Nicolaus, M.; Richter-Menge, J.; Tschudi, M.

    2013-01-01

    During 2013, Arctic sea ice extent remained well below normal, but the September 2013 minimum extent was substantially higher than the record-breaking minimum in 2012. Nonetheless, the minimum was still much lower than normal and the long-term trend Arctic September extent is -13.7 per decade relative to the 1981-2010 average. The less extreme conditions this year compared to 2012 were due to cooler temperatures and wind patterns that favored retention of ice through the summer. Sea ice thickness and volume remained near record-low levels, though indications are of slightly thicker ice compared to the record low of 2012.

  11. Sea-Ice Deformation in a Coupled Ocean-Sea Ice Model and in Satellite Remote Sensing Data

    Science.gov (United States)

    Spreen, G.; Kwok, R.; Menemenlis, D.; Nguyen, A. T.

    2016-12-01

    A realistic representation of sea-ice deformation in models is important for accurate simulation of the sea ice mass balance. Simulated sea-ice deformation strain rates from model simulations with 4.5, 9, and 18-km horizontal grid spacing are compared with Synthetic Aperture Radar (SAR) satellite observations (RGPS). The used MITgcm model employs a viscous-plastic sea ice rheology. The figure below shows the ice thickness distributions for the three simulations on 15 November 1999. More ice fracturing and leads are visible in the 4.5 km solution. All three simulations can reproduce the large-scale ice deformation patterns, but small-scale sea-ice deformations and linear kinematic features are not adequately reproduced. The mean sea-ice total deformation rate is about 50% lower in all model solutions than in the satellite observations, especially in the seasonal sea ice zone. A decrease in model grid spacing, however, produces a higher density and more localized ice deformation features. The spatial scaling and probability density functions of all three model solutions follow a power-law similar to the RGPS observations, and contrary to what is found in other studies. Overall, the 4.5-km simulation produces the lowest misfits in divergence, vorticity, and shear when compared with RGPS data. Model sensitivity experiments show a strong impact of the ice strength parametrization on the Arctic Basin sea ice volume, which increased by 7% and 35% for a decrease in ice strength of, respectively, 30% and 70%, after 8 years of model integration. This volume increase is caused by a combination of dynamic and thermodynamic processes: the ice thickness increased by enhanced deformation and ice growth in leads, which is followed by a decrease in ice export. The balance of these processes leads to a new equilibrium Arctic Basin ice volume. Not addressed in this study is whether the differences between simulated and observed deformation rates are an intrinsic limitation of the

  12. On the importance of conserving mass in sea ice models

    CERN Document Server

    Moon, Woosok

    2013-01-01

    We describe how a long standing approach used in the thermodynamic modeling of sea ice fails to conserve mass. The missing mass is traced to a term that is equivalent to neglecting a leading order latent heat flux and we demonstrate its influence using energy balance models with a fractional ice cover. It is shown that this neglect is particularly acute in a decaying ice cover approaching the transitions to seasonal and ice-free conditions. Accordingly, it is suggested that it may be of considerable relevance to re-examine the relevant climate model schemes.

  13. Satellite information of sea ice for model validation

    Science.gov (United States)

    Saheed, P. P.; Mitra, Ashis K.; Momin, Imranali M.; Mahapatra, Debasis K.; Rajagopal, E. N.

    2016-05-01

    Emergence of extensively large computational facilities have enabled the scientific world to use earth system models for understating the prevailing dynamics of the earth's atmosphere, ocean and cryosphere and their inter relations. The sea ice in the arctic and the Antarctic has been identified as one of the main proxies to study the climate changes. The rapid sea-ice melting in the Arctic and disappearance of multi-year sea ice has become a matter of concern. The earth system models couple the ocean, atmosphere and sea-ice in order to bring out the possible inter connections between these three very important components and their role in the changing climate. The Indian monsoon is seen to be subjected to nonlinear changes in the recent years. The rapid ice melt in the Arctic sea ice is apparently linked to the changes in the weather and climate of the Indian subcontinent. The recent findings reveal the relation between the high events occurs in the Indian subcontinent and the Arctic sea ice melt episodes. The coupled models are being used in order to study the depth of these relations. However, the models have to be validated extensively by using measured parameters. The satellite measurements of sea-ice starts from way back in 1979. There have been many data sets available since then. Here in this study, an evaluation of the existing data sets is conducted. There are some uncertainties in these data sets. It could be associated with the absence of a single sensor for a long period of time and also the absence of accurate in-situ measurements in order to validate the satellite measurements.

  14. Evaluation of Arctic Sea Ice Thickness Simulated by AOMIP Models

    Science.gov (United States)

    Johnson, Mark; Proshutinsky, Andrey; Aksenov, Yevgeny; Nguyen, An T.; Lindsay, Ron; Haas, Christian; Zhang, Jinlun; Diansky, Nimolay; Kwok, Ron; Maslowski, Wieslaw; Hakkinen, Sirpa; Ashik, Igor; de Cuevas, Beverly

    2011-01-01

    We compare results from six AOMIP model simulations with estimates of sea ice thickness obtained from ICESat, moored and submarine-based upward looking sensors, airborne electromagnetic measurements and drill holes. Our goal is to find patterns of model performance to guide model improvement. The satellite data is pan-arctic from 2004-2008, ice-draft data is from moored instruments in Fram Strait, the Greenland Sea and the Beaufort Sea from 1992-2008 and from submarines from 1975-2000. The drill hole data are from the Laptev and East Siberian marginal seas from 1982-1986 and from coastal stations from 1998-2009. While there are important caveats when comparing modeled results with measurements from different platforms and time periods such as these, the models agree well with moored ULS data. In general, the AOMIP models underestimate the thickness of measured ice thicker than about 2 m and overestimate thickness of ice thinner than 2 m. The simulated results are poor over the fast ice and marginal seas of the Siberian shelves. Averaging over all observational data sets, the better correlations and smaller differences from observed thickness are from the ECCO2 and UW models.

  15. Assessment of Sea Surface Temperature and Sea Ice Initial Conditions on Coupled Model Forecasts

    Science.gov (United States)

    Intrieri, J. M.; Solomon, A.; Persson, O. P. G.; Capotondi, A.; LaFontaine, F.; Jedlovec, G.

    2016-12-01

    We present weather-scale (0-10 day) sea ice forecast validation and skill results from an experimental coupled ice-ocean-atmosphere model during the fall freeze-up periods for 2015 and 2016. The model is a mesoscale, coupled atmosphere-ice-ocean mixed-layer model, termed RASM-ESRL, that was developed from the larger-scale Regional Arctic System Model (RASM) architecture. The atmospheric component of RASM-ESRL consists of the Weather Research and Forecasting (WRF) model, the sea-ice component is the Los Alamos CICE model, and the ocean model is POP. Experimental 5-day forecasts were run daily with RASM-ESRL from July through mid-November in 2015 and 2016. Our project focuses on how the modeled sea ice evolution compares to observed physical processes including atmospheric forcing of sea ice movement, melt, and freeze-up through energy fluxes. Model hindcast output is validated against buoy observations, satellite measurements, and concurrent in situ flux observations made from the R/V Sikuliaq in the fall of 2015. Model skill in predicting atmospheric state variables, wind and boundary layer structures, synoptic features, cloud microphysical and ocean properties will be discussed. We will show results of using different initializations of ocean sea surface temperature and sea ice extent and the impacts on sea ice edge prediction.

  16. IOMASA SEA ICE DEVELOPMENTS

    DEFF Research Database (Denmark)

    Andersen, Søren; Tonboe, Rasmus; Heygster, Georg

    2005-01-01

    Sensitivity studies show that the radiometer ice concentration estimate can be biased by +10% by anomalous atmospheric emissivity and -20% by anomalous ice surface emissivity. The aim of the sea ice activities in EU 5th FP project IOMASA is to improve sea ice concentration estimates at higher...... spatial resolution. The project is in the process of facilitating an ice concentration observing system through validation and a better understanding of the microwave radiative transfer of the sea ice and overlying snow layers. By use of a novel modelling approach, it is possible to better detect...... and determine the circumstances that may lead to anomalous sea ice concentration retrieval as well as to assess and possibly minimize the sensitivities of the retrieval system. Through an active partnership with the SAF on Ocean and Sea Ice, a prototype system will be implemented as an experimental product...

  17. IOMASA SEA ICE DEVELOPMENTS

    DEFF Research Database (Denmark)

    Andersen, Søren; Tonboe, Rasmus; Heygster, Georg

    2005-01-01

    Sensitivity studies show that the radiometer ice concentration estimate can be biased by +10% by anomalous atmospheric emissivity and -20% by anomalous ice surface emissivity. The aim of the sea ice activities in EU 5th FP project IOMASA is to improve sea ice concentration estimates at higher...... spatial resolution. The project is in the process of facilitating an ice concentration observing system through validation and a better understanding of the microwave radiative transfer of the sea ice and overlying snow layers. By use of a novel modelling approach, it is possible to better detect...... and determine the circumstances that may lead to anomalous sea ice concentration retrieval as well as to assess and possibly minimize the sensitivities of the retrieval system. Through an active partnership with the SAF on Ocean and Sea Ice, a prototype system will be implemented as an experimental product...

  18. Sea ice as a source of sea salt aerosol to Greenland ice cores: a model-based study

    Science.gov (United States)

    Rhodes, Rachael H.; Yang, Xin; Wolff, Eric W.; McConnell, Joseph R.; Frey, Markus M.

    2017-08-01

    Growing evidence suggests that the sea ice surface is an important source of sea salt aerosol and this has significant implications for polar climate and atmospheric chemistry. It also suggests the potential to use ice core sea salt records as proxies for past sea ice extent. To explore this possibility in the Arctic region, we use a chemical transport model to track the emission, transport, and deposition of sea salt from both the open ocean and the sea ice, allowing us to assess the relative importance of each. Our results confirm the importance of sea ice sea salt (SISS) to the winter Arctic aerosol burden. For the first time, we explicitly simulate the sea salt concentrations of Greenland snow, achieving values within a factor of two of Greenland ice core records. Our simulations suggest that SISS contributes to the winter maxima in sea salt characteristic of ice cores across Greenland. However, a north-south gradient in the contribution of SISS relative to open-ocean sea salt (OOSS) exists across Greenland, with 50 % of winter sea salt being SISS at northern sites such as NEEM (77° N), while only 10 % of winter sea salt is SISS at southern locations such as ACT10C (66° N). Our model shows some skill at reproducing the inter-annual variability in sea salt concentrations for 1991-1999, particularly at Summit where up to 62 % of the variability is explained. Future work will involve constraining what is driving this inter-annual variability and operating the model under different palaeoclimatic conditions.

  19. Introduction of parameterized sea ice drag coefficients into ice free-drift modeling

    Institute of Scientific and Technical Information of China (English)

    LU Peng; LI Zhijun; HAN Hongwei

    2016-01-01

    Many interesting characteristics of sea ice drift depend on the atmospheric drag coefficient (Ca) and oceanic drag coefficient (Cw). Parameterizations of drag coefficients rather than constant values provide us a way to look insight into the dependence of these characteristics on sea ice conditions. In the present study, the parameterized ice drag coefficients are included into a free-drift sea ice dynamic model, and the wind factorα and the deflection angleθ between sea ice drift and wind velocity as well as the ratio ofCa toCw are studied to investigate their dependence on the impact factors such as local drag coefficients, floe and ridge geometry. The results reveal that in an idealized steady ocean,Ca/Cw increases obviously with the increasing ice concentration for small ice floes in the marginal ice zone, while it remains at a steady level (0.2–0.25) for large floes in the central ice zone. The wind factorα increases rapidly at first and approaches a steady level of 0.018 whenA is greater than 20%. And the deflection angleθ drops rapidly from an initial value of approximate 80° and decreases slowly asA is greater than 20% without a steady level likeα. The values of these parameters agree well with the previously reported observations in Arctic. The ridging intensity is an important parameter to determine the dominant contribution of the ratio of skin friction drag coefficient (Cs’/Cs) and the ratio of ridge form drag coefficient (Cr’/Cr) to the value of Ca/Cw,α, andθ, because of the dominance of ridge form drag for large ridging intensity and skin friction for small ridging intensity among the total drag forces. Parameterization of sea ice drag coefficients has the potential to be embedded into ice dynamic models to better account for the variability of sea ice in the transient Arctic Ocean.

  20. Numerical modelling of thermodynamics and dynamics of sea ice in the Baltic Sea

    Directory of Open Access Journals (Sweden)

    A. Herman

    2011-01-01

    Full Text Available In this paper, a numerical dynamic-thermodynamic sea-ice model for the Baltic Sea is used to analyze the variability of ice conditions in three winter seasons. The modelling results are validated with station (water temperature and satellite data (ice concentration as well as by qualitative comparisons with the Swedish Meteorological and Hydrological Institute ice charts. Analysis of the results addresses two major questions. One concerns effects of meteorological forcing on the spatio-temporal distribution of ice concentration in the Baltic. Patterns of correlations between air temperature, wind speed, and ice-covered area are demonstrated to be different in larger, more open sub-basins (e.g., the Bothnian Sea than in the smaller ones (e.g., the Bothnian Bay. Whereas the correlations with the air temperature are positive in both cases, the influence of wind is pronounced only in large basins, leading to increase/decrease of areas with small/large ice concentrations, respectively. The other question concerns the role of ice dynamics in the evolution of the ice cover. By means of simulations with the dynamic model turned on and off, the ice dynamics is shown to play a crucial role in interactions between the ice and the upper layers of the water column, especially during periods with highly varying wind speeds and directions. In particular, due to the fragmentation of the ice cover and the modified surface fluxes, the ice dynamics influences the rate of change of the total ice volume, in some cases by as much as 1 km3 per day. As opposed to most other numerical studies on the sea-ice in the Baltic Sea, this work concentrates on the short-term variability of the ice cover and its response to the synoptic-scale forcing.

  1. Numerical modelling of thermodynamics and dynamics of sea ice in the Baltic Sea

    Directory of Open Access Journals (Sweden)

    A. Herman

    2011-04-01

    Full Text Available In this paper, a numerical dynamic-thermo-dynamic sea-ice model for the Baltic Sea is used to analyze the variability of ice conditions in three winter seasons. The modelling results are validated with station (water temperature and satellite data (ice concentration as well as by qualitative comparisons with the Swedish Meteorological and Hydrological Institute ice charts. Analysis of the results addresses two major questions. One concerns effects of meteorological forcing on the spatio-temporal distribution of ice concentration in the Baltic. Patterns of correlations between air temperature, wind speed, and ice-covered area are demonstrated to be different in larger, more open sub-basins (e.g., the Bothnian Sea than in the smaller ones (e.g., the Bothnian Bay. Whereas the correlations with the air temperature are positive in both cases, the influence of wind is pronounced only in large basins, leading to increase/decrease of areas with small/large ice concentrations, respectively. The other question concerns the role of ice dynamics in the evolution of the ice cover. By means of simulations with the dynamic model turned on and off, the ice dynamics is shown to play a crucial role in interactions between the ice and the upper layers of the water column, especially during periods with highly varying wind speeds and directions. In particular, due to the fragmentation of the ice cover and the modified surface fluxes, the ice dynamics influences the rate of change of the total ice volume, in some cases by as much as 1 km3 per day. As opposed to most other numerical studies on the sea-ice in the Baltic Sea, this work concentrates on the short-term variability of the ice cover and its response to the synoptic-scale forcing.

  2. Implementation of a one-dimensional enthalpy sea-ice model in a simple pycnocline prediction model for sea-ice data assimilation studies

    Science.gov (United States)

    Wu, Xinrong; Zhang, Shaoqing; Liu, Zhengyu

    2016-02-01

    To further explore enthalpy-based sea-ice assimilation, a one-dimensional (1D) enthalpy sea-ice model is implemented into a simple pycnocline prediction model. The 1D enthalpy sea-ice model includes the physical processes such as brine expulsion, flushing, and salt diffusion. After being coupled with the atmosphere and ocean components, the enthalpy sea-ice model can be integrated stably and serves as an important modulator of model variability. Results from a twin experiment show that the sea-ice data assimilation in the enthalpy space can produce smaller root-mean-square errors of model variables than the traditional scheme that assimilates the observations of ice concentration, especially for slow-varying states. This study provides some insights into the improvement of sea-ice data assimilation in a coupled general circulation model.

  3. Processes controlling surface, bottom and lateral melt of Arctic sea ice in a state of the art sea ice model.

    Science.gov (United States)

    Tsamados, Michel; Feltham, Daniel; Petty, Alek; Schroeder, David; Flocco, Daniela

    2015-10-13

    We present a modelling study of processes controlling the summer melt of the Arctic sea ice cover. We perform a sensitivity study and focus our interest on the thermodynamics at the ice-atmosphere and ice-ocean interfaces. We use the Los Alamos community sea ice model CICE, and additionally implement and test three new parametrization schemes: (i) a prognostic mixed layer; (ii) a three equation boundary condition for the salt and heat flux at the ice-ocean interface; and (iii) a new lateral melt parametrization. Recent additions to the CICE model are also tested, including explicit melt ponds, a form drag parametrization and a halodynamic brine drainage scheme. The various sea ice parametrizations tested in this sensitivity study introduce a wide spread in the simulated sea ice characteristics. For each simulation, the total melt is decomposed into its surface, bottom and lateral melt components to assess the processes driving melt and how this varies regionally and temporally. Because this study quantifies the relative importance of several processes in driving the summer melt of sea ice, this work can serve as a guide for future research priorities. © 2015 The Author(s).

  4. Evaluation of Arctic Sea Ice Thickness Simulated by Arctic Ocean Model Intercomparison Project Models

    Science.gov (United States)

    Johnson, Mark; Proshuntinsky, Andrew; Aksenov, Yevgeny; Nguyen, An T.; Lindsay, Ron; Haas, Christian; Zhang, Jinlun; Diansky, Nikolay; Kwok, Ron; Maslowski, Wieslaw; Hakkinen, Sirpa; Ashik, Igor; De Cuevas, Beverly

    2012-01-01

    Six Arctic Ocean Model Intercomparison Project model simulations are compared with estimates of sea ice thickness derived from pan-Arctic satellite freeboard measurements (2004-2008); airborne electromagnetic measurements (2001-2009); ice draft data from moored instruments in Fram Strait, the Greenland Sea, and the Beaufort Sea (1992-2008) and from submarines (1975-2000); and drill hole data from the Arctic basin, Laptev, and East Siberian marginal seas (1982-1986) and coastal stations (1998-2009). Despite an assessment of six models that differ in numerical methods, resolution, domain, forcing, and boundary conditions, the models generally overestimate the thickness of measured ice thinner than approximately 2 mand underestimate the thickness of ice measured thicker than about approximately 2m. In the regions of flat immobile landfast ice (shallow Siberian Seas with depths less than 25-30 m), the models generally overestimate both the total observed sea ice thickness and rates of September and October ice growth from observations by more than 4 times and more than one standard deviation, respectively. The models do not reproduce conditions of fast ice formation and growth. Instead, the modeled fast ice is replaced with pack ice which drifts, generating ridges of increasing ice thickness, in addition to thermodynamic ice growth. Considering all observational data sets, the better correlations and smaller differences from observations are from the Estimating the Circulation and Climate of the Ocean, Phase II and Pan-Arctic Ice Ocean Modeling and Assimilation System models.

  5. Modeling photosynthesis in sea ice-covered waters

    Science.gov (United States)

    Long, Matthew C.; Lindsay, Keith; Holland, Marika M.

    2015-09-01

    The lower trophic levels of marine ecosystems play a critical role in the Earth System mediating fluxes of carbon to the ocean interior. Many of the functional relationships describing biological rate processes, such as primary productivity, in marine ecosystem models are nonlinear functions of environmental state variables. As a result of nonlinearity, rate processes computed from mean fields at coarse resolution will differ from similar computations that incorporate small-scale heterogeneity. Here we examine how subgrid-scale variability in sea ice thickness impacts simulated net primary productivity (NPP) in a 1°×1° configuration of the Community Earth System Model (CESM). CESM simulates a subgrid-scale ice thickness distribution and computes shortwave penetration independently for each ice thickness category. However, the default model formulation uses grid-cell mean irradiance to compute NPP. We demonstrate that accounting for subgrid-scale shortwave heterogeneity by computing light limitation terms under each ice category then averaging the result is a more accurate invocation of the photosynthesis equations. Moreover, this change delays seasonal bloom onset and increases interannual variability in NPP in the sea ice zone in the model. The new treatment reduces annual production by about 32% in the Arctic and 19% in the Antarctic. Our results highlight the importance of considering heterogeneity in physical fields when integrating nonlinear biogeochemical reactions.

  6. Sea-ice extent provides a limited metric of model performance

    Directory of Open Access Journals (Sweden)

    D. Notz

    2013-06-01

    Full Text Available We examine the common practice of using sea-ice extent as the primary metric to evaluate modeled sea-ice coverage. Based on this analysis, we recommend a possible best practice for model evaluation. We find that for Arctic summer sea ice, model biases in sea-ice extent can be qualitatively different compared to biases in the geophysically more meaningful sea-ice area. These differences come about by a different frequency distribution of high-concentration sea-ice: while in summer about half of the CMIP5 models and satellite retrievals based on the Bootstrap and the ASI algorithm show a compact ice cover with large areas of high concentration sea ice, the other half of the CMIP5 models and satellite retrievals based on the NASA Team algorithm show a loose ice cover. The different behaviour of the CMIP5 models can be explained by their different distribution of excess heat between lateral melt and sea-ice thinning. Differences in grid geometry and round-off errors during interpolation only have a minor impact on the different biases in sea-ice extent and sea-ice area. Because of regional cancellation of biases in the integrative measures sea-ice extent and sea-ice area, these measures show little correlation with the more meaningful mean absolute bias in sea-ice concentration. Comparing the uncertainty arising directly from the satellite retrievals with those that arise from internal variability, we find that the latter by far dominates the uncertainty estimate for trends in sea-ice extent and area: much of the differences between modeled and observed trends can simply be explained by internal variability. Only for the absolute value of sea-ice area, differences between observations and models are so large that they cannot be explained by either observational uncertainty nor internal variability.

  7. Importance of Sea Ice for Validating Global Climate Models

    Science.gov (United States)

    Geiger, Cathleen A.

    1997-01-01

    Reproduction of current day large-scale physical features and processes is a critical test of global climate model performance. Without this benchmark, prognoses of future climate conditions are at best speculation. A fundamental question relevant to this issue is, which processes and observations are both robust and sensitive enough to be used for model validation and furthermore are they also indicators of the problem at hand? In the case of global climate, one of the problems at hand is to distinguish between anthropogenic and naturally occuring climate responses. The polar regions provide an excellent testing ground to examine this problem because few humans make their livelihood there, such that anthropogenic influences in the polar regions usually spawn from global redistribution of a source originating elsewhere. Concomitantly, polar regions are one of the few places where responses to climate are non-anthropogenic. Thus, if an anthropogenic effect has reached the polar regions (e.g. the case of upper atmospheric ozone sensitivity to CFCs), it has most likely had an impact globally but is more difficult to sort out from local effects in areas where anthropogenic activity is high. Within this context, sea ice has served as both a monitoring platform and sensitivity parameter of polar climate response since the time of Fridtjof Nansen. Sea ice resides in the polar regions at the air-sea interface such that changes in either the global atmospheric or oceanic circulation set up complex non-linear responses in sea ice which are uniquely determined. Sea ice currently covers a maximum of about 7% of the earth's surface but was completely absent during the Jurassic Period and far more extensive during the various ice ages. It is also geophysically very thin (typically global climate.

  8. A coupled multi-category sea ice model and POM for Baffin Bay and the Labrador Sea

    Institute of Scientific and Technical Information of China (English)

    TANG Zhi-li

    2008-01-01

    An overview of the seasonal variation of sea-ice cover in Baffin Bay and the Labrador Sea is given. A coupled ice-ocean model, CECOM, has been developed to study the seasonal variation and associated ice-ocean processes. The sea-ice component of the model is a multi-category ice model in which mean concentration and thickness are expressed in terms of a thickness distribution function. Ten categories of ice thickness are specified in the model. Sea ice is coupled dynamically and thermodynamically to the Princeton Ocean Model. Selected results from the model including the seasonal variation of sea ice in Baffin Bay, the North Water polynya and ice growth and melt over the Labrador Shelf are presented.

  9. Apparent Arctic sea ice modeling improvement caused by volcanoes

    CERN Document Server

    Rosenblum, Erica

    2016-01-01

    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 substantially reduced in models participating in the most recent phase of the Coupled Model Intercomparison Project (CMIP5) compared with the previous generation of models (CMIP3). This improvement has been attributed to improved physics in the models. Here we examine simulations from CMIP3 and CMIP5 and find that simulated sea ice trends are strongly influenced by historical volcanic forcing, which was included in all of the CMIP5 models but in only about half of the CMIP3 models. The volcanic forcing causes temporary simulated cooling in the 1980s and 1990s, which contributes to raising the simulated 1979-2013 global-mean surface temperature trends to values substantially larger than observed. This warming bias is accompan...

  10. The reversibility of sea ice loss in a state-of-the-art climate model

    OpenAIRE

    Armour, K. C.; Eisenman, I; Blanchard-Wrigglesworth, E.; McCusker, K. E.; Bitz, C.M.

    2011-01-01

    Rapid Arctic sea ice retreat has fueled speculation about the possibility of threshold (or ‘tipping point’) behavior and irreversible loss of the sea ice cover. We test sea ice reversibility within a state-of-the-art atmosphere–ocean global climate model by increasing atmospheric carbon dioxide until the Arctic Ocean becomes ice-free throughout the year and subsequently decreasing it until the initial ice cover returns. Evidence for irreversibility in the form of hysteresis outside the envelo...

  11. EOS Aqua AMSR-E Arctic Sea Ice Validation Program: Intercomparison Between Modeled and Measured Sea Ice Brightness Temperatures

    Science.gov (United States)

    Stroeve, J.; Markus, T.; Cavalieri, D. J.; Maslanik, J.; Sturm, M.; Henrichs, J.; Gasiewski, A.; Klein, M.

    2004-01-01

    During March 2003, an extensive field campaign was conducted near Barrow, Alaska to validate AQUA Advanced Microwave Scanning Radiometer (AMSR) sea ice products. Field, airborne and satellite data were collected over three different types of sea ice: 1) first year ice with little deformation, 2) first year ice with various amounts of deformation and 3) mixed first year ice and multi-year ice with various degrees of deformation. The validation plan relies primarily on comparisons between satellite, aircraft flights and ground-based measurements. Although these efforts are important, key aspects such as the effects of atmospheric conditions, snow properties, surface roughness, melt processes, etc on the sea ice algorithms are not sufficiently well understood or documented. To improve our understanding of these effects, we combined the detailed, in-situ data collection from the 2003 field campaign with radiance modeling using a radiative transfer model to simulate the top of the atmosphere AMSR brightness temperatures. This study reports on the results of the simulations for a variety of snow and ice types and compares the results with the National Oceanographic and Atmospheric Administration Environmental Technology Laboratory Polarimetric Scanning Radiometer (NOAA) (ETL) (PSR) microwave radiometer that was flown on the NASA P-3.

  12. Scaling properties of Arctic sea ice deformation in high-resolution viscous-plastic sea ice models and satellite observations

    Science.gov (United States)

    Hutter, Nils; Losch, Martin; Menemenlis, Dimitris

    2017-04-01

    Sea ice models with the traditional viscous-plastic (VP) rheology and very high grid resolution can resolve leads and deformation rates that are localised along Linear Kinematic Features (LKF). In a 1-km pan-Arctic sea ice-ocean simulation, the small scale sea-ice deformations in the Central Arctic are evaluated with a scaling analysis in relation to satellite observations of the Envisat Geophysical Processor System (EGPS). A new coupled scaling analysis for data on Eulerian grids determines the spatial and the temporal scaling as well as the coupling between temporal and spatial scales. The spatial scaling of the modelled sea ice deformation implies multi-fractality. The spatial scaling is also coupled to temporal scales and varies realistically by region and season. The agreement of the spatial scaling and its coupling to temporal scales with satellite observations and models with the modern elasto-brittle rheology challenges previous results with VP models at coarse resolution where no such scaling was found. The temporal scaling analysis, however, shows that the VP model does not fully resolve the intermittency of sea ice deformation that is observed in satellite data.

  13. Development, sensitivity analysis, and uncertainty quantification of high-fidelity arctic sea ice models.

    Energy Technology Data Exchange (ETDEWEB)

    Peterson, Kara J.; Bochev, Pavel Blagoveston; Paskaleva, Biliana S.

    2010-09-01

    Arctic sea ice is an important component of the global climate system and due to feedback effects the Arctic ice cover is changing rapidly. Predictive mathematical models are of paramount importance for accurate estimates of the future ice trajectory. However, the sea ice components of Global Climate Models (GCMs) vary significantly in their prediction of the future state of Arctic sea ice and have generally underestimated the rate of decline in minimum sea ice extent seen over the past thirty years. One of the contributing factors to this variability is the sensitivity of the sea ice to model physical parameters. A new sea ice model that has the potential to improve sea ice predictions incorporates an anisotropic elastic-decohesive rheology and dynamics solved using the material-point method (MPM), which combines Lagrangian particles for advection with a background grid for gradient computations. We evaluate the variability of the Los Alamos National Laboratory CICE code and the MPM sea ice code for a single year simulation of the Arctic basin using consistent ocean and atmospheric forcing. Sensitivities of ice volume, ice area, ice extent, root mean square (RMS) ice speed, central Arctic ice thickness, and central Arctic ice speed with respect to ten different dynamic and thermodynamic parameters are evaluated both individually and in combination using the Design Analysis Kit for Optimization and Terascale Applications (DAKOTA). We find similar responses for the two codes and some interesting seasonal variability in the strength of the parameters on the solution.

  14. Improving the WRF model's (version 3.6.1) simulation over sea ice surface through coupling with a complex thermodynamic sea ice model (HIGHTSI)

    Science.gov (United States)

    Yao, Yao; Huang, Jianbin; Luo, Yong; Zhao, Zongci

    2016-06-01

    Sea ice plays an important role in the air-ice-ocean interaction, but it is often represented simply in many regional atmospheric models. The Noah sea ice scheme, which is the only option in the current Weather Research and Forecasting (WRF) model (version 3.6.1), has a problem of energy imbalance due to its simplification in snow processes and lack of ablation and accretion processes in ice. Validated against the Surface Heat Budget of the Arctic Ocean (SHEBA) in situ observations, Noah underestimates the sea ice temperature which can reach -10 °C in winter. Sensitivity tests show that this bias is mainly attributed to the simulation within the ice when a time-dependent ice thickness is specified. Compared with the Noah sea ice model, the high-resolution thermodynamic snow and ice model (HIGHTSI) uses more realistic thermodynamics for snow and ice. Most importantly, HIGHTSI includes the ablation and accretion processes of sea ice and uses an interpolation method which can ensure the heat conservation during its integration. These allow the HIGHTSI to better resolve the energy balance in the sea ice, and the bias in sea ice temperature is reduced considerably. When HIGHTSI is coupled with the WRF model, the simulation of sea ice temperature by the original Polar WRF is greatly improved. Considering the bias with reference to SHEBA observations, WRF-HIGHTSI improves the simulation of surface temperature, 2 m air temperature and surface upward long-wave radiation flux in winter by 6, 5 °C and 20 W m-2, respectively. A discussion on the impact of specifying sea ice thickness in the WRF model is presented. Consistent with previous research, prescribing the sea ice thickness with observational information results in the best simulation among the available methods. If no observational information is available, we present a new method in which the sea ice thickness is initialized from empirical estimation and its further change is predicted by a complex thermodynamic

  15. Data-Driven Modeling and Prediction of Arctic Sea Ice

    Science.gov (United States)

    Kondrashov, Dmitri; Chekroun, Mickael; Ghil, Michael

    2016-04-01

    We present results of data-driven predictive analyses of sea ice over the main Arctic regions. Our approach relies on the Multilayer Stochastic Modeling (MSM) framework of Kondrashov, Chekroun and Ghil [Physica D, 2015] and it leads to probabilistic prognostic models of sea ice concentration (SIC) anomalies on seasonal time scales. This approach is applied to monthly time series of state-of-the-art data-adaptive decompositions of SIC and selected climate variables over the Arctic. We evaluate the predictive skill of MSM models by performing retrospective forecasts with "no-look ahead" for up to 6-months ahead. It will be shown in particular that the memory effects included intrinsically in the formulation of our non-Markovian MSM models allow for improvements of the prediction skill of large-amplitude SIC anomalies in certain Arctic regions on the one hand, and of September Sea Ice Extent, on the other. Further improvements allowed by the MSM framework will adopt a nonlinear formulation and explore next-generation data-adaptive decompositions, namely modification of Principal Oscillation Patterns (POPs) and rotated Multichannel Singular Spectrum Analysis (M-SSA).

  16. A coupled ice-ocean model for the Bohai Sea Ⅱ. Case study

    Institute of Scientific and Technical Information of China (English)

    SU Jie; WU Huiding; ZHANG Yunfei; LIU Qinzhen; BAI Shan

    2005-01-01

    The coupled ice-ocean model for the Bohai Sea is used for simulating the freezing, melting, and variation of ice cover and the heat balance at the sea-ice, air-ice, and air-sea interfaces of the Bohai Sea during the entire winter in 1998~1999 and 2000~2001. The coupled model is forced by real time numerical weather prediction fields. The results show that the thermodynamic effects of atmosphere and ocean are very important for the evolvement of ice in the Bohai Sea, especially in the period of ice freezing and melting. Ocean heat flux plays a key role in the thermodynamic coupling. The simulation also presents the different thermodynamic features in the ice covered region and the marginal ice zone. Ice thickness, heat budget at the interface, and surface sea temperature, etc. between the two representative points are discussed.

  17. Modelling sea ice for climate studies: recent advances and future challenges (Louis Agassiz Medal Lecture)

    Science.gov (United States)

    Fichefet, Thierry

    2016-04-01

    Since the beginning of satellite measurements in 1979, the summer Arctic sea ice extent has shrunk at a mean rate of ~12% per decade, and there is evidence that the rate of decline has accelerated over the last decade. Current global climate models project further decrease in Arctic sea ice areal coverage through the 21st century if atmospheric greenhouse gas concentrations continue to increase. However, rates of loss vary greatly between models, yielding a large uncertainty as to when a seasonally ice-free Arctic Ocean may be realized. Narrowing this uncertainty is of crucial importance since such changes in the Arctic sea ice cover might have profound ramifications, including the global ocean circulation and heat budget, regional ecosystems and wildlife, the indigenous human population, and commercial exploration and transportation. Regarding the Antarctic sea ice, its extent has been observed to slightly increase during the last 37 years, which appears puzzling in a global warming context. Several hypotheses have been proposed to explain this feature, but the issue is far from being settled. On the other hand, the majority of global climate models simulate a decreasing trend in Antarctic sea ice extent over this period, which questions the validity of their Antarctic sea ice projections for the coming decades. In this lecture, we show through simulations conducted with the state of the art Louvain-la-Neuve Sea Ice Model (LIM) coupled to the Nucleous European Modelling of the Ocean (NEMO) platform that a number of small-scale sea ice processes, which are omitted or crudely represented in global climate models (in particular, the subgrid-scale sea ice thickness distribution, the thermodynamics and dynamics of brine pockets trapped within sea ice, processes related to snow on top of sea ice, including surface melt ponds, the sea ice mechanical deformation, and the subgrid-scale heterogeneity of atmosphere-ice-ocean interactions), play a significant role in

  18. Wave–ice interactions in the neXtSIM sea-ice model

    Directory of Open Access Journals (Sweden)

    T. D. Williams

    2017-09-01

    Full Text Available In this paper we describe a waves-in-ice model (WIM, which calculates ice breakage and the wave radiation stress (WRS. This WIM is then coupled to the new sea-ice model neXtSIM, which is based on the elasto-brittle (EB rheology. We highlight some numerical issues involved in the coupling and investigate the impact of the WRS, and of modifying the EB rheology to lower the stiffness of the ice in the area where the ice has broken up (the marginal ice zone or MIZ. In experiments in the absence of wind, we find that wind waves can produce noticeable movement of the ice edge in loose ice (concentration around 70 % – up to 36 km, depending on the material parameters of the ice that are used and the dynamical model used for the broken ice. The ice edge position is unaffected by the WRS if the initial concentration is higher (≳ 0.9. Swell waves (monochromatic waves with low frequency do not affect the ice edge location (even for loose ice, as they are attenuated much less than the higher-frequency components of a wind wave spectrum, and so consequently produce a much lower WRS (by about an order of magnitude at least.In the presence of wind, we find that the wind stress dominates the WRS, which, while large near the ice edge, decays exponentially away from it. This is in contrast to the wind stress, which is applied over a much larger ice area. In this case (when wind is present the dynamical model for the MIZ has more impact than the WRS, although that effect too is relatively modest. When the stiffness in the MIZ is lowered due to ice breakage, we find that on-ice winds produce more compression in the MIZ than in the pack, while off-ice winds can cause the MIZ to be separated from the pack ice.

  19. A toy model linking atmospheric thermal radiation and sea ice growth

    Science.gov (United States)

    Thorndike, A. S.

    1992-01-01

    A simplified analytical model of sea ice growth is presented where the atmosphere is in thermal radiative equilibrium with the ice. This makes the downwelling longwave radiation reaching the ice surface an internal variable rather than a specified forcing. Analytical results demonstrate how the ice state depends on properties of the ice and on the externally specified climate.

  20. Processes controlling surface, bottom and lateral melt of Arctic sea ice in a state of the art sea ice model

    OpenAIRE

    Tsamados, Michel; Feltham, Danny; Petty, Alex; Schroeder, David; Flocco, Dani

    2015-01-01

    We present a modelling study of processes controlling the summer melt of the Arctic sea ice cover. We perform a sensitivity study and focus our interest on the thermodynamics at the ice–atmosphere and ice–ocean interfaces. We use the Los Alamos community sea ice model CICE, and additionally implement and test three new parametrization schemes: (i) a prognostic mixed layer; (ii) a three equation boundary condition for the salt and heat flux at the ice–ocean interface; and (iii) a new lateral m...

  1. Sea salt aerosol from blowing snow on sea ice - modeling vs observation

    Science.gov (United States)

    Yang, Xin; Frey, Markus; Norris, Sarah; Brooks, Ian; Anderson, Philip; Jones, Anna; wolff, Eric; Legrand, Michel

    2016-04-01

    Blowing snow over sea ice, through a subsequent sublimation process of salt-containing blown snow particles, has been hypothesized as a significant sea salt aerosol (SSA) source in high latitudes. This mechanism has been strongly supported by a winter cruise in the Weddell Sea (during June-August 2013). The newly collected data, including both physical and chemical components, provide a unique way to test and validate the parameterisation used for describing the SSA production from blowing snow events. With updates to some key parameters such as snow salinity in a global Chemistry-transport model pTOMCAT, simulated SSA concentrations can be well compared with measured SSA data. In this presentation, I will report modeled SSA number density against collected data on board of Polarstern ship during the Weddell Sea cruise, as well as modeled SSA massive concentrations against those measured at both coastal sites such as Alert in the North and Dumont d'Urville (DDU) in the South and central Antarctic sites such as Concordia and Kohnen stations. Model experiments indicated that open ocean-sourced SSA could not explain the observed winter SSA peaks seen in most polar sites, while with sea ice-sourced SSA in the model, the winter peaks can be well improved indicating the importance of sea ice-sourced SSA as a significant contributor to the salts (Na+, Cl-) recorded in the ice core.

  2. Recent changes in the dynamic properties of declining Arctic sea ice: A model study

    Science.gov (United States)

    Zhang, Jinlun; Lindsay, Ron; Schweiger, Axel; Rigor, Ignatius

    2012-10-01

    Results from a numerical model simulation show significant changes in the dynamic properties of Arctic sea ice during 2007-2011 compared to the 1979-2006 mean. These changes are linked to a 33% reduction in sea ice volume, with decreasing ice concentration, mostly in the marginal seas, and decreasing ice thickness over the entire Arctic, particularly in the western Arctic. The decline in ice volume results in a 37% decrease in ice mechanical strength and 31% in internal ice interaction force, which in turn leads to an increase in ice speed (13%) and deformation rates (17%). The increasing ice speed has the tendency to drive more ice out of the Arctic. However, ice volume export is reduced because the rate of decrease in ice thickness is greater than the rate of increase in ice speed, thus retarding the decline of Arctic sea ice volume. Ice deformation increases the most in fall and least in summer. Thus the effect of changes in ice deformation on the ice cover is likely strong in fall and weak in summer. The increase in ice deformation boosts ridged ice production in parts of the central Arctic near the Canadian Archipelago and Greenland in winter and early spring, but the average ridged ice production is reduced because less ice is available for ridging in most of the marginal seas in fall. The overall decrease in ridged ice production contributes to the demise of thicker, older ice. As the ice cover becomes thinner and weaker, ice motion approaches a state of free drift in summer and beyond and is therefore more susceptible to changes in wind forcing. This is likely to make seasonal or shorter-term forecasts of sea ice edge locations more challenging.

  3. Ice-ocean-ecosystem operational model of the Baltic Sea

    Science.gov (United States)

    Janecki, M.; Dzierzbicka-Glowacka, L.; Jakacki, J.; Nowicki, A.

    2012-04-01

    3D-CEMBS is a fully coupled model adopted for the Baltic Sea and have been developed within the grant, wchich is supported by the Polish State Committee of Scientific Reasearch. The model is based on CESM1.0 (Community Earth System Model), in our configuration it consists of two active components (ocean and ice) driven by central coupler (CPL7). Ocean (POP version 2.1) and ice models (CICE model, version 4.0) are forced by atmospheric and land data models. Atmospheric data sets are provided by ICM-UM model from University of Warsaw. Additionally land model provides runoff of the Baltic Sea (currently 78 rivers). Ecosystem model is based on an intermediate complexity marine ecosystem model for the global domain (J.K. Moore et. al., 2002) and consists of 11 main components: zooplankton, small phytoplankton, diatoms, cyanobacteria, two detrital classes, dissolved oxygen and the nutrients nitrate, ammonium, phosphate and silicate. The model is configured at two horizontal resolutions, approximately 9km and 2km (1/12° and 1/48° respectively). The model bathymetry is represented as 21 vertical levels and the thickness of the first four layers were chosen to be five metres. 3D-CEMBS model grid is based on stereographic coordinates, but equator of these coordinates is in the centre of the Baltic Sea (rotated stereographic coordinates) and we can assume that shape of the cells are square and they are identical. Currently model works in a operational state. The model creates 48-hour forecasts every 6 hours (or when new atmospheric dataset is available). Prognostic variables such as temperature, salinity, ice cover, currents, sea surface height and phytoplankton concentration are presented online on a the website and are available for registered users. Also time series for any location are accessible. This work was carried out in support of grant No NN305 111636 and No NN306 353239 - the Polish state Committee of Scientific Research. The partial support for this study was

  4. A Maxwell elasto-brittle rheology for sea ice modelling

    Science.gov (United States)

    Dansereau, Véronique; Weiss, Jérôme; Saramito, Pierre; Lattes, Philippe

    2016-07-01

    A new rheological model is developed that builds on an elasto-brittle (EB) framework used for sea ice and rock mechanics, with the intent of representing both the small elastic deformations associated with fracturing processes and the larger deformations occurring along the faults/leads once the material is highly damaged and fragmented. A viscous-like relaxation term is added to the linear-elastic constitutive law together with an effective viscosity that evolves according to the local level of damage of the material, like its elastic modulus. The coupling between the level of damage and both mechanical parameters is such that within an undamaged ice cover the viscosity is infinitely large and deformations are strictly elastic, while along highly damaged zones the elastic modulus vanishes and most of the stress is dissipated through permanent deformations. A healing mechanism is also introduced, counterbalancing the effects of damaging over large timescales. In this new model, named Maxwell-EB after the Maxwell rheology, the irreversible and reversible deformations are solved for simultaneously; hence drift velocities are defined naturally. First idealized simulations without advection show that the model reproduces the main characteristics of sea ice mechanics and deformation: strain localization, anisotropy, intermittency and associated scaling laws.

  5. Evidence for link between modelled trends in Antarctic sea ice and underestimated westerly wind changes

    Science.gov (United States)

    Purich, Ariaan; Cai, Wenju; England, Matthew H.; Cowan, Tim

    2016-02-01

    Despite global warming, total Antarctic sea ice coverage increased over 1979-2013. However, the majority of Coupled Model Intercomparison Project phase 5 models simulate a decline. Mechanisms causing this discrepancy have so far remained elusive. Here we show that weaker trends in the intensification of the Southern Hemisphere westerly wind jet simulated by the models may contribute to this disparity. During austral summer, a strengthened jet leads to increased upwelling of cooler subsurface water and strengthened equatorward transport, conducive to increased sea ice. As the majority of models underestimate summer jet trends, this cooling process is underestimated compared with observations and is insufficient to offset warming in the models. Through the sea ice-albedo feedback, models produce a high-latitude surface ocean warming and sea ice decline, contrasting the observed net cooling and sea ice increase. A realistic simulation of observed wind changes may be crucial for reproducing the recent observed sea ice increase.

  6. Can natural variability explain the discrepancy between observed and modeled sea ice trends?

    CERN Document Server

    Rosenblum, Erica

    2016-01-01

    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, tend to predict a moderate decrease in both the Arctic and Antarctic sea ice covers. A number of recent studies have attributed this discrepancy in each hemisphere to natural variability, suggesting that the models are consistent with the observations when simulated natural variability is taken into account. Here we examine sea ice changes during 1979-2013 in simulations from the most recent Coupled Model Intercomparison Project (CMIP5) as well as the Community Earth System Model Large Ensemble (CESM-LE). We find that accurately simulated Arctic sea ice retreat occurs only in simulations with too much global warming, whereas accurately simulated Antarctic sea ice expansion tends to occur in simulations with too little global warming. We show that because of this, simulations from both ensembles do not capture the observed asymmetry bet...

  7. Impact of surface wind biases on the Antarctic sea ice concentration budget in climate models

    Science.gov (United States)

    Lecomte, O.; Goosse, H.; Fichefet, T.; Holland, P. R.; Uotila, P.; Zunz, V.; Kimura, N.

    2016-09-01

    We derive the terms in the Antarctic sea ice concentration budget from the output of three models, and compare them to observations of the same terms. Those models include two climate models from the 5th Coupled Model Intercomparison Project (CMIP5) and one ocean-sea ice coupled model with prescribed atmospheric forcing. Sea ice drift and wind fields from those models, in average over April-October 1992-2005, all exhibit large differences with the available observational or reanalysis datasets. However, the discrepancies between the two distinct ice drift products or the two wind reanalyses used here are sometimes even greater than those differences. Two major findings stand out from the analysis. Firstly, large biases in sea ice drift speed and direction in exterior sectors of the sea ice covered region tend to be systematic and consistent with those in winds. This suggests that sea ice errors in these areas are most likely wind-driven, so as errors in the simulated ice motion vectors. The systematic nature of these biases is less prominent in interior sectors, nearer the coast, where sea ice is mechanically constrained and its motion in response to the wind forcing more depending on the model rheology. Second, the intimate relationship between winds, sea ice drift and the sea ice concentration budget gives insight on ways to categorize models with regard to errors in their ice dynamics. In exterior regions, models with seemingly too weak winds and slow ice drift consistently yield a lack of ice velocity divergence and hence a wrong wintertime sea ice growth rate. In interior sectors, too slow ice drift, presumably originating from issues in the physical representation of sea ice dynamics as much as from errors in surface winds, leads to wrong timing of the late winter ice retreat. Those results illustrate that the applied methodology provides a valuable tool for prioritizing model improvements based on the ice concentration budget-ice drift biases-wind biases

  8. Improved Upper Ocean/Sea Ice Modeling in the GISS GCM for Investigating Climate Change

    Science.gov (United States)

    1998-01-01

    This project built on our previous results in which we highlighted the importance of sea ice in overall climate sensitivity by determining that for both warming and cooling climates, when sea ice was not allowed to change, climate sensitivity was reduced by 35-40%. We also modified the GISS 8 deg x lO deg atmospheric GCM to include an upper-ocean/sea-ice model involving the Semtner three-layer ice/snow thermodynamic model, the Price et al. (1986) ocean mixed layer model and a general upper ocean vertical advection/diffusion scheme for maintaining and fluxing properties across the pycnocline. This effort, in addition to improving the sea ice representation in the AGCM, revealed a number of sensitive components of the sea ice/ocean system. For example, the ability to flux heat through the ice/snow properly is critical in order to resolve the surface temperature properly, since small errors in this lead to unrestrained climate drift. The present project, summarized in this report, had as its objectives: (1) introducing a series of sea ice and ocean improvements aimed at overcoming remaining weaknesses in the GCM sea ice/ocean representation, and (2) performing a series of sensitivity experiments designed to evaluate the climate sensitivity of the revised model to both Antarctic and Arctic sea ice, determine the sensitivity of the climate response to initial ice distribution, and investigate the transient response to doubling CO2.

  9. Sea ice thermohaline dynamics and biogeochemistry in the Arctic Ocean: Empirical and model results

    Science.gov (United States)

    Duarte, Pedro; Meyer, Amelie; Olsen, Lasse M.; Kauko, Hanna M.; Assmy, Philipp; Rösel, Anja; Itkin, Polona; Hudson, Stephen R.; Granskog, Mats A.; Gerland, Sebastian; Sundfjord, Arild; Steen, Harald; Hop, Haakon; Cohen, Lana; Peterson, Algot K.; Jeffery, Nicole; Elliott, Scott M.; Hunke, Elizabeth C.; Turner, Adrian K.

    2017-07-01

    Large changes in the sea ice regime of the Arctic Ocean have occurred over the last decades justifying the development of models to forecast sea ice physics and biogeochemistry. The main goal of this study is to evaluate the performance of the Los Alamos Sea Ice Model (CICE) to simulate physical and biogeochemical properties at time scales of a few weeks and to use the model to analyze ice algal bloom dynamics in different types of ice. Ocean and atmospheric forcing data and observations of the evolution of the sea ice properties collected from 18 April to 4 June 2015, during the Norwegian young sea ICE expedition, were used to test the CICE model. Our results show the following: (i) model performance is reasonable for sea ice thickness and bulk salinity; good for vertically resolved temperature, vertically averaged Chl a concentrations, and standing stocks; and poor for vertically resolved Chl a concentrations. (ii) Improving current knowledge about nutrient exchanges, ice algal recruitment, and motion is critical to improve sea ice biogeochemical modeling. (iii) Ice algae may bloom despite some degree of basal melting. (iv) Ice algal motility driven by gradients in limiting factors is a plausible mechanism to explain their vertical distribution. (v) Different ice algal bloom and net primary production (NPP) patterns were identified in the ice types studied, suggesting that ice algal maximal growth rates will increase, while sea ice vertically integrated NPP and biomass will decrease as a result of the predictable increase in the area covered by refrozen leads in the Arctic Ocean.

  10. Providing Real-time Sea Ice Modeling Support to the U.S. Coast Guard

    Science.gov (United States)

    Allard, Richard; Dykes, James; Hebert, David; Posey, Pamela; Rogers, Erick; Wallcraft, Alan; Phelps, Michael; Smedstad, Ole Martin; Wang, Shouping; Geiszler, Dan

    2016-04-01

    The Naval Research Laboratory (NRL) supported the U.S. Coast Guard Research Development Center (RDC) through a demonstration project during the summer and autumn of 2015. Specifically, a modeling system composed of a mesoscale atmospheric model, regional sea ice model, and regional wave model were loosely coupled to provide real-time 72-hr forecasts of environmental conditions for the Beaufort/Chukchi Seas. The system components included a 2-km regional Community Ice CodE (CICE) sea ice model, 15-km Coupled Ocean Atmosphere Mesoscale Prediction System (COAMPS) atmospheric model, and a 5-km regional WAVEWATCH III wave model. The wave model utilized modeled sea ice concentration fields to incorporate the effects of sea ice on waves. The other modeling components assimilated atmosphere, ocean, and ice observations available from satellite and in situ sources. The modeling system generated daily 72-hr forecasts of synoptic weather (including visibility), ice drift, ice thickness, ice concentration and ice strength for missions within the economic exclusion zone off the coast of Alaska and a transit to the North Pole in support of the National Science Foundation GEOTRACES cruise. Model forecasts graphics were shared on a common web page with selected graphical products made available via ftp for bandwidth limited users. Model ice thickness and ice drift show very good agreement compared with Cold Regions Research and Engineering Laboratory (CRREL) Ice Mass Balance buoys. This demonstration served as a precursor to a fully coupled atmosphere-ocean-wave-ice modeling system under development. National Ice Center (NIC) analysts used these model data products (CICE and COAMPS) along with other existing model and satellite data to produce the predicted 48-hr position of the ice edge. The NIC served as a liaison with the RDC and NRL to provide feedback on the model predictions. This evaluation provides a baseline analysis of the current models for future comparison studies

  11. Modeling the Floe-Size Distribution to Improve the Prediction of Sea Ice in the Marginal Seas

    Science.gov (United States)

    2002-09-30

    in basin-scale, rheology-type sea ice models. Lateral ablation and sea ice mechanics depend on the size of floes and yet their distribution in present-day models is assumed to be homogeneous in space and constant in time .

  12. The Arctic Sea ice in the CMIP3 climate model ensemble – variability and anthropogenic change

    Directory of Open Access Journals (Sweden)

    L. K. Behrens

    2012-12-01

    Full Text Available The strongest manifestation of global warming is observed in the Arctic. The warming in the Arctic during the recent decades is about twice as strong as in the global average and has been accompanied by a summer sea ice decline that is very likely unprecedented during the last millennium. Here, Arctic sea ice variability is analyzed in the ensemble of CMIP3 models. Complementary to several previous studies, we focus on regional aspects, in particular on the Barents Sea. We also investigate the changes in the seasonal cycle and interannual variability. In all regions, the models predict a reduction in sea ice area and sea ice volume during 1900–2100. Toward the end of the 21st century, the models simulate higher sea ice area variability in September than in March, whereas the variability in the preindustrial control runs is higher in March. Furthermore, the amplitude and phase of the sea ice seasonal cycle change in response to enhanced greenhouse warming. The amplitude of the sea ice area seasonal cycle increases due to the very strong sea ice area decline in September. The seasonal cycle amplitude of the sea ice volume decreases due to the stronger reduction of sea ice volume in March.

    Multi-model mean estimates for the late 20th century are comparable with observational data only for the entire Arctic and the Central Arctic. In the Barents Sea, differences between the multi-model mean and the observational data are more pronounced. Regional sea ice sensitivity to Northern Hemisphere average surface warming has been investigated.

  13. An analytical model for wind-driven Arctic summer sea ice drift

    Directory of Open Access Journals (Sweden)

    H.-S. Park

    2015-03-01

    Full Text Available The authors present an approximate analytical model for wind-induced sea-ice drift that includes an ice–ocean boundary layer with an Ekman spiral in the ocean velocity. This model provides an analytically tractable solution that is most applicable to the marginal ice zone, where sea-ice concentration is substantially below 100%. The model closely reproduces the ice and upper-ocean velocities observed recently by the first ice-tethered profiler equipped with a velocity sensor (ITPV. The analytical tractability of our model allows efficient calculation of the sea-ice velocity provided that the surface wind field is known and that the ocean surface geostrophic velocity is relatively weak. The model is applied to estimate intraseasonal variations in Arctic sea ice cover due to short-timescale (around 1 week intensification of the southerly winds. Utilizing 10 m surface winds from ERA-Interim reanalysis, the wind-induced sea-ice velocity and the associated changes in sea-ice concentration are calculated and compared with satellite observations. The analytical model captures the observed reduction of Arctic sea-ice concentration associated with the strengthening of southerlies on intraseasonal time scales. Further analysis indicates that the wind-induced surface Ekman flow in the ocean increases the sea-ice drift speed by 50% in the Arctic summer. It is proposed that the southerly wind-induced sea-ice drift, enhanced by the ocean's surface Ekman transport, can lead to substantial reduction in sea-ice concentration over a timescale of one week.

  14. Improved sea-ice radiative processes in a global coupled climate model

    Institute of Scientific and Technical Information of China (English)

    LIU Jiping; ZHANG Zhanhai; WU Huiding

    2005-01-01

    The NASA Goddard Institute for Space Studies (GISS) coupled global climate model was used to investigate the sensitivity of sea ice to improved representations of sea-ice radiative processes: (1) a more sophisticated surface albedo scheme and (2) the penetration of solar radiation in sea ice. The results show that the large-scale sea-ice conditions are very sensitive to the aforementioned parameterizations. Although the more sophisticated surface albedo scheme produces a more realistic seasonal cycle of the surface albedo as compared with the baseline simulation, the resulting higher albedo relative to the baseline simulation generates much more and thicker ice in the arctic. The penetration of solar radiation in sea-ice itself tends to reduce the ice cover and thickness in the entire arctic and the western antarctic, and increase the ice cover and thickness in the eastern antarctic. The combination of (1) and (2) significantly improves the simulations of the average ice thickness and its spatial distribution in the arctic. The atmospheric responses associated with sea-ice changes were also discussed. While improvements are seen, particularly of the ice thickness distribution, there are still some unrealistic aspects that will require further improvements to the sea-ice component.

  15. Comparison of advanced Arctic Ocean model sea ice fields to satellite derived measurements

    OpenAIRE

    Dimitriou, David S.

    1998-01-01

    Approved for public release; distribution is unlimited Numerical models have proven integral to the study of climate dynamics. Sea ice models are critical to the improvement of general circulation models used to study the global climate. The object of this study is to evaluate a high resolution ice-ocean coupled model by comparing it to derived measurements from SMMR and SSM/I satellite observations. Utilized for this study was the NASA Goddard Space Flight (GSFC) Sea Ice Concentration Dat...

  16. Sea-ice evaluation of NEMO-Nordic 1.0: a NEMO–LIM3.6-based ocean–sea-ice model setup for the North Sea and Baltic Sea

    Directory of Open Access Journals (Sweden)

    P. Pemberton

    2017-08-01

    Full Text Available The Baltic Sea is a seasonally ice-covered marginal sea in northern Europe with intense wintertime ship traffic and a sensitive ecosystem. Understanding and modeling the evolution of the sea-ice pack is important for climate effect studies and forecasting purposes. Here we present and evaluate the sea-ice component of a new NEMO–LIM3.6-based ocean–sea-ice setup for the North Sea and Baltic Sea region (NEMO-Nordic. The setup includes a new depth-based fast-ice parametrization for the Baltic Sea. The evaluation focuses on long-term statistics, from a 45-year long hindcast, although short-term daily performance is also briefly evaluated. We show that NEMO-Nordic is well suited for simulating the mean sea-ice extent, concentration, and thickness as compared to the best available observational data set. The variability of the annual maximum Baltic Sea ice extent is well in line with the observations, but the 1961–2006 trend is underestimated. Capturing the correct ice thickness distribution is more challenging. Based on the simulated ice thickness distribution we estimate the undeformed and deformed ice thickness and concentration in the Baltic Sea, which compares reasonably well with observations.

  17. Sea-ice evaluation of NEMO-Nordic 1.0: a NEMO-LIM3.6-based ocean-sea-ice model setup for the North Sea and Baltic Sea

    Science.gov (United States)

    Pemberton, Per; Löptien, Ulrike; Hordoir, Robinson; Höglund, Anders; Schimanke, Semjon; Axell, Lars; Haapala, Jari

    2017-08-01

    The Baltic Sea is a seasonally ice-covered marginal sea in northern Europe with intense wintertime ship traffic and a sensitive ecosystem. Understanding and modeling the evolution of the sea-ice pack is important for climate effect studies and forecasting purposes. Here we present and evaluate the sea-ice component of a new NEMO-LIM3.6-based ocean-sea-ice setup for the North Sea and Baltic Sea region (NEMO-Nordic). The setup includes a new depth-based fast-ice parametrization for the Baltic Sea. The evaluation focuses on long-term statistics, from a 45-year long hindcast, although short-term daily performance is also briefly evaluated. We show that NEMO-Nordic is well suited for simulating the mean sea-ice extent, concentration, and thickness as compared to the best available observational data set. The variability of the annual maximum Baltic Sea ice extent is well in line with the observations, but the 1961-2006 trend is underestimated. Capturing the correct ice thickness distribution is more challenging. Based on the simulated ice thickness distribution we estimate the undeformed and deformed ice thickness and concentration in the Baltic Sea, which compares reasonably well with observations.

  18. A New Discrete Element Sea-Ice Model for Earth System Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Turner, Adrian Keith [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-03-10

    Sea ice forms a frozen crust of sea water oating in high-latitude oceans. It is a critical component of the Earth system because its formation helps to drive the global thermohaline circulation, and its seasonal waxing and waning in the high north and Southern Ocean signi cantly affects planetary albedo. Usually 4{6% of Earth's marine surface is covered by sea ice at any one time, which limits the exchange of heat, momentum, and mass between the atmosphere and ocean in the polar realms. Snow accumulates on sea ice and inhibits its vertical growth, increases its albedo, and contributes to pooled water in melt ponds that darken the Arctic ice surface in the spring. Ice extent and volume are subject to strong seasonal, inter-annual and hemispheric variations, and climatic trends, which Earth System Models (ESMs) are challenged to simulate accurately (Stroeve et al., 2012; Stocker et al., 2013). This is because there are strong coupled feedbacks across the atmosphere-ice-ocean boundary layers, including the ice-albedo feedback, whereby a reduced ice cover leads to increased upper ocean heating, further enhancing sea-ice melt and reducing incident solar radiation re ected back into the atmosphere (Perovich et al., 2008). A reduction in perennial Arctic sea-ice during the satellite era has been implicated in mid-latitude weather changes, including over North America (Overland et al., 2015). Meanwhile, most ESMs have been unable to simulate observed inter-annual variability and trends in Antarctic sea-ice extent during the same period (Gagne et al., 2014).

  19. On the influence of model physics on simulations of Arctic and Antarctic sea ice

    Directory of Open Access Journals (Sweden)

    F. Massonnet

    2011-09-01

    Full Text Available Two hindcast (1983–2007 simulations are performed with the global, ocean-sea ice models NEMO-LIM2 and NEMO-LIM3 driven by atmospheric reanalyses and climatologies. The two simulations differ only in their sea ice component, while all other elements of experimental design (resolution, initial conditions, atmospheric forcing are kept identical. The main differences in the sea ice models lie in the formulation of the subgrid-scale ice thickness distribution, of the thermodynamic processes, of the sea ice salinity and of the sea ice rheology. To assess the differences in model skill over the period of investigation, we develop a set of metrics for both hemispheres, comparing the main sea ice variables (concentration, thickness and drift to available observations and focusing on both mean state and seasonal to interannual variability. Based upon these metrics, we discuss the physical processes potentially responsible for the differences in model skill. In particular, we suggest that (i a detailed representation of the ice thickness distribution increases the seasonal to interannual variability of ice extent, with spectacular improvement for the simulation of the recent observed summer Arctic sea ice retreats, (ii the elastic-viscous-plastic rheology enhances the response of ice to wind stress, compared to the classical viscous-plastic approach, (iii the grid formulation and the air-sea ice drag coefficient affect the simulated ice export through Fram Strait and the ice accumulation along the Canadian Archipelago, and (iv both models show less skill in the Southern Ocean, probably due to the low quality of the reanalyses in this region and to the absence of important small-scale oceanic processes at the models' resolution (~1°.

  20. Sea Ice Brightness Temperature as a Function of Ice Thickness, Part II: Computed curves for thermodynamically modelled ice profiles

    CERN Document Server

    Mills, Peter

    2012-01-01

    Ice thickness is an important variable for climate scientists and is still an unsolved problem for satellite remote sensing specialists. There has been some success detecting the thickness of thin ice from microwave radiometers, and with this in mind this study attempts to model the thickness-radiance relation of sea ice at frequencies employed by the Soil Moisture and Ocean Salinity (SMOS) radiometer and the Advanced Microwave Scanning Radiometer (AMSR): between 1.4 and 89 GHz. In the first part of the study, the salinity of the ice was determined by a pair of empirical relationships, while the temperature was determined by a thermodynamic model. Because the thermodynamic model can be used as a simple ice growth model, in this, second part, the salinities are determined by the growth model. Because the model uses two, constant-weather scenarios representing two extremes ("fall freeze-up" and "winter cold snap"), brine expulsion is modelled with a single correction-step founded on mass conservation. The growt...

  1. Impacts of freshwater changes on Antarctic sea ice in an eddy-permitting sea-ice-ocean model

    Science.gov (United States)

    Haid, Verena; Iovino, Doroteaciro; Masina, Simona

    2017-06-01

    In a warming climate, satellite data indicate that the sea ice extent around Antarctica has increased over the last decades. One of the suggested explanations is the stabilizing effect of increased mass loss of the Antarctic ice sheet. Here, we investigate the sea ice response to changes in both the amount and the spatial distribution of freshwater input to the ocean by comparing a set of numerical sensitivity simulations with additional supply of water at the Antarctic ocean surface. We analyze the short-term response of the sea ice cover and the on-shelf water column to variations in the amount and distribution of the prescribed surface freshwater flux.Our results confirm that enhancing the freshwater input can increase the sea ice extent. Our experiments show a negative development of the sea ice extent only for extreme freshwater additions. We find that the spatial distribution of freshwater is of great influence on sea ice concentration and thickness as it affects sea ice dynamics and thermodynamics. For strong regional contrasts in the freshwater addition the dynamic response dominates the local change in sea ice, which generally opposes the thermodynamic response. Furthermore, we find that additional coastal runoff generally leads to fresher and warmer dense shelf waters.

  2. A prognostic model of the sea ice floe size and thickness distribution

    Directory of Open Access Journals (Sweden)

    C. Horvat

    2015-05-01

    Full Text Available Sea ice exhibits considerable seasonal and longer-term variations in extent, concentration, thickness and age, and is characterized by a complex and continuously changing distribution of floe sizes and thicknesses. Models of sea ice used in current climate models keep track of its concentration and of the distribution of ice thicknesses, but do not account for the floe size distribution and its potential effects on air–sea exchange and sea-ice evolution. Accurately capturing sea-ice variability in climate models may require a better understanding and representation of the distribution of floe sizes and thicknesses. We develop and demonstrate a model for the evolution of the joint sea-ice floe size and thickness distribution that depends on atmospheric and oceanic forcing fields. The model accounts for effects due to multiple processes that are active in the marginal and seasonal ice zones: freezing and melting along the lateral side and base of floes, mechanical interactions due to floe collisions (ridging and rafting and sea-ice fracture due to swell propagation into the ice pack. The model is then examined and demonstrated in a series of idealized test cases.

  3. Modeled Arctic sea ice evolution through 2300 in CMIP5 extended RCPs

    Directory of Open Access Journals (Sweden)

    P. J. Hezel

    2014-07-01

    Full Text Available Almost all global climate models and Earth system models that participated in the Coupled Model Intercomparison Project 5 (CMIP5 show strong declines in Arctic sea ice extent and volume under the highest forcing scenario of the representative concentration pathways (RCPs through 2100, including a transition from perennial to seasonal ice cover. Extended RCP simulations through 2300 were completed for a~subset of models, and here we examine the time evolution of Arctic sea ice in these simulations. In RCP2.6, the summer Arctic sea ice extent increases compared to its minimum following the peak radiative forcing in 2044 in all nine models. RCP4.5 demonstrates continued summer Arctic sea ice decline after the forcing stabilizes due to continued warming on longer timescales. Based on the analysis of these two scenarios, we suggest that Arctic summer sea ice extent could begin to recover if and when radiative forcing from greenhouse gas concentrations were to decrease. In RCP8.5 the Arctic Ocean reaches annually ice-free conditions in seven of nine models. The ensemble of simulations completed under the extended RCPs provide insight into the global temperature increase at which sea ice disappears in the Arctic and the reversibility of declines in seasonal sea ice extent.

  4. Modeling of Electromagnetic Waves Scattering from Snow Covered First Year Sea Ice

    Science.gov (United States)

    Komarov, A. S.; Barber, D. G.; Isleifson, D. K.

    2011-12-01

    Modeling of electromagnetic wave interaction with sea ice is required for various remote sensing applications, such as an interpretation of Synthetic Aperture Radar (SAR) imagery over sea ice. In this study, we present numerical modeling of the Normalized Radar Cross Section (NRCS) at vertical and horizontal polarizations from snow covered First Year (FY) sea ice. We consider sea ice as a layered medium with an arbitrary profile of dielectric constant, and the snow cover as a homogeneous layer on the top of the sea ice. Surface scattering at the snow-sea ice interface was taken into account by the first-order approximation of the small perturbation method. We obtained an analytical formulation for radar cross-sections at vertical and horizontal polarizations and conducted numerical modeling of the backscattering characteristics. The solution derived for NRCSs includes reflection coefficients from snow and sea ice. The calculation of reflection coefficients from the stratified sea ice is considered separately as an auxiliary problem. In-situ geophysical properties of snow and sea ice collected during the Circumpolar Flow Lead (CFL) system study project were used to estimate the dielectric constants of snow and sea ice for several case studies. The dielectric constant of the sea ice was calculated using the Polder-van-Santen/de Loor (PVD) mixture model, while the dielectric constant of the snow was estimated using a Debye-like model. The calculated angular dependencies of the NRCSs (HH- and VV- polarizations) and co-polarization ratios were compared with in-situ C-band scatterometer measurements. These comparisons demonstrate a good agreement between simulated and observed scattering characteristics.

  5. Reversability of arctic sea ice retreat - A conceptual multi-scale modeling approach

    Science.gov (United States)

    Mueller-Stoffels, Marc

    The ice-albedo feedback has been identified as an important factor in the decay of the Arctic sea ice cover in a warming climate. Mechanisms of transition from perennial ice cover to seasonal ice cover are discussed in the literature; the existence of a tipping point is disputed. A newly developed regular network model for energy exchange and phase transition of an ice covered ocean mixed layer is introduced. The existence of bistability, a key ingredient for irreversibility, on local and regional scales is explored. It is shown in a spatially confined model that the asymptotic behavior and the existence of a parameter region of bistability strongly depend on the albedo parametrization. The spatial dynamics of sea ice retreat are studied for a high resolution latitudinal model of the ocean mixed layer. This regional model suggests that sea ice retreat is reversible. It is shown that laterally driven melt of thick multi-year sea ice, and thus, ice-albedo feedback, is an important mechanism in the transition from perennial to seasonal ice cover at the pole. Results are used to interpret observed changes in the recent ice extent and ice volume record. It is shown that the effectiveness of ice-albedo feedback strongly depends on the existence of lateral heat transfer mechanisms in the ocean.

  6. Level-Ice Melt Ponds in the Los Alamos Sea Ice Model, CICE

    Science.gov (United States)

    2012-12-06

    physical features such as snow topography and hydraulic meltwater transport rates both laterally and vertically. Departing from the cellular automaton...parameterizations before, or are mod- eled here in a different manner from prior work. When meltwater forms with snow still on the ice, the water is...thickest ice, near Greenland and the Canadian Arctic. A larger fraction of this thicker sea ice is ridged, less level ice is available for ponding, and

  7. Sensitivity of the recent increase in Antarctic sea ice in ocean models

    Science.gov (United States)

    Kjellsson, Joakim; Holland, Paul; Marshall, Gareth; Coward, Andrew; Aksenov, Yevgeny; Bacon, Sheldon; Megann, Alexis; Ridley, Jeff

    2015-04-01

    We study the recent increase in Antarctic sea ice using a coupled ocean--sea ice model forced by atmospheric reanalysis. We investigate the impact on sea ice from both model parameters (e.g. vertical mixing and eddy parameterisation) as well as external forcing (e.g. precipitation and melt water from the Antarctic continent). We use the NEMO ocean model coupled to the CICE sea-ice model at 1 degree horizontal resolution forced with ERA-Interim reanalysis. The results will have impacts for our understanding of the Southern Ocean, its sea ice and their representation in future coupled climate-model studies, e.g. CMIP6. Since the dawn of the satellite era there has been a slow increase in Antarctic sea ice with pronounced spatial structure. The reason for this increase is not yet fully understood and very few climate-model simulations reproduce the observed mean state and/or increase. By varying model parameters and external forcing, we determine that obtaining a realistic sea ice cover requires a complex balance of horizontal and vertical mixing as well as fresh water input. The surface fresh water balance impacts the vertical salinity gradient and thus vertical fluxes of heat and salt. Underestimation of precipitation or melt water results in deep convection in the open ocean and the opening of large polynyas in the Weddell and Ross sea. The presence of polynyas reduces the sea ice extent. The depth of the mixed layer has a large impact on the sea ice seasonal cycle. The summer mixed layer must be sufficiently deep to prevent SST from becoming too high but not so deep as to mix up heat and salt from below. In winter, a deep mixed layer lets brine rejected from sea ice mix down to depths below that of the summer mixed layer thus maintaining a necessary stratification.

  8. A comprehensive view of Kara Sea polynya dynamics, sea-ice compactness and export from model and remote sensing data

    Science.gov (United States)

    Kern, S.; Harms, I.; Bakan, S.; Chen, Y.

    2005-08-01

    The Shelf Seas of the Arctic are known for their large sea-ice production. This paper presents a comprehensive view of the Kara Sea sea-ice cover from high-resolution numerical modeling and space-borne microwave radiometry. As given by the latter the average polynya area in the Kara Sea takes a value of 21.2 × 103 km2 +/- 9.1 × 103 km2 for winters (Jan.-Apr.) 1996/97 to 2000/01, being as high as 32.0 × 103 km2 in 1999/2000 and below 12 × 103 km2 in 1998/99. Day-to-day variations of the Kara Sea polynya area can be as high as 50 × 103 km2. For the seasons 1996/97 to 2000/01 the modeled cumulative winter ice-volume flux out of the Kara Sea varied between 100 km3a-1 and 350 km3a-1. Modeled high (low) ice export coincides with a high (low) average and cumulative polynya area, and with a low (high) sea-ice compactness in the Kara Sea from remote sensing data, and with a high (low) sea-ice drift speed across its northern boundary derived from independent model data for the winters 1996/97 to 2000/01.

  9. Current state and future perspectives on coupled ice-sheet – sea-level modelling

    NARCIS (Netherlands)

    de Boer, B.; Stocchi, P.; Whitehouse, P.L.; van de Wal, R.S.W.

    2017-01-01

    The interaction between ice-sheet growth and retreat and sea-level change has been an established fieldof research for many years. However, recent advances in numerical modelling have shed new light on theprecise interaction of marine ice sheets with the change in near-field sea level, and the

  10. Long-term mesoscale variability of modelled sea-ice primary production in the northern Baltic Sea

    Directory of Open Access Journals (Sweden)

    Letizia Tedesco

    2017-06-01

    Full Text Available We describe a new ocean-sea ice-biogeochemical model, apply it to the Bothnian Bay in the northern Baltic Sea for the time period 1991–2007 and provide the first long-term mesoscale estimates of modelled sea-ice primary production in the northern Baltic Sea. After comparing the available physical and biogeochemical observations within the study area and the time period investigated with the model results, we show the modelled spatial, intra- and interannual variability in sea-ice physical and biogeochemical properties and consider the main factors limiting ice algal primary production. Sea-ice permeability in the studied area was low compared with the polar oceans, which appeared to be a major reason for the generally low primary production rates. Although the sea ice was less saline in the northernmost parts of the basin, these parts were characterized by sea ice with a larger amount of habitable space, higher levels of photosynthetically active radiation and increased macronutrient availability near the coast, which favoured higher algal growth rates. Other parts of the southern central basin were mostly co-limited by less favourable light conditions (i.e., earlier ice breakups associated with fewer sunlight hours and lower seawater macronutrient concentrations than in the coastal zones. Although a change towards milder winters (i.e., reduced ice cover, thickness and length of the ice season was previously detected on a half-century timescale and could partly be seen here, analysis of the temporal evolution of sea-ice biogeochemical properties showed no significant trends over time, though these properties were characterized by large interannual variability.

  11. Regular network model for the sea ice-albedo feedback in the Arctic.

    Science.gov (United States)

    Müller-Stoffels, Marc; Wackerbauer, Renate

    2011-03-01

    The Arctic Ocean and sea ice form a feedback system that plays an important role in the global climate. The complexity of highly parameterized global circulation (climate) models makes it very difficult to assess feedback processes in climate without the concurrent use of simple models where the physics is understood. We introduce a two-dimensional energy-based regular network model to investigate feedback processes in an Arctic ice-ocean layer. The model includes the nonlinear aspect of the ice-water phase transition, a nonlinear diffusive energy transport within a heterogeneous ice-ocean lattice, and spatiotemporal atmospheric and oceanic forcing at the surfaces. First results for a horizontally homogeneous ice-ocean layer show bistability and related hysteresis between perennial ice and perennial open water for varying atmospheric heat influx. Seasonal ice cover exists as a transient phenomenon. We also find that ocean heat fluxes are more efficient than atmospheric heat fluxes to melt Arctic sea ice.

  12. Future Arctic marine access: analysis and evaluation of observations, models, and projections of sea ice

    Directory of Open Access Journals (Sweden)

    T. S. Rogers

    2013-02-01

    Full Text Available There is an emerging need for regional applications of sea ice projections to provide more accuracy and greater detail to scientists, national, state and local planners, and other stakeholders. The present study offers a prototype for a comprehensive, interdisciplinary study to bridge observational data, climate model simulations, and user needs. The study's first component is an observationally based evaluation of Arctic sea ice trends during 1980–2008, with an emphasis on seasonal and regional differences relative to the overall pan-Arctic trend. Regional sea ice loss has varied, with a significantly larger decline of winter maximum (January–March extent in the Atlantic region than in other sectors. A lead–lag regression analysis of Atlantic sea ice extent and ocean temperatures indicates that reduced sea ice extent is associated with increased Atlantic Ocean temperatures. Correlations between the two variables are greater when ocean temperatures lag rather than lead sea ice. The performance of 13 global climate models is evaluated using three metrics to compare sea ice simulations with the observed record. We rank models over the pan-Arctic domain and regional quadrants and synthesize model performance across several different studies. The best performing models project reduced ice cover across key access routes in the Arctic through 2100, with a lengthening of seasons for marine operations by 1–3 months. This assessment suggests that the Northwest and Northeast Passages hold potential for enhanced marine access to the Arctic in the future, including shipping and resource development opportunities.

  13. Future Arctic marine access: analysis and evaluation of observations, models, and projections of sea ice

    Directory of Open Access Journals (Sweden)

    T. S. Rogers

    2012-09-01

    Full Text Available There is an emerging need for regional applications of sea ice projections to provide more accuracy and greater detail to scientists, national, state and local planners, and other stakeholders. The present study offers a prototype for a comprehensive, interdisciplinary study to bridge observational data, climate model simulations, and user needs. The study's first component is an observationally-based evaluation of Arctic sea ice trends during 1980–2008, with an emphasis on seasonal and regional differences relative to the overall pan-Arctic trend. Regional sea ice los has varied, with a significantly larger decline of winter maximum (January–March extent in the Atlantic region than in other sectors. A lead-lag regression analysis of Atlantic sea ice extent and ocean temperatures indicates that reduced sea ice extent is associated with increased Atlantic Ocean temperatures. Correlations between the two variables are greater when ocean temperatures lag rather than lead sea ice. The performance of 13 global climate models is evaluated using three metrics to compare sea ice simulations with the observed record. We rank models over the pan-Arctic domain and regional quadrants, and synthesize model performance across several different studies. The best performing models project reduced ice cover across key access routes in the Arctic through 2100, with a lengthening of seasons for marine operations by 1–3 months. This assessment suggests that the Northwest and Northeast Passages hold potential for enhanced marine access to the Arctic in the future, including shipping and resource development opportunities.

  14. Toward Unanimous Projections for Sea Ice Using CMIP5 Multi-model Simulations

    Science.gov (United States)

    Yang, S.; Christensen, J. H.; Langen, P. P.; Thejll, P.

    2015-12-01

    Coupled global climate models have been used to provide future climate projections as major objective tools based on physical laws that govern the dynamics and thermodynamics of the climate system. However, while climate models in general predict declines in Arctic sea ice cover (i.e., ice extent and volume) from late 20th century through the next decades in response to increase of anthropogenic forcing, the model simulated Arctic sea ice demonstrates considerable biases in both the mean and the declining trend in comparison with the observations over the satellite era (1979-present). The models also show wide inter-model spread in hindcast and projected sea ice decline, raising the question of uncertainty in model predicted polar climate. In order to address the model uncertainty in the Arctic sea ice projection, we analyze the Arctic sea ice extent under the context of surface air temperature (SAT) as simulated in the historical, RCP4.5 and RCP8.5 experiments by 27 CMIP5 models. These 27 models are all we could obtain from the CMIP5 archive with sufficient gird information for processing the sea ice data. Unlike many previous studies in which only limited number of models were selected based on metrics of modeled sea ice characteristics for getting projected ice with reduced uncertainty, our analysis is applied to all model simulations with no discrimination. It is found that the changes in total Arctic sea ice in various seasons from one model are closely related to the changes in global mean SAT in the corresponding model. This relationship appears very similar in all models and agrees well with that in the observational data. In particular, the ratio of the total Arctic sea ice changes in March, September and annual mean with respect to the baseline climatology (1979-2008) are seen to linearly correlate to the global mean annual SAT anomaly, suggesting unanimous projection of the sea ice extent may be possible with this relationship. Further analysis is

  15. Parameterisation of sea and lake ice in numerical weather prediction models of the German Weather Service

    Directory of Open Access Journals (Sweden)

    Dmitrii Mironov

    2012-04-01

    Full Text Available A bulk thermodynamic (no rheology sea-ice parameterisation scheme for use in numerical weather prediction (NWP is presented. The scheme is based on a self-similar parametric representation (assumed shape of the evolving temperature profile within the ice and on the integral heat budget of the ice slab. The scheme carries ordinary differential equations (in time for the ice surface temperature and the ice thickness. The proposed sea-ice scheme is implemented into the NWP models GME (global and COSMO (limited-area of the German Weather Service. In the present operational configuration, the horizontal distribution of the sea ice is governed by the data assimilation scheme, no fractional ice cover within the GME/COSMO grid box is considered, and the effect of snow above the ice is accounted for through an empirical temperature dependence of the ice surface albedo with respect to solar radiation. The lake ice is treated similarly to the sea ice, except that freeze-up and break-up of lakes occurs freely, independent of the data assimilation. The sea and lake ice schemes (the latter is a part of the fresh-water lake parameterisation scheme FLake show a satisfactory performance in GME and COSMO. The ice characteristics are not overly sensitive to the details of the treatment of heat transfer through the ice layer. This justifies the use of a simplified but computationally efficient bulk approach to model the ice thermodynamics in NWP, where the ice surface temperature is a major concern whereas details of the temperature distribution within the ice are of secondary importance. In contrast to the details of the heat transfer through the ice, the cloud cover is of decisive importance for the ice temperature as it controls the radiation energy budget at the ice surface. This is particularly true for winter, when the long-wave radiation dominates the surface energy budget. During summer, the surface energy budget is also sensitive to the grid-box mean ice

  16. Jet formation at the sea ice edge

    Science.gov (United States)

    Feltham, D. L.; Heorton, H. D.

    2014-12-01

    The sea ice edge presents a region of many feedback processes between the atmosphere, ocean and sea ice, which are inadequately represented in current climate models. Here we focus on on-ice atmospheric and oceanic flows at the sea ice edge. Mesoscale jet formation due to the Coriolis effect is well understood over sharp changes in surface roughness such as coastlines. This sharp change in surface roughness is experienced by the atmosphere flowing over, and ocean flowing under, a compacted sea ice edge. We have studied a dynamic sea ice edge responding to atmospheric and oceanic jet formation. The shape and strength of atmospheric and oceanic jets during on-ice flows is calculated from existing studies of the sea ice edge and prescribed to idealised models of the sea ice edge. An idealised analytical model of sea ice drift is developed and compared to a sea ice climate model (the CICE model) run on an idealised domain. The response of the CICE model to jet formation is tested at various resolutions. We find that the formation of atmospheric jets during on-ice winds at the sea ice edge increases the wind speed parallel to the sea ice edge and results in the formation of a sea ice edge jet. The modelled sea ice edge jet is in agreement with an observed jet although more observations are needed for validation. The increase in ice drift speed is dependent upon the angle between the ice edge and wind and can result in a 40% increase in ice transport along the sea ice edge. The possibility of oceanic jet formation during on-ice currents and the resultant effect upon the sea ice edge is less conclusive. Observations and climate model data of the polar oceans has been analysed to show areas of likely atmospheric jet formation, with the Fram Strait being of particular interest.

  17. The Effect of Ice Shelf Meltwater on Antarctic Sea Ice and the Southern Ocean in an Earth System Model

    Science.gov (United States)

    Pauling, A.; Bitz, C. M.; Smith, I.; Langhorne, P.

    2015-12-01

    It has been suggested that recent Antarctic sea ice expansion resulted from an increase in fresh water reaching the Southern Ocean. This presentation investigates this conjecture in an Earth System Model. The freshwater flux from ice sheet and ice shelf mass imbalance is largely missing in models that participated in the Fifth Coupled Model Intercomparison Project (CMIP5). However, CMIP5 models do account for the fresh water from precipitation minus evaporation (P-E). On average in CMIP5 models P- E reaching the Southern Ocean has increased to a present value of about 2600 Gt yr-1 greater than pre-industrial times and 3-8 times larger than estimates of the mass imbalance of Antarctic ice sheets and shelves. Two sets of model experiments were conducted from 1980-2013 in CESM1-CAM5 artificially distributing fresh water either at the ocean surface according to an estimate of iceberg melt, or at the ice shelf fronts at depth. An anomalous reduction in vertical advection of heat into the surface mixed layer resulted in sea surface cooling at high southern latitudes, and an associated increase in sea ice area. A freshwater enhancement of 1780 Gt yr-1 (approximately 1.3 times either present day basal melt or iceberg calving freshwater fluxes) raised the sea ice total area by 1×106 km2. Yet, even a freshwater enhancement up to 2670 Gt yr-1 was insufficient to offset the sea ice decline due to anthropogenic forcing for any period of 20 years or longer. Further, the sea ice response was found to be insensitive to the depth of fresh water injection.

  18. A coupled ice-ocean ecosystem model for 1-D and 3-D applications in the Bering and Chukchi Seas

    Institute of Scientific and Technical Information of China (English)

    Jin Meibing; Clara Deal; WANG Jia

    2008-01-01

    Primary production in the Bering and Chukchi Seas is strongly influenced by the annual cycle of sea ice. Here pelagic and sea ice algal ecosystems coexist and interact with each other. Ecosystem modeling of sea ice associated phytoplankton blooms has been understudied compared to open water ecosystem model applications.This study introduces a general coupled ice-ocean ecosystem model with equations and parameters for 1-D and 3-D applications that is based on 1-D coupled ice-ocean ecosystem model development in the landfast ice in the Chukchi Sea and marginal ice zone of Bering Sea. The biological model includes both pelagic and sea ice algal habitats with 10 compartments: three phytoplankton (pelagic diatom, flagellates and ice algae: D, F, and Ai), three zooplankton (copepods, large zooplankton, and microzooplankton: ZS, ZL, ZP), three nutrients (nitrate + nitrite, ammonium, silicon:NO3, NH4, Si) and detritus (Det). The coupling of the biological models with physical ocean models is straightforward with just the addition of the advection and diffusion terms to the ecosystem model. The coupling with a multi-category sea ice model requires the same calculation of the sea ice ecosystem model in each ice thickness category and the redistribution between categories caused by both dynamic and thermodynamic forcing as in the physical model. Phytoplankton and ice algal self-shading effect is the sole feedback from the ecosystem model to the physical model.

  19. A viscoelastic-plastic constitutive model with Mohr-Coulomb yielding criterion for sea ice dynamics

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    A new viscoelastic-plastic (VEP) constitutive model for sea ice dynamics was developed based on continuum mechanics. This model consists of four components: Kelvin-Vogit viscoelastic model, Mohr-Coulomb yielding criterion, associated normality flow rule for plastic rehololgy, and hydrostatic pressure. The numerical simulations for ice motion in an idealized rectangular basin were made using smoothed particle hydrodynamics (SPH) method, and compared with the analytical solution as well as those based on the modified viscous plastic(VP) model and static ice jam theory. These simulations show that the new VEP modelcan simulate ice dynamics accurately. The new constitutive model was further applied to simulate ice dynamics of the Bohai Sea and compared with the traditional VP, and modified VP models. The results of the VEP model are compared better with the satellite remote images, and the simulated ice conditions in the JZ20-2 oil platform area were more reasonable.

  20. Influence of coupling on atmosphere, sea ice and ocean regional models in the Ross Sea sector, Antarctica

    Energy Technology Data Exchange (ETDEWEB)

    Jourdain, Nicolas C. [LGGE, UMR 5183, CNRS-UJF, Grenoble (France); LEGI, UMR 5519, CNRS-UJF-INPG, Grenoble (France); Mathiot, Pierre; Barnier, Bernard [LEGI, UMR 5519, CNRS-UJF-INPG, Grenoble (France); Gallee, Hubert [LGGE, UMR 5183, CNRS-UJF, Grenoble (France)

    2011-04-15

    Air-sea ice-ocean interactions in the Ross Sea sector form dense waters that feed the global thermohaline circulation. In this paper, we develop the new limited-area ocean-sea ice-atmosphere coupled model TANGO to simulate the Ross Sea sector. TANGO is built up by coupling the atmospheric limited-area model MAR to a regional configuration of the ocean-sea ice model NEMO. A method is then developed to identify the mechanisms by which local coupling affects the simulations. TANGO is shown to simulate realistic sea ice properties and atmospheric surface temperatures. These skills are mostly related to the skills of the stand alone atmospheric and oceanic models used to build TANGO. Nonetheless, air temperatures over ocean and winter sea ice thickness are found to be slightly improved in coupled simulations as compared to standard stand alone ones. Local atmosphere ocean feedbacks over the open ocean are found to significantly influence ocean temperature and salinity. In a stand alone ocean configuration, the dry and cold air produces an ocean cooling through sensible and latent heat loss. In a coupled configuration, the atmosphere is in turn moistened and warmed by the ocean; sensible and latent heat loss is therefore reduced as compared to the stand alone simulations. The atmosphere is found to be less sensitive to local feedbacks than the ocean. Effects of local feedbacks are increased in the coastal area because of the presence of sea ice. It is suggested that slow heat conduction within sea ice could amplify the feedbacks. These local feedbacks result in less sea ice production in polynyas in coupled mode, with a subsequent reduction in deep water formation. (orig.)

  1. Observations and modeling of the ice-ocean conditions in the coastal Chukchi and Beaufort Seas

    Institute of Scientific and Technical Information of China (English)

    JIN Meibing; WANG Jia; MIZOBATA Kohei; HU Haoguo; SHIMADA Koji

    2008-01-01

    The Chukchi and Beaufort Seas include several important hydrological features: inflow of the Pacific water, Alaska coast current (ACC), the seasonal to perennial sea ice cover, and landfast ice along the Alaskan coast. The dynamics of this coupled ice-ocean sys-tem is important for both regional scale oceanography and large-scale global climate change research. A number of moorings were de-ployed in the area by JAMSTEC since 1992, and the data revealed highly variable characteristics of the hydrological environment. A re-gional high-resolution coupled ice-ocean model of the Chukchi and Beaufort Seas was established to simulate the ice-ocean environment and unique seasonal landfast ice in the coastal Beaufort Sea. The model results reproduced the Beaufort gyre and the ACC. The depth-averaged annual mean ocean currents along the Beaufort Sea coast and shelf break compared well with data from four moored ADCPs, but the simulated velocity had smaller standard deviations, which indicate small-scale eddies were frequent in the region. The model re-suits captured the seasonal variations of sea ice area as compared with remote sensing data, and the simulated sea ice velocity showed an almost stationary area along the Beaufort Sea coast that was similar to the observed landfast ice extent. It is the combined effects of the weak oceanic current near the coast, a prevailing wind with an onshore component, the opposite direction of the ocean current, and the blocking by the coastline that make the Beaufort Sea coastal areas prone to the formation of landfast ice.

  2. Arctic Sea Ice Predictability and the Sea Ice Prediction Network

    Science.gov (United States)

    Wiggins, H. V.; Stroeve, J. C.

    2014-12-01

    Drastic reductions in Arctic sea ice cover have increased the demand for Arctic sea ice predictions by a range of stakeholders, including local communities, resource managers, industry and the public. The science of sea-ice prediction has been challenged to keep up with these developments. Efforts such as the SEARCH Sea Ice Outlook (SIO; http://www.arcus.org/sipn/sea-ice-outlook) and the Sea Ice for Walrus Outlook have provided a forum for the international sea-ice prediction and observing community to explore and compare different approaches. The SIO, originally organized by the Study of Environmental Change (SEARCH), is now managed by the new Sea Ice Prediction Network (SIPN), which is building a collaborative network of scientists and stakeholders to improve arctic sea ice prediction. The SIO synthesizes predictions from a variety of methods, including heuristic and from a statistical and/or dynamical model. In a recent study, SIO data from 2008 to 2013 were analyzed. The analysis revealed that in some years the predictions were very successful, in other years they were not. Years that were anomalous compared to the long-term trend have proven more difficult to predict, regardless of which method was employed. This year, in response to feedback from users and contributors to the SIO, several enhancements have been made to the SIO reports. One is to encourage contributors to provide spatial probability maps of sea ice cover in September and the first day each location becomes ice-free; these are an example of subseasonal to seasonal, local-scale predictions. Another enhancement is a separate analysis of the modeling contributions. In the June 2014 SIO report, 10 of 28 outlooks were produced from models that explicitly simulate sea ice from dynamic-thermodynamic sea ice models. Half of the models included fully-coupled (atmosphere, ice, and ocean) models that additionally employ data assimilation. Both of these subsets (models and coupled models with data

  3. A sea-ice thickness retrieval model for 1.4 GHz radiometry and application to airborne measurements over low salinity sea-ice

    Directory of Open Access Journals (Sweden)

    L. Kaleschke

    2010-12-01

    Full Text Available In preparation for the European Space Agency's (ESA Soil Moisture and Ocean Salinity (SMOS mission, we investigated the potential of L-band (1.4 GHz radiometry to measure sea-ice thickness.

    Sea-ice brightness temperature was measured at 1.4 GHz and ice thickness was measured along nearly coincident flight tracks during the SMOS Sea-Ice campaign in the Bay of Bothnia in March 2007. A research aircraft was equipped with the L-band Radiometer EMIRAD and coordinated with helicopter based electromagnetic induction (EM ice thickness measurements.

    We developed a three layer (ocean-ice-atmosphere dielectric slab model for the calculation of ice thickness from brightness temperature. The dielectric properties depend on the relative brine volume which is a function of the bulk ice salinity and temperature.

    The model calculations suggest a thickness sensitivity of up to 1.5 m for low-salinity (multi-year or brackish sea-ice. For Arctic first year ice the modelled thickness sensitivity is less than half a meter. It reduces to a few centimeters for temperatures approaching the melting point.

    The campaign was conducted under unfavorable melting conditions and the spatial overlap between the L-band and EM-measurements was relatively small. Despite these disadvantageous conditions we demonstrate the possibility to measure the sea-ice thickness with the certain limitation up to 1.5 m.

    The ice thickness derived from SMOS measurements would be complementary to ESA's CryoSat-2 mission in terms of the error characteristics and the spatiotemporal coverage. The relative error for the SMOS ice thickness retrieval is expected to be not less than about 20%.

  4. Analogue modelling of the influence of ice shelf collapse on the flow of ice sheets grounded below sea-level

    Science.gov (United States)

    Corti, Giacomo; Zeoli, Antonio

    2016-04-01

    The sudden breakup of ice shelves is expected to result in significant acceleration of inland glaciers, a process related to the removal of the buttressing effect exerted by the ice shelf on the tributary glaciers. This effect has been tested in previous analogue models, which however applied to ice sheets grounded above sea level (e.g., East Antarctic Ice Sheet; Antarctic Peninsula and the Larsen Ice Shelf). In this work we expand these previous results by performing small-scale laboratory models that analyse the influence of ice shelf collapse on the flow of ice streams draining an ice sheet grounded below sea level (e.g., the West Antarctic Ice Sheet). The analogue models, with dimensions (width, length, thickness) of 120x70x1.5cm were performed at the Tectonic Modelling Laboratory of CNR-IGG of Florence, Italy, by using Polydimethilsyloxane (PDMS) as analogue for the flowing ice. This transparent, Newtonian silicone has been shown to well approximate the rheology of natural ice. The silicone was allowed to flow into a water reservoir simulating natural conditions in which ice streams flow into the sea, terminating in extensive ice shelves which act as a buttress for their glaciers and slow their flow. The geometric scaling ratio was 10(-5), such that 1cm in the models simulated 1km in nature; velocity of PDMS (a few mm per hour) simulated natural velocities of 100-1000 m/year. Instability of glacier flow was induced by manually removing a basal silicone platform (floating on water) exerting backstresses to the flowing analogue glacier: the simple set-up adopted in the experiments isolates the effect of the removal of the buttressing effect that the floating platform exerts on the flowing glaciers, thus offering insights into the influence of this parameter on the flow perturbations resulting from a collapse event. The experimental results showed a significant increase in glacier velocity close to its outlet following ice shelf breakup, a process similar to what

  5. Model simulations of the annual cycle of the landfast ice thickness in the East Siberian Sea

    Institute of Scientific and Technical Information of China (English)

    YANG Yu; Matti Leppranta; LI Zhijun; Bin Cheng; ZHAI Mengxi; Denis Demchev

    2015-01-01

    The annual cycle of the thickness and temperature of landfast sea ice in the East Siberian Sea has been examined using a one-dimensional thermodynamic model. The model was calibrated for the year August 2012–July 2013, forced using the data of the Russian weather station Kotel’ny Island and ECMWF reanalyses. Thermal growth and decay of ice were reproduced well, and the maximum annual ice thickness and breakup day became 1.64 m and the end of July. Oceanic heat lfux was 2 W.m–2 in winter and raised to 25 W.m–2 in summer, albedo was 0.3–0.8 depending on the surface type (snow/ice and wet/dry). The model outcome showed sensitivity to the albedo, air temperature and oceanic heat lfux. The modelled snow cover was less than 10 cm having a small inlfuence on the ice thickness. In situ sea ice thickness in the East Siberian Sea is rarely available in publications. This study provides a method for quantitative ice thickness estimation by modelling. The result can be used as a proxy to understand the sea ice conditions on the Eurasian Arctic coast, which is important for shipping and high-resolution Arctic climate modelling.

  6. Sea ice leads in the Arctic Ocean: Model assessment, interannual variability and trends

    Science.gov (United States)

    Wang, Q.; Danilov, S.; Jung, T.; Kaleschke, L.; Wernecke, A.

    2016-07-01

    Sea ice leads in the Arctic are important features that give rise to strong localized atmospheric heating; they provide the opportunity for vigorous biological primary production, and predicting leads may be of relevance for Arctic shipping. It is commonly believed that traditional sea ice models that employ elastic-viscous-plastic (EVP) rheologies are not capable of properly simulating sea ice deformation, including lead formation, and thus, new formulations for sea ice rheologies have been suggested. Here we show that classical sea ice models have skill in simulating the spatial and temporal variation of lead area fraction in the Arctic when horizontal resolution is increased (here 4.5 km in the Arctic) and when numerical convergence in sea ice solvers is considered, which is frequently neglected. The model results are consistent with satellite remote sensing data and discussed in terms of variability and trends of Arctic sea ice leads. It is found, for example, that wintertime lead area fraction during the last three decades has not undergone significant trends.

  7. Holocene Northern Hemisphere sea-ice distribution - proxy data reconstruction and modelling

    Science.gov (United States)

    Seidenkrantz, Marit-Solveig; de Vernal, Anne; Goosse, Hugues; Klein, François; Solignac, Sandrine; Van Nieuwenhove, Nicolas; Pearce, Christof; Caissie, Beth; Belt, Simon; Sha, Longbin; Cronin, Thomas M.; Stein, Rüdiger; Macias-Fauria, Marc; DeNinno, Lauren H.

    2016-04-01

    resolution, our data indicate that sea ice was present in the Arctic throughout the Holocene and that no longer periods of absence of sea ice occurred. Our proxy data interpretations have been used to constrain model output using data assimilation in the LOVECLIM model, focusing on the period 6±0.5 ka. This period of warmer than present summer conditions can help to understand the dynamics of the system in a warmer world. As expected, data assimilation leads to an overall better agreement with the reconstructions, mainly because of changes in the simulated wind patterns. Overall, the model simulation suggests that during the Holocene Thermal Maximum sea ice distribution was controlled by a strong positive Northern Annular Mode.

  8. A modeling investigation of the Arctic sea ice-atmosphere feedback

    Science.gov (United States)

    Liptak, Jessica; Strong, Courtenay

    2016-10-01

    We examine the effects of a general sea ice-atmosphere feedback (SAF) over the Barents Sea by turning it on and off in a coupled climate model. The SAF is "turned off" by forcing the atmosphere with surface turbulent and longwave heat fluxes and surface temperatures that reflect climatological sea ice cover over the Barents Sea, while allowing the sea ice and sea surface temperature (SST) to freely evolve. Suppressing the SAF reduces the variability of near-surface air temperature ( T), sea ice concentration ( I) , and SST averaged over the Barents Sea by up to 35 %, confirming the existence of a positive thermodynamically-driven SAF found in prior uncoupled modeling studies. Decreased interannual variability accounts for most of the total reduction in I, T, and SST variability, and the largest reductions in variability occur during the winter sea ice growth and spring melt seasons. In contrast to the results from the coupled model experiment, the total variances of I, T, and SST do not significantly change in response to suppressing the SAF in a simple vector autoregressive model, indicating that the SAF is nonlinear.

  9. Snow and sea ice thermodynamics in the Arctic: Model validation and sensitivity study against SHEBA data

    Institute of Scientific and Technical Information of China (English)

    CHENG Bin; Timo Vihma; ZHANG Zhan-hai; LI Zhi-jun; WU Hui-ding

    2008-01-01

    Evolution of the Arctic sea ice and its snow cover during the SHEBA year were simulated by applying a high-resolution thermodynamic snow/ice model (HIGHTSI). Attention was paid to the impact of albedo on snow and sea ice mass balance, effect of snow on total ice mass balance, and the model vertical resolution.The SHEBA annual simulation was made applying the best possible external forcing data set created by the Sea Ice Model Intercomparison Project. The HIGHTSI control run reasonably reproduced the observed snow and ice thickness. A number of albedo schemes were incorporated into HIGHTSI to study the feedhack processes between the albedo and snow and ice thickness. The snow thickness turned out to be an essential variable in the albedo parametetization. Albedo schemes dependent on the surface temperature were liable to excessive positive feedback effects generated by errors in the modelled surface temperature. The superimposed ice formation should be taken into account for the annual Arctic sea ice mass balance.

  10. Assessment of the sea-ice carbon pump: Insights from a three-dimensional ocean-sea-ice-biogeochemical model (MPIOM/HAMOCC

    Directory of Open Access Journals (Sweden)

    R. Grimm

    2016-11-01

    Full Text Available Abstract It has been suggested that geochemical processes related to sea-ice growth and melt might be important for the polar carbon cycle via the so called sea-ice carbon pump (SICP. The SICP affects the air-sea CO2 exchange by influencing the composition of dissolved inorganic carbon (DIC and total alkalinity (TA in the surface ocean. Here we quantify the strength of the SICP-induced air-sea CO2 flux using the global three-dimensional ocean-sea-ice-biogeochemical model MPIOM/HAMOCC. Simulations prescribing the range of observed DIC and TA concentrations in the sea ice were performed under two idealized climate scenarios for the present-day and the future oceanic and sea-ice state, both forced with a fixed atmospheric CO2 concentration. Model results indicate that the SICP-induced air-sea CO2 uptake increases with higher ratios of TA:DIC prescribed in the sea ice relative to the basic oceanic TA:DIC ratios. Independent of the modeled scenario, the simulated strength of the SICP is larger in the Antarctic than in the Arctic, because of more efficient export of brine-associated DIC from the Antarctic mixed layer. On an annual basis, we generally find an enhanced SICP-induced oceanic CO2 uptake in regions with net sea-ice melt, and enhanced SICP-induced oceanic CO2 out-gassing in regions with net sea-ice growth. These general regional patterns are modified further by the blockage of air-sea gas exchange through sea-ice coverage. Integrated over the sea-ice zones of both hemispheres, the SICP-induced oceanic CO2 uptake ranges from 2 to 14 Tg C yr−1, which is up to 7% of the simulated net CO2 uptake in polar regions, but far less than 1% of the current global oceanic CO2 uptake. Hence, while we find that the SICP plays a minor role in the modern global carbon cycle, it is of importance for the regional carbon cycle at high latitudes.

  11. A hybrid Lagrangian-Eulerian numerical model for sea-ice dynamics

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    A hybrid Lagrangian-Eulerian (HLE) method is developed for sea ice dynamics, which combines the high computational efficiency of finite difference method (FDM) with the high numerical accuracy of smoothed particle hydrodynamics (SPH). In this HLE model, the sea ice cover is represented by a group of Lagrangian ice particles with their own thicknesses and concentrations. These ice variables are interpolated to the Eularian gird nodes using the Gaussian interpolation function. The FDM is used to determine the ice velocities at Eulerian grid nodes, and the velocities of Lagrangian ice particles are interpolated from these grid velocities with the Gaussian function also. The thicknesses and concentrations of ice particles are determined based on their new locations. With the HLE numerical model, the ice ridging process in a rectangular basin is simulated, and the simulated results are validated with the analytical solution. This method is also applied to the simulation of sea ice dynamics in a vortex wind field. At last, this HLE model is applied to the Bohai Sea, and the simulated concentration, thickness and velocity match the satellite images and the field observed data well.

  12. Incorporation of a physically based melt pond scheme into the sea ice component of a climate model

    OpenAIRE

    Flocco, Daniela; Feltham, Danny; Turner, Adrian K.

    2010-01-01

    The extent and thickness of the Arctic sea ice cover has decreased dramatically in the past few decades with minima in sea ice extent in September 2005 and 2007. These minima have not been predicted in the IPCC AR4 report, suggesting that the sea ice component of climate models should more realistically represent the processes controlling the sea ice mass balance. One of the processes poorly represented in sea ice models is the formation and evolution of melt ponds. Melt ponds accumulate on t...

  13. A sea ice thickness retrieval model for 1.4 GHz radiometry and application to airborne measurements over low salinity sea ice

    Directory of Open Access Journals (Sweden)

    L. Kaleschke

    2009-11-01

    Full Text Available In preparation for the European Space Agency's (ESA Soil Moisture and Ocean Salinity (SMOS mission we investigated the potential of L-band (1.4 GHz radiometery to measure sea ice thickness.

    Sea ice brightness temperature was measured at 1.4 GHz and ice thickness were measured along nearly coincident flight tracks during the SMOS Sea-Ice campaign in the Bay of Bothnia in March 2007. A research aircraft was equipped with the L-band Radiometer EMIRAD and coordinated with helicopter based electromagnetic induction (EM ice thickness measurements.

    We developed a three layer (ocean-ice-atmosphere dielectric slab model for the calculation of ice thickness from brightness temperature. The dielectric properties depend on the relative brine volume which is a function of the bulk ice salinity and temperature.

    The model calculations suggest a thickness sensitivity of up to 1.5 m for low-salinity (multi-year or brackish sea ice. For Arctic first year ice the modeled thickness sensitivity is roughly half a meter. It reduces to a few centimeters for temperatures approaching the melting point. Although the campaign was conducted under such unfavorable melting conditions and despite limited spatial overlap between the L-band and EM-measurements was small we demonstrate a large potential for retrieving the ice thickness in the range of 0.2 to 1.5 m.

    Furthermore, we show that the ice thickness derived from SMOS measurements would be complementary to ESA's CryoSat-2 mission in terms of the error characteristics and the spatio-temporal coverage.

  14. Discrete-element model for the interaction between ocean waves and sea ice.

    Science.gov (United States)

    Xu, Zhijie; Tartakovsky, Alexandre M; Pan, Wenxiao

    2012-01-01

    We present a discrete-element method (DEM) model to simulate the mechanical behavior of sea ice in response to ocean waves. The interaction of ocean waves and sea ice potentially can lead to the fracture and fragmentation of sea ice depending on the wave amplitude and period. The fracture behavior of sea ice explicitly is modeled by a DEM method where sea ice is modeled by densely packed spherical particles with finite sizes. These particles are bonded together at their contact points through mechanical bonds that can sustain both tensile and compressive forces and moments. Fracturing naturally can be represented by the sequential breaking of mechanical bonds. For a given amplitude and period of incident ocean waves, the model provides information for the spatial distribution and time evolution of stress and microfractures and the fragment size distribution. We demonstrate that the fraction of broken bonds α increases with increasing wave amplitude. In contrast, the ice fragment size l decreases with increasing amplitude. This information is important for the understanding of the breakup of individual ice floes and floe fragment size.

  15. Regional distribution and variability of model-simulated Arctic snow on sea ice

    Science.gov (United States)

    Castro-Morales, Karel; Ricker, Robert; Gerdes, Rüdiger

    2017-09-01

    Numerical models face the challenge of representing the present-day spatiotemporal distribution of snow on sea ice realistically. We present modeled Arctic-wide snow depths on sea ice (hs_mod) obtained with the MITgcm configured with a single snow layer that accumulates proportionally to the thickness of sea ice. When compared to snow depths derived from radar measurements (NASA Operation IceBridge, 2009-2013), the model snow depths are overestimated on first-year ice (2.5 ± 8.1 cm) and multiyear ice (0.8 ± 8.3 cm). The large variance between model and observations lies mainly in the limitations of the model snow scheme and the large uncertainties in the radar measurements. In a temporal analysis, during the peak of snowfall accumulation (April), hs_mod show a decline between 2000 and 2013 associated to long-term reduction of summer sea ice extent, surface melting and sublimation. With the aim of gaining knowledge on how to improve hs_mod, we investigate the contribution of the explicitly modeled snow processes to the resulting hs_mod. Our analysis reveals that this simple snow scheme offers a practical solution to general circulation models due to its ability to replicate robustly the distribution of the large-scale Arctic snow depths. However, benefit can be gained from the integration of explicit wind redistribution processes to potentially improve the model performance and to better understand the interaction between sources and sinks of contemporary Arctic snow.

  16. Sea ice thickness and recent Arctic warming

    Science.gov (United States)

    Lang, Andreas; Yang, Shuting; Kaas, Eigil

    2017-01-01

    The climatic impact of increased Arctic sea ice loss has received growing attention in the last years. However, little focus has been set on the role of sea ice thickness, although it strongly determines surface heat fluxes. Here ensembles of simulations using the EC-Earth atmospheric model (Integrated Forecast System) are performed and analyzed to quantify the atmospheric impacts of Arctic sea ice thickness change since 1982 as revealed by the sea ice model assimilation Global Ice-Ocean Modeling and Assimilation System. Results show that the recent sea ice thinning has significantly affected the Arctic climate, while remote atmospheric responses are less pronounced owing to a high internal atmospheric variability. Locally, the sea ice thinning results in enhancement of near-surface warming of about 1°C per decade in winter, which is most pronounced over marginal sea ice areas with thin ice. This leads to an increase of the Arctic amplification factor by 37%.

  17. Influence of Sea Ice on Arctic Marine Sulfur Biogeochemistry in the Community Climate System Model

    Energy Technology Data Exchange (ETDEWEB)

    Deal, Clara [Univ. of Alaska, Fairbanks, AL (United States); Jin, Meibing [Univ. of Alaska, Fairbanks, AL (United States)

    2013-06-30

    Global climate models (GCMs) have not effectively considered how responses of arctic marine ecosystems to a warming climate will influence the global climate system. A key response of arctic marine ecosystems that may substantially influence energy exchange in the Arctic is a change in dimethylsulfide (DMS) emissions, because DMS emissions influence cloud albedo. This response is closely tied to sea ice through its impacts on marine ecosystem carbon and sulfur cycling, and the ice-albedo feedback implicated in accelerated arctic warming. To reduce the uncertainty in predictions from coupled climate simulations, important model components of the climate system, such as feedbacks between arctic marine biogeochemistry and climate, need to be reasonably and realistically modeled. This research first involved model development to improve the representation of marine sulfur biogeochemistry simulations to understand/diagnose the control of sea-ice-related processes on the variability of DMS dynamics. This study will help build GCM predictions that quantify the relative current and possible future influences of arctic marine ecosystems on the global climate system. Our overall research objective was to improve arctic marine biogeochemistry in the Community Climate System Model (CCSM, now CESM). Working closely with the Climate Ocean Sea Ice Model (COSIM) team at Los Alamos National Laboratory (LANL), we added 1 sea-ice algae and arctic DMS production and related biogeochemistry to the global Parallel Ocean Program model (POP) coupled to the LANL sea ice model (CICE). Both CICE and POP are core components of CESM. Our specific research objectives were: 1) Develop a state-of-the-art ice-ocean DMS model for application in climate models, using observations to constrain the most crucial parameters; 2) Improve the global marine sulfur model used in CESM by including DMS biogeochemistry in the Arctic; and 3) Assess how sea ice influences DMS dynamics in the arctic marine

  18. Snow Cover on the Arctic Sea Ice: Model Validation, Sensitivity, and 21st Century Projections

    Science.gov (United States)

    Blazey, Benjamin Andrew

    The role of snow cover in controlling Arctic Ocean sea ice thickness and extent is assessed with a series of models. Investigations with the stand alone Community Ice CodE (CICE) show, first, a reduction in snow depth triggers a decrease in ice volume and area, and, second, that the impact of increased snow is heavily dependent on ice and atmospheric conditions. Hindcast snow depths on the Arctic ice, simulated by the fully coupled Community Climate System Model (CCSM) are validated with 20th century in situ snow depth measurements. The snow depths in CCSM are found to be deeper than observed, likely due to excessive precipitation produced by the component atmosphere model. The sensitivity of the ice to the thermal barrier imposed by the biased snow depth is assessed. The removal of the thermodynamic impact of the exaggerated snow depth increases ice area and volume. The initial increases in ice due to enhanced conductive flux triggers feedback mechanisms with the atmosphere and ocean, reinforcing the increase in ice. Finally, the 21st century projections of decreased Arctic Ocean snow depth in CCSM are reported and diagnosed. The changes in snow are dominated by reduced accumulation due to the lack of autumn ice cover. Without this platform, much of the early snowfall is lost directly to the ocean. While this decrease in snow results in enhanced conductive flux through the ice as in the validation sensitivity experiment, the decreased summer albedo is found to dominate, as in the CICE stand alone sensitivity experiment. As such, the decrease in snow projected by CCSM in the 21st century presents a mechanism to continued ice loss. These negative (ice growth due decreased insulation) and positive (ice melt due to decreased albedo) feedback mechanisms highlight the need for an accurate representation snow cover on the ice in order to accurately simulate the evolution of Arctic Ocean sea ice.

  19. A coupled ice-ocean model for the Bohai Sea Ⅰ.Study on model and parameter

    Institute of Scientific and Technical Information of China (English)

    SU Jie; WU Huiding; ZHANG Yunfei; LIU Qinzhen; BAI Shan

    2004-01-01

    According to the earlier international studies on the coupled ice-ocean model and the hydrology, meteorology, and ice features in the Bohai Sea, a coupled ice-ocean model is developed based on the National Marine Environment Forecast Center's (NMEFC) numerical forecasting ice model of the Bohai Sea and the Princeton ocean model (POM).In the coupled model, the transfer of momentum and heat between ocean and ice is two-way, and the change of ice thickness and concentration depends on heat budget not only at the surface and bottom of ice, but also at the surface of open water between ices. The dynamic and thermodynamic coupling process is expatiated emphatically. Some thermodynamic parameters are discussed as well.

  20. Inter-comparisons of thermodynamic sea-ice modeling results using various parameterizations of radiative flux

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Radiative fluxes are of primary importance in the energy and mass balance of the sea-ice cover. Various parameterizations of the radiative fluxes are studied in a thermodynamic sea-ice model. Model outputs of the surface radiative and heat fluxes and mass balance are compared with observations. The contribution of short-wave radiation is limited to a long part of winter. Therefore, simple schemes are often sufficient. Errors in estimations of the short-wave radiation are due mainly to cloud effects and occasionally to multi-reflection between surface and ice crystals in the air. The long-wave radiation plays an important role in the ice surface heat and mass balance during most part of a winter. The effect of clouds on the accuracy of the simple radiative schemes is critical, which needs further attention. In general, the accuracy of an ice model depends on that of the radiative fluxes.

  1. Modeled Effects of Encapsulated Crude Oil on Light Transmission Through Sea Ice

    Science.gov (United States)

    Carns, R.; Light, B.

    2015-12-01

    As part of ongoing research to further advance a range of oil spill response technologies in the Arctic, nine oil and gas companies established the Arctic Oil Spill Response Technology Joint Industry Programme (JIP) in 2012. One research theme is designed to expand the industry's remote-sensing and monitoring capabilities. A suite of sensors was tested on a saltwater ice sheet grown in the U.S. Army Corps of Engineers Cold Regions Research and Engineering Laboratory (CRREL) Ice Engineering Research Facility test basin while oil was injected under the ice at different points in the ice growth. The ice continued to grow after the oil injection, allowing the oil to become encapsulated so testing could occur with various thicknesses of ice below the oil. Measurements of apparent optical properties were taken before and after the injection of oil and during various stages of ice growth. We have used a Monte Carlo model of radiative transfer for sea ice [Light et al., 2003] to explore light transmission through sea ice containing encapsulated oil. This model uses a cylindrical domain, making it well-suited for determining how large a pool of oil encapsulated in a given thickness of ice must be before it is detectable from beneath the ice cover. We use this model in combination with the optical observations to predict the amount of light transmitted and reflected from sea ice of various thicknesses containing oil. We also examine the effects of a scattering layer on the ice surface, as would commonly be present in the Arctic, either in the form of snow or the surface scattering layer that develops on melting ice. We evaluate the feasibility of distinguishing between different types of oil based on the spectral signature of light transmitted through the ice. Further model sensitivity studies yield insight about the effects of the distribution of the oil within the ice cover. Light, B., G. A. Maykut, and T. C. Grenfell (2003), A two-dimensional Monte Carlo model of

  2. Modeling brine and nutrient dynamics in Antarctic sea ice: the case of dissolved silica

    Science.gov (United States)

    Vancoppenolle, M.; Goosse, H.; de Montety, A.; Fichefet, T.; Tremblay, B.; Tison, J.

    2009-12-01

    Sea ice ecosystems are characterized by micro-algae living in brine inclusions. The growth rate of ice algae depends on light and nutrient supply. Here, the interactions between nutrients and brine dynamics under the influence of algae are investigated using a one-dimensional model. The model includes snow and ice thermodynamics with brine physics and an idealized sea ice biological component, characterized by one nutrient, namely dissolved silica (DSi). In the model, DSi follows brine motion and is consumed by ice algae. Depending on physical ice characteristics, the brine flow is either advective, diffusive or turbulent. The vertical profiles of ice salinity and DSi concentration are solutions of advection-diffusion equations. The model is configured to simulate the typical thermodynamic regimes of first-year Antarctic pack ice. The simulated vertical profiles of salinity and DSi qualitatively reproduce observations. Analysis of results highlights the role of convection in the lowermost 5-10 cm of ice. Convection mixes saline, nutrient-poor brine with comparatively fresh, nutrient-rich seawater. This implies a rejection of salt to the ocean and a flux of DSi to the ice. In presence of growing algae, the simulated ocean-to-ice DSi flux increases by 0-115% compared to an abiotic situation. In turn, primary production and brine convection act in synergy to form a nutrient pump. The other important processes are the flooding of the surface by seawater and the percolation of meltwater. The former refills nutrients near the ice surface in spring. The latter, if present, tends to expell nutrients from the ice in summer. Sketch of salt (left) and nutrient (right) exchanges at the ice-ocean interface proposed in this paper.

  3. Assessment of the sea-ice carbon pump: Insights from a three-dimensional ocean-sea-ice biogeochemical model (NEMO-LIM-PISCES

    Directory of Open Access Journals (Sweden)

    Sébastien Moreau

    2016-08-01

    Full Text Available Abstract The role of sea ice in the carbon cycle is minimally represented in current Earth System Models (ESMs. Among potentially important flaws, mentioned by several authors and generally overlooked during ESM design, is the link between sea-ice growth and melt and oceanic dissolved inorganic carbon (DIC and total alkalinity (TA. Here we investigate whether this link is indeed an important feature of the marine carbon cycle misrepresented in ESMs. We use an ocean general circulation model (NEMO-LIM-PISCES with sea-ice and marine carbon cycle components, forced by atmospheric reanalyses, adding a first-order representation of DIC and TA storage and release in/from sea ice. Our results suggest that DIC rejection during sea-ice growth releases several hundred Tg C yr−1 to the surface ocean, of which < 2% is exported to depth, leading to a notable but weak redistribution of DIC towards deep polar basins. Active carbon processes (mainly CaCO3 precipitation but also ice-atmosphere CO2 fluxes and net community production increasing the TA/DIC ratio in sea-ice modified ocean-atmosphere CO2 fluxes by a few Tg C yr−1 in the sea-ice zone, with specific hemispheric effects: DIC content of the Arctic basin decreased but DIC content of the Southern Ocean increased. For the global ocean, DIC content increased by 4 Tg C yr−1 or 2 Pg C after 500 years of model run. The simulated numbers are generally small compared to the present-day global ocean annual CO2 sink (2.6 ± 0.5 Pg C yr−1. However, sea-ice carbon processes seem important at regional scales as they act significantly on DIC redistribution within and outside polar basins. The efficiency of carbon export to depth depends on the representation of surface-subsurface exchanges and their relationship with sea ice, and could differ substantially if a higher resolution or different ocean model were used.

  4. Statistical Modeling of Sea Ice Concentration Using Satellite Imagery and Climate Reanalysis Data in the Barents and Kara Seas, 1979–2012

    Directory of Open Access Journals (Sweden)

    Jihye Ahn

    2014-06-01

    Full Text Available Extensive sea ice over Arctic regions is largely involved in heat, moisture, and momentum exchanges between the atmosphere and ocean. Some previous studies have been conducted to develop statistical models for the status of Arctic sea ice and showed considerable possibilities to explain the impacts of climate changes on the sea ice extent. However, the statistical models require improvements to achieve better predictions by incorporating techniques that can deal with temporal variation of the relationships between sea ice concentration and climate factors. In this paper, we describe the statistical approaches by ordinary least squares (OLS regression and a time-series method for modeling sea ice concentration using satellite imagery and climate reanalysis data for the Barents and Kara Seas during 1979–2012. The OLS regression model could summarize the overall climatological characteristics in the relationships between sea ice concentration and climate variables. We also introduced autoregressive integrated moving average (ARIMA models because the sea ice concentration is such a long-range dataset that the relationships may not be explained by a single equation of the OLS regression. Temporally varying relationships between sea ice concentration and the climate factors such as skin temperature, sea surface temperature, total column liquid water, total column water vapor, instantaneous moisture flux, and low cloud cover were modeled by the ARIMA method, which considerably improved the prediction accuracies. Our method may also be worth consideration when forecasting future sea ice concentration by using the climate data provided by general circulation models (GCM.

  5. Time-dependent response of a zonally averaged ocean-atmosphere-sea ice model to Milankovitch forcing

    Energy Technology Data Exchange (ETDEWEB)

    Antico, Andres; Mysak, Lawrence A. [McGill University, Department of Atmospheric and Oceanic Sciences, Montreal, QC (Canada); Marchal, Olivier [Woods Hole Oceanographic Institution, Department of Geology and Geophysics, Woods Hole, MA (United States)

    2010-05-15

    An ocean-atmosphere-sea ice model is developed to explore the time-dependent response of climate to Milankovitch forcing for the time interval 5-3 Myr BP. The ocean component is a zonally averaged model of the circulation in five basins (Arctic, Atlantic, Indian, Pacific, and Southern Oceans). The atmospheric component is a one-dimensional (latitudinal) energy balance model, and the sea-ice component is a thermodynamic model. Two numerical experiments are conducted. The first experiment does not include sea ice and the Arctic Ocean; the second experiment does. Results from the two experiments are used to investigate (1) the response of annual mean surface air and ocean temperatures to Milankovitch forcing, and (2) the role of sea ice in this response. In both experiments, the response of air temperature is dominated by obliquity cycles at most latitudes. On the other hand, the response of ocean temperature varies with latitude and depth. Deep water formed between 45 N and 65 N in the Atlantic Ocean mainly responds to precession. In contrast, deep water formed south of 60 S responds to obliquity when sea ice is not included. Sea ice acts as a time-integrator of summer insolation changes such that annual mean sea-ice conditions mainly respond to obliquity. Thus, in the presence of sea ice, air temperature changes over the sea ice are amplified, and temperature changes in deep water of southern origin are suppressed since water below sea ice is kept near the freezing point. (orig.)

  6. Last Interglacial climate and sea-level evolution from a coupled ice sheet-climate model

    Science.gov (United States)

    Goelzer, Heiko; Huybrechts, Philippe; Loutre, Marie-France; Fichefet, Thierry

    2016-12-01

    As the most recent warm period in Earth's history with a sea-level stand higher than present, the Last Interglacial (LIG, ˜ 130 to 115 kyr BP) is often considered a prime example to study the impact of a warmer climate on the two polar ice sheets remaining today. Here we simulate the Last Interglacial climate, ice sheet, and sea-level evolution with the Earth system model of intermediate complexity LOVECLIM v.1.3, which includes dynamic and fully coupled components representing the atmosphere, the ocean and sea ice, the terrestrial biosphere, and the Greenland and Antarctic ice sheets. In this setup, sea-level evolution and climate-ice sheet interactions are modelled in a consistent framework.Surface mass balance change governed by changes in surface meltwater runoff is the dominant forcing for the Greenland ice sheet, which shows a peak sea-level contribution of 1.4 m at 123 kyr BP in the reference experiment. Our results indicate that ice sheet-climate feedbacks play an important role to amplify climate and sea-level changes in the Northern Hemisphere. The sensitivity of the Greenland ice sheet to surface temperature changes considerably increases when interactive albedo changes are considered. Southern Hemisphere polar and sub-polar ocean warming is limited throughout the Last Interglacial, and surface and sub-shelf melting exerts only a minor control on the Antarctic sea-level contribution with a peak of 4.4 m at 125 kyr BP. Retreat of the Antarctic ice sheet at the onset of the LIG is mainly forced by rising sea level and to a lesser extent by reduced ice shelf viscosity as the surface temperature increases. Global sea level shows a peak of 5.3 m at 124.5 kyr BP, which includes a minor contribution of 0.35 m from oceanic thermal expansion. Neither the individual contributions nor the total modelled sea-level stand show fast multi-millennial timescale variations as indicated by some reconstructions.

  7. A parameter model of gas exchange for the seasonal sea ice zone

    Directory of Open Access Journals (Sweden)

    B. Loose

    2013-07-01

    Full Text Available Carbon budgets for the polar oceans require better constraint on air-sea gas exchange in the sea ice zone (SIZ. Here, we utilize recent advances in the theory of turbulence, mixing and air-sea flux in the ice-ocean boundary layer (IOBL to formulate a simple model for gas exchange when the surface ocean is partially covered by sea ice. The gas transfer velocity (k is related to shear-driven and convection-driven turbulence in the aqueous mass boundary layer, and to the mean-squared wave slope at the air–sea interface. We use the model to estimate k along the drift track of Ice-Tethered Profilers (ITPs in the Arctic. Individual estimates of daily-averaged k from ITP drifts ranged between 1.1 and 22 m d−1, and the fraction of open water (f ranged from 0 to 0.83. Converted to area-weighted effective transfer velocities (keff, the minimum value of keff was 10−5 m d−1 near f = 0 with values exceeding keff = 5 m d−1 at f = 0.4. The largest values of k occurred during the periods when ice cover around the ITP was changing rapidly; either in advance or retreat. The model indicates that effects from shear and convection in the sea ice zone contribute an additional 40% to the magnitude of keff, beyond what would be predicted from an estimate of keff based solely upon a windspeed parameterization. Although the ultimate scaling relationship for gas exchange in the sea ice zone will require validation in laboratory and field studies, the basic parameter model described here demonstrates that it is feasible to formulate estimates of k based upon properties of the IOBL using data sources that presently exist.

  8. The sea level response to ice sheet freshwater forcing in the Community Earth System Model

    Science.gov (United States)

    Slangen, Aimée B. A.; Lenaerts, Jan T. M.

    2016-10-01

    We study the effect of a realistic ice sheet freshwater forcing on sea-level change in the fully coupled Community Earth System Model (CESM) showing not only the effect on the ocean density and dynamics, but also the gravitational response to mass redistribution between ice sheets and the ocean. We compare the ‘standard’ model simulation (NO-FW) to a simulation with a more realistic ice sheet freshwater forcing (FW) for two different forcing scenario’s (RCP2.6 and RCP8.5) for 1850-2100. The effect on the global mean thermosteric sea-level change is small compared to the total thermosteric change, but on a regional scale the ocean steric/dynamic change shows larger differences in the Southern Ocean, the North Atlantic and the Arctic Ocean (locally over 0.1 m). The gravitational fingerprints of the net sea-level contributions of the ice sheets are computed separately, showing a regional pattern with a magnitude that is similar to the difference between the NO-FW and FW simulations of the ocean steric/dynamic pattern. Our results demonstrate the importance of ice sheet mass loss for regional sea-level projections in light of the projected increasing contribution of ice sheets to future sea-level rise.

  9. A forward model for calculating the AMSR brightness temperatures of sea-ice and ocean as seen through the atmosphere

    DEFF Research Database (Denmark)

    Pedersen, Leif Toudal; Hofmann-Bang, Dorthe

    This report describes a forward model for open water and the atmosphere, and how the contribution from sea ice can be included in these. In addition the report describes a retrieval algorithm that allows validation of the forward model. The model and the algorithm are verified by comparison...... with SSM/I retrievals, with ocean and atmosphere retrievals by Remote Sensing Systems, with SST data from the Ocean and Sea Ice SAF and with sea ice concentrations and MY-fractions of the NASA Team and Comiso Bootstrap sea ice algorithms. The forward model is the level 0 emissivity and radiative transfer...

  10. Sea Ice Outlook for September 2015 June Report - NASA Global Modeling and Assimilation Office

    Science.gov (United States)

    Cullather, Richard I.; Keppenne, Christian L.; Marshak, Jelena; Pawson, Steven; Schubert, Siegfried D.; Suarez, Max J.; Vernieres, Guillaume; Zhao, Bin

    2015-01-01

    The recent decline in perennial sea ice cover in Arctic Ocean is a topic of enormous scientific interest and has relevance to a broad variety of scientific disciplines and human endeavors including biological and physical oceanography, atmospheric circulation, high latitude ecology, the sustainability of indigenous communities, commerce, and resource exploration. A credible seasonal prediction of sea ice extent would be of substantial use to many of the stakeholders in these fields and may also reveal details on the physical processes that result in the current trends in the ice cover. Forecasts are challenging due in part to limitations in the polar observing network, the large variability in the climate system, and an incomplete knowledge of the significant processes. Nevertheless it is a useful to understand the current capabilities of high latitude seasonal forecasting and identify areas where such forecasts may be improved. Since 2008 the Arctic Research Consortium of the United States (ARCUS) has conducted a seasonal forecasting contest in which the average Arctic sea ice extent for the month of September (the month of the annual extent minimum) is predicted from available forecasts in early June, July, and August. The competition is known as the Sea Ice Outlook (SIO) but recently came under the auspices of the Sea Ice Prediction Network (SIPN), and multi-agency funded project to evaluate the SIO. The forecasts are submitted based on modeling, statistical, and heuristic methods. Forecasts of Arctic sea ice extent from the GMAO are derived from seasonal prediction system of the NASA Goddard Earth Observing System model, version 5 (GEOS 5) coupled atmosphere and ocean general circulation model (AOGCM). The projections are made in order to understand the relative skill of the forecasting system and to determine the effects of future improvements to the system. This years prediction is for a September average Arctic ice extent of 5.030.41 million km2.

  11. Assessment of sea ice-atmosphere links in CMIP5 models

    Science.gov (United States)

    Boland, Emma J. D.; Bracegirdle, Thomas J.; Shuckburgh, Emily F.

    2016-09-01

    The Arctic is currently undergoing drastic changes in climate, largely thought to be due to so-called `Arctic amplification', whereby local feedbacks enhance global warming. Recently, a number of observational and modelling studies have questioned what the implications of this change in Arctic sea ice extent might be for weather in Northern Hemisphere midlatitudes, and in particular whether recent extremely cold winters such as 2009/10 might be consistent with an influence from observed Arctic sea ice decline. However, the proposed mechanisms for these links have not been consistently demonstrated. In a uniquely comprehensive cross-season and cross-model study, we show that the CMIP5 models provide no support for a relationship between declining Arctic sea ice and a negative NAM, or between declining Barents-Kara sea ice and cold European temperatures. The lack of evidence for the proposed links is consistent with studies that report a low signal-to-noise ratio in these relationships. These results imply that, whilst links may exist between declining sea ice and extreme cold weather events in the Northern Hemisphere, the CMIP5 model experiments do not show this to be a leading order effect in the long-term. We argue that this is likely due to a combination of the limitations of the CMIP5 models and an indication of other important long-term influences on Northern Hemisphere climate.

  12. Assessment of sea ice-atmosphere links in CMIP5 models

    Science.gov (United States)

    Boland, Emma J. D.; Bracegirdle, Thomas J.; Shuckburgh, Emily F.

    2017-07-01

    The Arctic is currently undergoing drastic changes in climate, largely thought to be due to so-called `Arctic amplification', whereby local feedbacks enhance global warming. Recently, a number of observational and modelling studies have questioned what the implications of this change in Arctic sea ice extent might be for weather in Northern Hemisphere midlatitudes, and in particular whether recent extremely cold winters such as 2009/10 might be consistent with an influence from observed Arctic sea ice decline. However, the proposed mechanisms for these links have not been consistently demonstrated. In a uniquely comprehensive cross-season and cross-model study, we show that the CMIP5 models provide no support for a relationship between declining Arctic sea ice and a negative NAM, or between declining Barents-Kara sea ice and cold European temperatures. The lack of evidence for the proposed links is consistent with studies that report a low signal-to-noise ratio in these relationships. These results imply that, whilst links may exist between declining sea ice and extreme cold weather events in the Northern Hemisphere, the CMIP5 model experiments do not show this to be a leading order effect in the long-term. We argue that this is likely due to a combination of the limitations of the CMIP5 models and an indication of other important long-term influences on Northern Hemisphere climate.

  13. Ocean sea-ice modelling in the Southern Ocean around Indian Antarctic stations

    Indian Academy of Sciences (India)

    Anurag Kumar; Suneet Dwivedi; D Ram Rajak

    2017-07-01

    An eddy-resolving coupled ocean sea-ice modelling is carried out in the Southern Ocean region (9∘–78∘E; 51∘–71∘S) using the MITgcm. The model domain incorporates the Indian Antarctic stations, Maitri (11.7∘E; 70.7∘S) and Bharati (76.1∘E; 69.4∘S). The realistic simulation of the surface variables, namely, sea surface temperature (SST), sea surface salinity (SSS), surface currents, sea ice concentration (SIC) and sea ice thickness (SIT) is presented for the period of 1997–2012. The horizontal resolution of the model varies between 6 and 10 km. The highest vertical resolution of 5 m is taken near the surface, which gradually increases with increasing depths. The seasonal variability of the SST, SSS, SIC and currents is compared with the available observations in the region of study. It is found that the SIC of the model domain is increasing at a rate of 0.09% per month (nearly 1% per year), whereas, the SIC near Maitri and Bharati regions is increasing at a rate of 0.14 and 0.03% per month, respectively. The variability of the drift of the sea-ice is also estimated over the period of simulation. It is also found that the sea ice volume of the region increases at the rate of 0.0004 km3 per month (nearly 0.005 km3 per year). Further, it is revealed that the accumulation of sea ice around Bharati station is more as compared to Maitri station.

  14. Better constraints on the sea-ice state using global sea-ice data assimilation

    Directory of Open Access Journals (Sweden)

    P. Mathiot

    2012-06-01

    Full Text Available Short-term and decadal sea-ice prediction systems need a realistic initial state, generally obtained using ice-ocean model simulations with data assimilation. However, only sea-ice concentration and velocity data are currently assimilated. In this work, an Ensemble Kalman Filter system is used to assimilate observed ice concentration and freeboard (i.e. thickness of emerged sea ice data into a global coupled ocean–sea-ice model. The impact and effectiveness of our data assimilation system is assessed in two steps: firstly, through the assimilation of synthetic data (i.e., model-generated data and, secondly, through the assimilation of satellite data. While ice concentrations are available daily, freeboard data used in this study are only available during six one-month periods spread over 2005–2007. Our results show that the simulated Arctic and Antarctic sea-ice extents are improved by the assimilation of synthetic ice concentration data. Assimilation of synthetic ice freeboard data improves the simulated sea-ice thickness field. Using real ice concentration data enhances the model realism in both hemispheres. Assimilation of ice concentration data significantly improves the total hemispheric sea-ice extent all year long, especially in summer. Combining the assimilation of ice freeboard and concentration data leads to better ice thickness, but does not further improve the ice extent. Moreover, the improvements in sea-ice thickness due to the assimilation of ice freeboard remain visible well beyond the assimilation periods.

  15. Factors controlling phytoplankton ice-edge blooms in the marginal ice-zone of the northwestern Weddell Sea during sea ice retreat 1988: field observations and mathematical modelling

    OpenAIRE

    Lancelot, Christiane; Mathot, Sylvie; Veth, Cornelis; de Baar, Hein

    1993-01-01

    The factors controlling phytoplankton bloom development in the marginal ice zone of the northwestern Weddell Sea were investigated during the EPOS (Leg 2) expedition (1988). Measurements were made of physical and chemical processes and biological activities associated with the process of ice-melting and their controlling variables particularly light limitation mediated by vertical stability and ice-cover, trace metal deficiency and grazing pressure. The combined observations and process studi...

  16. Factors controlling phytoplankton ice-edge blooms in the marginal ice-zone of the northwestern Weddell Sea during sea ice retreat 1988 : field observations and mathematical modelling

    NARCIS (Netherlands)

    Lancelot, Christiane; Mathot, Sylvie; Veth, Cornelis; Baar, Hein de

    1993-01-01

    The factors controlling phytoplankton bloom development in the marginal ice zone of the northwestern Weddell Sea were investigated during the EPOS (Leg 2) expedition (1988). Measurements were made of physical and chemical processes and biological activities associated with the process of ice-melting

  17. Factors controlling phytoplankton ice-edge blooms in the marginal ice-zone of the northwestern Weddell Sea during sea ice retreat 1988 : field observations and mathematical modelling

    NARCIS (Netherlands)

    Lancelot, Christiane; Mathot, Sylvie; Veth, Cornelis; Baar, Hein de

    1993-01-01

    The factors controlling phytoplankton bloom development in the marginal ice zone of the northwestern Weddell Sea were investigated during the EPOS (Leg 2) expedition (1988). Measurements were made of physical and chemical processes and biological activities associated with the process of ice-melting

  18. Chemical Atmosphere-Snow-Sea Ice Interactions: defining future research in the field, lab and modeling

    Science.gov (United States)

    Frey, Markus

    2015-04-01

    The air-snow-sea ice system plays an important role in the global cycling of nitrogen, halogens, trace metals or carbon, including greenhouse gases (e.g. CO2 air-sea flux), and therefore influences also climate. Its impact on atmospheric composition is illustrated for example by dramatic ozone and mercury depletion events which occur within or close to the sea ice zone (SIZ) mostly during polar spring and are catalysed by halogens released from SIZ ice, snow or aerosol. Recent field campaigns in the high Arctic (e.g. BROMEX, OASIS) and Antarctic (Weddell sea cruises) highlight the importance of snow on sea ice as a chemical reservoir and reactor, even during polar night. However, many processes, participating chemical species and their interactions are still poorly understood and/or lack any representation in current models. Furthermore, recent lab studies provide a lot of detail on the chemical environment and processes but need to be integrated much better to improve our understanding of a rapidly changing natural environment. During a 3-day workshop held in Cambridge/UK in October 2013 more than 60 scientists from 15 countries who work on the physics, chemistry or biology of the atmosphere-snow-sea ice system discussed research status and challenges, which need to be addressed in the near future. In this presentation I will give a summary of the main research questions identified during this workshop as well as ways forward to answer them through a community-based interdisciplinary approach.

  19. Effects of sinking of salt rejected during formation of sea ice on results of an ocean-atmosphere-sea ice climate model

    Science.gov (United States)

    Duffy, P. B.; Eby, M.; Weaver, A. J.

    We show that results of an ocean-atmosphere-sea-ice model are sensitive to the treatment of salt rejected during formation of sea ice. In our Control simulation, we place all rejected salt in the top ocean-model level. In the Plume simulation, we instantaneously mix rejected salt into the subsurface ocean, to a maximum depth which depends on local density gradients. This mimics the effects of subgrid-scale convection of rejected salt. The results of the Plume simulation are more realistic than those of the Control simulation: the spatial pattern of simulated salinities (especially in the Southern Ocean), deep-ocean temperatures, simulated sea-ice extents and surface air temperatures all agree better with observations. A similar pair of simulations using horizontal tracer diffusion instead of the Gent-McWilliams eddy parameterization show similar changes due to instantaneous mixing of rejected salt.

  20. Atmospheric winter response to Arctic sea ice changes in reanalysis data and model simulations

    Science.gov (United States)

    Jaiser, Ralf; Nakamura, Tetsu; Handorf, Dörthe; Dethloff, Klaus; Ukita, Jinro; Yamazaki, Koji

    2016-07-01

    The changes of atmospheric flow patterns related to Arctic Amplification have impacts well beyond the Arctic regional weather and climate system. Here we examine modulations of vertically propagating planetary waves, a major feature of the climate response to Arctic sea ice reduction by comparing the corresponding results of an atmospheric general circulation model with reanalysis data for periods of high and low sea ice conditions. Under low sea ice condition we find enhanced coupling between troposphere and stratosphere starting in November with preferred polar stratospheric vortex breakdowns in February, which then feeds back to the troposphere. The model experiment and ERA-Interim reanalysis data agree well with respect to temporal and spatial characteristics associated with vertical planetary wave propagation including its precursors. The upward propagating planetary wave anomalies resemble a wave number 1 and 2 pattern depending on region and timing. Since our experimental design only allows influences from sea ice changes and there is a high degree of resemblance between model results and observations, we conclude that sea ice is a main driver of observed winter circulation changes.

  1. Predicting Land-Ice Retreat and Sea-Level Rise with the Community Earth System Model

    Energy Technology Data Exchange (ETDEWEB)

    Lipscomb, William [Los Alamos National Laboratory

    2012-06-19

    Coastal stakeholders need defensible predictions of 21st century sea-level rise (SLR). IPCC assessments suggest 21st century SLR of {approx}0.5 m under aggressive emission scenarios. Semi-empirical models project SLR of {approx}1 m or more by 2100. Although some sea-level contributions are fairly well constrained by models, others are highly uncertain. Recent studies suggest a potential large contribution ({approx}0.5 m/century) from the marine-based West Antarctic Ice Sheet, linked to changes in Southern Ocean wind stress. To assess the likelihood of fast retreat of marine ice sheets, we need coupled ice-sheet/ocean models that do not yet exist (but are well under way). CESM is uniquely positioned to provide integrated, physics based sea-level predictions.

  2. Arctic Sea Ice

    Science.gov (United States)

    Stroeve, J. C.; Fetterer, F.; Knowles, K.; Meier, W.; Serreze, M.; Arbetter, T.

    2004-12-01

    Of all the recent observed changes in the Arctic environment, the reduction of sea ice cover stands out most prominantly. Several independent analysis have established a trend in Arctic ice extent of -3% per decade from the late 1970s to the late 1990s, with a more pronounced trend in summer. The overall downward trend in ice cover is characterized by strong interannual variability, with a low September ice extent in one year typically followed by recovery the next September. Having two extreme minimum years, such as what was observed in 2002 and 2003 is unusual. 2004 marks the third year in a row of substantially below normal sea ice cover in the Arctic. Early summer 2004 appeared unusual in terms of ice extent, with May a record low for the satellite period (1979-present) and June also exhibiting below normal ice extent. August 2004 extent is below that of 2003 and large reductions in ice cover are observed once again off the coasts of Siberia and Alaska and the Greenland Sea. Neither the 2002 or 2003 anomaly appeared to be strongly linked to the positive phase of the Arctic Oscillation (AO) during the preceding winter. Similarly, the AO was negative during winter 2003/2004. In the previous AO framework of Rigor et al (2002), a positive winter AO implied preconditioning of the ice cover to extensive summer decay. In this hypothesis, the AO does not explain all aspects of the recent decline in Arctic ice cover, such as the extreme minima of 2002, 2003 and 2004. New analysis by Rigor and Wallace (2004) suggest that the very positive AO state from 1989-1995 can explain the recent sea ice minima in terms of changes in the Arctic surface wind field associated with the previous high AO state. However, it is also reasonable to expect that a general decrease in ice thickness accompanying warming would manifest itself as greater sensitivity of the ice pack to wind forcings and albedo feedbacks. The decrease in multiyear ice and attendant changes in ice thickness

  3. Snow on Arctic sea ice: model representation and last decade changes

    Directory of Open Access Journals (Sweden)

    K. Castro-Morales

    2015-10-01

    Full Text Available Together with sea ice, Arctic snow has experienced vast changes during the last decade due to a warming climate. Thus, it is relevant to study the past and present changes of Arctic snow to understand the implications to the sea ice component, precipitation, heat and radiation budgets. In this study, we analyze the changes of snow depth between 2000 and 2013 at regional scale represented in an Arctic coupled sea ice-general circulation model. We evaluate the model performance by direct comparison of the modeled snow depths (hs_mod to snow depths from radar measurements from the NASA Operation IceBridge (hs_OIB during the flight campaigns completed from 2009 to 2013. Despite the description of the snow in our model is simple (i.e. single layer without explicit snow redistribution processes as in many current sea-ice models; the latitudinal distribution of hs_mod in the western Arctic is in good agreement to observations. The hs_mod is on average 3 cm thicker than hs_OIB in latitudes > 76° N. According to the model results, the hs in 2013 decreased 21 % with respect to the multi-year mean between 2000 and 2013. This snow reduction occurred mainly in FYI dominated areas, and is in good agreement to the year-to-year loss of sea ice, also well reproduced by the model. In a simple snow mass budget, our results show that 65 % of the yearly accumulated snow is lost by sublimation and snowmelt due to the heat transfer between the snow/ice interface and the atmosphere. Although the snow layer accumulates again every year, the long-term reduction in the summer sea-ice extent ultimately affects the maximum spring accumulation of snow. The model results exhibit a last decade thinning of the snowpack that is however one order of magnitude lower than previous estimates based on radar measurements. We suggest that the later is partially due to the lack of explicit snow redistribution processes in the model, emphasizing the need to include these in current sea-ice

  4. The sea-level fingerprint of the Antarctic ice sheet: an ensemble GIA modelling approach

    Science.gov (United States)

    Spada, Giorgio; Galassi, Gaia; Melini, Daniele

    2017-04-01

    During the last decade, Glacial Isostatic Adjustment (GIA) modelling has seen a considerable development, stimulated by the increasing number and quality of sea-level observations and of various geodetic constraints. The fundamental equation of GIA (the Sea Level Equation) accounts for a number of physical ingredients that make GIA modelling quite realistic, such as rotational effects on sea-level change, the migration of the shorelines, and the time-evolving topography in the presence of marine based ice. However, concerning the spatiotemporal distribution of the late-Pleistocene ice sheets, the GIA models published in the literature by different groups are characterised by significantly different features. These are the volumes of the ice sheets at the Last Glacial Maximum, the presence and the duration of abrupt melting episodes (meltwater pulses) and the timing of the end of deglaciation. These differences can be mainly attributed to the different sets of proxies employed to constrain the melting chronology and, sometimes, to different assumptions about the Earth's viscosity profile. One of most important sources of uncertainty is the melting chronology of the Antarctic ice sheet, which is poorly constrained by the limited amount of relative sea-level data available in the near field of the ice sheet. To test whether the GIA models developed so far for the deglaciation of Antarctic ice sheet are converging or not towards a unique solution, here we collectively consider the models of the melting history of Antarctica published in the literature so far and for each of them we solve the Sea Level Equation. Following a multi-model ensemble approach, we estimate the ensemble mean and its uncertainty, in terms of the geometry and of the time history of the sea-level fingerprints.

  5. Modelling acoustic propagation beneath Antarctic sea ice using measured environmental parameters

    Science.gov (United States)

    Alexander, Polly; Duncan, Alec; Bose, Neil; Williams, Guy

    2016-09-01

    Autonomous underwater vehicles are improving and expanding in situ observations of sea ice for the validation of satellite remote sensing and climate models. Missions under sea ice, particularly over large distances (up to 100 km) away from the immediate vicinity of a ship or base, require accurate acoustic communication for monitoring, emergency response and some navigation systems. We investigate the propagation of acoustic signals in the Antarctic seasonal ice zone using the BELLHOP model, examining the influence of ocean and sea ice properties. We processed available observations from around Antarctica to generate input variables such as sound speed, surface reflection coefficient (R) and roughness parameters. The results show that changes in the sound speed profile make the most significant difference to the propagation of the direct path signal. The inclusion of the surface reflected signals from a flat ice surface was found to greatly decrease the transmission loss with range. When ice roughness was added, the transmission loss increased with roughness, in a manner similar to the direct path transmission loss results. The conclusions of this work are that: (1) the accuracy of acoustic modelling in this environment is greatly increased by using realistic sound speed data; (2) a risk averse ranging model would use only the direct path signal transmission; and (3) in a flat ice scenario, much greater ranges can be achieved if the surface reflected transmission paths are included. As autonomous missions under sea ice increase in scale and complexity, it will be increasingly important for operational procedures to include effective modelling of acoustic propagation with representative environmental data.

  6. Coupled model of INM-IO global ocean model, CICE sea ice model and SCM OIAS framework

    Science.gov (United States)

    Bayburin, Ruslan; Rashit, Ibrayev; Konstantin, Ushakov; Vladimir, Kalmykov; Gleb, Dyakonov

    2015-04-01

    Status of coupled Arctic model of ocean and sea ice is presented. Model consists of INM IO global ocean component of high resolution, Los Alamos National Laboratory CICE sea ice model and a framework SCM OIAS for the ocean-ice-atmosphere-land coupled modeling on massively-parallel architectures. Model is currently under development at the Institute of Numerical Mathematics (INM), Hydrometeorological Center (HMC) and P.P. Shirshov Institute of Oceanology (IO). Model is aimed at modeling of intra-annual variability of hydrodynamics in Arctic and. The computational characteristics of the world ocean-sea ice coupled model governed by SCM OIAS are presented. The model is parallelized using MPI technologies and currently can use efficiently up to 5000 cores. Details of programming implementation, computational configuration and physical phenomena parametrization are analyzed in terms of intercoupling complex. Results of five year computational experiment of sea ice, snow and ocean state evolution in Arctic region on tripole grid with horizontal resolution of 3-5 kilometers, closed by atmospheric forcing field from repeating "normal" annual course taken from CORE1 experiment data base are presented and analyzed in terms of the state of vorticity and warm Atlantic water expansion.

  7. Sea ice, climate, and multiscale composites

    Science.gov (United States)

    Golden, Kenneth

    2014-03-01

    In September of 2012, the area of the Arctic Ocean covered by sea ice reached its lowest level ever recorded in more than three decades of satellite measurements. In fact, compared to the 1980's and 1990's, this represents a loss of more than half of the summer Arctic sea ice pack. While global climate models generally predict sea ice declines over the 21st century, the precipitous losses observed so far have significantly outpaced most projections. I will discuss how mathematical models of composite materials and statistical physics are being used to study key sea ice processes and advance how sea ice is represented in climate models. This work is helping to improve projections of the fate of Earth's ice packs, and the response of polar ecosystems. A brief video of a recent Antarctic expedition where sea ice properties were measured will be shown. Supported by NSF and ONR.

  8. Quantification of ice production in Laptev Sea polynyas and its sensitivity to thin-ice parameterizations in a regional climate model

    Science.gov (United States)

    Gutjahr, Oliver; Heinemann, Günther; Preußer, Andreas; Willmes, Sascha; Drüe, Clemens

    2016-12-01

    The quantification of sea-ice production in the Laptev Sea polynyas is important for the Arctic sea-ice budget and the heat loss to the atmosphere. We estimated the ice production for the winter season 2007/2008 (November-April) based on simulations with the regional climate model COSMO-CLM at a horizontal resolution of 5 km and compared it to remote sensing estimates. A reference and five sensitivity simulations were performed with different assumptions on grid-scale and subgrid-scale ice thickness considered within polynyas, using a tile approach for fractional sea ice. In addition, the impact of heat loss on the atmospheric boundary layer was investigated. About 29.1 km3 of total winter ice production was estimated for the reference simulation, which varies by up to +124 % depending on the thin-ice assumptions. For the most realistic assumptions based on remote sensing of ice thickness the ice production increases by +39 %. The use of the tile approach enlarges the area and enhances the magnitude of the heat loss from polynyas up to +110 % if subgrid-scale open water is assumed and by +20 % for realistic assumptions. This enhanced heat loss causes in turn higher ice production rates and stronger impact on the atmospheric boundary layer structure over the polynyas. The study shows that ice production is highly sensitive to the thin-ice parameterizations for fractional sea-ice cover. In summary, realistic ice production estimates could be retrieved from our simulations. Neglecting subgrid-scale energy fluxes might considerably underestimate the ice production in coastal polynyas, such as in the Laptev Sea, with possible consequences on the Arctic sea-ice budget.

  9. Arctic sea ice area in CMIP3 and CMIP5 climate model ensembles - variability and change

    Science.gov (United States)

    Semenov, V. A.; Martin, T.; Behrens, L. K.; Latif, M.

    2015-02-01

    The shrinking Arctic sea ice cover observed during the last decades is probably the clearest manifestation of ongoing climate change. While climate models in general reproduce the sea ice retreat in the Arctic during the 20th century and simulate further sea ice area loss during the 21st century in response to anthropogenic forcing, the models suffer from large biases and the model results exhibit considerable spread. The last generation of climate models from World Climate Research Programme Coupled Model Intercomparison Project Phase 5 (CMIP5), when compared to the previous CMIP3 model ensemble and considering the whole Arctic, were found to be more consistent with the observed changes in sea ice extent during the recent decades. Some CMIP5 models project strongly accelerated (non-linear) sea ice loss during the first half of the 21st century. Here, complementary to previous studies, we compare results from CMIP3 and CMIP5 with respect to regional Arctic sea ice change. We focus on September and March sea ice. Sea ice area (SIA) variability, sea ice concentration (SIC) variability, and characteristics of the SIA seasonal cycle and interannual variability have been analysed for the whole Arctic, termed Entire Arctic, Central Arctic and Barents Sea. Further, the sensitivity of SIA changes to changes in Northern Hemisphere (NH) averaged temperature is investigated and several important dynamical links between SIA and natural climate variability involving the Atlantic Meridional Overturning Circulation (AMOC), North Atlantic Oscillation (NAO) and sea level pressure gradient (SLPG) in the western Barents Sea opening serving as an index of oceanic inflow to the Barents Sea are studied. The CMIP3 and CMIP5 models not only simulate a coherent decline of the Arctic SIA but also depict consistent changes in the SIA seasonal cycle and in the aforementioned dynamical links. The spatial patterns of SIC variability improve in the CMIP5 ensemble, particularly in summer. Both

  10. Indicators of Arctic Sea Ice Bistability in Climate Model Simulations and Observations

    Science.gov (United States)

    2014-09-30

    1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Indicators of Arctic Sea Ice Bistability in Climate...possibility that the climate system supports multiple Arctic sea ice states that are relevant for the evolution of sea ice during the next several...the most relevant scalar quantities related to the hemisphere-scale Arctic sea ice cover that indicate the presence of bistability, as well as the

  11. Modeling the seasonal evolution of the Arctic sea ice floe size distribution

    Directory of Open Access Journals (Sweden)

    Jinlun Zhang

    2016-09-01

    Full Text Available Abstract To better simulate the seasonal evolution of sea ice in the Arctic, with particular attention to the marginal ice zone, a sea ice model of the distribution of ice thickness, floe size, and enthalpy was implemented into the Pan-arctic Ice–Ocean Modeling and Assimilation System (PIOMAS. Theories on floe size distribution (FSD and ice thickness distribution (ITD were coupled in order to explicitly simulate multicategory FSD and ITD distributions simultaneously. The expanded PIOMAS was then used to estimate the seasonal evolution of the Arctic FSD in 2014 when FSD observations are available for model calibration and validation. Results indicate that the simulated FSD, commonly described equivalently as cumulative floe number distribution (CFND, generally follows a power law across space and time and agrees with the CFND observations derived from TerraSAR-X satellite images. The simulated power-law exponents also correlate with those derived using MODIS images, with a low mean bias of –2%. In the marginal ice zone, the modeled CFND shows a large number of small floes in winter because of stronger winds acting on thin, weak first-year ice in the ice edge region. In mid-spring and summer, the CFND resembles an upper truncated power law, with the largest floes mostly broken into smaller ones; however, the number of small floes is lower than in winter because floes of small sizes or first-year ice are easily melted away. In the ice pack interior there are fewer floes in late fall and winter than in summer because many of the floes are “welded” together into larger floes in freezing conditions, leading to a relatively flat CFND with low power-law exponents. The simulated mean floe size averaged over all ice-covered areas shows a clear annual cycle, large in winter and smaller in summer. However, there is no obvious annual cycle of mean floe size averaged over the marginal ice zone. The incorporation of FSD into PIOMAS results in reduced

  12. Snow on Sea Ice Workshop - An Icy Meeting of the Minds: Modelers and Measurers

    Science.gov (United States)

    2015-09-30

    cover resides atop Arctic and Antarctic sea ice for much of the...year. This snow cover impacts the surface heat budget, the atmosphere– ocean heat exchange, ice growth, ice melt, and light transmission to the ocean . It...period, the group went out on the ice and made measurements of snow and ice cover , and spent time indoors talking about how large scale sea ice

  13. Assessing the O2 budget under sea ice: An experimental and modelling approach

    Directory of Open Access Journals (Sweden)

    S. Moreau

    2015-12-01

    Full Text Available Abstract The objective of this study was to assess the O2 budget in the water under sea ice combining observations and modelling. Modelling was used to discriminate between physical processes, gas-specific transport (i.e., ice-atmosphere gas fluxes and gas bubble buoyancy and bacterial respiration (BR and to constrain bacterial growth efficiency (BGE. A module describing the changes of the under-ice water properties, due to brine rejection and temperature-dependent BR, was implemented in the one-dimensional halo-thermodynamic sea ice model LIM1D. Our results show that BR was the dominant biogeochemical driver of O2 concentration in the water under ice (in a system without primary producers, followed by gas specific transport. The model suggests that the actual contribution of BR and gas specific transport to the change in seawater O2 concentration was 37% during ice growth and 48% during melt. BGE in the water under sea ice, as retrieved from the simulated O2 budget, was found to be between 0.4 and 0.5, which is in line with published BGE values for cold marine waters. Given the importance of BR to seawater O2 in the present study, it can be assumed that bacteria contribute substantially to organic matter consumption and gas fluxes in ice-covered polar oceans. In addition, we propose a parameterization of polar marine bacterial respiration, based on the strong temperature dependence of bacterial respiration and the high growth efficiency observed here, for further biogeochemical ocean modelling applications, such as regional or large-scale Earth System models.

  14. Sea-ice Thickness and Draft Statistics from Submarine ULS, Moored ULS, and a Coupled Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set consists of estimates of mean values of sea-ice thickness and sea-ice draft in meters computed from three different input data sets: sea ice draft from...

  15. Modeling Abrupt Change in Global Sea Level Arising from Ocean - Ice-Sheet Interaction

    Energy Technology Data Exchange (ETDEWEB)

    Holland, David M

    2011-09-24

    It is proposed to develop, validate, and apply a coupled ocean ice-sheet model to simulate possible, abrupt future change in global sea level. This research is to be carried out collaboratively between an academic institute and a Department of Energy Laboratory (DOE), namely, the PI and a graduate student at New York University (NYU) and climate model researchers at the Los Alamos National Laboratory (LANL). The NYU contribution is mainly in the area of incorporating new physical processes into the model, while the LANL efforts are focused on improved numerics and overall model development. NYU and LANL will work together on applying the model to a variety of modeling scenarios of recent past and possible near-future abrupt change to the configuration of the periphery of the major ice sheets. The project's ultimate goal is to provide a robust, accurate prediction of future global sea level change, a feat that no fully-coupled climate model is currently capable of producing. This proposal seeks to advance that ultimate goal by developing, validating, and applying a regional model that can simulate the detailed processes involved in sea-level change due to ocean ice-sheet interaction. Directly modeling ocean ice-sheet processes in a fully-coupled global climate model is not a feasible activity at present given the near-complete absence of development of any such causal mechanism in these models to date.

  16. Modelling sea level data from China and Malay-Thailand to estimate Holocene ice-volume equivalent sea level change

    Science.gov (United States)

    Bradley, Sarah L.; Milne, Glenn A.; Horton, Benjamin P.; Zong, Yongqiang

    2016-04-01

    This study presents a new model of Holocene ice-volume equivalent sea level (ESL), extending a previously published global ice sheet model (Bassett et al., 2005), which was unconstrained from 10 kyr BP to present. This new model was developed by comparing relative sea level (RSL) predictions from a glacial isostatic adjustment (GIA) model to a suite of Holocene sea level index points from China and Malay-Thailand. Three consistent data-model misfits were found using the Bassett et al. (2005) model: an over-prediction in the height of maximum sea level, the timing of this maximum, and the temporal variation of sea level from the time of the highstand to present. The data-model misfits were examined for a large suite of ESL scenarios and a range of earth model parameters to determine an optimum model of Holocene ESL. This model is characterised by a slowdown in melting at ∼7 kyr BP, associated with the final deglaciation of the Laurentide Ice Sheet, followed by a continued rise in ESL until ∼1 kyr BP of ∼5.8 m associated with melting from the Antarctic Ice Sheet. It was not possible to identify an earth viscosity model that provided good fits for both regions; with the China data preferring viscosity values in the upper mantle of less than 1.5 × 1020 Pa s and the Malay-Thailand data preferring greater values. We suggest that this inference of a very weak upper mantle for the China data originates from the nearby subduction zone and Hainan Plume. The low viscosity values may also account for the lack of a well-defined highstand at the China sites.

  17. Atmospheric Profiles, Clouds and the Evolution of Sea Ice Cover in the Beaufort and Chukchi Seas: Atmospheric Observations and Modeling as Part of the Seasonal Ice Zone Reconnaissance Surveys

    Science.gov (United States)

    2017-06-04

    models such as the Navy NA V GEM. IR Dropsonde During a September 29 2014 SIZRS mission we had the opportunity to overfly the Canadian Coast Guard Ice... Journal of Climate, [accepted with revisions, refereed] Zhang, J. L., A. Schweiger, M. Steele, and H. Stem (2015); Sea ice floe size distribution in the...Accuracy of short-term sea ice drift forecasts using a coupled ice-ocean model, Journal , 120, doi: 10.1002/2015jc011273. [published, referreed

  18. EXPERIMENTS OF SEA ICE SIMULATION

    Institute of Scientific and Technical Information of China (English)

    LIU Xi-ying; ZHANG Xue-hong; YU Ru-cong; LIU Hai-long; YU Yong-qiang

    2005-01-01

    As a substitute for the original displaced pole grids, a simple rotated spherical coordinate system was introduced into the Community Sea Ice Model version 4(CSIM4), which is a component of the Community Climate System Model(CCSM) of the American National Center of Atmospheric Research(NCAR), to deal with the "pole problems".In the new coordinates, both the geographical North Pole and South Pole lie in the model equator and grid sizes near the polar region are more uniform.With reanalysis dataset of American National Centers for Environment Prediction(NCEP) and Levitus dataset without considering sub-mixed layer heat flux, the model was integrated for 100 years with thermodynamics process involved only in the former 49 years and both dynamic and thermodynamic processes involved in the left time.Inner consistency of model results was checked with no contradiction found.The results of last 10 years' model output were analyzed and it is shown that the simulated sea ice seasonal variation is rational whereas sea ice extent in the Barents Sea in winter is larger than that of observation.Numerical experiment on influence of sub-mixed layer heat flux was also carried out and it is shown that the sub-mixed layer heat flux can modulate seasonal variation of sea ice greatly.As a model component, the sea ice model with rotated spherical coordinates was coupled with other models (the oceanic general circulation model is the LASG/IAP Climate System Ocean Model(LICOM) with reduced grid, other models are components of NCAR CCSM2) forming a climate system model and its preliminary results were also given briefly.

  19. Drivers of inorganic carbon dynamics in first-year sea ice: A model study

    DEFF Research Database (Denmark)

    Moreau, Sebastien; Vancoppenolle, Martin; Delille, Bruno

    2015-01-01

    included. The model is evaluated using observations from a 6 month field study at Point Barrow, Alaska, and an ice-tank experi- ment. At Barrow, results show that the DIC budget is mainly driven by physical processes, wheras brine-air CO2 fluxes, ikaite formation, and net primary production, are secondary...... factors. In terms of ice-atmosphere CO2 exchanges, sea ice is a net CO2 source and sink in winter and summer, respectively. The formulation of the ice-atmosphere CO2 flux impacts the simulated near-surface CO2 partial pressure (pCO2), but not the DIC budget. Because the simulated ice-atmosphere CO2 fluxes...

  20. The impact of early Holocene Arctic shelf flooding on climate in an atmosphere-ocean-sea-ice model

    Science.gov (United States)

    Blaschek, M.; Renssen, H.

    2013-11-01

    Glacial terminations are characterized by a strong rise in sea level related to melting ice sheets. This rise in sea level is not uniform all over the world, because regional effects (uplift and subsidence of coastal zones) are superimposed on global trends. During the early Holocene the Siberian Shelf became flooded before 7.5 ka BP and the coastline reached modern-day high stands at 5 ka BP. This area is currently known as a sea-ice production area and contributes significantly to the sea-ice exported from the Arctic through the Fram Strait. This leads to the following hypothesis: during times of rising sea levels, shelves become flooded, increasing sea-ice production on these shelves, increasing sea-ice volume and export through the Fram Strait and causing the sea-ice extent to advance in the Nordic Seas, yielding cooler and fresher sea surface conditions. We have tested this hypothesis in an atmosphere-ocean-sea-ice coupled model of intermediate complexity (LOVECLIM). Our experiment on early Holocene Siberian Shelf flooding shows that in our model sea-ice production in the Northern Hemisphere increases (15%) and that sea-ice extent in the Northern Hemisphere increases (14%) but sea-ice export decreases (-15%) contrary to our hypothesis. The reason of this unexpected behaviour has its origin in a weakened polar vortex, induced by the land-ocean changes due to the shelf flooding, and a resulting decrease of zonality in the Nordic Seas pressure regime. Hence the winter Greenland high and the Icelandic low strengthen, yielding stronger winds on both sides of the Nordic Seas. Increased winds along the East Greenland Current support local sea-ice production and transport towards the South, resulting in a wider sea-ice cover and a southward shift of convection areas. The overall strength of the Atlantic meridional overturning circulation is reduced by 4% and the heat transport in the Atlantic basin by 7%, resulting in an annual cooling pattern over the Nordic Seas by

  1. Sea Ice Outlook for September 2017 July Report - NASA Global Modeling and Assimilation Office

    Science.gov (United States)

    Cullather, Richard I.; Borovikov, Anna Y.; Hackert, Eric C.; Kovach, Robin M.; Marshak, Jelena; Molod, Andrea M.; Pawson, Steven; Suarez, Max J.; Vikhliaev, Yury V.; Zhao, Bin

    2017-01-01

    The GMAO seasonal forecast is produced from coupled model integrations that are initialized every five days, with seven additional ensemble members generated by coupled model breeding and initialized on the date closest to the beginning of the month. The main components of the AOGCM are the GEOS-5 atmospheric model, the MOM4 ocean model, and CICE sea ice model. Forecast fields were re-gridded to the passive microwave grid for averaging.

  2. Sea Ice Outlook for September 2017: June Report - NASA Global Modeling and Assimilation Office

    Science.gov (United States)

    Cullather, Richard I.; Borovikov, Anna Y.; Hackert, Eric C.; Kovach, Robin M.; Marshak, Jelena; Molod, Andrea M.; Pawson, Steven; Suarez, Max J.; Vikhliaev, Yury V.; Zhao, Bin

    2017-01-01

    The GMAO seasonal forecast is produced from coupled model integrations that are initialized every five days, with seven additional ensemble members generated by coupled model breeding and initialized on the date closest to the beginning of the month. The main components of the AOGCM are the GEOS-5 atmospheric model, the MOM4 ocean model, and CICE sea ice model. Forecast fields were re-gridded to the passive microwave grid for averaging.

  3. Large-Ensemble modeling of past and future variations of the Antarctic Ice Sheet with a coupled ice-Earth-sea level model

    Science.gov (United States)

    Pollard, David; DeConto, Robert; Gomez, Natalya

    2016-04-01

    To date, most modeling of the Antarctic Ice Sheet's response to future warming has been calibrated using recent and modern observations. As an alternate approach, we apply a hybrid 3-D ice sheet-shelf model to the last deglacial retreat of Antarctica, making use of geologic data of the last ~20,000 years to test the model against the large-scale variations during this period. The ice model is coupled to a global Earth-sea level model to improve modeling of the bedrock response and to capture ocean-ice gravitational interactions. Following several recent ice-sheet studies, we use Large Ensemble (LE) statistical methods, performing sets of 625 runs from 30,000 years to present with systematically varying model parameters. Objective scores for each run are calculated using modern data and past reconstructed grounding lines, relative sea level records, cosmogenic elevation-age data and uplift rates. The LE results are analyzed to calibrate 4 particularly uncertain model parameters that concern marginal ice processes and interaction with the ocean. LE's are extended into the future with climates following RCP scenarios. An additional scoring criterion tests the model's ability to reproduce estimated sea-level high stands in the warm mid-Pliocene, for which drastic retreat mechanisms of hydrofracturing and ice-cliff failure are needed in the model. The LE analysis provides future sea-level-rise envelopes with well-defined parametric uncertainty bounds. Sensitivities of future LE results to Pliocene sea-level estimates, coupling to the Earth-sea level model, and vertical profiles of Earth properties, will be presented.

  4. Seafloor Control on Sea Ice

    Science.gov (United States)

    Nghiem, S. V.; Clemente-Colon, P.; Rigor, I. G.; Hall, D. K.; Neumann, G.

    2011-01-01

    The seafloor has a profound role in Arctic sea ice formation and seasonal evolution. Ocean bathymetry controls the distribution and mixing of warm and cold waters, which may originate from different sources, thereby dictating the pattern of sea ice on the ocean surface. Sea ice dynamics, forced by surface winds, are also guided by seafloor features in preferential directions. Here, satellite mapping of sea ice together with buoy measurements are used to reveal the bathymetric control on sea ice growth and dynamics. Bathymetric effects on sea ice formation are clearly observed in the conformation between sea ice patterns and bathymetric characteristics in the peripheral seas. Beyond local features, bathymetric control appears over extensive ice-prone regions across the Arctic Ocean. The large-scale conformation between bathymetry and patterns of different synoptic sea ice classes, including seasonal and perennial sea ice, is identified. An implication of the bathymetric influence is that the maximum extent of the total sea ice cover is relatively stable, as observed by scatterometer data in the decade of the 2000s, while the minimum ice extent has decreased drastically. Because of the geologic control, the sea ice cover can expand only as far as it reaches the seashore, the continental shelf break, or other pronounced bathymetric features in the peripheral seas. Since the seafloor does not change significantly for decades or centuries, sea ice patterns can be recurrent around certain bathymetric features, which, once identified, may help improve short-term forecast and seasonal outlook of the sea ice cover. Moreover, the seafloor can indirectly influence cloud cover by its control on sea ice distribution, which differentially modulates the latent heat flux through ice covered and open water areas.

  5. The interaction of seasonality and low-frequencies in a stochastic Arctic sea ice model

    CERN Document Server

    Moon, Woosok

    2016-01-01

    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 forcing into the Fokker-Planck equation and then seek approximate stochastic solutions. The formalism based on the Fokker-Planck equation with a singular perturbation method is flexible with regard to accommodating further complexity that arises due to the inclusion of long-term forcing. These solutions are then applied to the stochastic Arctic sea ice model with long-term forcing. Strong seasonality in the Arctic sea ice mod...

  6. Multi-model seasonal forecast of Arctic sea-ice: forecast uncertainty at pan-Arctic and regional scales

    Science.gov (United States)

    Blanchard-Wrigglesworth, E.; Barthélemy, A.; Chevallier, M.; Cullather, R.; Fučkar, N.; Massonnet, F.; Posey, P.; Wang, W.; Zhang, J.; Ardilouze, C.; Bitz, C. M.; Vernieres, G.; Wallcraft, A.; Wang, M.

    2016-10-01

    Dynamical model forecasts in the Sea Ice Outlook (SIO) of September Arctic sea-ice extent over the last decade have shown lower skill than that found in both idealized model experiments and hindcasts of previous decades. Additionally, it is unclear how different model physics, initial conditions or forecast post-processing (bias correction) techniques contribute to SIO forecast uncertainty. In this work, we have produced a seasonal forecast of 2015 Arctic summer sea ice using SIO dynamical models initialized with identical sea-ice thickness in the central Arctic. Our goals are to calculate the relative contribution of model uncertainty and irreducible error growth to forecast uncertainty and assess the importance of post-processing, and to contrast pan-Arctic forecast uncertainty with regional forecast uncertainty. We find that prior to forecast post-processing, model uncertainty is the main contributor to forecast uncertainty, whereas after forecast post-processing forecast uncertainty is reduced overall, model uncertainty is reduced by an order of magnitude, and irreducible error growth becomes the main contributor to forecast uncertainty. While all models generally agree in their post-processed forecasts of September sea-ice volume and extent, this is not the case for sea-ice concentration. Additionally, forecast uncertainty of sea-ice thickness grows at a much higher rate along Arctic coastlines relative to the central Arctic ocean. Potential ways of offering spatial forecast information based on the timescale over which the forecast signal beats the noise are also explored.

  7. Multi-model seasonal forecast of Arctic sea-ice: forecast uncertainty at pan-Arctic and regional scales

    Science.gov (United States)

    Blanchard-Wrigglesworth, E.; Barthélemy, A.; Chevallier, M.; Cullather, R.; Fučkar, N.; Massonnet, F.; Posey, P.; Wang, W.; Zhang, J.; Ardilouze, C.; Bitz, C. M.; Vernieres, G.; Wallcraft, A.; Wang, M.

    2017-08-01

    Dynamical model forecasts in the Sea Ice Outlook (SIO) of September Arctic sea-ice extent over the last decade have shown lower skill than that found in both idealized model experiments and hindcasts of previous decades. Additionally, it is unclear how different model physics, initial conditions or forecast post-processing (bias correction) techniques contribute to SIO forecast uncertainty. In this work, we have produced a seasonal forecast of 2015 Arctic summer sea ice using SIO dynamical models initialized with identical sea-ice thickness in the central Arctic. Our goals are to calculate the relative contribution of model uncertainty and irreducible error growth to forecast uncertainty and assess the importance of post-processing, and to contrast pan-Arctic forecast uncertainty with regional forecast uncertainty. We find that prior to forecast post-processing, model uncertainty is the main contributor to forecast uncertainty, whereas after forecast post-processing forecast uncertainty is reduced overall, model uncertainty is reduced by an order of magnitude, and irreducible error growth becomes the main contributor to forecast uncertainty. While all models generally agree in their post-processed forecasts of September sea-ice volume and extent, this is not the case for sea-ice concentration. Additionally, forecast uncertainty of sea-ice thickness grows at a much higher rate along Arctic coastlines relative to the central Arctic ocean. Potential ways of offering spatial forecast information based on the timescale over which the forecast signal beats the noise are also explored.

  8. Predictability of the Arctic sea ice edge

    Science.gov (United States)

    Goessling, H. F.; Tietsche, S.; Day, J. J.; Hawkins, E.; Jung, T.

    2016-02-01

    Skillful sea ice forecasts from days to years ahead are becoming increasingly important for the operation and planning of human activities in the Arctic. Here we analyze the potential predictability of the Arctic sea ice edge in six climate models. We introduce the integrated ice-edge error (IIEE), a user-relevant verification metric defined as the area where the forecast and the "truth" disagree on the ice concentration being above or below 15%. The IIEE lends itself to decomposition into an absolute extent error, corresponding to the common sea ice extent error, and a misplacement error. We find that the often-neglected misplacement error makes up more than half of the climatological IIEE. In idealized forecast ensembles initialized on 1 July, the IIEE grows faster than the absolute extent error. This means that the Arctic sea ice edge is less predictable than sea ice extent, particularly in September, with implications for the potential skill of end-user relevant forecasts.

  9. A comparison between gradient descent and stochastic approaches for parameter optimization of a sea ice model

    Science.gov (United States)

    Sumata, H.; Kauker, F.; Gerdes, R.; Köberle, C.; Karcher, M.

    2013-07-01

    Two types of optimization methods were applied to a parameter optimization problem in a coupled ocean-sea ice model of the Arctic, and applicability and efficiency of the respective methods were examined. One optimization utilizes a finite difference (FD) method based on a traditional gradient descent approach, while the other adopts a micro-genetic algorithm (μGA) as an example of a stochastic approach. The optimizations were performed by minimizing a cost function composed of model-data misfit of ice concentration, ice drift velocity and ice thickness. A series of optimizations were conducted that differ in the model formulation ("smoothed code" versus standard code) with respect to the FD method and in the population size and number of possibilities with respect to the μGA method. The FD method fails to estimate optimal parameters due to the ill-shaped nature of the cost function caused by the strong non-linearity of the system, whereas the genetic algorithms can effectively estimate near optimal parameters. The results of the study indicate that the sophisticated stochastic approach (μGA) is of practical use for parameter optimization of a coupled ocean-sea ice model with a medium-sized horizontal resolution of 50 km × 50 km as used in this study.

  10. A numerical model for interdecadal variability of sea ice cover in the Greenland-Iceland-Norwegian sea

    Energy Technology Data Exchange (ETDEWEB)

    Morales-Maqueda, M.A.; Willmott, A.J. [Keele Univ. (United Kingdom). Dept. of Mathematics; Darby, M.S. [Department of Mathematics, University of Exeter, North Park Road, Exeter, Devon EX4 4QE (United Kingdom)

    1999-02-01

    A coupled ocean-sea ice-atmosphere model is used to study interdecadal variability ({proportional_to}40 years) of sea ice depth and concentration in the Greenland-Iceland-Norwegian Sea. This oceanic region is represented by a meridionally aligned channel on a {beta}-plane with open zonal boundaries at 60 N and 80 N. The model consists of a one and a half layer reduced gravity ocean model, a thermodynamic/dynamic sea ice model and an energy balance model of the atmosphere. The coupled model is driven by prescribed surface wind stress, fluxes of heat, salt and ice at inflow points on the northern and southern open zonal boundaries and annual distribution of solar radiation. It is shown that the coupled model supports unforced modes of interdecadal oscillation resulting from a form of hydraulic control which regulates the total fluid volume in the oceanic active layer. The mechanism for the oscillations relies on the presence of three key features: (1) a region of intense oceanic entrainment located in the eastern part of the domain, (2) a vigorous southward flowing western boundary current, representing the east greenland current (EGC), which supports most of the meridional transport across the domain, and (3) a marked buoyancy contrast between the relatively salty domain interior and the much fresher western boundary region. During an oscillation excess water is pumped into the domain via entrainment, thereby creating an active layer depth anomaly, which then propagates westward via long baroclinic Rossby waves until it reaches the EGC where it is subsequently drained out of the domain across the southern open zonal boundary. (orig.) With 12 figs., 34 refs.

  11. The Sea Ice Board Game

    Science.gov (United States)

    Bertram, Kathryn Berry

    2008-01-01

    The National Science Foundation-funded Arctic Climate Modeling Program (ACMP) provides "curriculum resource-based professional development" materials that combine current science information with practical classroom instruction embedded with "best practice" techniques for teaching science to diverse students. The Sea Ice Board…

  12. The Sea Ice Board Game

    Science.gov (United States)

    Bertram, Kathryn Berry

    2008-01-01

    The National Science Foundation-funded Arctic Climate Modeling Program (ACMP) provides "curriculum resource-based professional development" materials that combine current science information with practical classroom instruction embedded with "best practice" techniques for teaching science to diverse students. The Sea Ice Board…

  13. Mean Climatic Characteristics in High Northern Latitudes in an Ocean-Sea Ice-Atmosphere Coupled Model

    Institute of Scientific and Technical Information of China (English)

    刘喜迎; 张学洪; 俞永强; 宇如聪

    2004-01-01

    Emphasizing the model's ability in mean climate reproduction in high northern latitudes, results from an ocean-sea ice-atmosphere coupled model are analyzed. It is shown that the coupled model can simulate the main characteristics of annual mean global sea surface temperature and sea level pressure well, but the extent of ice coverage produced in the Southern Hemisphere is not large enough. The main distribution characteristics of simulated sea level pressure and temperature at 850 hPa in high northern latitudes agree well with their counterparts in the NCEP reanalysis dataset, and the model can reproduce the Arctic Oscillation (AO) mode successfully. The simulated seasonal variation of sea ice in the Northern Hemisphere is rational and its main distribution features in winter agree well with those from observations.But the ice concentration in the sea ice edge area close to the Eurasian continent in the inner Arctic Ocean is much larger than the observation. There are significant interannual variation signals in the simulated sea ice concentration in winter in high northern latitudes and the most significant area lies in the Greenland Sea, followed by the Barents Sea. All of these features agree well with the results from observations.

  14. The Last Arctic Sea Ice Refuge

    Science.gov (United States)

    Pfirman, S. L.; Tremblay, B.; Newton, R.; Fowler, C.

    2010-12-01

    Summer sea ice may persist along the northern flank of Canada and Greenland for decades longer than the rest of the Arctic, raising the possibility of a naturally formed refugium for ice-associated species. Observations and models indicate that some ice in this region forms locally, while some is transported to the area by winds and ocean currents. Depending on future changes in melt patterns and sea ice transport rates, both the central Arctic and Siberian shelf seas may be sources of ice to the region. An international system of monitoring and management of the sea ice refuge, along with the ice source regions, has the potential to maintain viable habitat for ice-associated species, including polar bears, for decades into the future. Issues to consider in developing a strategy include: + the likely duration and extent of summer sea ice in this region based on observations, models and paleoenvironmental information + the extent and characteristics of the “ice shed” contributing sea ice to the refuge, including its dynamics, physical and biological characteristics as well as potential for contamination from local or long-range sources + likely assemblages of ice-associated species and their habitats + potential stressors such as transportation, tourism, resource extraction, contamination + policy, governance, and development issues including management strategies that could maintain the viability of the refuge.

  15. Modeling ocean and sea ice dynamics of the Canadian Arctic Archipelago: Aspects of forcing

    Science.gov (United States)

    Wekerle, Claudia; Wang, Qiang; Danilov, Sergey; Myers, Paul G.; Jung, Thomas; Schröter, Jens

    2013-04-01

    The Canadian Arctic Archipelago (CAA) is one of the main pathways for freshwater exiting the Arctic Ocean. Freshwater exported to the North Atlantic may influence the deep water formation in the Labrador Sea, and thus the meridional overturning circulation. Modeling ocean and sea ice conditions of the CAA is difficult because of narrow straits and complex coastlines. The Finite-Element Sea-ice Ocean circulation Model (FESOM) configured on a global mesh is applied to assess the volume, freshwater and sea ice transports through the CAA. With a mesh resolution of 5 km in the CAA we are able to accurately resolve complex coastlines. Outside the CAA the mesh is refined to 24 km north of 55°N with a global background resolution of 1.5°. In this study, first, it is shown that the transports modeled with FESOM correlate well with the available observational data. Second, the model is used to learn about the impact of different atmospheric forcing datasets differing in spatial and temporal resolution (CORE 2 and the Reforecast dataset from Environment Canada). The CORE 2 dataset is on the T62 grid, which is coarse compared to the Reforecast dataset with grid resolution of 0.45° longitude and 0.3° latitude. The temporal resolution of the Reforecast dataset is higher than the CORE 2 dataset (one hourly and 6-hourly data, respectively, for wind, surface temperature and specific humidity fields). The representation of sea ice in the CAA can be improved by using the high resolution atmospheric forcing.

  16. Classification of new-ice in the Greenland Sea using Satellite SSM/I radiometer and SeaWinds scatterometer data and comparison with ice model

    DEFF Research Database (Denmark)

    Tonboe, Rasmus; Pedersen, Leif Toudal

    2005-01-01

    In the ice covered waters of the Greenland Sea the polarisation ratio of QuikSCAT SeaWinds Ku-band (13.4 GHz) scatterometer measurements and the polarisation ratio of DMSP-SSM/I 19 GHz radiometer measurements are used in combination to classify new-ice and mature ice. In particular, the formation...... and radiative properties as reflected in the polarisation ratio. Our results based on these comparisons show that the transformation into older mature (sheet) ice occurs within 5 - 10 days. During one day the new-ice cover increased by 33 000 km(2). The new-ice appears in March 2001 as a peninsula (maximum...... to the physical transition of the ice cover from pancake ice to a consolidated young-ice sheet. The classification of each pixel into ice or water is done using two scatterometer parameters, namely the polarisation ratio and the daily standard deviation of the backscatter. (C) 2005 Elsevier Inc. All rights...

  17. Limitations of a coupled regional climate model in the reproduction of the observed Arctic sea-ice retreat

    Directory of Open Access Journals (Sweden)

    W. Dorn

    2012-03-01

    Full Text Available The effects of internal model variability on the simulation of Arctic sea-ice extent and volume have been examined with the aid of a seven-member ensemble with a coupled regional climate model for the period 1948–2008. Beyond general weaknesses related to insufficient representation of feedback processes, it is found that the model's ability to reproduce observed summer sea-ice retreat depends mainly on two factors: the correct simulation of the atmospheric circulation during the summer months and the sea-ice volume at the beginning of the melting period. Since internal model variability shows its maximum during the summer months, the ability to reproduce the observed atmospheric summer circulation is limited. In addition, the atmospheric circulation during summer also significantly affects the sea-ice volume over the years, leading to a limited ability to start with reasonable sea-ice volume into the melting period. Furthermore, the sea-ice volume pathway shows notable decadal variability which amplitude varies among the ensemble members. The scatter is particularly large in periods when the ice volume increases, indicating limited skill in reproducing high-ice years.

  18. Early 21st Century Anomalously Cold Central Eurasian Winters Forced By Arctic Sea Ice Retreat in an Atmosphere Model

    Science.gov (United States)

    Semenov, V. A.; Latif, M.

    2014-12-01

    The early 21st century was marked by several severe winters over Central Eurasia linked to a blocking anti-cyclone centered south of the Barents Sea (BS). The increased occurrence of such anomalously cold winters coincided with a strong reduction of winter Arctic sea ice cover (ASIC), especially in the BS where sea ice area exhibited a step-like decline in 2005, suggesting a possible connection. To study the possible link we performed simulations with a high-resolution global atmospheric general circulation model forced by a set of multi-year sea ice anomalies observed during the last decades. The regional circulation response to reduced ASIC in 2005-2012 exhibits a statistically significant anti-cyclonic surface pressure anomaly and a surface temperature response similar to that observed. The results suggest that the recent BS sea ice reduction may have been responsible for the recent anomalously cold winters in Central Eurasia. Furthermore, a positive sea ice anomaly in the late 1960s associated with negative phase of the North Atlantic Oscillation also results in a similar anti-cyclonic anomaly and a cooling over the continent in the model. This implies that the atmospheric circulation response to sea ice anomalies during the period of modern sea ice decline can be essentially non-linear, both with respect to amplitude and pattern.

  19. The impact of a thermodynamic sea-ice module in the COSMO numerical weather prediction model on simulations for the Laptev Sea, Siberian Arctic

    Directory of Open Access Journals (Sweden)

    David Schröder

    2011-05-01

    Full Text Available Previous versions of the Consortium for Small-scale Modelling (COSMO numerical weather prediction model have used a constant sea-ice surface temperature, but observations show a high degree of variability on sub-daily timescales. To account for this, we have implemented a thermodynamic sea-ice module in COSMO and performed simulations at a resolution of 15 km and 5 km for the Laptev Sea area in April 2008. Temporal and spatial variability of surface and 2-m air temperature are verified by four automatic weather stations deployed along the edge of the western New Siberian polynya during the Transdrift XIII-2 expedition and by surface temperature charts derived from Moderate Resolution Imaging Spectroradiometer (MODIS satellite data. A remarkable agreement between the new model results and these observations demonstrates that the implemented sea-ice module can be applied for short-range simulations. Prescribing the polynya areas daily, our COSMO simulations provide a high-resolution and high-quality atmospheric data set for the Laptev Sea for the period 14–30 April 2008. Based on this data set, we derive a mean total sea-ice production rate of 0.53 km3/day for all Laptev Sea polynyas under the assumption that the polynyas are ice-free and a rate of 0.30 km3/day if a 10-cm-thin ice layer is assumed. Our results indicate that ice production in Laptev Sea polynyas has been overestimated in previous studies.

  20. Modified PIC Method for Sea Ice Dynamics

    Institute of Scientific and Technical Information of China (English)

    WANG Rui-xue; JI Shun-ying; SHEN Hung-tao; YUE Qian-jin

    2005-01-01

    The sea ice cover displays various dynamical characteristics such as breakup, rafting, and ridging under external forces. To model the ice dynamic process accurately, the effective numerical modeling method should be established. In this paper, a modified particle-in-cell (PIC) method for sea ice dynamics is developed coupling the finite difference (FD) method and smoothed particle hydrodynamics (SPH). In this method, the ice cover is first discretized into a series of Lagrangian ice particles which have their own sizes, thicknesses, concentrations and velocities. The ice thickness and concentration at Eulerian grid positions are obtained by interpolation with the Gaussian function from their surrounding ice particles. The momentum of ice cover is solved with FD approach to obtain the Eulerian cell velocity, which is used to estimate the ice particle velocity with the Gaussian function also. The thickness and concentration of ice particles are adjusted with particle mass density and smooth length, which are adjusted with the redistribution of ice particles. With the above modified PIC method, numerical simulations for ice motion in an idealized rectangular basin and the ice dynamics in the Bohai Sea are carried out. These simulations show that this modified PIC method is applicable to sea ice dynamics simulation.

  1. Explicit representation and parametrised impacts of under ice shelf seas in the z∗ coordinate ocean model NEMO 3.6

    Directory of Open Access Journals (Sweden)

    P. Mathiot

    2017-07-01

    Full Text Available Ice-shelf–ocean interactions are a major source of freshwater on the Antarctic continental shelf and have a strong impact on ocean properties, ocean circulation and sea ice. However, climate models based on the ocean–sea ice model NEMO (Nucleus for European Modelling of the Ocean currently do not include these interactions in any detail. The capability of explicitly simulating the circulation beneath ice shelves is introduced in the non-linear free surface model NEMO. Its implementation into the NEMO framework and its assessment in an idealised and realistic circum-Antarctic configuration is described in this study. Compared with the current prescription of ice shelf melting (i.e. at the surface, inclusion of open sub-ice-shelf cavities leads to a decrease in sea ice thickness along the coast, a weakening of the ocean stratification on the shelf, a decrease in salinity of high-salinity shelf water on the Ross and Weddell sea shelves and an increase in the strength of the gyres that circulate within the over-deepened basins on the West Antarctic continental shelf. Mimicking the overturning circulation under the ice shelves by introducing a prescribed meltwater flux over the depth range of the ice shelf base, rather than at the surface, is also assessed. It yields similar improvements in the simulated ocean properties and circulation over the Antarctic continental shelf to those from the explicit ice shelf cavity representation. With the ice shelf cavities opened, the widely used three equation ice shelf melting formulation, which enables an interactive computation of melting, is tested. Comparison with observational estimates of ice shelf melting indicates realistic results for most ice shelves. However, melting rates for the Amery, Getz and George VI ice shelves are considerably overestimated.

  2. Explicit representation and parametrised impacts of under ice shelf seas in the z∗ coordinate ocean model NEMO 3.6

    Science.gov (United States)

    Mathiot, Pierre; Jenkins, Adrian; Harris, Christopher; Madec, Gurvan

    2017-07-01

    Ice-shelf-ocean interactions are a major source of freshwater on the Antarctic continental shelf and have a strong impact on ocean properties, ocean circulation and sea ice. However, climate models based on the ocean-sea ice model NEMO (Nucleus for European Modelling of the Ocean) currently do not include these interactions in any detail. The capability of explicitly simulating the circulation beneath ice shelves is introduced in the non-linear free surface model NEMO. Its implementation into the NEMO framework and its assessment in an idealised and realistic circum-Antarctic configuration is described in this study. Compared with the current prescription of ice shelf melting (i.e. at the surface), inclusion of open sub-ice-shelf cavities leads to a decrease in sea ice thickness along the coast, a weakening of the ocean stratification on the shelf, a decrease in salinity of high-salinity shelf water on the Ross and Weddell sea shelves and an increase in the strength of the gyres that circulate within the over-deepened basins on the West Antarctic continental shelf. Mimicking the overturning circulation under the ice shelves by introducing a prescribed meltwater flux over the depth range of the ice shelf base, rather than at the surface, is also assessed. It yields similar improvements in the simulated ocean properties and circulation over the Antarctic continental shelf to those from the explicit ice shelf cavity representation. With the ice shelf cavities opened, the widely used three equation ice shelf melting formulation, which enables an interactive computation of melting, is tested. Comparison with observational estimates of ice shelf melting indicates realistic results for most ice shelves. However, melting rates for the Amery, Getz and George VI ice shelves are considerably overestimated.

  3. EASE-Grid Sea Ice Age

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides weekly estimates of sea ice age for the Arctic Ocean from remotely sensed sea ice motion and sea ice extent. The ice age data are derived from...

  4. Reconstructing the Last Glacial Maximum ice sheet in the Weddell Sea embayment, Antarctica, using numerical modelling constrained by field evidence

    Science.gov (United States)

    Le Brocq, A. M.; Bentley, M. J.; Hubbard, A.; Fogwill, C. J.; Sugden, D. E.; Whitehouse, P. L.

    2011-09-01

    The Weddell Sea Embayment (WSE) sector of the Antarctic ice sheet has been suggested as a potential source for a period of rapid sea-level rise - Meltwater Pulse 1a, a 20 m rise in ˜500 years. Previous modelling attempts have predicted an extensive grounding line advance in the WSE, to the continental shelf break, leading to a large equivalent sea-level contribution for the sector. A range of recent field evidence suggests that the ice sheet elevation change in the WSE at the Last Glacial Maximum (LGM) is less than previously thought. This paper describes and discusses an ice flow modelling derived reconstruction of the LGM ice sheet in the WSE, constrained by the recent field evidence. The ice flow model reconstructions suggest that an ice sheet consistent with the field evidence does not support grounding line advance to the continental shelf break. A range of modelled ice sheet surfaces are instead produced, with different grounding line locations derived from a novel grounding line advance scheme. The ice sheet reconstructions which best fit the field constraints lead to a range of equivalent eustatic sea-level estimates between approximately 1.4 and 3 m for this sector. This paper describes the modelling procedure in detail, considers the assumptions and limitations associated with the modelling approach, and how the uncertainty may impact on the eustatic sea-level equivalent results for the WSE.

  5. Using the EC-Earth atmospheric model to quantify the impact of recent thinning of Arctic sea ice

    Science.gov (United States)

    Lang, Andreas Michael; Yang, Shuting; Kaas, Eigil

    2016-04-01

    The atmospheric general circulation model EC-EARTH has been employed to investigate the influence of a realistic change in recent Arctic sea ice thickness on local and remote climate. To investigate the atmospheric response of a realistically thinning sea ice compared to a uniform ice thickness of 1.5 m, two 32-year-long sets of simulations have been performed covering the period 1982-2013 and driven by observed SST and SIC which are only differing by the description of the sea ice thickness. Thickness data is taken from the GIOMAS dataset, which assimilates observed sea ice conditions. The results suggest that the atmospheric impact of recent declining thickness compared to a uniform thickness shows a higher warming trend over the central Arctic, consistent with the observed sea ice thinning, and a less strong warming trend over continental Europe. The influence of a variable thickness is most pronounced in winter and in the lowermost troposphere. Overall, the Arctic SAT response to a realistic sea ice loss including its thinning is in better agreement with the one seen in the reanalysis product ERA-Interim. Precipitation and cloud cover responses do not show a significant reponse to a realistic thickness change. Further analysis of potential remote responses to Arctic sea ice thinning is currently being performed.

  6. Climatology of the HOPE-G global ocean general circulation model - Sea ice general circulation model

    Energy Technology Data Exchange (ETDEWEB)

    Legutke, S. [Deutsches Klimarechenzentrum (DKRZ), Hamburg (Germany); Maier-Reimer, E. [Max-Planck-Institut fuer Meteorologie, Hamburg (Germany)

    1999-12-01

    The HOPE-G global ocean general circulation model (OGCM) climatology, obtained in a long-term forced integration is described. HOPE-G is a primitive-equation z-level ocean model which contains a dynamic-thermodynamic sea-ice model. It is formulated on a 2.8 grid with increased resolution in low latitudes in order to better resolve equatorial dynamics. The vertical resolution is 20 layers. The purpose of the integration was both to investigate the models ability to reproduce the observed general circulation of the world ocean and to obtain an initial state for coupled atmosphere - ocean - sea-ice climate simulations. The model was driven with daily mean data of a 15-year integration of the atmosphere general circulation model ECHAM4, the atmospheric component in later coupled runs. Thereby, a maximum of the flux variability that is expected to appear in coupled simulations is included already in the ocean spin-up experiment described here. The model was run for more than 2000 years until a quasi-steady state was achieved. It reproduces the major current systems and the main features of the so-called conveyor belt circulation. The observed distribution of water masses is reproduced reasonably well, although with a saline bias in the intermediate water masses and a warm bias in the deep and bottom water of the Atlantic and Indian Oceans. The model underestimates the meridional transport of heat in the Atlantic Ocean. The simulated heat transport in the other basins, though, is in good agreement with observations. (orig.)

  7. Climatology of the HOPE-G global ocean general circulation model - Sea ice general circulation model

    Energy Technology Data Exchange (ETDEWEB)

    Legutke, S. [Deutsches Klimarechenzentrum (DKRZ), Hamburg (Germany); Maier-Reimer, E. [Max-Planck-Institut fuer Meteorologie, Hamburg (Germany)

    1999-12-01

    The HOPE-G global ocean general circulation model (OGCM) climatology, obtained in a long-term forced integration is described. HOPE-G is a primitive-equation z-level ocean model which contains a dynamic-thermodynamic sea-ice model. It is formulated on a 2.8 grid with increased resolution in low latitudes in order to better resolve equatorial dynamics. The vertical resolution is 20 layers. The purpose of the integration was both to investigate the models ability to reproduce the observed general circulation of the world ocean and to obtain an initial state for coupled atmosphere - ocean - sea-ice climate simulations. The model was driven with daily mean data of a 15-year integration of the atmosphere general circulation model ECHAM4, the atmospheric component in later coupled runs. Thereby, a maximum of the flux variability that is expected to appear in coupled simulations is included already in the ocean spin-up experiment described here. The model was run for more than 2000 years until a quasi-steady state was achieved. It reproduces the major current systems and the main features of the so-called conveyor belt circulation. The observed distribution of water masses is reproduced reasonably well, although with a saline bias in the intermediate water masses and a warm bias in the deep and bottom water of the Atlantic and Indian Oceans. The model underestimates the meridional transport of heat in the Atlantic Ocean. The simulated heat transport in the other basins, though, is in good agreement with observations. (orig.)

  8. The consolidation of rafted sea ice

    Science.gov (United States)

    Bailey, E.; Feltham, D.; Sammonds, P.

    2009-04-01

    Rafting is an important process in the deformation of sea ice that occurs when two ice sheets collide. This process is particularly common in the North Caspian Sea, where ice floes override one another multiple times to produce thick sea ice features. To date, rafting has received little attention in the literature perhaps because in most regions pressure ridges produce the greatest loads on offshore structures. In the North Caspian Sea the shallow waters constrain the size to which pressure ridges can grow and the low salinity seems to favor rafting over ridging. Therefore it is likely that multiply-rafted sea ice may be the governing design feature for ice loads in the Caspian Sea. Here we present a one-dimensional, thermal-consolidation model for rafted sea ice. This is of interest because the degree of consolidation will affect the strength of a rafted structure, and therefore may be of value for modeling rafted ice loads. Results show that the thickness of the liquid layers reduces asymptotically with time, such that there always remains a thin liquid layer. We propose that when the liquid layer is equal to the surface roughness the adjacent layers can be considered consolidated. Using parameters specific to the North Caspian Sea, calculations show that it took 1hr, 14mins for the ice sheets to consolidate. To test the accuracy of the model concurrent experiments were carried out in the HSVA ice basin. During an experiment, equally sized portions of level ice were manually piled on top of one another to produce a rafted section. The rate of consolidation or bonding of the layers was then monitored by coring and using thermistors that were frozen into the level ice prior to rafting. Once consolidated, strength tests were carried out on the rafted ice and compared with those of level ice.

  9. Arctic tides from GPS on sea ice

    DEFF Research Database (Denmark)

    Kildegaard Rose, Stine; Skourup, Henriette; Forsberg, René

    The presence of sea-ice in the Arctic Ocean plays a significant role in the Arctic climate. Sea ice dampens the ocean tide amplitude with the result that global tidal models which use only astronomical data perform less accurately in the polar regions. This study presents a kinematic processing...... of Global Positioning System (GPS) buoys placed on sea-ice at five different sites north of Greenland for the study of sea level height and tidal analysis to improve tidal models in the Central Arctic. The GPS measurements are compared with the Arctic tidal model AOTIM-5, which assimilates tide...

  10. Discrete-Element bonded particle Sea Ice model DESIgn, version 1.3 – model description and implementation

    Directory of Open Access Journals (Sweden)

    A. Herman

    2015-07-01

    Full Text Available This paper presents theoretical foundations, numerical implementation and examples of application of a two-dimensional Discrete-Element bonded-particle Sea Ice model DESIgn. In the model, sea ice is represented as an assemblage of objects of two types: disk-shaped "grains", and semi-elastic bonds connecting them. Grains move on the sea surface under the influence of forces from the atmosphere and the ocean, as well as interactions with surrounding grains through a direct contact (Hertzian contact mechanics and/or through bonds. The model has an option of taking into account quasi-threedimensional effects related to space- and time-varying curvature of the sea surface, thus enabling simulation of ice breaking due to stresses resulting from bending moments associated with surface waves. Examples of the model's application to simple sea ice deformation and breaking problems are presented, with an analysis of the influence of the basic model parameters ("microscopic" properties of grains and bonds on the large-scale response of the modeled material. The model is written as a toolbox suitable for usage with the open-source numerical library LIGGGHTS. The code, together with a full technical documentation and example input files, is freely available with this paper and on the Internet.

  11. Discrete-Element bonded-particle Sea Ice model DESIgn, version 1.3a - model description and implementation

    Science.gov (United States)

    Herman, Agnieszka

    2016-04-01

    This paper presents theoretical foundations, numerical implementation and examples of application of the two-dimensional Discrete-Element bonded-particle Sea Ice model - DESIgn. In the model, sea ice is represented as an assemblage of objects of two types: disk-shaped "grains" and semi-elastic bonds connecting them. Grains move on the sea surface under the influence of forces from the atmosphere and the ocean, as well as interactions with surrounding grains through direct contact (Hertzian contact mechanics) and/or through bonds. The model has an experimental option of taking into account quasi-three-dimensional effects related to the space- and time-varying curvature of the sea surface, thus enabling simulation of ice breaking due to stresses resulting from bending moments associated with surface waves. Examples of the model's application to simple sea ice deformation and breaking problems are presented, with an analysis of the influence of the basic model parameters ("microscopic" properties of grains and bonds) on the large-scale response of the modeled material. The model is written as a toolbox suitable for usage with the open-source numerical library LIGGGHTS. The code, together with full technical documentation and example input files, is freely available with this paper and on the Internet.

  12. Analysis of an Arctic sea ice loss model in the limit of a discontinuous albedo

    CERN Document Server

    Hill, Kaitlin; Silber, Mary

    2015-01-01

    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 makes the system piecewise-smooth. Our analysis provides a case study where we use the piecewise-smooth system to explore bifurcation behavior of the smooth system. In this case study, we demonstrate that certain qualitative bifurcation behaviors of the smooth system can have nonsmooth counterparts. We use this perspective to systematically search parameter space. For example, we uncover parameter sets for which the largest transition, with increasing g...

  13. Observational and Theoretical Foundation for the Dynamics in a High-resolution Sea Ice Model

    Science.gov (United States)

    2016-06-07

    The thickness distribution of the ice cover has a significant impact on heat and energy exchange between the atmosphere, ice , and ocean . 2) I am...the ice mechanics at a regional scale, from observations made during the Sea Ice Mechanics Initiative (SIMI) and the Surface Heat Budget of the Arctic ...floes was stronger than the correlation between sites on the same floe. This result also validates our approach to measuring stress in the ice cover

  14. Wave Climate and Wave Mixing in the Marginal Ice Zones of Arctic Seas, Observations and Modelling

    Science.gov (United States)

    2015-09-30

    PROJECTS Section). With the group of Rogers, observation/modeling study of an energetic wave event in the Arctic marginal zone was conducted ...floe. (right) Surface elevation in the lee of a 5 mm thick polypropylene floe (thick black curves) and incident wave (grey), normalised with respect...Toffoli, A., Marusic, I., Klewicki, J., Hutchins, N., Suslov, S., Walker, D., Chung, D., “A Thermally Stratified Sea-Ice-Wave Interaction Facility”, ARC

  15. On the Role of Arctic Sea Ice Deformations: An Evaluation of the Regional Arctic System Model Results with Observations.

    Science.gov (United States)

    Osinski, Robert; Maslowski, Wieslaw; Roberts, Andrew

    2016-04-01

    The atmosphere - sea ice - ocean fluxes and their contribution to rapid changes in the Arctic system are not well understood and generally are not resolved by global climate models (GCMs). While many significant model refinements have been made in the recent past, including the representation of sea ice rheology, surface albedo and ice-albedo feedback, other processes such as sea ice deformations, still require further studies and model advancements. Of particular potential interest here are linear kinematic features (LKFs), which control winter air-sea heat exchange and affect buoyancy forces in the ocean. Their importance in Arctic climate change, especially under an increasing first-year ice cover, is yet to be determined and their simulation requires representation of processes currently at sub-grid scale of most GCMs. To address some of the GCM limitations and to better understand the role of LKFs in air-sea exchange we use the Regional Arctic System Model (RASM), which allows high spatio-temporal resolution and regional focus on the Arctic. RASM is a fully coupled regional climate model, developed to study dynamic and thermodynamic processes and their coupling across the atmosphere-sea ice-ocean interface. It consists of the Weather Research and Forecasting (WRF) atmospheric model, the Parallel Ocean Program (POP), the Community Ice Model (CICE) and the Variable Infiltration Capacity (VIC) land hydrology model. The sea ice component has been upgraded to the Los Alamos Community Ice Model version 5.1 (CICE5.1), which allows either Elastic-Viscous-Plastic (EVP) or a new anisotropic (EPA) rheology. RASM's domain is pan-Arctic, with the ocean and sea ice components configured at an eddy-permitting horizontal resolution of 1/12-degree as well as 1/48-degree, for limited simulations. The atmosphere and land model components are configured at 50-km grids. All the components are coupled at a 20-minute time step. Results from multiple RASM simulations are analyzed and

  16. On the Predictability of Sea Ice

    Science.gov (United States)

    Blanchard-Wrigglesworth, Edward

    We investigate the persistence and predictability of sea ice in numerical models and observations. We first use the 3rd generation Community Climate System Model (CCSM3) General Circulation Model (GCM) to investigate the inherent persistence of sea-ice area and thickness. We find that sea-ice area anomalies have a seasonal decay timescale, exhibiting an initial decorrelation similar to a first order auto-regressive (AR1, or red noise) process. Beyond this initial loss of memory, there is a re-emergence of memory at certain times of the year. There are two distinct modes of re-emergence in the model, one driven by the seasonal coupling of area and thickness anomalies in the summer, the other by the persistence of upper ocean temperature anomalies that originate from ice anomalies in the melt season and then influence ice anomalies in the growth season. Comparison with satellite observations where available indicate these processes appear in nature. We then use the 4th generation CCSM (CCSM4) to investigate the partition of Arctic sea-ice predictability into its initial-value and boundary forced components under present day forcing conditions. We find that initial-value predictability lasts for 1-2 years for sea-ice area, and 3-4 years for sea-ice volume. Forced predictability arises after just 4-5 years for both area and volume. Initial-value predictability of sea-ice area during the summer hinges on the coupling between thickness and area anomalies during that season. We find that the loss of initial-value predictability with time is not uniform --- there is a rapid loss of predictability of sea-ice volume during the late spring early summer associated with snow melt and albedo feedbacks. At the same time, loss of predictability is not uniform across different regions. Given the usefulness of ice thickness as a predictor of summer sea-ice area, we obtain a hindcast of September sea-ice area initializing the GCM on May 1with an estimate of observed sea-ice thickness

  17. Biogeochemical Coupling between Ocean and Sea Ice

    Science.gov (United States)

    Wang, S.; Jeffery, N.; Maltrud, M. E.; Elliott, S.; Wolfe, J.

    2016-12-01

    Biogeochemical processes in ocean and sea ice are tightly coupled at high latitudes. Ongoing changes in Arctic and Antarctic sea ice domain likely influence the coupled system, not only through physical fields but also biogeochemical properties. Investigating the system and its changes requires representation of ocean and sea ice biogeochemical cycles, as well as their coupling in Earth System Models. Our work is based on ACME-HiLAT, a new offshoot of the Community Earth System Model (CESM), including a comprehensive representation of marine ecosystems in the form of the Biogeochemical Elemental Cycling Module (BEC). A full vertical column sea ice biogeochemical module has recently been incorporated into the sea ice component. We have further introduced code modifications to couple key growth-limiting nutrients (N, Si, Fe), dissolved and particulate organic matter, and phytoplankton classes that are important in polar regions between ocean and sea ice. The coupling of ocean and sea ice biology-chemistry will enable representation of key processes such as the release of important climate active constituents or seeding algae from melting sea ice into surface waters. Sensitivity tests suggest sea ice and ocean biogeochemical coupling influences phytoplankton competition, biological production, and the CO2 flux. Sea ice algal seeding plays an important role in determining phytoplankton composition of Arctic early spring blooms, since different groups show various responses to the seeding biomass. Iron coupling leads to increased phytoplankton biomass in the Southern Ocean, which also affects carbon uptake via the biological pump. The coupling of macronutrients and organic matter may have weaker influences on the marine ecosystem. Our developments will allow climate scientists to investigate the fully coupled responses of the sea ice-ocean BGC system to physical changes in polar climate.

  18. Simulated Annual and Seasonal Arctic Ocean and Sea-Ice Variability From a High Resolution, Coupled Ice-Ocean Model

    Science.gov (United States)

    2001-09-01

    influence heat transfer to the surface, impacting polynya formation, ice melt, and ice growth. 13 Wang et al. (1994) presented results from a sigma level...Longmans, Green and Co., 1902. Nansen, F., Northern water: Captain Roald Amundsen’s oceanographic observations in the Arctic Seas in 1901...

  19. Sensitivity of Greenland Ice Sheet surface mass balance to perturbations in sea surface temperature and sea ice cover: a study with the regional climate model MAR

    Science.gov (United States)

    Noël, B.; Fettweis, X.; van de Berg, W. J.; van den Broeke, M. R.; Erpicum, M.

    2014-10-01

    During recent summers (2007-2012), several surface melt records were broken over the Greenland Ice Sheet (GrIS). The extreme summer melt resulted in part from a persistent negative phase of the North Atlantic Oscillation (NAO), favoring warmer atmospheric conditions than normal over the GrIS. Simultaneously, large anomalies in sea ice cover (SIC) and sea surface temperature (SST) were observed in the North Atlantic, suggesting a possible connection. To assess the direct impact of 2007-2012 SIC and SST anomalies on GrIS surface mass balance (SMB), a set of sensitivity experiments was carried out with the regional climate model MAR forced by ERA-Interim. These simulations suggest that perturbations in SST and SIC in the seas surrounding Greenland do not considerably impact GrIS SMB, as a result of the katabatic wind blocking effect. These offshore-directed winds prevent oceanic near-surface air, influenced by SIC and SST anomalies, from penetrating far inland. Therefore, the ice sheet SMB response is restricted to coastal regions, where katabatic winds cease. A topic for further investigation is how anomalies in SIC and SST might have indirectly affected the surface melt by changing the general circulation in the North Atlantic region, hence favoring more frequent warm air advection towards the GrIS.

  20. Glacial isostatic adjustment associated with the Barents Sea ice sheet: A modelling inter-comparison

    Science.gov (United States)

    Auriac, A.; Whitehouse, P. L.; Bentley, M. J.; Patton, H.; Lloyd, J. M.; Hubbard, A.

    2016-09-01

    The 3D geometrical evolution of the Barents Sea Ice Sheet (BSIS), particularly during its late-glacial retreat phase, remains largely ambiguous due to the paucity of direct marine- and terrestrial-based evidence constraining its horizontal and vertical extent and chronology. One way of validating the numerous BSIS reconstructions previously proposed is to collate and apply them under a wide range of Earth models and to compare prognostic (isostatic) output through time with known relative sea-level (RSL) data. Here we compare six contrasting BSIS load scenarios via a spherical Earth system model and derive a best-fit, χ2 parameter using RSL data from the four main terrestrial regions within the domain: Svalbard, Franz Josef Land, Novaya Zemlya and northern Norway. Poor χ2 values allow two load scenarios to be dismissed, leaving four that agree well with RSL observations. The remaining four scenarios optimally fit the RSL data when combined with Earth models that have an upper mantle viscosity of 0.2-2 × 1021 Pa s, while there is less sensitivity to the lithosphere thickness (ranging from 71 to 120 km) and lower mantle viscosity (spanning 1-50 × 1021 Pa s). GPS observations are also compared with predictions of present-day uplift across the Barents Sea. Key locations where relative sea-level and GPS data would prove critical in constraining future ice-sheet modelling efforts are also identified.

  1. Evaluating Physical Processes during the Freeze-Up Season using a Coupled Sea Ice-Ocean-Atmosphere Forecast Model

    Science.gov (United States)

    Solomon, Amy; Intrieri, Janet; Persson, Ola; Cox, Christopher; Hughes, Mimi; Grachev, Andrey; Capotondi, Antonietta; de Boer, Gijs

    2017-04-01

    Improved sea ice forecasting must be based on improved model representation of coupled system processes that impact the sea ice thermodynamic and dynamic state. Pertinent coupled system processes remain uncertain and include surface energy fluxes, clouds, precipitation, boundary layer structure, momentum transfer and sea-ice dynamics, interactions between large-scale circulation and local processes, and others. In this presentation, we use a fully-coupled ocean-sea ice-atmosphere forecast system as a testbed for investigating biases in 0-10 day forecasts, with a focus on processes that determine fluxes at the ocean-ice-air interface. Model results and validation examples from an experimental, weather-scale, coupled ice-ocean-atmosphere model for 2015 and 2016 fall, sea ice freeze-up season will be presented. The model, a limited-area, fully-coupled atmosphere-ice-ocean model (named, RASM-ESRL), was developed from the larger-scale Regional Arctic System Model (RASM) architecture. RASM-ESRL includes the Weather Research and Forecasting (WRF) atmospheric model, Parallel Ocean Program (POP2) model, Community Ice Model (CICE5) and the NCAR Community Land Model. The domain is limited to the Arctic and all components are run with 10 km horizontal resolution. Components are coupled using a regionalized version of the CESM flux coupler (CPL7), which includes modifications important for resolving the sea ice pack's inertial response to transient (i.e. weather) events. The model is initialized with a GFS atmosphere, satellite-derived sea ice analyses using AMSR-2, and forced by 3-hourly GFS forecasts at the lateral boundaries. Experimental forecasts were run daily from late-July through mid-November in 2015 and 2016. These daily forecasts have been compared with observations of surface fluxes and vertical atmospheric profiles at the International Arctic Systems for Observing the Atmosphere (IASOA) stations, and with atmospheric and oceanic observations obtained within the sea

  2. On sea level - ice sheet interactions

    Science.gov (United States)

    Gomez, Natalya Alissa

    This thesis focuses on the physics of static sea-level changes following variations in the distribution of grounded ice and the influence of these changes on the stability and dynamics of marine ice sheets. Gravitational, deformational and rotational effects associated with changes in grounded ice mass lead to markedly non-uniform spatial patterns of sea-level change. I outline a revised theory for computing post-glacial sea-level predictions and discuss the dominant physical effects that contribute to the patterns of sea-level change associated with surface loading on different timescales. I show, in particular, that a large sea-level fall (rise) occurs in the vicinity of a retreating (advancing) ice sheet on both short and long timescales. I also present an application of the sea-level theory in which I predict the sea-level changes associated with a new model of North American ice sheet evolution and consider the implications of the results for efforts to establish the sources of Meltwater Pulse 1A. These results demonstrate that viscous deformational effects can influence the amplitude of sea-level changes observed at far-field sea-level sites, even when the time window being considered is relatively short (≤ 500 years). Subsequently, I investigate the feedback of sea-level changes on marine ice-sheet stability and dynamics by coupling a global sea-level model to ice-sheet models of increasing complexity. To begin, I incorporate gravitationally self-consistent sea-level changes into an equilibrium marine ice-sheet stability theory to show that the sea-level changes have a stabilizing influence on ice-sheet retreat. Next, I consider the impact of the stabilizing mechanism on the timescale of ice-sheet retreat using a 1D dynamic coupled ice sheet - sea level model. Simulations with the coupled model, which incorporate viscoelastic deformation of the solid Earth, show that local sea-level changes at the grounding line act to slow, and in some cases, halt

  3. The Impact of Sea Ice Concentration Accuracies on Climate Model Simulations with the GISS GCM

    Science.gov (United States)

    Parkinson, Claire L.; Rind, David; Healy, Richard J.; Martinson, Douglas G.; Zukor, Dorothy J. (Technical Monitor)

    2000-01-01

    The Goddard Institute for Space Studies global climate model (GISS GCM) is used to examine the sensitivity of the simulated climate to sea ice concentration specifications in the type of simulation done in the Atmospheric Modeling Intercomparison Project (AMIP), with specified oceanic boundary conditions. Results show that sea ice concentration uncertainties of +/- 7% can affect simulated regional temperatures by more than 6 C, and biases in sea ice concentrations of +7% and -7% alter simulated annually averaged global surface air temperatures by -0.10 C and +0.17 C, respectively, over those in the control simulation. The resulting 0.27 C difference in simulated annual global surface air temperatures is reduced by a third, to 0.18 C, when considering instead biases of +4% and -4%. More broadly, least-squares fits through the temperature results of 17 simulations with ice concentration input changes ranging from increases of 50% versus the control simulation to decreases of 50% yield a yearly average global impact of 0.0107 C warming for every 1% ice concentration decrease, i.e., 1.07 C warming for the full +50% to -50% range. Regionally and on a monthly average basis, the differences can be far greater, especially in the polar regions, where wintertime contrasts between the +50% and -50% cases can exceed 30 C. However, few statistically significant effects are found outside the polar latitudes, and temperature effects over the non-polar oceans tend to be under 1 C, due in part to the specification of an unvarying annual cycle of sea surface temperatures. The +/- 7% and 14% results provide bounds on the impact (on GISS GCM simulations making use of satellite data) of satellite-derived ice concentration inaccuracies, +/- 7% being the current estimated average accuracy of satellite retrievals and +/- 4% being the anticipated improved average accuracy for upcoming satellite instruments. Results show that the impact on simulated temperatures of imposed ice concentration

  4. DRUCKER-PRAGER YIELD CRITERIA IN VISCOELASTIC-PLASTIC CONSTITUTIVE MODEL FOR THE STUDY OF SEA ICE DYNAMICS

    Institute of Scientific and Technical Information of China (English)

    WANG Gang; JI Shun-ying; LV He-xiang; YUE Qian-jin

    2006-01-01

    Based on the characteristics of sea ice drifting and ridging at meso-small scale, the Drucker-Prager (D-P) yield criteria was introduced into the Viscoelastic-Plastic (VEP) constitutive model for the study of sea ice dynamics. In this model, the Kelvin-Vogit viscoelastic model was adopted in the elastic stage, and the associated normal flow rule was used in the plastic stage. Using the VEP model, the sea ice ridging process was simulated in an idealized rectangular basin, and the simulation results show that the simulated ice ridge thickness is consistent with the analytical solution. Moreover, the VEP model with the D-P yield criteria was also applied for the sea ice simulation of Bohai Sea, and the ice thickness, concentration, velocity, and ice stress were obtained in 48 h. The simulated thickness distributions agree well with the satellite images. The singular problem in the Mohr-Coulomb (M-C) yield criteria was overcome by the D-P yield criteria, and the computational efficiency was also improved. In the numerical simulations described above, the smoothed particle hydrodynamics was applied.

  5. A fully coupled 3-D ice-sheet–sea-level model: algorithm and applications

    NARCIS (Netherlands)

    De Boer, B.; Stocchi, P.; van de Wal, R.S.W.

    2014-01-01

    Relative sea-level variations during the late Pleistocene can only be reconstructed with the knowledge of ice-sheet history. On the other hand, the knowledge of regional and global relative sea-level variations is necessary to learn about the changes in ice volume. Overcoming this problem of

  6. A fully coupled 3-D ice-sheet-sea-level model : Algorithm and applications

    NARCIS (Netherlands)

    De Boer, B.; Stocchi, P.; Van De Wal, R. S W

    2014-01-01

    Relative sea-level variations during the late Pleistocene can only be reconstructed with the knowledge of ice-sheet history. On the other hand, the knowledge of regional and global relative sea-level variations is necessary to learn about the changes in ice volume. Overcoming this problem of

  7. Using records from submarine, aircraft and satellite to evaluate climate model simulations of Arctic sea ice thickness

    Directory of Open Access Journals (Sweden)

    J. Stroeve

    2014-04-01

    Full Text Available Arctic sea ice thickness distributions from models participating in the World Climate Research Programme Coupled Model Intercomparison Project Phase 5 are evaluated against observations from submarines, aircraft and satellites. While it's encouraging that the mean thickness distributions from the models are in general agreement with observations, the spatial patterns of sea ice thickness are poorly represented in most models. The poor spatial representation of thickness patterns is associated with a failure of models to represent details of the mean atmospheric circulation pattern that governs the transport and spatial distribution of sea ice. The climate models as a whole also tend to underestimate the rate of ice volume loss from 1979 to 2013, though the multi-model ensemble mean trend remains within the uncertainty of that from the Pan-Arctic Ice Ocean Modeling and Assimilation System. These results raise concerns regarding the ability of CMIP5 models to realistically represent the processes driving the decline of Arctic sea ice and project the timing of when a seasonally ice-free Arctic may be realized.

  8. Interactions between Arctic sea ice drift, concentration and thickness modeled by NEMO-LIM3 at different resolutions

    Science.gov (United States)

    Docquier, David; Massonnet, François; Raulier, Jonathan; Lecomte, Olivier; Fichefet, Thierry

    2016-04-01

    Sea ice concentration and thickness have substantially decreased in the Arctic since the beginning of the satellite era. As a result, mechanical strength has decreased allowing more fracturing and leading to increased sea ice drift. However, recent studies have highlighted that the interplay between sea ice thermodynamics and dynamics is poorly represented in contemporary global climate model (GCM) simulations. Thus, the considerable inter-model spread in terms of future sea ice extent projections could be reduced by better understanding the interactions between drift, concentration and thickness. This study focuses on the results coming from the global coupled ocean-sea ice model NEMO-LIM3 between 1979 and 2012. Three different simulations are forced by the Drakkar Forcing Set (DFS) 5.2 and run on the global tripolar ORCA grid at spatial resolutions of 0.25, 1° and 2°. The relation between modeled sea ice drift, concentration and thickness is further analyzed, compared to observations and discussed in the framework of the above-mentioned poor representation. It is proposed as a process-based metric for evaluating model performance. This study forms part of the EU Horizon 2020 PRIMAVERA project aiming at developing a new generation of advanced and well-evaluated high-resolution GCMs.

  9. Development of statistical seasonal prediction models of Arctic Sea Ice concentration using CERES absorbed solar radiation

    Science.gov (United States)

    Kim, Yoojin; Kim, Ha-Rim; Choi, Yong-Sang; Kim, WonMoo; Kim, Hye-Sil

    2016-11-01

    Statistical seasonal prediction models for the Arctic sea ice concentration (SIC) were developed for the late summer (August-October) when the downward trend is dramatic. The absorbed solar radiation (ASR) at the top of the atmosphere in June has a significant seasonal leading role on the SIC. Based on the lagged ASR-SIC relationship, two simple statistical models were established: the Markovian stochastic and the linear regression models. Crossvalidated hindcasts of SIC from 1979 to 2014 by the two models were compared with each other and observation. The hindcasts showed general agreement between the models as they share a common predictor, ASR in June and the observed SIC was well reproduced, especially over the relatively thin-ice regions (of one- or multi-year sea ice). The robust predictability confirms the functional role of ASR in the prediction of SIC. In particular, the SIC prediction in October was quite promising probably due to the pronounced icealbedo feedback. The temporal correlation coefficients between the predicted SIC and the observed SIC were 0.79 and 0.82 by the Markovian and regression models, respectively. Small differences were observed between the two models; the regression model performed slightly better in August and September in terms of temporal correlation coefficients. Meanwhile, the prediction skills of the Markovian model in October were higher in the north of Chukchi, the East Siberian, and the Laptev Seas. A strong non-linear relationship between ASR in June and SIC in October in these areas would have increased the predictability of the Markovian model.

  10. Constraining projections of summer Arctic sea ice

    Directory of Open Access Journals (Sweden)

    F. Massonnet

    2012-11-01

    Full Text Available We examine the recent (1979–2010 and future (2011–2100 characteristics of the summer Arctic sea ice cover as simulated by 29 Earth system and general circulation models from the Coupled Model Intercomparison Project, phase 5 (CMIP5. As was the case with CMIP3, a large intermodel spread persists in the simulated summer sea ice losses over the 21st century for a given forcing scenario. The 1979–2010 sea ice extent, thickness distribution and volume characteristics of each CMIP5 model are discussed as potential constraints on the September sea ice extent (SSIE projections. Our results suggest first that the future changes in SSIE with respect to the 1979–2010 model SSIE are related in a complicated manner to the initial 1979–2010 sea ice model characteristics, due to the large diversity of the CMIP5 population: at a given time, some models are in an ice-free state while others are still on the track of ice loss. However, in phase plane plots (that do not consider the time as an independent variable, we show that the transition towards ice-free conditions is actually occurring in a very similar manner for all models. We also find that the year at which SSIE drops below a certain threshold is likely to be constrained by the present-day sea ice properties. In a second step, using several adequate 1979–2010 sea ice metrics, we effectively reduce the uncertainty as to when the Arctic could become nearly ice-free in summertime, the interval [2041, 2060] being our best estimate for a high climate forcing scenario.

  11. Enhancing calculation of thin sea ice growth

    Science.gov (United States)

    Appel, Igor

    2016-12-01

    The goal of the present study is to develop, generate, and integrate into operational practice a new model of ice growth. The development of this Sea Ice Growth Model for Arctic (SIGMA), a description of the theoretical foundation, the model advantages and analysis of its results are considered in the paper. The enhanced model includes two principal modifications. Surface temperature of snow on ice is defined as internal model parameter maintaining rigorous consistency between processes of atmosphere-ice thermodynamic interaction and ice growth. The snow depth on ice is naturally defined as a function of a local snowfall rate and linearly depends on time rather than ice thickness. The model was initially outlined in the Visible Infrared Radiometer Suite (VIIRS) Sea Ice Characterization Algorithm Theoretical Basis Document (Appel et al., 2005) that included two different approaches to retrieve sea ice age: reflectance analysis for daytime and derivation of ice thickness using energy balance for nighttime. Only the latter method is considered in this paper. The improved account for the influence of surface temperature and snow depth increases the reliability of ice thickness calculations and is used to develop an analytical Snow Depth/Ice Thickness Look up table suitable to the VIIRS observations as well as to other instruments. The applicability of SIGMA to retrieve ice thickness from the VIIRS satellite observations and the comparison of its results with the One-dimensional Thermodynamic Ice Model (OTIM) are also considered. The comparison of the two models demonstrating the difference between their assessments of heat fluxes and radical distinction between the influences of snow depth uncertainty on errors of ice thickness calculations is of great significance to further improve the retrieval of ice thickness from satellite observations.

  12. Calibrating a glaciological model of the Greenland ice sheet from the Last Glacial Maximum to present-day using field observations of relative sea level and ice extent

    Science.gov (United States)

    Simpson, Matthew J. R.; Milne, Glenn A.; Huybrechts, Philippe; Long, Antony J.

    2009-08-01

    We constrain a three-dimensional thermomechanical model of Greenland ice sheet (GrIS) evolution from the Last Glacial Maximum (LGM, 21 ka BP) to the present-day using, primarily, observations of relative sea level (RSL) as well as field data on past ice extent. Our new model (Huy2) fits a majority of the observations and is characterised by a number of key features: (i) the ice sheet had an excess volume (relative to present) of 4.1 m ice-equivalent sea level at the LGM, which increased to reach a maximum value of 4.6 m at 16.5 ka BP; (ii) retreat from the continental shelf was not continuous around the entire margin, as there was a Younger Dryas readvance in some areas. The final episode of marine retreat was rapid and relatively late (c. 12 ka BP), leaving the ice sheet land based by 10 ka BP; (iii) in response to the Holocene Thermal Maximum (HTM) the ice margin retreated behind its present-day position by up to 80 km in the southwest, 20 km in the south and 80 km in a small area of the northeast. As a result of this retreat the modelled ice sheet reaches a minimum extent between 5 and 4 ka BP, which corresponds to a deficit volume (relative to present) of 0.17 m ice-equivalent sea level. Our results suggest that remaining discrepancies between the model and the observations are likely associated with non-Greenland ice load, differences between modelled and observed present-day ice elevation around the margin, lateral variations in Earth structure and/or the pattern of ice margin retreat.

  13. Modeling seasonal variations of ocean and sea ice circulation in the Beaufort and Chukchi Seas: A model-data fusion study

    Institute of Scientific and Technical Information of China (English)

    WANG Jia; Kohei Mizobata; HU Haoguo; JIN Mei-bing; ZHANG Sheng; Walter Johnson; Koji Shimada; Moto Ikeda

    2008-01-01

    A 3.8-km Coupled Ice-Ocean Model (CIOM) was implemented to successfully reproduce many observed phenomena in the Beaufort and Chukchi seas, including the Bering-inflow-originated coastal current that splits into three branches:Alaska Coastal Water (ACW) , Central Channel, and Herald Valley branches. Other modeled phenomena include the Beaufort Slope Current (BSC) , the Beautort Gyre,the East Siberian Current (ESC), mesoscale eddies, seasonal landfast ice, sea ice ridging, shear, and deformation. Many of these downscaling processes can only be captured by using a high-resolution C1OM, nested in a global climate model. The seasonal cycles for sea ice concentration, thickness, velocity, and other variables are well reproduced with solid validation by satellite measurements. The seasonal cycles for upper ocean dynamics and thermodynamics are also well reproduced, which inelude the formation of the cold saline layer due to the injection of salt during sea ice formation, the BSC, and the subsurface upwelling in winter that brings up warm, even more saline Atlantic Water along the shelfbreak and shelf along the Beaufort coast.

  14. A comparison between gradient descent and stochastic approaches for parameter optimization of a coupled ocean-sea ice model

    Science.gov (United States)

    Sumata, H.; Kauker, F.; Gerdes, R.; Köberle, C.; Karcher, M.

    2012-11-01

    Two types of optimization methods were applied to a parameter optimization problem in a coupled ocean-sea ice model, and applicability and efficiency of the respective methods were examined. One is a finite difference method based on a traditional gradient descent approach, while the other adopts genetic algorithms as an example of stochastic approaches. Several series of parameter optimization experiments were performed by minimizing a cost function composed of model-data misfit of ice concentration, ice drift velocity and ice thickness. The finite difference method fails to estimate optimal parameters due to an ill-shaped nature of the cost function, whereas the genetic algorithms can effectively estimate near optimal parameters with a practical number of iterations. The results of the study indicate that a sophisticated stochastic approach is of practical use to a parameter optimization of a coupled ocean-sea ice model.

  15. Snow on Antarctic sea ice

    Science.gov (United States)

    Massom, Robert A.; Eicken, Hajo; Hass, Christian; Jeffries, Martin O.; Drinkwater, Mark R.; Sturm, Matthew; Worby, Anthony P.; Wu, Xingren; Lytle, Victoria I.; Ushio, Shuki; Morris, Kim; Reid, Phillip A.; Warren, Stephen G.; Allison, Ian

    2001-08-01

    Snow on Antarctic sea ice plays a complex and highly variable role in air-sea-ice interaction processes and the Earth's climate system. Using data collected mostly during the past 10 years, this paper reviews the following topics: snow thickness and snow type and their geographical and seasonal variations; snow grain size, density, and salinity; frequency of occurrence of slush; thermal conductivity, snow surface temperature, and temperature gradients within snow; and the effect of snow thickness on albedo. Major findings include large regional and seasonal differences in snow properties and thicknesses; the consequences of thicker snow and thinner ice in the Antarctic relative to the Arctic (e.g., the importance of flooding and snow-ice formation); the potential impact of increasing snowfall resulting from global climate change; lower observed values of snow thermal conductivity than those typically used in models; periodic large-scale melt in winter; and the contrast in summer melt processes between the Arctic and the Antarctic. Both climate modeling and remote sensing would benefit by taking account of the differences between the two polar regions.

  16. Biases of the Arctic climate in a regional ocean-sea ice-atmosphere coupled model:an annual validation

    Institute of Scientific and Technical Information of China (English)

    LIU Xiying

    2014-01-01

    The Coupling of three model components, WRF/PCE (polar climate extension version of weather research and forecasting model ( WRF)), ROMS (regional ocean modeling system), and CICE (community ice code), has been implemented, and the regional atmosphere-ocean-sea ice coupled model named WRF/PCE-ROMS-CICE has been validated against ERA-interim reanalysis data sets for 1989. To better understand the reasons that generate model biases, the WRF/PCE-ROMS-CICE results were compared with those of its components, the WRF/PCE and the ROMS-CICE. There are cold biases in surface air temperature (SAT) over the Arctic Ocean, which contribute to the sea ice concentration (SIC) and sea surface temperature (SST) biases in the results of the WRF/PCE-ROMS-CICE. The cold SAT biases also appear in results of the atmo-spheric component with a mild temperature in winter and similar temperature in summer. Compared to results from the WRF/PCE, due to influences of different distributions of the SIC and the SST and inclusion of interactions of air-sea-sea ice in the WRF/PCE-ROMS-CICE, the simulated SAT has new features. These influences also lead to apparent differences at higher levels of the atmosphere, which can be thought as responses to biases in the SST and sea ice extent. There are similar atmospheric responses in feature of distribution to sea ice biases at 700 and 500 hPa, and the strength of responses weakens when the pressure decreases in January. The atmospheric responses in July reach up to 200 hPa. There are surplus sea ice ex-tents in the Greenland Sea, the Barents Sea, the Davis Strait and the Chukchi Sea in winter and in the Beau-fort Sea, the Chukchi Sea, the East Siberian Sea and the Laptev Sea in summer in the ROMS-CICE. These differences in the SIC distribution can all be explained by those in the SST distributions. These features in the simulated SST and SIC from ROMS-CICE also appear in the WRF/PCE-ROMS-CICE. It is shown that the performance of the WRF/PCE-ROMS-CICE is

  17. Insights into Spatial Sensitivities of Ice Mass Response to Environmental Change from the SeaRISE Ice Sheet Modeling Project I: Antarctica

    Science.gov (United States)

    Nowicki, Sophie; Bindschadler, Robert A.; Abe-Ouchi, Ayako; Aschwanden, Andy; Bueler, Ed; Choi, Hyengu; Fastook, Jim; Granzow, Glen; Greve, Ralf; Gutowski, Gail; Herzfeld, Ute; Jacskon, Charles; Johnson, Jesse; Khroulev, Constantine; Larour, Eric; Levermann, Anders; Lipscomb, William H.; Martin, Maria A.; Morlighem, Mathieu; Parizek, Byron R; Pollard, David; Price, Stephen F.; Seroussi, Helene; Walker, Ryan; Wang, Wei Li

    2013-01-01

    Atmospheric, oceanic, and subglacial forcing scenarios from the Sea-level Response to Ice Sheet Evolution (SeaRISE) project are applied to six three-dimensional thermomechanical ice-sheet models to assess Antarctic ice sheet sensitivity over a 500 year timescale and to inform future modeling and field studies. Results indicate (i) growth with warming, except within low-latitude basins (where inland thickening is outpaced by marginal thinning); (ii) mass loss with enhanced sliding (with basins dominated by high driving stresses affected more than basins with low-surface-slope streaming ice); and (iii) mass loss with enhanced ice shelf melting (with changes in West Antarctica dominating the signal due to its marine setting and extensive ice shelves; cf. minimal impact in the Terre Adelie, George V, Oates, and Victoria Land region of East Antarctica). Ice loss due to dynamic changes associated with enhanced sliding and/or sub-shelf melting exceeds the gain due to increased precipitation. Furthermore, differences in results between and within basins as well as the controlling impact of sub-shelf melting on ice dynamics highlight the need for improved understanding of basal conditions, grounding-zone processes, ocean-ice interactions, and the numerical representation of all three.

  18. The seasonal foot printing mechanism of spring Arctic sea ice in the Bergen climate models

    Institute of Scientific and Technical Information of China (English)

    GUO Dong; GAO Yongqi; GONG Daoyi

    2014-01-01

    The inlfuence of spring Arctic sea ice variability on the Paciifc Decadal Oscillation (PDO) like sea surface temperature (SST) variability is established and investigated using an Atmosphere Ocean General Circulation Model (AOGCM) of the Bergen Climate Model version 2 (BCM2). The spring Arctic sea ice variability affects the mid-latitudes and tropics through the propagation of the anomalous Eliassen-Palm (E-P) lfux from the polar region to mid- and low-latitudes during boreal spring. The pathway includes anomalous upward wave activity, which propagates to the high troposphere from near the surface of the polar region, turns southward between 500 hPa and 200 hPa and extends downward between 50°N and 70°N, influencing the near surface atmospheric circulation. The alteration of the near surface atmospheric circulation then causes anomalous surface ocean circulation. These circulation changes consequently leads to the SST anomalies in the North Paciifc which may persist until the following summer, named seasonal “foot printing” mechanism (SFPM).

  19. Sensitivity of Antarctic sea ice to form drag parameterization: model results and remote sensing observations

    Science.gov (United States)

    Tsamados, M.; Barbic, G.; Petty, A.; Schroeder, D.; Holland, P.; Feltham, D. L.

    2016-12-01

    A new drag parametrization accounting explicitly for form drag has been recently formulated and applied to the Arctic sea ice (Lupkes et al, 2012 and Tsamados et al, 2014). We summarizehere the fundamental elements of this formulation and we then adapt it to the Antarctic sea ice. Considering the general expression of the momentum balance of sea ice, we analyze thetotal (neutral) drag coefficients by studying separately air-ice and ocean-ice momentum fluxes, and by introducing the parameterization for both the atmospheric neutral drag coeffcient (ANDC)and the oceanic neutral drag coeffcient (ONDC). The two coefficients are calculated as a sum of their skin frictional contribution and form drag contribution, which comes from ridges and floeedges for the ANDC and keels and floe edges for the ONDC. Due to the contrasting geography of the two polar regions, there are important differences, both dynamic and thermodynamic, betweenArctic and Antarctic sea ice. In the Antarctic, sea ice is younger, less ridged (hence thinner and smoother). Due to the intense snowfalls, the snow cover is generally thicker than in theArctic, with values that vary significantly both seasonally and regionally and can affect the roughness of the surface and can lead to flooding of the ice. At the outer boundary of the SouthernOcean, the ice is unconstrained by land, divergent and subject to meridional advection, which leads to a much faster ice drift than in the Arctic. We show here how the new parameterization accountingfor form drag influences the Antarctic sea ice characteristics.

  20. Modeling and Control for Dynamic Positioned Marine Vessels in Drifting Managed Sea Ice

    Directory of Open Access Journals (Sweden)

    Øyvind Kåre Kjerstad

    2014-10-01

    Full Text Available This paper presents a development framework for dynamic positioning control systems for marine vessels in managed ice. Due to the complexity of the vessel-ice and ice-ice interactions a configurable high fidelity numerical model simulating the vessel, the ice floes, the water, and the boundaries is applied. The numerical model is validated using experimental data and coupled with a control application incorporating sensor models, control systems, actuator models, and other external dynamics to form a closed loop development platform. The ice drift reversal is simulated by moving the positioning reference frame in an elliptic trajectory, rather than moving each individual ice floe. A control plant model is argued, and a control system for managed ice is proposed based on conventional open water design methods. A case study shows that dynamic positioning in managed ice is feasible for some moderate ice conditions.

  1. Sunlight, Sea Ice, and the Ice Albedo Feedback in a Changing Arctic Sea Ice Cover

    Science.gov (United States)

    2015-09-30

    the Arctic Ocean and surrounding seas, with particular emphasis on the Chukchi and Beaufort Seas. Some of the largest changes to the sea ice cover are...Changing Arctic Sea Ice Cover Don Perovich ERDC – CRREL 72 Lyme Road Hanover, NH 03755 Phone: 603-646-4255 Email: donald.k.perovich...quantitative understanding of the partitioning of solar radiation by the Arctic sea ice cover and its impact on the heat and mass balance of the ice and upper

  2. Fracture Networks in Sea Ice

    Directory of Open Access Journals (Sweden)

    Jonas Nesland Vevatne

    2014-04-01

    Full Text Available Fracturing and refreezing of sea ice in the Kara sea are investigated using complex networkanalysis. By going to the dual network, where the fractures are nodes and their intersectionslinks, we gain access to topological features which are easy to measure and hence comparewith modeled networks. Resulting network reveal statistical properties of the fracturing process.The dual networks have a broad degree distribution, with a scale-free tail, high clusteringand efficiency. The degree-degree correlation profile shows disassortative behavior, indicatingpreferential growth. This implies that long, dominating fractures appear earlier than shorterfractures, and that the short fractures which are created later tend to connect to the longfractures.The knowledge of the fracturing process is used to construct growing fracture network (GFNmodel which provides insight into the generation of fracture networks. The GFN model isprimarily based on the observation that fractures in sea ice are likely to end when hitting existingfractures. Based on an investigation of which fractures survive over time, a simple model forrefreezing is also added to the GFN model, and the model is analyzed and compared to the realnetworks.

  3. Linking scales in sea ice mechanics

    Science.gov (United States)

    Weiss, Jérôme; Dansereau, Véronique

    2017-02-01

    Mechanics plays a key role in the evolution of the sea ice cover through its control on drift, on momentum and thermal energy exchanges between the polar oceans and the atmosphere along cracks and faults, and on ice thickness distribution through opening and ridging processes. At the local scale, a significant variability of the mechanical strength is associated with the microstructural heterogeneity of saline ice, however characterized by a small correlation length, below the ice thickness scale. Conversely, the sea ice mechanical fields (velocity, strain and stress) are characterized by long-ranged (more than 1000 km) and long-lasting (approx. few months) correlations. The associated space and time scaling laws are the signature of the brittle character of sea ice mechanics, with deformation resulting from a multi-scale accumulation of episodic fracturing and faulting events. To translate the short-range-correlated disorder on strength into long-range-correlated mechanical fields, several key ingredients are identified: long-ranged elastic interactions, slow driving conditions, a slow viscous-like relaxation of elastic stresses and a restoring/healing mechanism. These ingredients constrained the development of a new continuum mechanics modelling framework for the sea ice cover, called Maxwell-elasto-brittle. Idealized simulations without advection demonstrate that this rheological framework reproduces the main characteristics of sea ice mechanics, including anisotropy, spatial localization and intermittency, as well as the associated scaling laws. This article is part of the themed issue 'Microdynamics of ice'.

  4. Ocean circulation: its effects on seasonal sea-ice simulations.

    Science.gov (United States)

    Hibler, W D; Bryan, K

    1984-05-04

    A diagnostic ice-ocean model of the Arctic, Greenland, and Norwegian seas is constructed and used to examine the role of ocean circulation in seasonal sea-ice simulations. The model includes lateral ice motion and three-dimensional ocean circulation. The ocean portion of the model is weakly forced by observed temperature and salinity data. Simulation results show that including modeled ocean circulation in seasonal sea-ice simulations substantially improves the predicted ice drift and ice margin location. Simulations that do not include lateral ocean movment predict a much less realistic ice edge.

  5. Sea-ice dynamics strongly promote Snowball Earth initiation and destabilize tropical sea-ice margins

    Directory of Open Access Journals (Sweden)

    A. Voigt

    2012-12-01

    Full Text Available The Snowball Earth bifurcation, or runaway ice-albedo feedback, is defined for particular boundary conditions by a critical CO2 and a critical sea-ice cover (SI, both of which are essential for evaluating hypotheses related to Neoproterozoic glaciations. Previous work has shown that the Snowball Earth bifurcation, denoted as (CO2, SI*, differs greatly among climate models. Here, we study the effect of bare sea-ice albedo, sea-ice dynamics and ocean heat transport on (CO2, SI* in the atmosphere–ocean general circulation model ECHAM5/MPI-OM with Marinoan (~ 635 Ma continents and solar insolation (94% of modern. In its standard setup, ECHAM5/MPI-OM initiates a~Snowball Earth much more easily than other climate models at (CO2, SI* ≈ (500 ppm, 55%. Replacing the model's standard bare sea-ice albedo of 0.75 by a much lower value of 0.45, we find (CO2, SI* ≈ (204 ppm, 70%. This is consistent with previous work and results from net evaporation and local melting near the sea-ice margin. When we additionally disable sea-ice dynamics, we find that the Snowball Earth bifurcation can be pushed even closer to the equator and occurs at a hundred times lower CO2: (CO2, SI* ≈ (2 ppm, 85%. Therefore, the simulation of sea-ice dynamics in ECHAM5/MPI-OM is a dominant determinant of its high critical CO2 for Snowball initiation relative to other models. Ocean heat transport has no effect on the critical sea-ice cover and only slightly decreases the critical CO2. For disabled sea-ice dynamics, the state with 85% sea-ice cover is stabilized by the Jormungand mechanism and shares characteristics with the Jormungand climate states. However, there is no indication of the Jormungand bifurcation and hysteresis in ECHAM5/MPI-OM. The state with 85% sea-ice cover therefore is a soft Snowball state rather than a true

  6. Stratospheric Impacts on Arctic Sea Ice

    Science.gov (United States)

    Reichler, Thomas

    2016-04-01

    Long-term circulation change in the stratosphere can have substantial effects on the oceans and their circulation. In this study we investigate whether and how sea ice at the ocean surface responds to intraseasonal stratospheric variability. Our main question is whether the surface impact of stratospheric sudden warmings (SSWs) is strong and long enough to affect sea ice. A related question is whether the increased frequency of SSWs during the 2000s contributed to the rapid decrease in Arctic sea ice during this time. To this end we analyze observations of sea ice, NCEP/NCAR reanalysis, and a long control integration with a stratospherically-enhanced version of the GFDL CM2.1 climate model. From both observations and the model we find that stratospheric extreme events have a demonstrable impact on the distribution of Arctic sea ice. The areas most affected are near the edge of the climatological ice line over the North Atlantic, North Pacific, and the Arctic Ocean. The absolute changes in sea ice coverage amount to +/-10 %. Areas and magnitudes of increase and decrease are about the same. It is thus unlikely that the increased SSW frequency during the 2000s contributed to the decline of sea ice during that period. The sea ice changes are consistent with the impacts of a negative NAO at the surface and can be understood in terms of (1) dynamical change due to altered surface wind stress and (2) thermodynamical change due to altered temperature advection. Both dynamical and thermodynamical change positively reinforce each other in producing sea change. A simple advection model is used to demonstrate that most of the sea ice change can be explained from the sea ice drift due to the anomalous surface wind stress. Changes in the production or melt of sea ice by thermodynamical effects are less important. Overall, this study adds to an increasing body of evidence that the stratosphere not only impacts weather and climate of the atmosphere but also the surface and

  7. Arctic sea ice thickness changes in terms of sea ice age

    Institute of Scientific and Technical Information of China (English)

    BI Haibo; FU Min; SUN Ke; LIU Yilin; XU Xiuli; HUANG Haijun

    2016-01-01

    In this study, changes in Arctic sea ice thickness for each ice age category were examined based on satellite observations and modelled results. Interannual changes obtained from Ice, Cloud, and Land Elevation Satellite (ICESat)-based results show a thickness reduction over perennial sea ice (ice that survives at least one melt season with an age of no less than 2 year) up to approximately 0.5–1.0 m and 0.6–0.8 m (depending on ice age) during the investigated winter and autumn ICESat periods, respectively. Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS)-based results provide a view of a continued thickness reduction over the past four decades. Compared to 1980s, there is a clear thickness drop of roughly 0.50 m in 2010s for perennial ice. This overall decrease in sea ice thickness can be in part attributed to the amplified warming climate in north latitudes. Besides, we figure out that strongly anomalous southerly summer surface winds may play an important role in prompting the thickness decline in perennial ice zone through transporting heat deposited in open water (primarily via albedo feedback) in Eurasian sector deep into a broader sea ice regime in central Arctic Ocean. This heat source is responsible for enhanced ice bottom melting, leading to further reduction in ice thickness.

  8. A modified global Newton solver for viscous-plastic sea ice models

    Science.gov (United States)

    Mehlmann, C.; Richter, T.

    2017-08-01

    We present and analyze a modified Newton solver, the so called operator-related damped Jacobian method, with a line search globalization for the solution of the strongly nonlinear momentum equation in a viscous-plastic (VP) sea ice model.Due to large variations in the viscosities, the resulting nonlinear problem is very difficult to solve. The development of fast, robust and converging solvers is subject to present research. There are mainly three approaches for solving the nonlinear momentum equation of the VP model, a fixed-point method denoted as Picard solver, an inexact Newton method and a subcycling procedure based on an elastic-viscous-plastic model approximation. All methods tend to have problems on fine meshes by sharp structures in the solution. Convergence rates deteriorate such that either too many iterations are required to reach sufficient accuracy or convergence is not obtained at all.To improve robustness globalization and acceleration approaches, which increase the area of fast convergence, are needed. We develop an implicit scheme with improved convergence properties by combining an inexact Newton method with a Picard solver. We derive the full Jacobian of the viscous-plastic sea ice momentum equation and show that the Jacobian is a positive definite matrix, guaranteeing global convergence of a properly damped Newton iteration. We compare our modified Newton solver with line search damping to an inexact Newton method with established globalization and acceleration techniques. We present a test case that shows improved robustness of our new approach, in particular on fine meshes.

  9. Mirabilite solubility in equilibrium sea ice brines

    Science.gov (United States)

    Butler, Benjamin Miles; Papadimitriou, Stathys; Santoro, Anna; Kennedy, Hilary

    2016-06-01

    The sea ice microstructure is permeated by brine channels and pockets that contain concentrated seawater-derived brine. Cooling the sea ice results in further formation of pure ice within these pockets as thermal equilibrium is attained, resulting in a smaller volume of increasingly concentrated residual brine. The coupled changes in temperature and ionic composition result in supersaturation of the brine with respect to mirabilite (Na2SO4·10H2O) at temperatures below -6.38 °C, which consequently precipitates within the sea ice microstructure. Here, mirabilite solubility in natural and synthetic seawater derived brines, representative of sea ice at thermal equilibrium, has been measured in laboratory experiments between 0.2 and -20.6 °C, and hence we present a detailed examination of mirabilite dynamics within the sea ice system. Below -6.38 °C mirabilite displays particularly large changes in solubility as the temperature decreases, and by -20.6 °C its precipitation results in 12.90% and 91.97% reductions in the total dissolved Na+ and SO42- concentrations respectively, compared to that of conservative seawater concentration. Such large non-conservative changes in brine composition could potentially impact upon the measurement of sea ice brine salinity and pH, whilst the altered osmotic conditions may create additional challenges for the sympagic organisms that inhabit the sea ice system. At temperatures above -6.38 °C, mirabilite again displays large changes in solubility that likely aid in impeding its identification in field samples of sea ice. Our solubility measurements display excellent agreement with that of the FREZCHEM model, which was therefore used to supplement our measurements to colder temperatures. Measured and modelled solubility data were incorporated into a 1D model for the growth of first-year Arctic sea ice. Model results ultimately suggest that mirabilite has a near ubiquitous presence in much of the sea ice on Earth, and illustrate the

  10. Sea Ice Trends in the AO-UMUKCA model: Interplay of Forcing and Internal Variability

    Science.gov (United States)

    Jrrar, Amna; Abraham, Luke; Holland, David; Pyle, John

    2016-04-01

    While Arctic Sea is showing a declining trend particularly in summer. Antarctic sea is showing a modest increase, a very controversial observation in a warming climate. Several studies have attributed these changes to internal variability. Hence in this paper we investigate sea ice trends in both hemispheres as simulated in a version of the Atmosphere-Ocean coupled chemistry climate model AO-UMUKCA under two different atmospheric forcing scenarios. One simulation is a pre-industrial control, where atmospheric forcing is fixed at 1850 level. The second simulation is also a time slice experiment but forced with the year 2000 atmospheric forcing (TS2000). The model simulates a significant reduction in NH Sea Ice Extent (SIE) under the TS2000 scenario, but shows negligible difference in SH SIE between the two scenarios. In agreement with observational studies, we find that NH SIE and distribution are connected to the Arctic Oscillation and the Dipole Anomaly in both simulations, particularly in summer time. While SH winter SIE shows a high correlation with zonal wave-3 pattern and the Pacific South American mode, particularly in TS2000. Connections between SIE and oceanic modes of variability in both hemispheres are also detected. Total NH SIE shows significant correlation with Atlantic Multidecadal Oscillation (AMO) on interannual and decadal timescales, but shows significant correlation with the Inter Pacific Decadal Oscillation (IPO) on multi-decadal timescale only. However, total SH SIE shows significant correlation only with IPO on decadal and multi-decadal scales. The SIE response to oceanic modes is comparable in both simulations.

  11. The EUMETSAT sea ice concentration climate data record

    Science.gov (United States)

    Tonboe, Rasmus T.; Eastwood, Steinar; Lavergne, Thomas; Sørensen, Atle M.; Rathmann, Nicholas; Dybkjær, Gorm; Toudal Pedersen, Leif; Høyer, Jacob L.; Kern, Stefan

    2016-09-01

    An Arctic and Antarctic sea ice area and extent dataset has been generated by EUMETSAT's Ocean and Sea Ice Satellite Application Facility (OSISAF) using the record of microwave radiometer data from NASA's Nimbus 7 Scanning Multichannel Microwave radiometer (SMMR) and the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) and Special Sensor Microwave Imager and Sounder (SSMIS) satellite sensors. The dataset covers the period from October 1978 to April 2015 and updates and further developments are planned for the next phase of the project. The methodology for computing the sea ice concentration uses (1) numerical weather prediction (NWP) data input to a radiative transfer model for reduction of the impact of weather conditions on the measured brightness temperatures; (2) dynamical algorithm tie points to mitigate trends in residual atmospheric, sea ice, and water emission characteristics and inter-sensor differences/biases; and (3) a hybrid sea ice concentration algorithm using the Bristol algorithm over ice and the Bootstrap algorithm in frequency mode over open water. A new sea ice concentration uncertainty algorithm has been developed to estimate the spatial and temporal variability in sea ice concentration retrieval accuracy. A comparison to US National Ice Center sea ice charts from the Arctic and the Antarctic shows that ice concentrations are higher in the ice charts than estimated from the radiometer data at intermediate sea ice concentrations between open water and 100 % ice. The sea ice concentration climate data record is available for download at www.osi-saf.org, including documentation.

  12. Early Student Support to Investigate the Role of Sea Ice-Albedo Feedback in Sea Ice Predictions

    Science.gov (United States)

    2014-09-30

    all its versions employs the Los Alamos National Laboratory ( LANL ) sea ice model, known as CICE. The sea ice in CESM1 has been documented in a...their method so successful and yet a nonlocal relationship exists between sea ice meltponds and the location Report Documentation Page Form ApprovedOMB... LANL , who is the chief developer of CICE. Dr. Hunke is a partner with the sea ice prediction network and has a postdoc working with her to improve CICE

  13. Atmospheric Profiles, Clouds, and the Evolution of Sea Ice Cover in the Beaufort and Chukchi Seas: Atmospheric Observations and Modeling as Part of the SeasonalIce Zone Reconnaissance Surveys

    Science.gov (United States)

    2015-09-30

    ability of global atmospheric reanalyses and forecast models to reflect the details of the seasonal evolution of atmosphere- ice -ocean interactions in the...analog for expected future ice retreat. SIZRS takes advantage of routine Coast Guard C-130 domain awareness missions that take place at bi-weekly...radiative processes might be more important for the underlying sea ice . Under synoptic condition S04, the warm , dry, and strongly stratified atmosphere

  14. Structural Uncertainty in Antarctic sea ice simulations

    Science.gov (United States)

    Schneider, D. P.

    2016-12-01

    The inability of the vast majority of historical climate model simulations to reproduce the observed increase in Antarctic sea ice has motivated many studies about the quality of the observational record, the role of natural variability versus forced changes, and the possibility of missing or inadequate forcings in the models (such as freshwater discharge from thinning ice shelves or an inadequate magnitude of stratospheric ozone depletion). In this presentation I will highlight another source of uncertainty that has received comparatively little attention: Structural uncertainty, that is, the systematic uncertainty in simulated sea ice trends that arises from model physics and mean-state biases. Using two large ensembles of experiments from the Community Earth System Model (CESM), I will show that the model is predisposed towards producing negative Antarctic sea ice trends during 1979-present, and that this outcome is not simply because the model's decadal variability is out-of-synch with that in nature. In the "Tropical Pacific Pacemaker" ensemble, in which observed tropical Pacific SST anomalies are prescribed, the model produces very realistic atmospheric circulation trends over the Southern Ocean, yet the sea ice trend is negative in every ensemble member. However, if the ensemble-mean trend (commonly interpreted as the forced response) is removed, some ensemble members show a sea ice increase that is very similar to the observed. While this results does confirm the important role of natural variability, it also suggests a strong bias in the forced response. I will discuss the reasons for this systematic bias and explore possible remedies. This an important problem to solve because projections of 21st -Century changes in the Antarctic climate system (including ice sheet surface mass balance changes and related changes in the sea level budget) have a strong dependence on the mean state of and changes in the Antarctic sea ice cover. This problem is not unique to

  15. MODEL OF SEA ICE BREAKUP ON SHALLOW BEACH DUE TO TIDAL FLUCTUATION

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    There are many factors that may lead to the breakup of shore fast ice, such as wind, wave, tide and so on.This paper mainly analyzed the ice breakup on the shallow beach due to tidal fluctuation.The theoretical model was set up and the fitting range was given.The calculated result shows that the slope angle α, the ice thickness h, and the ice length l are key factors in determining the ice breakup length lp.

  16. Greenland ice sheet contribution to sea level rise during the last interglacial period: a modelling study driven and constrained by ice core data

    Directory of Open Access Journals (Sweden)

    A. Quiquet

    2013-02-01

    Full Text Available As pointed out by the forth assessment report of the Intergovernmental Panel on Climate Change, IPCC-AR4 (Meehl et al., 2007, the contribution of the two major ice sheets, Antarctica and Greenland, to global sea level rise, is a subject of key importance for the scientific community. By the end of the next century, a 3–5 °C warming is expected in Greenland. Similar temperatures in this region were reached during the last interglacial (LIG period, 130–115 ka BP, due to a change in orbital configuration rather than to an anthropogenic forcing. Ice core evidence suggests that the Greenland ice sheet (GIS survived this warm period, but great uncertainties remain about the total Greenland ice reduction during the LIG. Here we perform long-term simulations of the GIS using an improved ice sheet model. Both the methodologies chosen to reconstruct palaeoclimate and to calibrate the model are strongly based on proxy data. We suggest a relatively low contribution to LIG sea level rise from Greenland melting, ranging from 0.7 to 1.5 m of sea level equivalent, contrasting with previous studies. Our results suggest an important contribution of the Antarctic ice sheet to the LIG highstand.

  17. Polar bears and sea ice habitat change

    Science.gov (United States)

    Durner, George M.; Atwood, Todd C.; Butterworth, Andy

    2017-01-01

    The polar bear (Ursus maritimus) is an obligate apex predator of Arctic sea ice and as such can be affected by climate warming-induced changes in the extent and composition of pack ice and its impacts on their seal prey. Sea ice declines have negatively impacted some polar bear subpopulations through reduced energy input because of loss of hunting habitats, higher energy costs due to greater ice drift, ice fracturing and open water, and ultimately greater challenges to recruit young. Projections made from the output of global climate models suggest that polar bears in peripheral Arctic and sub-Arctic seas will be reduced in numbers or become extirpated by the end of the twenty-first century if the rate of climate warming continues on its present trajectory. The same projections also suggest that polar bears may persist in the high-latitude Arctic where heavy multiyear sea ice that has been typical in that region is being replaced by thinner annual ice. Underlying physical and biological oceanography provides clues as to why polar bear in some regions are negatively impacted, while bears in other regions have shown no apparent changes. However, continued declines in sea ice will eventually challenge the survival of polar bears and efforts to conserve them in all regions of the Arctic.

  18. Forecasting Future Sea Ice Conditions: A Lagrangian Approach

    Science.gov (United States)

    2014-09-30

    that survives the summer melt season in each of the Arctic peripheral seas. The Lagrangian Model is forced with weekly mean satellite-derived sea- ice ...GCM to drive the Lagrangian code and map the regions for the multi-year ice surviving the summer melt in each of the Arctic peripheral seas in todays...1995, Emery et al. 1997, Meier et al. 2000, Tschudi et al. 2010) 3- Assess whether the source region of sea ice melting in peripheral seas in the

  19. Short-term sea ice forecasts with the RASM-ESRL coupled model: A testbed for improving simulations of ocean-ice-atmosphere interactions in the marginal ice zone

    Science.gov (United States)

    Solomon, A.; Cox, C. J.; Hughes, M.; Intrieri, J. M.; Persson, O. P. G.

    2015-12-01

    The dramatic decrease of Arctic sea-ice has led to a new Arctic sea-ice paradigm and to increased commercial activity in the Arctic Ocean. NOAA's mission to provide accurate and timely sea-ice forecasts, as explicitly outlined in the National Ocean Policy and the U.S. National Strategy for the Arctic Region, needs significant improvement across a range of time scales to improve safety for human activity. Unfortunately, the sea-ice evolution in the new Arctic involves the interaction of numerous physical processes in the atmosphere, ice, and ocean, some of which are not yet understood. These include atmospheric forcing of sea-ice movement through stress and stress deformation; atmospheric forcing of sea-ice melt and formation through energy fluxes; and ocean forcing of the atmosphere through new regions of seasonal heat release. Many of these interactions involve emerging complex processes that first need to be understood and then incorporated into forecast models in order to realize the goal of useful sea-ice forecasting. The underlying hypothesis for this study is that errors in simulations of "fast" atmospheric processes significantly impact the forecast of seasonal sea-ice retreat in summer and its advance in autumn in the marginal ice zone (MIZ). We therefore focus on short-term (0-20 day) ice-floe movement, the freeze-up and melt-back processes in the MIZ, and the role of storms in modulating stress and heat fluxes. This study uses a coupled ocean-atmosphere-seaice forecast model as a testbed to investigate; whether ocean-sea ice-atmosphere coupling improves forecasts on subseasonal time scales, where systematic biases develop due to inadequate parameterizations (focusing on mixed-phase clouds and surface fluxes), how increased atmospheric resolution of synoptic features improves the forecasts, and how initialization of sea ice area and thickness and snow depth impacts the skill of the forecasts. Simulations are validated with measurements at pan-Arctic land

  20. Sunlight, Sea Ice, and the Ice Albedo Feedback in a Changing Artic Sea Ice Cover

    Science.gov (United States)

    2015-11-30

    Arctic sea ice cover and its impact on the heat and mass balance of the ice and upper ocean ... Arctic Ocean and surrounding seas, with particular emphasis on the Chukchi and Beaufort Seas. Some of the largest changes to the sea ice cover are...other parts of the Arctic ice cover appear to now be accelerating. Figure 6. Maps of the linear trend of annual solar heat input to the ocean

  1. Model estimating the effect of marginal ice zone processes on the phytoplankton primary production and air-sea flux of CO2 in the Barents Sea

    Science.gov (United States)

    Dvornikov, Anton; Sein, Dmitry; Ryabchenko, Vladimir; Gorchakov, Victor; Martjyanov, Stanislav

    2016-04-01

    This study is aimed to assess the impact of sea ice on the primary production of phytoplankton (PPP) and air-sea CO2 flux in the Barents Sea. To get the estimations, we apply a three-dimensional eco-hydrodynamic model based on the Princeton Ocean Model which includes: 1) a module of sea ice with 7 categories, and 2) the 11-component module of marine pelagic ecosystem developed in the St. Petersburg Branch, Institute of Oceanology. The model is driven by atmospheric forcing, prescribed from the reanalysis NCEP / NCAR, and conditions on the open sea boundary, prescribed from the regional model of the atmosphere-ocean-sea ice-ocean biogeochemistry, developed at Max Planck Institute for Meteorology, Hamburg. Comparison of the model results for the period 1998-2007 with satellite data showed that the model reproduces the main features of the evolution of the sea surface temperature, seasonal changes in the ice extent, surface chlorophyll "a" concentration and PPP in the Barents Sea. Model estimates of the annual PPP for whole sea, APPmod, appeared in 1.5-2.3 times more than similar estimates, APPdata, from satellite data. The main reasons for this discrepancy are: 1) APPdata refers to the open water, while APPmod, to the whole sea area (under the pack ice and marginal ice zone (MIZ) was produced 16 - 38% of PPP); and 2) values of APPdata are underestimated because of the subsurface chlorophyll maximum. During the period 1998-2007, the modelled maximal (in the seasonal cycle) sea ice area has decreased by 15%. This reduction was accompanied by an increase in annual PPP of the sea at 54 and 63%, based, respectively, on satellite data and the model for the open water. According to model calculations for the whole sea area, the increase is only 19%. Using a simple 7-component model of oceanic carbon cycle incorporated into the above hydrodynamic model, the CO2 exchange between the atmosphere and sea has been estimated in different conditions. In the absence of biological

  2. Atmospheric winter response to Arctic sea ice changes in reanalysis data and model simulations

    Science.gov (United States)

    Jaiser, Ralf; Nakamura, Tetsu; Handorf, Dörthe; Romanowsky, Erik; Dethloff, Klaus; Ukita, Jinro; Yamazaki, Koji

    2017-04-01

    In recent years, Arctic regions showcased the most pronounced signals of a changing climate: Sea ice is reduced by more the ten percent per decade. At the same time, global warming trends have their maximum in Arctic latitudes often labled Arctic Amplification. There is strong evidence that amplified Arctic changes feed back into mid-latitudes in winter. We identified mechanisms that link recent Arctic changes through vertically propagating planetary waves to events of a weakened stratospheric polar vortex. Related anomalies propagate downward and lead to negative AO-like situations in the troposphere. European winter climate is sensitive to negative AO situations in terms of cold air outbreaks that are likely to occur more often in that case. These results based on ERA-Interim reanalysis data do not allow to dismiss other potential forcing factors leading to observed mid-latitude climate changes. Nevertheless, properly designed Atmospheric General Circulation Model (AGCM) experiments with AFES and ECHAM6 are able to reproduce observed atmospheric circulation changes if only observed sea ice changes in the Arctic are prescribed. This allows to deduce mechanisms that explain how Arctic Amplification can lead to a negative AO response via a stratospheric pathway. Further investigation of these mechanisms may feed into improved prediction systems.

  3. Fluctuating Arctic Sea ice thickness changes estimated by an in situ learned and empirically forced neural network model

    Science.gov (United States)

    Belchansky, G.I.; Douglas, D.C.; Platonov, N.G.

    2008-01-01

    Sea ice thickness (SIT) is a key parameter of scientific interest because understanding the natural spatiotemporal variability of ice thickness is critical for improving global climate models. In this paper, changes in Arctic SIT during 1982-2003 are examined using a neural network (NN) algorithm trained with in situ submarine ice draft and surface drilling data. For each month of the study period, the NN individually estimated SIT of each ice-covered pixel (25-km resolution) based on seven geophysical parameters (four shortwave and longwave radiative fluxes, surface air temperature, ice drift velocity, and ice divergence/convergence) that were cumulatively summed at each monthly position along the pixel's previous 3-yr drift track (or less if the ice was <3 yr old). Average January SIT increased during 1982-88 in most regions of the Arctic (+7.6 ?? 0.9 cm yr-1), decreased through 1996 Arctic-wide (-6.1 ?? 1.2 cm yr-1), then modestly increased through 2003 mostly in the central Arctic (+2.1 ?? 0.6 cm yr-1). Net ice volume change in the Arctic Ocean from 1982 to 2003 was negligible, indicating that cumulative ice growth had largely replaced the estimated 45 000 km3 of ice lost by cumulative export. Above 65??N, total annual ice volume and interannual volume changes were correlated with the Arctic Oscillation (AO) at decadal and annual time scales, respectively. Late-summer ice thickness and total volume varied proportionally until the mid-1990s, but volume did not increase commensurate with the thickening during 1996-2002. The authors speculate that decoupling of the ice thickness-volume relationship resulted from two opposing mechanisms with different latitudinal expressions: a recent quasi-decadal shift in atmospheric circulation patterns associated with the AO's neutral state facilitated ice thickening at high latitudes while anomalously warm thermal forcing thinned and melted the ice cap at its periphery. ?? 2008 American Meteorological Society.

  4. Simulating the mass balance and salinity of Arctic and Antarctic sea ice. 1. Model description and validation

    OpenAIRE

    Vancoppenolle, M.; Fichefet, T.; Goosse, H.; Bouillon, S; Madec, G.; Maqueda, M.A.M.

    2009-01-01

    This paper is the first part of a twofold contribution dedicated to the new version of the Louvain-la-Neuve sea ice model LIM3. In this part, LIM3 is described and its results arc, compared with observations. LIM3 is a C-grid dynamic-thermodynamic model, including the representation of the subgrid-scale distributions of ice thickness, enthalpy, salinity and age. Brine entrapment and drainage as well as brine impact on ice thermodynamics are explicitly included. LIM3 is embedded into the ocean...

  5. Arctic sea-ice cover and sea-ice cover anomalies over eastern Canadian waters

    Energy Technology Data Exchange (ETDEWEB)

    Agnew, T.

    1990-01-01

    Concerns about global climate warming have increased interest in climate monitoring and analysis of climate trends in Canada. Sea-ice cover is of interest for climate monitoring since it is very sensitive to changes in the climate controls over a region and is an integrator of temperature anomalies over periods of a week and longer. In addition, climate models suggest that polar regions will have the largest climate warming signal. The existence of long-term digital sea-ice databases makes analysis of sea ice as a climate change indicator possible. The northern hemisphere sea-ice concentration database for 1953 to 1988 was qualitatively evaluated for its representativeness over eastern Canadian Arctic waters. Despite inhomogeneity problems, the database identifies the average freezeup and breakup patterns in the Canadian Arctic islands, Baffin Bay/Davis Strait, and the Hudson Bay area, and can be used for sea-ice variability and anomaly studies. However, inhomogeneity problems put into question the use of the database for sea-ice trend analysis. Sea-ice anomalies for the 1982/83 El Nino winter are compared to atmospheric temperature and circulation anomalies over the Baffin Bay/Davis Strait area. Sea-ice anomaly charts for 1953-1988 are calculated and have been made available as an unpublished catalogue within the Canadian Climate Centre. 15 refs., 27 figs.

  6. Increased CO2 uptake due to sea ice growth and decay in the Nordic Seas

    DEFF Research Database (Denmark)

    Rysgaard, Søren; Bendtsen, Jørgen; Petersen, L.T.

    2009-01-01

    uptake in the Nordic Seas is currently unknown. We present evidence from 50 localities in the Arctic Ocean that dissolved inorganic carbon is rejected together with brine from growing sea ice and that sea ice melting during summer is rich in carbonates. Model calculations show that melting of sea ice......The uptake rates of atmospheric CO2 in the Nordic Seas are among the highest in the world's oceans. This has been ascribed mainly to a strong biological drawdown, but chemical processes within the sea ice itself have also been suggested to play a role. The importance of sea ice for the carbon...

  7. Dynamic preconditioning of the September sea-ice extent minimum

    Science.gov (United States)

    Williams, James; Tremblay, Bruno; Newton, Robert; Allard, Richard

    2016-04-01

    There has been an increased interest in seasonal forecasting of the sea-ice extent in recent years, in particular the minimum sea-ice extent. We propose a dynamical mechanism, based on winter preconditioning through first year ice formation, that explains a significant fraction of the variance in the anomaly of the September sea-ice extent from the long-term linear trend. To this end, we use a Lagrangian trajectory model to backtrack the September sea-ice edge to any time during the previous winter and quantify the amount of sea-ice divergence along the Eurasian and Alaskan coastlines as well as the Fram Strait sea-ice export. We find that coastal divergence that occurs later in the winter (March, April and May) is highly correlated with the following September sea-ice extent minimum (r = -0.73). This is because the newly formed first year ice will melt earlier allowing for other feedbacks (e.g. ice albedo feedback) to start amplifying the signal early in the melt season when the solar input is large. We find that the winter mean Fram Strait sea-ice export anomaly is also correlated with the minimum sea-ice extent the following summer. Next we backtrack a synthetic ice edge initialized at the beginning of the melt season (June 1st) in order to develop hindcast models of the September sea-ice extent that do not rely on a-priori knowledge of the minimum sea-ice extent. We find that using a multi-variate regression model of the September sea-ice extent anomaly based on coastal divergence and Fram Strait ice export as predictors reduces the error by 41%. A hindcast model based on the mean DJFMA Arctic Oscillation index alone reduces the error by 24%.

  8. USGS Sea Ice Email Script

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Daily sea ice imagery and charting benefits logistics and navigational planning in the Alaskan Arctic waters, yet access to these data often requires high bandwidth...

  9. The research of Polar sea ice and its role in climate change

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    As an important part of global climate system, the Polar sea ice is effecting on global climate changes through ocean surface radiation balance, mass balance, energy balance as well as the circulating of sea water temperature and salinity. Sea ice research has a centuries-old history. The many correlative sea ice projects were established through the extensive international cooperation during the period from the primary research of intensity and the bearing capacity of sea ice to the development of sea/ice/air coupled model. Based on these researches, the sea ice variety was combined with the global climate change. All research about sea ice includes: the physical properties and processes of sea ice and its snow cover, the ecosystem of sea ice regions, sea ice and upper snow albedo, mass balance of sea ice regions, sea ice and climate coupled model. The simulation suggests that the both of the area and volume of polar sea ice would be reduced in next century. With the developing of the sea ice research, more scientific issues are mentioned. Such as the interaction between sea ice and the other factors of global climate system, the seasonal and regional distribution of polar sea ice thickness, polar sea ice boundary and area variety trends, the growth and melt as well as their influencing factors, the role of the polynya and the sea/air interactions. We should give the best solutions to all of the issues in future sea ice studying.

  10. The effects of additional black carbon on Arctic sea ice surface albedo: variation with sea ice type and snow cover

    Directory of Open Access Journals (Sweden)

    A. A. Marks

    2013-03-01

    Full Text Available Black carbon in sea ice will decrease sea ice surface albedo through increased absorption of incident solar radiation, exacerbating sea ice melting. Previous literature has reported different albedo responses to additions of black carbon in sea ice and has not considered how a snow cover may mitigate the effect of black carbon in sea ice. Sea ice is predominately snow covered. Visible light absorption and light scattering coefficients are calculated for a typical first year and multi-year sea ice and "dry" and "wet" snow types that suggest black carbon is the dominating absorbing impurity. The albedo response of first year and multi-year sea ice to increasing black carbon, from 1–1024 ng g−1, in a top 5 cm layer of a 155 cm thick sea ice was calculated using the radiative transfer model: TUV-snow. Sea ice albedo is surprisingly unresponsive to black carbon additions up to 100 ng g−1 with a decrease in albedo to 98.7% of the original albedo value due to an addition of 8 ng g−1 of black carbon in first year sea ice compared to an albedo decrease to 99.6% for the same black carbon mass ratio increase in multi-year sea ice. The first year sea ice proved more responsive to black carbon additions than the multi-year ice. Comparison with previous modelling of black carbon in sea ice suggests a more scattering sea ice environment will be less responsive to black carbon additions. Snow layers on sea ice may mitigate the effects of black carbon in sea ice. "Wet" and "dry" snow layers of 0.5, 1, 2, 5 and 10 cm were added onto the sea ice surface and the snow surface albedo calculated with the same increase in black carbon in the underlying sea ice. Just a 0.5 cm layer of snow greatly diminishes the effect of black carbon on surface albedo, and a 2–5 cm layer (less than half the e-folding depth of snow is enough to "mask" any change in surface albedo owing to additional black carbon in sea ice, but not thick enough to ignore the underlying sea ice.

  11. Thermal Diffusivity Identification of Distributed Parameter Systems to Sea Ice

    Directory of Open Access Journals (Sweden)

    Liqiong Shi

    2013-01-01

    Full Text Available A method of optimal control is presented as a numerical tool for solving the sea ice heat transfer problem governed by a parabolic partial differential equation. Taken the deviation between the calculated ice temperature and the measurements as the performance criterion, an optimal control model of distributed parameter systems with specific constraints of thermal properties of sea ice was proposed to determine the thermal diffusivity of sea ice. Based on sea ice physical processes, the parameterization of the thermal diffusivity was derived through field data. The simulation results illustrated that the identified parameterization of the thermal diffusivity is reasonably effective in sea ice thermodynamics. The direct relation between the thermal diffusivity of sea ice and ice porosity is physically significant and can considerably reduce the computational errors. The successful application of this method also explained that the optimal control model of distributed parameter systems in conjunction with the engineering background has great potential in dealing with practical problems.

  12. Intercomparison of the Arctic sea ice cover in global ocean-sea ice reanalyses from the ORA-IP project

    Science.gov (United States)

    Chevallier, Matthieu; Smith, Gregory C.; Dupont, Frédéric; Lemieux, Jean-François; Forget, Gael; Fujii, Yosuke; Hernandez, Fabrice; Msadek, Rym; Peterson, K. Andrew; Storto, Andrea; Toyoda, Takahiro; Valdivieso, Maria; Vernieres, Guillaume; Zuo, Hao; Balmaseda, Magdalena; Chang, You-Soon; Ferry, Nicolas; Garric, Gilles; Haines, Keith; Keeley, Sarah; Kovach, Robin M.; Kuragano, Tsurane; Masina, Simona; Tang, Yongming; Tsujino, Hiroyuki; Wang, Xiaochun

    2017-08-01

    Ocean-sea ice reanalyses are crucial for assessing the variability and recent trends in the Arctic sea ice cover. This is especially true for sea ice volume, as long-term and large scale sea ice thickness observations are inexistent. Results from the Ocean ReAnalyses Intercomparison Project (ORA-IP) are presented, with a focus on Arctic sea ice fields reconstructed by state-of-the-art global ocean reanalyses. Differences between the various reanalyses are explored in terms of the effects of data assimilation, model physics and atmospheric forcing on properties of the sea ice cover, including concentration, thickness, velocity and snow. Amongst the 14 reanalyses studied here, 9 assimilate sea ice concentration, and none assimilate sea ice thickness data. The comparison reveals an overall agreement in the reconstructed concentration fields, mainly because of the constraints in surface temperature imposed by direct assimilation of ocean observations, prescribed or assimilated atmospheric forcing and assimilation of sea ice concentration. However, some spread still exists amongst the reanalyses, due to a variety of factors. In particular, a large spread in sea ice thickness is found within the ensemble of reanalyses, partially caused by the biases inherited from their sea ice model components. Biases are also affected by the assimilation of sea ice concentration and the treatment of sea ice thickness in the data assimilation process. An important outcome of this study is that the spatial distribution of ice volume varies widely between products, with no reanalysis standing out as clearly superior as compared to altimetry estimates. The ice thickness from systems without assimilation of sea ice concentration is not worse than that from systems constrained with sea ice observations. An evaluation of the sea ice velocity fields reveals that ice drifts too fast in most systems. As an ensemble, the ORA-IP reanalyses capture trends in Arctic sea ice area and extent

  13. How reversible is sea ice loss?

    Directory of Open Access Journals (Sweden)

    J. K. Ridley

    2012-02-01

    Full Text Available It is well accepted that increasing atmospheric CO2 results in global warming, leading to a decline in polar sea ice area. Here, the specific question of whether there is a tipping point in the sea ice cover is investigated. The global climate model HadCM3 is used to map the trajectory of sea ice area under idealised scenarios. The atmospheric CO2 is first ramped up to four times pre-industrial levels (4 × CO2, then ramped down to pre-industrial levels. We also examine the impact of stabilising climate at 4 × CO2 prior to ramping CO2 down to pre-industrial levels. Against global mean temperature, Arctic sea ice area is reversible, while the Antarctic sea ice shows some asymmetric behaviour – its rate of change slower, with falling temperatures, than its rate of change with rising temperatures. However, we show that the asymmetric behaviour is driven by hemispherical differences in temperature change between transient and stabilisation periods. We find no irreversible behaviour in the sea ice cover.

  14. How reversible is sea ice loss?

    Directory of Open Access Journals (Sweden)

    J. K. Ridley

    2011-09-01

    Full Text Available It is well accepted that increasing atmospheric CO2 results in global warming, leading to a decline in polar sea ice area. Here, the specific question of whether there is a tipping point in the sea ice cover is investigated. The global climate model HadCM3, is used to map the trajectory of sea ice area under idealised scenarios. The atmospheric CO2 is first ramped up to four times pre-industrial levels (4 × CO2 then ramped down back to pre-industrial levels. We also examine the impact of stabilising climate at 4 × CO2 prior to ramping CO2 down to pre-industrial levels. Against global mean temperature Arctic sea ice area has little hysteresis while the Antarctic sea ice shows significant hysteresis – its rate of change slower, with falling temperatures, than its rate of change with rising temperatures. However, we show that the driver of the hysteresis is the hemispherical differences in temperature change between transient and stabilisation periods. We find no irreversible behaviour in the sea ice cover.

  15. Albedo parametrization and reversibility of sea ice decay

    OpenAIRE

    M. Müller-Stoffels; R. Wackerbauer

    2012-01-01

    The Arctic's sea ice cover has been receding rapidly in recent years, and global climate models typically predict a further decline over the next century. It is an open question whether a possible loss of Arctic sea ice is reversible. We study the stability of Arctic model sea ice in a conceptual, two-dimensional energy-based regular network model of the ice-ocean layer that considers ARM's longwave radiative budget data and SHEBA albedo measurements. Seasonal ice cover, perennial ice and per...

  16. Influence of stochastic sea ice parametrization on climate and the role of atmosphere-sea ice-ocean interaction.

    Science.gov (United States)

    Juricke, Stephan; Jung, Thomas

    2014-06-28

    The influence of a stochastic sea ice strength parametrization on the mean climate is investigated in a coupled atmosphere-sea ice-ocean model. The results are compared with an uncoupled simulation with a prescribed atmosphere. It is found that the stochastic sea ice parametrization causes an effective weakening of the sea ice. In the uncoupled model this leads to an Arctic sea ice volume increase of about 10-20% after an accumulation period of approximately 20-30 years. In the coupled model, no such increase is found. Rather, the stochastic perturbations lead to a spatial redistribution of the Arctic sea ice thickness field. A mechanism involving a slightly negative atmospheric feedback is proposed that can explain the different responses in the coupled and uncoupled system. Changes in integrated Antarctic sea ice quantities caused by the stochastic parametrization are generally small, as memory is lost during the melting season because of an almost complete loss of sea ice. However, stochastic sea ice perturbations affect regional sea ice characteristics in the Southern Hemisphere, both in the uncoupled and coupled model. Remote impacts of the stochastic sea ice parametrization on the mean climate of non-polar regions were found to be small.

  17. The sensitivity of Arctic sea ice production to shelf flooding during the early Holocene: a modelling study

    Science.gov (United States)

    Blaschek, M.; Renssen, H.

    2012-04-01

    During the last deglaciation, the global sea-level started rising, changing the coastlines from an early Holocene stand (40 m lower than today at approximately 10 kyr BP, Siddall et al., 2003) to modern day coastlines. Proxy evidence shows that this transgression occurred non-uniformly over the globe. For instance, Bauch et al. (2001) report for the Laptev Sea (Arctic Ocean), that the modern coastline was only established at 5 kyr BP after a fast transgression from the early Holocene, leading to a flooding of the extensive shelf area. This shelf area is presently regarded to be an important production zone of Arctic sea ice, playing an important role in the dynamics of sea ice in the Arctic, as well as its export to the Nordic Seas along the East Greenland Current (EGC). Through this sea ice export, changes in the Laptev Sea shelf area during the Holocene could potentially have had a substantial impact on the sea surface conditions of the EGC, and the Denmark Strait, which is known to be sensitive to sea ice. This is consistent with a rapid increase in sea ice export through the EGC around 5 kyr BP as reported by Jennings et al. (2002). In this study we investigate the impact of this Arctic shelf flooding on sea ice production in the Holocene, and on the climate of the Nordic Seas in the LOVECLIM1.2 global ocean-atmosphere-vegetation model. We present results of several experiments in which we study the sensitivity of Arctic sea ice production to various Arctic shelf areas under early Holocene conditions (9 kyr BP). We approach this by changing the land-sea mask to represent different lower-than-present sea-level coastlines. For example, we perform experiments with the Last Glacial Maximum (LGM) land-sea mask, representing a lowering of the sea-level by 120 m, while keeping other forcings at 9 kyr BP. A further step is to modify selected areas in the Arctic, such as the Laptev Sea area, to examine the importance of different areas. Our results help to explain long

  18. Quantifying Seasonal Skill In Coupled Sea Ice Models Using Freeboard Measurements From Spaceborne Laser Altimeters

    Science.gov (United States)

    2016-06-01

    10  Figure 9.  Linear Trend (%/year) of solar heat flux into the Arctic Ocean. Source: Perovich (2007). The color scale...Anisotropic ice flow in the Beaufort Sea, April 29, 2011. Source: Global Fiducials Library (2015) Angles between leads that are formed across ice floes... Panels a-d correspond to Figure 44 c-f. Bias( fbmodel ) that is statistically significant at the 95% confidence interval is represented in red

  19. Mechanical sea-ice strength parameterized as a function of ice temperature

    Science.gov (United States)

    Hata, Yukie; Tremblay, Bruno

    2016-04-01

    Mechanical sea-ice strength is key for a better simulation of the timing of landlock ice onset and break-up in the Canadian Arctic Archipelago (CAA). We estimate the mechanical strength of sea ice in the CAA by analyzing the position record measured by the several buoys deployed in the CAA between 2008 and 2013, and wind data from the Canadian Meteorological Centre's Global Deterministic Prediction System (CMC_GDPS) REforecasts (CGRF). First, we calculate the total force acting on the ice using the wind data. Next, we estimate upper (lower) bounds on the sea-ice strength by identifying cases when the sea ice deforms (does not deform) under the action of a given total force. Results from this analysis show that the ice strength of landlock sea ice in the CAA is approximately 40 kN/m on the landfast ice onset (in ice growth season). Additionally, it becomes approximately 10 kN/m on the landfast ice break-up (in melting season). The ice strength decreases with ice temperature increase, which is in accord with results from Johnston [2006]. We also include this new parametrization of sea-ice strength as a function of ice temperature in a coupled slab ocean sea ice model. The results from the model with and without the new parametrization are compared with the buoy data from the International Arctic Buoy Program (IABP).

  20. Arctic Sea Ice : Trends, Stability and Variability

    Science.gov (United States)

    Moon, W.; Wettlaufer, J. S.

    2014-12-01

    A stochastic Arctic sea-ice model is derived and analysed in detail to interpret the recent decay and associated variability of Arctic sea-ice under changes in radiative forcing. The approach begins from a deterministic model of the heat flux balance through the air/sea/ice system, which uses observed monthly-averaged heat fluxesto drive a time evolution of sea-ice thickness. This model reproduces the observed seasonal cycle of the ice cover and it is to this that stochastic noise--representing high frequency variability--is introduced.The model takes the form of a single periodic non-autonomous stochastic ordinary differential equation. The value of such a model is that it provides a relatively simple framework to examine the role of noise in the basic nonlinear interactions at play as transitions in the state of the ice cover (e.g., from perennial to seasonal) are approached. Moreover, the stability and the noise conspire to underlie the inter annual variability and how that variability changes as one approaches the deterministic bifurcations in the system.

  1. Simulating Baltic Sea climate for the period 1902-1998 with the Rossby Centre coupled ice-ocean model

    Energy Technology Data Exchange (ETDEWEB)

    Meier, H.E. Markus [Swedish Meteorological and Hydrological Inst., Rossby Centre, Norrkoeping (Sweden); Kauker, Frank [Alfred Wegener Inst. for Polar and Marine Research, Bremerhaven (Germany)

    2002-12-01

    Hindcast simulations for the period 1902-1998 have been performed using a 3D coupled ice-ocean model for the Baltic Sea. Daily sea level observations in Kattegat, monthly basin-wide discharge data, and reconstructed atmospheric surface data have been used to force the Baltic Sea model. The reconstruction utilizes a statistical model to calculate daily sea level pressure and monthly surface air temperature, dew point temperature, precipitation, and cloud cover fields on a 1 deg x 1 deg regular horizontal grid for the Baltic Sea region. An improved turbulence scheme has been implemented into the Baltic Sea model to simulate saltwater inflows realistically. The results are validated against available observational datasets for sea level, salinity, saltwater inflow, volume transport, and sea ice. In addition, a comparison is performed with simulations for the period 1980-1993 using 3-hourly gridded atmospheric observations from synoptic stations. It is shown that the results of the Baltic Sea model forced with the reconstructed data are satisfactory. Sensitivity experiments have been performed to explore the impact of internal mixing, fresh and saltwater inflows, sea ice, and the sea level in Kattegat on the salinity of the Baltic Sea. It is found that the decadal variability of mean salinity is explained partly by decadal volume variations of the accumulated freshwater inflow from river runoff and net precipitation and partly by decadal variations of the large-scale sea level pressure over Scandinavia. During the last century two exceptionally long stagnation periods are found, the 1920s to the 1930s and the 1980s to the mid 1990s. During these periods precipitation, runoff and westerly winds were stronger than normal. Stronger westerly winds caused increased eastward surface-layer transports. Consequently, the mean eastward lower layer transports through the Stolpe Channel is reduced. The response time scale of the Baltic Sea is of the order of 30-40 years. The large

  2. Sea Ice Back to 1850: A Longer Observational Record for Assimilation By Models and Use In Reanalyses

    Science.gov (United States)

    Fetterer, Florence; Walsh, John; Chapman, William; Stewart, J. Scott

    2016-04-01

    Gridded Monthly Sea Ice Extent and Concentration, 1850 Onward is the title of a new data set available from the U.S. National Snow and Ice Data Center. Observations from 13 historical sources such as whaling ship logs, compilations by naval oceanographers, and analyses by national ice services cover 1850 through 1978, while 1979-2013 ice concentration fields are derived from satellite passive microwave data. The sea ice concentration and source variables are provided in a NetCDF-4 file. The observation-based data product meets a need for longer records to use in reanalysis and climate diagnostic applications. It extends the record of an earlier version of this pan-Arctic data set that is heavily used by modelers, and improves upon it by incorporating newly available historical sources, using a more accurate data set for the satellite era, and by filling temporal gaps using an analog method. The resulting sea ice concentration fields have realistic values and variability throughout the record; in earlier versions, unvarying climatological values often fill gaps. The historical data vary greatly in their observational methods and came to us as both original data (e.g. a transcription of shipboard ice observations), or as observations to which some synthesis or analysis has already been applied (e.g. the Danish Meteorological Instituted yearbooks of charts). Each required different treatment before it could be used in our product, ranging from simple regridding to digitization and interpretation. The current version spans 1850-2013. With it, we can more confidently address questions like "Is the diminished ice cover of the past few years unique to the period since 1850?" And "Is the rapidity of the retreat of ice in the years since 2000 unique in the longer historical record?" We hope to continue improving the product with refinements to the gap filling method, additional historical sources, and assessment of the consistency of pre and post satellite period data, and

  3. Modelling the Antarctic Ice Sheet

    DEFF Research Database (Denmark)

    Pedersen, Jens Olaf Pepke; Holm, A.

    2015-01-01

    The Antarctic ice sheet is a major player in the Earth’s climate system and is by far the largest depository of fresh water on the planet. Ice stored in the Antarctic ice sheet (AIS) contains enough water to raise sea level by about 58 m, and ice loss from Antarctica contributed significantly...... Science) Antarctic Ice Sheet (DAIS) model (Shaffer 2014) is forced by reconstructed time series of Antarctic temperature, global sea level and ocean subsurface temperature over the last two glacial cycles. In this talk a modelling work of the Antarctic ice sheet over most of the Cenozoic era using...

  4. Gas transport processes in sea ice: How convection and diffusion processes might affect biological imprints, a challenge for modellers

    DEFF Research Database (Denmark)

    Tison, J.-L.; Zhou, Shaola J. G.; Thomas, D. N.

    2012-01-01

    . The INTERICE IV and Barrow experiment show that the initial equilibrium dissolved gas entrapment within the skeletal layer basically governs most of the profiles higher up in the sea ice cover during the active sea ice growth. However, as the ice layers age and cool down under the temperature gradient, bubble......Recent data from a year-round survey of landfast sea ice growth in Barrow (Alaska) have shown how O2/N2 and O2/Ar ratios could be used to pinpoint primary production in sea ice and derive net productivity rates from the temporal evolution of the oxygen concentration at a given depth within the sea...... nucleation occurs while the concentration in the ice goes well above the theoretical one, calculated from brine equilibrium under temperature and salinity changes and observed brine volumes. This phase change locks the gases within the sea ice structure, preventing "degassing" of the ice, as is observed...

  5. Regionally coupled atmosphere-ocean-sea ice-marine biogeochemistry model ROM: 1. Description and validation

    Science.gov (United States)

    Sein, Dmitry V.; Mikolajewicz, Uwe; Gröger, Matthias; Fast, Irina; Cabos, William; Pinto, Joaquim G.; Hagemann, Stefan; Semmler, Tido; Izquierdo, Alfredo; Jacob, Daniela

    2015-03-01

    The general circulation models used to simulate global climate typically feature resolution too coarse to reproduce many smaller-scale processes, which are crucial to determining the regional responses to climate change. A novel approach to downscale climate change scenarios is presented which includes the interactions between the North Atlantic Ocean and the European shelves as well as their impact on the North Atlantic and European climate. The goal of this paper is to introduce the global ocean-regional atmosphere coupling concept and to show the potential benefits of this model system to simulate present-day climate. A global ocean-sea ice-marine biogeochemistry model (MPIOM/HAMOCC) with regionally high horizontal resolution is coupled to an atmospheric regional model (REMO) and global terrestrial hydrology model (HD) via the OASIS coupler. Moreover, results obtained with ROM using NCEP/NCAR reanalysis and ECHAM5/MPIOM CMIP3 historical simulations as boundary conditions are presented and discussed for the North Atlantic and North European region. The validation of all the model components, i.e., ocean, atmosphere, terrestrial hydrology, and ocean biogeochemistry is performed and discussed. The careful and detailed validation of ROM provides evidence that the proposed model system improves the simulation of many aspects of the regional climate, remarkably the ocean, even though some biases persist in other model components, thus leaving potential for future improvement. We conclude that ROM is a powerful tool to estimate possible impacts of climate change on the regional scale.

  6. Evaluation of the Simulation of Arctic and Antarctic Sea Ice Coverages by Eleven Major Global Climate Models

    Science.gov (United States)

    Parksinson, Claire; Vinnikov, Konstantin Y.; Cavalieri, Donald J.

    2005-01-01

    Comparison of polar sea ice results from 11 major global climate models and satellite-derived observations for 1979-2004 reveals that each of the models is simulating seasonal cycles that are phased at least approximately correctly in both hemispheres. Each is also simulating various key aspects of the observed ice cover distributions, such as winter ice not only throughout the central Arctic basin but also throughout Hudson Bay, despite its relatively low latitudes. However, some of the models simulate too much ice, others too little ice (in some cases varying depending on hemisphere and/or season), and some match the observations better in one season versus another. Several models do noticeably better in the Northern Hemisphere than in the Southern Hemisphere, and one does noticeably better in the Southern Hemisphere. In the Northern Hemisphere all simulate monthly average ice extents to within +/-5.1 x 10(exp 6)sq km of the observed ice extent throughout the year; and in the Southern Hemisphere all except one simulate the monthly averages to within +/-6.3 x 10(exp 6) sq km of the observed values. All the models properly simulate a lack of winter ice to the west of Norway; however, most do not obtain as much absence of ice immediately north of Norway as the observations show, suggesting an under simulation of the North Atlantic Current. The spread in monthly averaged ice extents amongst the 11 model simulations is greater in the Southern Hemisphere than in the Northern Hemisphere and greatest in the Southern Hemisphere winter and spring.

  7. Sea Ice Concentration and Extent

    Science.gov (United States)

    Comiso, Josefino C.

    2014-01-01

    Among the most seasonal and most dynamic parameters on the surface of the Earth is sea ice which at any one time covers about 3-6% of the planet. In the Northern Hemisphere, sea ice grows in extent from about 6 x 10(exp 6) sq km to 16 x 10(exp 6) sq km, while in the Southern Hemisphere, it grows from about 3 x 10(exp 6) sq km to about 19 x 10(exp 6) sq km (Comiso, 2010; Gloersen et al., 1992). Sea ice is up to about 2-3 m thick in the Northern Hemisphere and about 1 m thick in the Southern Hemisphere (Wadhams, 2002), and compared to the average ocean depth of about 3 km, it is a relatively thin, fragile sheet that can break due to waves and winds or melt due to upwelling of warm water. Being constantly advected by winds, waves, and currents, sea ice is very dynamic and usually follows the directions of the many gyres in the polar regions. Despite its vast expanse, the sea ice cover was previously left largely unstudied and it was only in recent years that we have understood its true impact and significance as related to the Earths climate, the oceans, and marine life.

  8. Sea Ice Concentration and Extent

    Science.gov (United States)

    Comiso, Josefino C.

    2014-01-01

    Among the most seasonal and most dynamic parameters on the surface of the Earth is sea ice which at any one time covers about 3-6% of the planet. In the Northern Hemisphere, sea ice grows in extent from about 6 x 10(exp 6) sq km to 16 x 10(exp 6) sq km, while in the Southern Hemisphere, it grows from about 3 x 10(exp 6) sq km to about 19 x 10(exp 6) sq km (Comiso, 2010; Gloersen et al., 1992). Sea ice is up to about 2-3 m thick in the Northern Hemisphere and about 1 m thick in the Southern Hemisphere (Wadhams, 2002), and compared to the average ocean depth of about 3 km, it is a relatively thin, fragile sheet that can break due to waves and winds or melt due to upwelling of warm water. Being constantly advected by winds, waves, and currents, sea ice is very dynamic and usually follows the directions of the many gyres in the polar regions. Despite its vast expanse, the sea ice cover was previously left largely unstudied and it was only in recent years that we have understood its true impact and significance as related to the Earths climate, the oceans, and marine life.

  9. Interannual Variability of the Sea-Ice-Induced Salt Flux in the Greenland Sea

    DEFF Research Database (Denmark)

    Pedersen, Leif Toudal; Coon, M.D.

    2001-01-01

    ; Visbeck and others, 1995). The predominant ice types in the Greenland Sea arc frazil/grease ice and pancake ice. A numerical model has been developed relating ice formation and decay of these ice types as observed by the SMMR and SSM/I microwave radiometers and evaluating their contribution to salt...

  10. Interannual Variability of the Sea-Ice-Induced Salt Flux in the Greenland Sea

    DEFF Research Database (Denmark)

    Pedersen, Leif Toudal; Coon, M.D.

    2001-01-01

    ; Visbeck and others, 1995). The predominant ice types in the Greenland Sea arc frazil/grease ice and pancake ice. A numerical model has been developed relating ice formation and decay of these ice types as observed by the SMMR and SSM/I microwave radiometers and evaluating their contribution to salt...

  11. Global coupled sea ice-ocean state estimation

    Science.gov (United States)

    Fenty, Ian; Menemenlis, Dimitris; Zhang, Hong

    2015-09-01

    We study the impact of synthesizing ocean and sea ice concentration data with a global, eddying coupled sea ice-ocean configuration of the Massachusetts Institute of Technology general circulation model with the goal of reproducing the 2004 three-dimensional time-evolving ice-ocean state. This work builds on the state estimation framework developed in the Estimating the Circulation and Climate of the Ocean consortium by seeking a reconstruction of the global sea ice-ocean system that is simultaneously consistent with (1) a suite of in situ and remotely-sensed ocean and ice data and (2) the physics encoded in the numerical model. This dual consistency is successfully achieved here by adjusting only the model's initial hydrographic state and its atmospheric boundary conditions such that misfits between the model and data are minimized in a least-squares sense. We show that synthesizing both ocean and sea ice concentration data is required for the model to adequately reproduce the observed details of the sea ice annual cycle in both hemispheres. Surprisingly, only modest adjustments to our first-guess atmospheric state and ocean initial conditions are necessary to achieve model-data consistency, suggesting that atmospheric reanalysis products remain a leading source of errors for sea ice-ocean model hindcasts and reanalyses. The synthesis of sea ice data is found to ameliorate misfits in the high latitude ocean, especially with respect to upper ocean stratification, temperature, and salinity. Constraining the model to sea ice concentration modestly reduces ICESat-derived Arctic ice thickness errors by improving the temporal and spatial evolution of seasonal ice. Further increases in the accuracy of global sea ice thickness in the model likely require the direct synthesis of sea ice thickness data.

  12. Canadian Arctic sea ice reconstructed from bromine in the Greenland NEEM ice core

    Science.gov (United States)

    Spolaor, Andrea; Vallelonga, Paul; Turetta, Clara; Maffezzoli, Niccolò; Cozzi, Giulio; Gabrieli, Jacopo; Barbante, Carlo; Goto-Azuma, Kumiko; Saiz-Lopez, Alfonso; Cuevas, Carlos A.; Dahl-Jensen, Dorthe

    2016-09-01

    Reconstructing the past variability of Arctic sea ice provides an essential context for recent multi-year sea ice decline, although few quantitative reconstructions cover the Holocene period prior to the earliest historical records 1,200 years ago. Photochemical recycling of bromine is observed over first-year, or seasonal, sea ice in so-called “bromine explosions” and we employ a 1-D chemistry transport model to quantify processes of bromine enrichment over first-year sea ice and depositional transport over multi-year sea ice and land ice. We report bromine enrichment in the Northwest Greenland Eemian NEEM ice core since the end of the Eemian interglacial 120,000 years ago, finding the maximum extension of first-year sea ice occurred approximately 9,000 years ago during the Holocene climate optimum, when Greenland temperatures were 2 to 3 °C above present values. First-year sea ice extent was lowest during the glacial stadials suggesting complete coverage of the Arctic Ocean by multi-year sea ice. These findings demonstrate a clear relationship between temperature and first-year sea ice extent in the Arctic and suggest multi-year sea ice will continue to decline as polar amplification drives Arctic temperatures beyond the 2 °C global average warming target of the recent COP21 Paris climate agreement.

  13. Canadian Arctic sea ice reconstructed from bromine in the Greenland NEEM ice core.

    Science.gov (United States)

    Spolaor, Andrea; Vallelonga, Paul; Turetta, Clara; Maffezzoli, Niccolò; Cozzi, Giulio; Gabrieli, Jacopo; Barbante, Carlo; Goto-Azuma, Kumiko; Saiz-Lopez, Alfonso; Cuevas, Carlos A; Dahl-Jensen, Dorthe

    2016-09-21

    Reconstructing the past variability of Arctic sea ice provides an essential context for recent multi-year sea ice decline, although few quantitative reconstructions cover the Holocene period prior to the earliest historical records 1,200 years ago. Photochemical recycling of bromine is observed over first-year, or seasonal, sea ice in so-called "bromine explosions" and we employ a 1-D chemistry transport model to quantify processes of bromine enrichment over first-year sea ice and depositional transport over multi-year sea ice and land ice. We report bromine enrichment in the Northwest Greenland Eemian NEEM ice core since the end of the Eemian interglacial 120,000 years ago, finding the maximum extension of first-year sea ice occurred approximately 9,000 years ago during the Holocene climate optimum, when Greenland temperatures were 2 to 3 °C above present values. First-year sea ice extent was lowest during the glacial stadials suggesting complete coverage of the Arctic Ocean by multi-year sea ice. These findings demonstrate a clear relationship between temperature and first-year sea ice extent in the Arctic and suggest multi-year sea ice will continue to decline as polar amplification drives Arctic temperatures beyond the 2 °C global average warming target of the recent COP21 Paris climate agreement.

  14. Canadian Arctic sea ice reconstructed from bromine in the Greenland NEEM ice core

    Science.gov (United States)

    Spolaor, Andrea; Vallelonga, Paul; Turetta, Clara; Maffezzoli, Niccolò; Cozzi, Giulio; Gabrieli, Jacopo; Barbante, Carlo; Goto-Azuma, Kumiko; Saiz-Lopez, Alfonso; Cuevas, Carlos A.; Dahl-Jensen, Dorthe

    2016-01-01

    Reconstructing the past variability of Arctic sea ice provides an essential context for recent multi-year sea ice decline, although few quantitative reconstructions cover the Holocene period prior to the earliest historical records 1,200 years ago. Photochemical recycling of bromine is observed over first-year, or seasonal, sea ice in so-called “bromine explosions” and we employ a 1-D chemistry transport model to quantify processes of bromine enrichment over first-year sea ice and depositional transport over multi-year sea ice and land ice. We report bromine enrichment in the Northwest Greenland Eemian NEEM ice core since the end of the Eemian interglacial 120,000 years ago, finding the maximum extension of first-year sea ice occurred approximately 9,000 years ago during the Holocene climate optimum, when Greenland temperatures were 2 to 3 °C above present values. First-year sea ice extent was lowest during the glacial stadials suggesting complete coverage of the Arctic Ocean by multi-year sea ice. These findings demonstrate a clear relationship between temperature and first-year sea ice extent in the Arctic and suggest multi-year sea ice will continue to decline as polar amplification drives Arctic temperatures beyond the 2 °C global average warming target of the recent COP21 Paris climate agreement. PMID:27650478

  15. The impact of under-ice melt ponds on Arctic sea ice volume

    Science.gov (United States)

    Smith, Naomi; Flocco, Daniela; Feltham, Daniel

    2016-04-01

    A one-dimensional, thermodynamic model of Arctic sea ice [Flocco et al, 2015] has been adapted to study the evolution of under-ice melt ponds, pools of fresh water that are found below the Arctic sea ice, and false bottoms, sheets of ice that form at the boundary between the under-ice melt pond and the oceanic mixed layer. Over time, either the under-ice melt pond freezes or the false bottom is completely ablated. We have been investigating the impact that these features have on the growth or ablation of sea ice during the time that they are present. The sensitivity of our model to a range of parameters has been tested, revealing some interesting effects of the thermodynamic processes taking place during the life-cycle of these phenomena. For example, the under-ice melt pond and its associated false bottom can insulate the sea ice layer from ocean, increasing the thickness of sea ice present at the end of the time frame considered. A comparison of the results of the model of under-ice melt pond evolution with that of sea ice with a bare base has been used to estimate the impact of under-ice melt ponds on sea ice volume towards the end of the melt season. We find that the under-ice melt ponds could have a significant impact on the mass balance of the sea ice, suggesting that it could be desirable to include a parameterisation of the effects of under-ice melt pond in the sea ice components of climate models.

  16. Storm-induced sea-ice breakup and the implications for ice extent

    Science.gov (United States)

    Kohout, A. L.; Williams, M. J. M.; Dean, S. M.; Meylan, M. H.

    2014-05-01

    The propagation of large, storm-generated waves through sea ice has so far not been measured, limiting our understanding of how ocean waves break sea ice. Without improved knowledge of ice breakup, we are unable to understand recent changes, or predict future changes, in Arctic and Antarctic sea ice. Here we show that storm-generated ocean waves propagating through Antarctic sea ice are able to transport enough energy to break sea ice hundreds of kilometres from the ice edge. Our results, which are based on concurrent observations at multiple locations, establish that large waves break sea ice much farther from the ice edge than would be predicted by the commonly assumed exponential decay. We observed the wave height decay to be almost linear for large waves--those with a significant wave height greater than three metres--and to be exponential only for small waves. This implies a more prominent role for large ocean waves in sea-ice breakup and retreat than previously thought. We examine the wider relevance of this by comparing observed Antarctic sea-ice edge positions with changes in modelled significant wave heights for the Southern Ocean between 1997 and 2009, and find that the retreat and expansion of the sea-ice edge correlate with mean significant wave height increases and decreases, respectively. This includes capturing the spatial variability in sea-ice trends found in the Ross and Amundsen-Bellingshausen seas. Climate models fail to capture recent changes in sea ice in both polar regions. Our results suggest that the incorporation of explicit or parameterized interactions between ocean waves and sea ice may resolve this problem.

  17. Gas transport processes in sea ice: How convection and diffusion processes might affect biological imprints, a challenge for modellers

    DEFF Research Database (Denmark)

    Tison, J.-L.; Zhou, Shaola J. G.; Thomas, D. N.

    2012-01-01

    nucleation occurs while the concentration in the ice goes well above the theoretical one, calculated from brine equilibrium under temperature and salinity changes and observed brine volumes. This phase change locks the gases within the sea ice structure, preventing "degassing" of the ice, as is observed...... within the sea ice cover, including in the gaseous form. Diffusive processes will become dominant once internal melting is strong enough to stratify the brine network within the ice. In the Kapisilit case, the regular decrease of an internal gas peak intensity due to external forcing during ice growth......Recent data from a year-round survey of landfast sea ice growth in Barrow (Alaska) have shown how O2/N2 and O2/Ar ratios could be used to pinpoint primary production in sea ice and derive net productivity rates from the temporal evolution of the oxygen concentration at a given depth within the sea...

  18. Ice Tank Experiments Highlight Changes in Sea Ice Types

    Science.gov (United States)

    Wilkinson, Jeremy P.; DeCarolis, Giacomo; Ehlert, Iris; Notz, Dirk; Evers, Karl-Ulrich; Jochmann, Peter; Gerland, Sebastian; Nicolaus, Marcel; Hughes, Nick; Kern, Stefan; de la Rosa, Sara; Smedsrud, Lars; Sakai, Shigeki; Shen, Hayley; Wadhams, Peter

    2009-03-01

    With the current and likely continuing reduction of summer sea ice extent in the Arctic Ocean, the predominant mechanism of sea ice formation in the Arctic is likely to change in the future. Although substantial new ice formation occurred under preexisting ice in the past, the fraction of sea ice formation in open water likely will increase significantly. In open water, sea ice formation starts with the development of small ice crystals, called frazil ice, which are suspended in the water column [World Meteorological Organization, 1985]. Under quiescent conditions, these crystals accumulate at the surface to form an unbroken ice sheet known in its early stage as nilas. Under turbulent conditions, caused by wind and waves, frazil ice continues to grow and forms into a thick, soupy mixture called grease ice. Eventually the frazil ice will coalesce into small, rounded pieces known as pancake ice, which finally consolidate into an ice sheet with the return of calm conditions. This frazil/pancake/ice sheet cycle is currently frequently observed in the Antarctic [Lange et al., 1989]. The cycle normally occurs in regions that have a significant stretch of open water, because this allows for the formation of larger waves and hence increased turbulence. Given the increase of such open water in the Arctic Ocean caused by retreating summer sea ice, the frazil/pancake/ice sheet cycle may also become the dominant ice formation process during freezeup in the Arctic.

  19. Arctic sea ice in the PlioMIP ensemble: is model performance for modern climates a reliable guide to performance for the past or the future?

    Directory of Open Access Journals (Sweden)

    F. W. Howell

    2015-04-01

    Full Text Available Eight general circulation models have simulated the mid-Pliocene Warm Period (mPWP, 3.264 to 3.025 Ma as part of the Pliocene Modelling Intercomparison Project (PlioMIP. Here, we analyse and compare their simulation of Arctic sea ice for both the pre-industrial and the mid-Pliocene. Mid-Pliocene sea ice thickness and extent is reduced and displays greater variability within the ensemble compared to the pre-industrial. This variability is highest in the summer months, when the model spread in the mid-Pliocene is more than three times larger than the rest of the year. Correlations between mid-Pliocene Arctic temperatures and sea ice extents are almost twice as strong as the equivalent correlations for the pre-industrial simulations. It is suggested that the weaker relationship between pre-industrial Arctic sea ice and temperatures is likely due to the tuning of climate models to achieve an optimal pre-industrial sea ice cover, which may also affect future predictions of Arctic sea ice. Model tuning for the pre-industrial does not appear to be best suited for simulating the different climate state of the mid-Pliocene. This highlights the importance of evaluating climate models through simulation of past climates, and the urgent need for more proxy evidence of sea ice during the Pliocene.

  20. Ice sheet systems and sea level change.

    Science.gov (United States)

    Rignot, E. J.

    2015-12-01

    Modern views of ice sheets provided by satellites, airborne surveys, in situ data and paleoclimate records while transformative of glaciology have not fundamentally changed concerns about ice sheet stability and collapse that emerged in the 1970's. Motivated by the desire to learn more about ice sheets using new technologies, we stumbled on an unexplored field of science and witnessed surprising changes before realizing that most were coming too fast, soon and large. Ice sheets are integrant part of the Earth system; they interact vigorously with the atmosphere and the oceans, yet most of this interaction is not part of current global climate models. Since we have never witnessed the collapse of a marine ice sheet, observations and exploration remain critical sentinels. At present, these observations suggest that Antarctica and Greenland have been launched into a path of multi-meter sea level rise caused by rapid climate warming. While the current loss of ice sheet mass to the ocean remains a trickle, every mm of sea level change will take centuries of climate reversal to get back, several major marine-terminating sectors have been pushed out of equilibrium, and ice shelves are irremediably being lost. As glaciers retreat from their salty, warm, oceanic margins, they will melt away and retreat slower, but concerns remain about sea level change from vastly marine-based sectors: 2-m sea level equivalent in Greenland and 23-m in Antarctica. Significant changes affect 2/4 marine-based sectors in Greenland - Jakobshavn Isb. and the northeast stream - with Petermann Gl. not far behind. Major changes have affected the Amundsen Sea sector of West Antarctica since the 1980s. Smaller yet significant changes affect the marine-based Wilkes Land sector of East Antarctica, a reminder that not all marine-based ice is in West Antarctica. Major advances in reducing uncertainties in sea level projections will require massive, interdisciplinary efforts that are not currently in place

  1. Summer sea ice characteristics of the Chukchi Sea

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    During August 1999, we investigated sea ice characteristics; its distribution, surface feature, thickness, ice floe movement, and the temperature field around inter-borders of air/ice/seawater in the Chukchi Sea. Thirteen ice cores were drilled at 11 floe stations in the area of 72°24′ 77°18′N, 153°34′ 163°28′W and the ice core structure was observed. From field observation, three melting processes of ice were observed; surface layer melting, surface and bottom layers melting, and all of ice melting. The observation of temperature fields around sea ice floes showed that the bottom melting under the ice floes were important process. As ice floes and open water areas were alternately distributed in summer Arctic Ocean; the water under ice was colder than the open water by 0.4 2.8℃. The sun radiation heated seawater in open sea areas so that the warmer water went to the bottom when the ice floes move to those areas. This causes ice melting to start at the bottom of the ice floes. This process can balance effectively the temperature fluctuating in the sea in summer. From the crystalline structure of sea ice observed from the cores, it was concluded that the ice was composed of ice crystals and brine-ice films. During the sea ice melting, the brine-ice films between ice crystals melted firstly; then the ice crystals were encircled by brine films; the sea ice became the mixture of ice and liquid brine. At the end of melting, the ice crystals would be separated each other, the bond between ice crystals weakens and this leads to the collapse of the ice sheet.

  2. Air-ice carbon pathways inferred from a sea ice tank experiment

    OpenAIRE

    Marie Kotovitch; Sébastien Moreau; Jiayun Zhou; Martin Vancoppenolle; Dieckmann, Gerhard S.; Karl-Ulrich Evers; Fanny Van der Linden; Thomas, David N.; Jean-Louis Tison; Bruno Delille

    2016-01-01

    Abstract Given rapid sea ice changes in the Arctic Ocean in the context of climate warming, better constraints on the role of sea ice in CO2 cycling are needed to assess the capacity of polar oceans to buffer the rise of atmospheric CO2 concentration. Air-ice CO2 fluxes were measured continuously using automated chambers from the initial freezing of a sea ice cover until its decay during the INTERICE V experiment at the Hamburg Ship Model Basin. Cooling seawater prior to sea ice formation act...

  3. The sensitivity of the Arctic sea ice to orbitally induced insolation changes: a study of the mid-Holocene Paleoclimate Modelling Intercomparison Project 2 and 3 simulations

    Directory of Open Access Journals (Sweden)

    M. Berger

    2013-04-01

    Full Text Available In the present work the Arctic sea ice in the mid-Holocene and the pre-industrial climates are analysed and compared on the basis of climate-model results from the Paleoclimate Modelling Intercomparison Project phase 2 (PMIP2 and phase 3 (PMIP3. The PMIP3 models generally simulate smaller and thinner sea-ice extents than the PMIP2 models both for the pre-industrial and the mid-Holocene climate. Further, the PMIP2 and PMIP3 models all simulate a smaller and thinner Arctic summer sea-ice cover in the mid-Holocene than in the pre-industrial control climate. The PMIP3 models also simulate thinner winter sea ice than the PMIP2 models. The winter sea-ice extent response, i.e. the difference between the mid-Holocene and the pre-industrial climate, varies among both PMIP2 and PMIP3 models. Approximately one half of the models simulate a decrease in winter sea-ice extent and one half simulates an increase. The model-mean summer sea-ice extent is 11 % (21 % smaller in the mid-Holocene than in the pre-industrial climate simulations in the PMIP2 (PMIP3. In accordance with the simple model of Thorndike (1992, the sea-ice thickness response to the insolation change from the pre-industrial to the mid-Holocene is stronger in models with thicker ice in the pre-industrial climate simulation. Further, the analyses show that climate models for which the Arctic sea-ice responses to increasing atmospheric CO2 concentrations are similar may simulate rather different sea-ice responses to the change in solar forcing between the mid-Holocene and the pre-industrial. For two specific models, which are analysed in detail, this difference is found to be associated with differences in the simulated cloud fractions in the summer Arctic; in the model with a larger cloud fraction the effect of insolation change is muted. A sub-set of the mid-Holocene simulations in the PMIP ensemble exhibit open water off the north-eastern coast of Greenland in summer, which can provide a fetch

  4. The Finite Element Sea Ice-Ocean Model (FESOM v.1.4: formulation of an ocean general circulation model

    Directory of Open Access Journals (Sweden)

    Q. Wang

    2014-04-01

    Full Text Available The Finite Element Sea Ice-Ocean Model (FESOM is the first global ocean general circulation model based on unstructured-mesh methods that has been developed for the purpose of climate research. The advantage of unstructured-mesh models is their flexible multi-resolution modelling functionality. In this study, an overview of the main features of FESOM will be given; based on sensitivity experiments a number of specific parameter choices will be explained; and directions of future developments will be outlined. It is argued that FESOM is sufficiently mature to explore the benefits of multi-resolution climate modelling and that its applications will provide information useful for the advancement of climate modelling on unstructured meshes.

  5. Loss of sea ice in the Arctic.

    Science.gov (United States)

    Perovich, Donald K; Richter-Menge, Jacqueline A

    2009-01-01

    The Arctic sea ice cover is in decline. The areal extent of the ice cover has been decreasing for the past few decades at an accelerating rate. Evidence also points to a decrease in sea ice thickness and a reduction in the amount of thicker perennial sea ice. A general global warming trend has made the ice cover more vulnerable to natural fluctuations in atmospheric and oceanic forcing. The observed reduction in Arctic sea ice is a consequence of both thermodynamic and dynamic processes, including such factors as preconditioning of the ice cover, overall warming trends, changes in cloud coverage, shifts in atmospheric circulation patterns, increased export of older ice out of the Arctic, advection of ocean heat from the Pacific and North Atlantic, enhanced solar heating of the ocean, and the ice-albedo feedback. The diminishing Arctic sea ice is creating social, political, economic, and ecological challenges.

  6. Radar for Mapping Sea Ice

    Science.gov (United States)

    Barath, F. T.; Jordan, R. L.

    1983-01-01

    X-band system has 100-m2 resolution. Wide swath imaging radar of synthetic aperature type transmits signal to ground station for subsequent processing into imagery. Concept meets functional requirements for continuously mapping sea ice in north and south polar regions.

  7. Controls on Arctic sea ice from first-year and multi-year ice survival rates

    Science.gov (United States)

    Armour, K.; Bitz, C. M.; Hunke, E. C.; Thompson, L.

    2009-12-01

    The recent decrease in Arctic sea ice cover has transpired with a significant loss of multi-year (MY) ice. The transition to an Arctic that is populated by thinner first-year (FY) sea ice has important implications for future trends in area and volume. We develop a reduced model for Arctic sea ice with which we investigate how the survivability of FY and MY ice control various aspects of the sea-ice system. We demonstrate that Arctic sea-ice area and volume behave approximately as first-order autoregressive processes, which allows for a simple interpretation of September sea-ice in which its mean state, variability, and sensitivity to climate forcing can be described naturally in terms of the average survival rates of FY and MY ice. This model, used in concert with a sea-ice simulation that traces FY and MY ice areas to estimate the survival rates, reveals that small trends in the ice survival rates explain the decline in total Arctic ice area, and the relatively larger loss of MY ice area, over the period 1979-2006. Additionally, our model allows for a calculation of the persistence time scales of September area and volume anomalies. A relatively short memory time scale for ice area (~ 1 year) implies that Arctic ice area is nearly in equilibrium with long-term climate forcing at all times, and therefore observed trends in area are a clear indication of a changing climate. A longer memory time scale for ice volume (~ 5 years) suggests that volume can be out of equilibrium with climate forcing for long periods of time, and therefore trends in ice volume are difficult to distinguish from its natural variability. With our reduced model, we demonstrate the connection between memory time scale and sensitivity to climate forcing, and discuss the implications that a changing memory time scale has on the trajectory of ice area and volume in a warming climate. Our findings indicate that it is unlikely that a “tipping point” in September ice area and volume will be

  8. Global Sea Ice Charting at the National Ice Center

    Science.gov (United States)

    Clemente-Colon, P.

    2006-12-01

    The National Ice Center (NIC) is a U.S. government tri-agency operational center comprised of components from the United States Navy, the National Oceanic and Atmospheric Administration (NOAA), and the U. S. Coast Guard (USCG). The mission of the NIC is to provide the highest quality strategic and tactical ice services tailored to meet operational requirements of U.S. national interests. This includes broad responsibilities to monitor all frozen ocean regions of the world in support of coastal and marine sea ice operations and research. Sea ice conditions are routinely monitored and mapped using satellite imagery along with ancillary model and in-situ data. Active microwave images from Synthetic Aperture Radar (SAR) sensors are the data of choice for NIC analysts because of their high spatial resolution (~100 m). SAR is in fact the primary data source for ice analysis when available. The high spatial resolution of available SAR data and the reliability shown by the RADARSAT- 1 mission in particular have made the use of these data critical for vessels operating in or near the ice. Limited data from the ESA Envisat Advanced SAR (ASAR) are also used in the analyses when available. Preparations for the use of the Phased Array type L-band SAR (PALSAR) aboard the soon to be launched Japanese ALOS satellite are also underway. Scatterometer backscatter imagery from QuikSCAT is also routinely used for basin-scale and circumpolar ice edge mapping. Automated algorithms for ice type and melt ponds detection as well as the synergy between these observations and the QuikSCAT wind vectors off the marginal ice zone (MIZ) are been explored. ESA Envisat Advanced SAR (ASAR) Global Monitoring Mode (GMM) mosaics of the Arctic and Antarctic regions are becoming an important tool for sea ice edge delineation too. Although SAR observations are the choice for NIC analysts to produce high spatial resolution products gear toward tactical support, passive microwave data such as those from the

  9. Ecological consequences of sea-ice decline.

    Science.gov (United States)

    Post, Eric; Bhatt, Uma S; Bitz, Cecilia M; Brodie, Jedediah F; Fulton, Tara L; Hebblewhite, Mark; Kerby, Jeffrey; Kutz, Susan J; Stirling, Ian; Walker, Donald A

    2013-08-02

    After a decade with nine of the lowest arctic sea-ice minima on record, including the historically low minimum in 2012, we synthesize recent developments in the study of ecological responses to sea-ice decline. Sea-ice loss emerges as an important driver of marine and terrestrial ecological dynamics, influencing productivity, species interactions, population mixing, gene flow, and pathogen and disease transmission. Major challenges in the near future include assigning clearer attribution to sea ice as a primary driver of such dynamics, especially in terrestrial systems, and addressing pressures arising from human use of arctic coastal and near-shore areas as sea ice diminishes.

  10. Arctic sea ice decline: Projected changes in timing and extent of sea ice in the Bering and Chukchi Seas

    Science.gov (United States)

    Douglas, D.C.

    2010-01-01

    The Arctic region is warming faster than most regions of the world due in part to increasing greenhouse gases and positive feedbacks associated with the loss of snow and ice cover. One consequence has been a rapid decline in Arctic sea ice over the past 3 decades?a decline that is projected to continue by state-of-the-art models. Many stakeholders are therefore interested in how global warming may change the timing and extent of sea ice Arctic-wide, and for specific regions. To inform the public and decision makers of anticipated environmental changes, scientists are striving to better understand how sea ice influences ecosystem structure, local weather, and global climate. Here, projected changes in the Bering and Chukchi Seas are examined because sea ice influences the presence of, or accessibility to, a variety of local resources of commercial and cultural value. In this study, 21st century sea ice conditions in the Bering and Chukchi Seas are based on projections by 18 general circulation models (GCMs) prepared for the fourth reporting period by the Intergovernmental Panel on Climate Change (IPCC) in 2007. Sea ice projections are analyzed for each of two IPCC greenhouse gas forcing scenarios: the A1B `business as usual? scenario and the A2 scenario that is somewhat more aggressive in its CO2 emissions during the second half of the century. A large spread of uncertainty among projections by all 18 models was constrained by creating model subsets that excluded GCMs that poorly simulated the 1979-2008 satellite record of ice extent and seasonality. At the end of the 21st century (2090-2099), median sea ice projections among all combinations of model ensemble and forcing scenario were qualitatively similar. June is projected to experience the least amount of sea ice loss among all months. For the Chukchi Sea, projections show extensive ice melt during July and ice-free conditions during August, September, and October by the end of the century, with high agreement

  11. Assessment of the sea-ice carbon pump

    DEFF Research Database (Denmark)

    Grimm, R.; Notz, D.; Glud, Ronnie N.

    2016-01-01

    It has been suggested that geochemical processes related to sea-ice growth and melt might be important for the polar carbon cycle via the so called sea-ice carbon pump (SICP). The SICP affects the air-sea CO2 exchange by influencing the composition of dissolved inorganic carbon (DIC) and total...... in regions with net sea-ice melt, and enhanced SICP-induced oceanic CO2 out-gassing in regions with net sea-ice growth. These general regional patterns are modified further by the blockage of air-sea gas exchange through sea-ice coverage. Integrated over the sea-ice zones of both hemispheres, the SICP...... alkalinity (TA) in the surface ocean. Here we quantify the strength of the SICP-induced air-sea CO2 flux using the global three-dimensional ocean-sea-ice-biogeochemical model MPIOM/HAMOCC. Simulations prescribing the range of observed DIC and TA concentrations in the sea ice were performed under two...

  12. NUMERICAL SIMULATIONS OF SEA ICE WITH DIFFERENT ADVECTION SCHEMES

    Institute of Scientific and Technical Information of China (English)

    LIU Xi-ying

    2011-01-01

    Numerical simulations are carried out for sea ice with four different advection schemes to study their effects on the simulation results.The sea ice model employed here is the Sea Ice Simulator (SIS) of the Geophysical Fluid Dynamics Laboratory (GFDL) Modular Ocean Model version 4b (MOM4b) and the four advection schemes are, the upwind scheme originally used in the SIS, the Multi-Dimensional Positive Advection (MDPA) scheme, the Incremental Remapping Scheme (IRS) and the Two Step Shape Preserving (TSSP) scheme.The latter three schemes are newly introduced.To consider the interactions between sea ice and ocean, a mixed layer ocean model is introduced and coupled to the SIS.The coupled model uses a tri-polar coordinate with 120×65 grids,covering the whole earth globe, in the horizontal plane.Simulation results in the northern high latitudes are analyzed.In all simulations, the model reproduces the seasonal variation of sea ice in the northern high latitudes well.Compared with the results from the observation, the sea ice model produces some extra sea ice coverage in the Greenland Sea and Barents Sea in winter due to the exclusion of ocean current effects and the smaller simulated sea ice thickness in the Arctic basin.There are similar features among the results obtained with the introduced three advection schemes.The simulated sea ice thickness with the three newly introduced schemes are all smaller than that of the upwind scheme and the simulated sea ice velocities of movement are all smaller than that of the upwind scheme.There are more similarities shared in the results obtained with the MPDA and TSSP schemes.

  13. Sea ice thickness estimation in the Bohai Sea using geostationary ocean color imager data

    Institute of Scientific and Technical Information of China (English)

    LIU Wensong; SHENG Hui; ZHANG Xi

    2016-01-01

    A method to estimate the thickness of the sea ice of the Bohai Sea is proposed using geostationary ocean color imager (GOCI) data and then applied to the dynamic monitoring of the sea ice thickness in the Bohai Sea during the winter of 2014 to 2015. First of all, a model is given between the GOCI shortwave broadband albedo and the reflectance of each band with high temporal resolution GOCI data. Then, the relationship model between the sea ice thickness and the GOCI shortwave broadband albedo is established and applied to the thickness extraction of the sea ice in the Bohai Sea. Finally, the sea ice thickness extraction method is tested by the results based on the MODIS data, thermodynamic empirical models (Lebedev and Zubov), and thein situ ice thickness data. The test results not only indicated that the sea ice thickness retrieval method based on the GOCI data was a good correlation (r2>0.86) with the sea ice thickness retrieved by the MODIS and thermodynamic empirical models, but also that the RMS is only 6.82 cm different from the thickness of the sea ice based on the GOCI andin situ data.

  14. A recent bifurcation in Arctic sea-ice cover

    Directory of Open Access Journals (Sweden)

    V. N. Livina

    2012-07-01

    Full Text Available There is ongoing debate over whether Arctic sea-ice has already passed a "tipping point", or whether it will do so in future, with several recent studies arguing that the loss of summer sea ice does not involve a bifurcation because it is highly reversible in models. Recently developed methods can detect and sometimes forewarn of bifurcations in time-series data, hence we applied them to satellite data for Arctic sea-ice cover. Here we show that a new low ice cover state has appeared from 2007 onwards, which is distinct from the normal state of seasonal sea ice variation, suggesting a bifurcation has occurred from one attractor to two. There was no robust early warning signal of critical slowing down prior to this bifurcation, consistent with it representing the appearance of a new ice cover state rather than the loss of stability of the existing state. The new low ice cover state has been sampled predominantly in summer-autumn and seasonal forcing combined with internal climate variability are likely responsible for triggering recent transitions between the two ice cover states. However, all early warning indicators show destabilization of the summer-autumn sea-ice since 2007. This suggests the new low ice cover state may be a transient feature and further abrupt changes in summer-autumn Arctic sea-ice cover could lie ahead; either reversion to the normal state or a yet larger ice loss.

  15. Fine-resolution simulation of surface current and sea ice in the Arctic Mediterranean Seas

    Institute of Scientific and Technical Information of China (English)

    LIU Xiying; ZHANG Xuehong; YU Rucong; LIU Hailong; LI Wei

    2007-01-01

    A fine-resolution model is developed for ocean circulation simulation in the National Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG),Chinese Academy of Sciences, and is applied to simulate surface current and sea ice variations in the Arctic Mediterranean Seas. A dynamic sea ice model in elastic-viscous-plastic rheology and a thermodynamic sea ice model are employed. A 200-year simulation is performed and a dimatological average of a 10-year period (141 st-150 th) is presented with focus on sea ice concentration and surface current variations in the Arctic Mediterranean Seas. The model is able to simulate well the East Greenland Current, Beaufort Gyre and the Transpolar Drift, but the simulated West Spitsbergen Current is small and weak. In the March climatology, the sea ice coverage can be simulated well except for a bit more ice in east of Spitsbergen Island. The result is also good for the September scenario except for less ice concentration east of Greenland and greater ice concentration near the ice margin. The extra ice east of Spitsbergen Island is caused by sea ice current convergence forced by atmospheric wind stress.

  16. Sea Ice Processes

    Science.gov (United States)

    1988-01-01

    aq pnoiqs suol)0!pOid AixoolQA 00! 191100 (1I ’uoTow poAlosqo aql jo lqlgti 04) ol a~xe juqp suotioaJip 4)!A% parto s~t S stqi pule ’spoods 001 a)tUJT...to provide information as ating characteristics of PIPS. These factors in- to processes and their scales (as ascertained by elude the vertical grid...warranted horizontal compression being compensated by at this time. Further investigation is needed. vertical motion. In the case of ice, upward The space

  17. Air-ice carbon pathways inferred from a sea ice tank experiment

    Directory of Open Access Journals (Sweden)

    Marie Kotovitch

    2016-06-01

    Full Text Available Abstract Given rapid sea ice changes in the Arctic Ocean in the context of climate warming, better constraints on the role of sea ice in CO2 cycling are needed to assess the capacity of polar oceans to buffer the rise of atmospheric CO2 concentration. Air-ice CO2 fluxes were measured continuously using automated chambers from the initial freezing of a sea ice cover until its decay during the INTERICE V experiment at the Hamburg Ship Model Basin. Cooling seawater prior to sea ice formation acted as a sink for atmospheric CO2, but as soon as the first ice crystals started to form, sea ice turned to a source of CO2, which lasted throughout the whole ice growth phase. Once ice decay was initiated by warming the atmosphere, the sea ice shifted back again to a sink of CO2. Direct measurements of outward ice-atmosphere CO2 fluxes were consistent with the depletion of dissolved inorganic carbon in the upper half of sea ice. Combining measured air-ice CO2 fluxes with the partial pressure of CO2 in sea ice, we determined strongly different gas transfer coefficients of CO2 at the air-ice interface between the growth and the decay phases (from 2.5 to 0.4 mol m−2 d−1 atm−1. A 1D sea ice carbon cycle model including gas physics and carbon biogeochemistry was used in various configurations in order to interpret the observations. All model simulations correctly predicted the sign of the air-ice flux. By contrast, the amplitude of the flux was much more variable between the different simulations. In none of the simulations was the dissolved gas pathway strong enough to explain the large fluxes during ice growth. This pathway weakness is due to an intrinsic limitation of ice-air fluxes of dissolved CO2 by the slow transport of dissolved inorganic carbon in the ice. The best means we found to explain the high air-ice carbon fluxes during ice growth is an intense yet uncertain gas bubble efflux, requiring sufficient bubble nucleation and upwards rise. We

  18. Simulation of snowbands in the Baltic Sea area with the coupled atmosphere-ocean-ice model COSMO-CLM/NEMO

    Directory of Open Access Journals (Sweden)

    Trang Van Pham

    2017-02-01

    Full Text Available Wind-parallel bands of snowfall over the Baltic Sea area are common during late autumn and early winter. This phenomenon occurs when cold air flows over the warm water surface, enhancing convection and leading to heavy snow fall. Six snowband events from 1985 to 2010 are simulated by using the coupled atmosphere-ocean-ice model COSMO-CLM/NEMO. The model resolution is reasonably high to capture the snowbands; the atmospheric model COSMO-CLM has a horizontal grid-spacing of approximately 25 km and the ocean sea-ice model NEMO has a horizontal grid-spacing of approximately 3 km. The model results show that the coupled system COSMO-CLM/NEMO successfully reproduced the snowband events with a high contrast of temperatures between the surface and the atmosphere, sharp bands of precipitation over the sea, as well as the enormous heat fluxes released by the ocean to the atmosphere during the days when snowbands occurred. In the two cases when radar data are available, the model precipitation is shown to be in satisfactory agreement. The precipitation patterns closely follow the cloud shapes on satellite images. When not coupled with the ocean model, the atmospheric stand-alone model provided acceptable results if forced by high-quality sea surface temperatures (SSTs from reanalysis data. However, COSMO-CLM forced with lower quality SSTs could not recreate the snowbands. The results indicate the need of an atmospheric model with high SST skill or a coupled ocean model when extreme event climatology is the primary aim in the Baltic Sea area.

  19. Ice and AIS: ship speed data and sea ice forecasts in the Baltic Sea

    Directory of Open Access Journals (Sweden)

    U. Löptien

    2014-12-01

    Full Text Available The Baltic Sea is a seasonally ice-covered marginal sea located in a densely populated area in northern Europe. Severe sea ice conditions have the potential to hinder the intense ship traffic considerably. Thus, sea ice fore- and nowcasts are regularly provided by the national weather services. Typically, the forecast comprises several ice properties that are distributed as prognostic variables, but their actual usefulness is difficult to measure, and the ship captains must determine their relative importance and relevance for optimal ship speed and safety ad hoc. The present study provides a more objective approach by comparing the ship speeds, obtained by the automatic identification system (AIS, with the respective forecasted ice conditions. We find that, despite an unavoidable random component, this information is useful to constrain and rate fore- and nowcasts. More precisely, 62–67% of ship speed variations can be explained by the forecasted ice properties when fitting a mixed-effect model. This statistical fit is based on a test region in the Bothnian Sea during the severe winter 2011 and employs 15 to 25 min averages of ship speed.

  20. Arctic sea ice decline contributes to thinning lake ice trend in northern Alaska

    Science.gov (United States)

    Alexeev, Vladimir; Arp, Christopher D.; Jones, Benjamin M.; Cai, Lei

    2016-01-01

    Field measurements, satellite observations, and models document a thinning trend in seasonal Arctic lake ice growth, causing a shift from bedfast to floating ice conditions. September sea ice concentrations in the Arctic Ocean since 1991 correlate well (r = +0.69,p sea ice affects lakes, we conducted model experiments to simulate winters with years of high (1991/92) and low (2007/08) sea ice extent for which we also had field measurements and satellite imagery characterizing lake ice conditions. A lake ice growth model forced with Weather Research and Forecasting model output produced a 7% decrease in lake ice growth when 2007/08 sea ice was imposed on 1991/92 climatology and a 9% increase in lake ice growth for the opposing experiment. Here, we clearly link early winter 'ocean-effect' snowfall and warming to reduced lake ice growth. Future reductions in sea ice extent will alter hydrological, biogeochemical, and habitat functioning of Arctic lakes and cause sub-lake permafrost thaw.

  1. Quantifying the influence of sea ice on ocean microseism using observations from the Bering Sea, Alaska

    Science.gov (United States)

    Tsai, Victor C.; McNamara, Daniel E.

    2011-01-01

    Microseism is potentially affected by all processes that alter ocean wave heights. Because strong sea ice prevents large ocean waves from forming, sea ice can therefore significantly affect microseism amplitudes. Here we show that this link between sea ice and microseism is not only a robust one but can be quantified. In particular, we show that 75–90% of the variability in microseism power in the Bering Sea can be predicted using a fairly crude model of microseism damping by sea ice. The success of this simple parameterization suggests that an even stronger link can be established between the mechanical strength of sea ice and microseism power, and that microseism can eventually be used to monitor the strength of sea ice, a quantity that is not as easily observed through other means.

  2. Albedo evolution of seasonal Arctic sea ice

    Science.gov (United States)

    Perovich, Donald K.; Polashenski, Christopher

    2012-04-01

    There is an ongoing shift in the Arctic sea ice cover from multiyear ice to seasonal ice. Here we examine the impact of this shift on sea ice albedo. Our analysis of observations from four years of field experiments indicates that seasonal ice undergoes an albedo evolution with seven phases; cold snow, melting snow, pond formation, pond drainage, pond evolution, open water, and freezeup. Once surface ice melt begins, seasonal ice albedos are consistently less than albedos for multiyear ice resulting in more solar heat absorbed in the ice and transmitted to the ocean. The shift from a multiyear to seasonal ice cover has significant implications for the heat and mass budget of the ice and for primary productivity in the upper ocean. There will be enhanced melting of the ice cover and an increase in the amount of sunlight available in the upper ocean.

  3. Arctic Summer Sea-Ice Extent: How Free is Free?

    Science.gov (United States)

    Tremblay, B.; Cullather, R. I.; DeRepentigny, P.; Pfirman, S. L.; Newton, R.

    2015-12-01

    As Northern Hemisphere perennial sea ice cover continues a long-term downward trend, attention has begun to focus on the implications of the changing conditions. A summertime ice-free Arctic Ocean is frequently indicated as a signature milestone for these changes, however "ice-free" has a substantially different meaning among scientists and interested stakeholders. To climate scientists it may mean when there is so little sea ice that it plays a minimal role in the climate system. To those interested in development, it may mean a threshold where icebreaker support is not required. To coastal communities it may mean so little ice that hunting is not possible. To species dependent on sea ice, it may mean the point where they cannot find sufficient habitat to survive from spring until fall. In this contribution we document the projected seasonality of the sea ice retreat and address the following questions. For how long will the Arctic Ocean be ice free on average each year? What is the impact of such changes in the seasonality of the sea ice cover on species that are dependent on sea ice? To this end, we analyze the seasonal cycle in the sea-ice extent simulated by the Community Earth System Model 1 - Large Ensemble (CESM1-LE) output for the 21st century. CESM1-LE simulates a realistic late 20th, early 21st century Arctic climate with a seasonal cycle in sea ice extent and rate of decline in good agreement with observations. Results from this model show that even by the end of the 21st century, the length of the ice-free season is relatively short, with ice-free conditions mainly present for 2-3 months between August and October. The result is a much larger amplitude seasonal cycle when compared with the late 20th century climate.

  4. Seasonal sea ice changes in the Amundsen Sea, Antarctica, over the period of 1979–2014

    Directory of Open Access Journals (Sweden)

    S. E. Stammerjohn

    2015-06-01

    Full Text Available Abstract Recent attention has focused on accelerated glacial losses along the Amundsen Sea coast that result from changes in atmosphere and ocean circulation, with sea ice playing a mediating but not well-understood role. Here, we investigated how sea ice has changed in the Amundsen Sea over the period of 1979 to 2014, focusing on spatio-temporal changes in ice edge advance/retreat and percent sea ice cover in relation to changes in winds. In contrast to the widespread sea ice decreases to the east and increases to the west of the Amundsen Sea, sea ice changes in the Amundsen Sea were confined to three areas: (i offshore of the shelf break, (ii the southern Pine Island Polynya, and (iii the eastern Amundsen Sea Polynya. Offshore, a 2-month decrease in ice season duration coincided with seasonal shifts in wind speed and direction from March to May (relating to later ice advance and from September to August (relating to earlier retreat, consistent with reported changes in the depth/location of the Amundsen Sea Low. In contrast, sea ice decreases in the polynya areas corresponded to episodic or step changes in spring ice retreat (earlier by 1–2 months and were coincident with changes to Thwaites Iceberg Tongue (located between the two polynyas and increased southeasterly winds. Temporal correlations among these three areas were weak, indicating different local forcing and/or differential response to large-scale forcing. Although our analysis has shown that part of the variability can be explained by changes in winds or to the coastal icescape, an additional but unknown factor is how sea ice has responded to changes in ocean heat and freshwater inputs. Unraveling cause and effect, critical for predicting changes to this rapidly evolving ocean-ice shelf-sea ice system, will require in situ observations, along with improved remote sensing capabilities and ocean modeling.

  5. History of sea ice in the Arctic

    DEFF Research Database (Denmark)

    Polyak, Leonid; Alley, Richard B.; Andrews, John T.

    2010-01-01

    Arctic sea-ice extent and volume are declining rapidly. Several studies project that the Arctic Ocean may become seasonally ice-free by the year 2040 or even earlier. Putting this into perspective requires information on the history of Arctic sea-ice conditions through the geologic past. This inf...

  6. Age characteristics in a multidecadal Arctic sea ice simulation

    Energy Technology Data Exchange (ETDEWEB)

    Hunke, Elizabeth C [Los Alamos National Laboratory; Bitz, Cecllia M [UNIV. OF WASHINGTON

    2008-01-01

    Results from adding a tracer for age of sea ice to a sophisticated sea ice model that is widely used for climate studies are presented. The consistent simulation of ice age, dynamics, and thermodynamics in the model shows explicitly that the loss of Arctic perennial ice has accelerated in the past three decades, as has been seen in satellite-derived observations. Our model shows that the September ice age average across the Northern Hemisphere varies from about 5 to 8 years, and the ice is much younger (about 2--3 years) in late winter because of the expansion of first-year ice. We find seasonal ice on average comprises about 5% of the total ice area in September, but as much as 1.34 x 10{sup 6} km{sup 2} survives in some years. Our simulated ice age in the late 1980s and early 1990s declined markedly in agreement with other studies. After this period of decline, the ice age began to recover, but in the final years of the simulation very little young ice remains after the melt season, a strong indication that the age of the pack will again decline in the future as older ice classes fail to be replenished. The Arctic ice pack has fluctuated between older and younger ice types over the past 30 years, while ice area, thickness, and volume all declined over the same period, with an apparent acceleration in the last decade.

  7. Iodine emissions from the sea ice of the Weddell Sea

    Directory of Open Access Journals (Sweden)

    H. M. Atkinson

    2012-05-01

    Full Text Available Iodine compounds were measured above, below and within the sea ice of the Weddell Sea during a cruise in 2009, to elucidate the mechanism of local enhancement and volatilisation of iodine. I2 mixing ratios of up to 12.4 pptv were measured 10 m above the sea ice, and up to 31 pptv was observed above surface snow on the nearby Brunt Ice Shelf – large amounts. Atmospheric IO of up to 7 pptv was measured from the ship, and the average sum of HOI and ICl was 1.9 pptv. These measurements confirm the Weddell Sea as an iodine hotspot. Average atmospheric concentrations of CH3I, C2H5I, CH2ICl, 2-C3H7I, CH2IBr and 1-C3H7I were each 0.2 pptv or less. On the Brunt Ice Shelf, enhanced concentrations of CH3I and C2H5I (up to 0.5 and 1 pptv, respectively were observed in firn air, with a diurnal profile that suggests the snow may be a source. In the sea ice brine, iodocarbons concentrations were over 10 times those of the sea water below. The sum of iodide + iodate was depleted in sea ice samples, suggesting some missing iodine chemistry. Flux calculations suggest I2 dominates the iodine atom flux to the atmosphere, but models cannot reconcile the observations and suggest either a missing iodine source or other deficiencies in our understanding of iodine chemistry. The observation of new particle formation, consistent with the model predictions, strongly suggests an iodine source. This combined study of iodine compounds is the first of its kind in this unique region of sea ice rich in biology and rich in iodine chemistry.

  8. Iodine emissions from the sea ice of the Weddell Sea

    Directory of Open Access Journals (Sweden)

    H. M. Atkinson

    2012-11-01

    Full Text Available Iodine compounds were measured above, below and within the sea ice of the Weddell Sea during a cruise in 2009, to make progress in elucidating the mechanism of local enhancement and volatilisation of iodine. I2 mixing ratios of up to 12.4 pptv were measured 10 m above the sea ice, and up to 31 pptv was observed above surface snow on the nearby Brunt Ice Shelf – large amounts. Atmospheric IO of up to 7 pptv was measured from the ship, and the average sum of HOI and ICl was 1.9 pptv. These measurements confirm the Weddell Sea as an iodine hotspot. Average atmospheric concentrations of CH3I, C2H5I, CH2ICl, 2-C3H7I, CH2IBr and 1-C3H7I were each 0.2 pptv or less. On the Brunt Ice Shelf, enhanced concentrations of CH3I and C2H5I (up to 0.5 and 1 pptv respectively were observed in firn air, with a diurnal profile that suggests the snow may be a source. In the sea ice brine, iodocarbons concentrations were over 10 times those of the sea water below. The sum of iodide + iodate was depleted in sea ice samples, suggesting some missing iodine chemistry. Flux calculations suggest I2 dominates the iodine atom flux to the atmosphere, but models cannot reconcile the observations and suggest either a missing iodine source or other deficiencies in our understanding of iodine chemistry. The observation of new particle formation, consistent with the model predictions, strongly suggests an iodine source. This combined study of iodine compounds is the first of its kind in this unique region of sea ice rich in biology and rich in iodine chemistry.

  9. Arctic sea ice decline contributes to thinning lake ice trend in northern Alaska

    Science.gov (United States)

    Alexeev, Vladimir A.; Arp, Christopher D.; Jones, Benjamin M.; Cai, Lei

    2016-07-01

    Field measurements, satellite observations, and models document a thinning trend in seasonal Arctic lake ice growth, causing a shift from bedfast to floating ice conditions. September sea ice concentrations in the Arctic Ocean since 1991 correlate well (r = +0.69, p Weather Research and Forecasting model output produced a 7% decrease in lake ice growth when 2007/08 sea ice was imposed on 1991/92 climatology and a 9% increase in lake ice growth for the opposing experiment. Here, we clearly link early winter ‘ocean-effect’ snowfall and warming to reduced lake ice growth. Future reductions in sea ice extent will alter hydrological, biogeochemical, and habitat functioning of Arctic lakes and cause sub-lake permafrost thaw.

  10. Simulation of the melt season using a resolved sea ice model with snow cover and melt ponds

    Science.gov (United States)

    Skyllingstad, Eric D.; Shell, Karen M.; Collins, Lee; Polashenski, Chris

    2015-07-01

    A three-dimensional sea ice model is presented with resolved snow thickness variations and melt ponds. The model calculates heating from solar radiative transfer and simulates the formation and movement of brine/melt water through the ice system. Initialization for the model is based on observations of snow topography made during the summer melt seasons of 2009, 2010, and 2012 from a location off the coast of Barrow, AK. Experiments are conducted to examine the importance of snow properties and snow and ice thickness by comparing observed and modeled pond fraction and albedo. One key process simulated by the model is the formation of frozen layers in the ice as relatively warm fresh water grid cells freeze when cooled by adjacent, cold brine-filled grid cells. These layers prevent vertical drainage and lead to flooding of melt water commonly observed at the beginning of the melt season. Flooding persists until enough heat is absorbed to melt through the frozen layer. The resulting long-term melt pond coverage is sensitive to both the spatial variability of snow cover and the minimum snow depth. For thin snow cover, initial melting results in earlier, reduced flooding with a small change in pond fraction after drainage of the melt water. Deeper snow tends to generate a delayed, larger peak pond fraction before drainage.

  11. Amplification of European Little Ice Age by sea ice-ocean-atmosphere feedbacks

    Science.gov (United States)

    Lehner, Flavio; Born, Andreas; Raible, Christoph C.; Stocker, Thomas F.

    2013-04-01

    The transition from the Medieval Climate Anomaly (~950-1250 AD) to the Little Ice Age (~1400-1700 AD) is believed to have been driven by an interplay of external forcing and climate system-internal variability. While the hemispheric signal seems to have been dominated by solar irradiance and volcanic eruptions, the understanding of mechanisms shaping the climate on continental scale is less robust. Examining an ensemble of transient model simulations as well as a new type of sensitivity experiments with artificial sea ice growth, we identify a sea ice-ocean-atmosphere feedback mechanism that amplifies the Little Ice Age cooling in the North Atlantic-European region and produces the temperature pattern expected from reconstructions. Initiated by increasing negative forcing, the Arctic sea ice substantially expands at the beginning of the Little Ice Age. The excess of sea ice is exported to the subpolar North Atlantic, where it melts, thereby weakening convection of the ocean. As a consequence, northward ocean heat transport is reduced, reinforcing the expansion of the sea ice and the cooling of the Northern Hemisphere. In the Nordic Seas, sea surface height anomalies cause the oceanic recirculation to strengthen at the expense of the warm Barents Sea inflow, thereby further reinforcing sea ice growth in the Barents Sea. The absent ocean-atmosphere heat flux in the Barents Sea results in an amplified cooling over Northern Europe. The positive nature of this feedback mechanism enables sea ice to remain in an expanded state for decades to centuries and explain sustained cold periods over Europe such as the Little Ice Age. Support for the feedback mechanism comes from recent proxy reconstructions around the Nordic Seas.

  12. Geometrical constraints on the evolution of ridged sea ice

    Science.gov (United States)

    Amundrud, Trisha L.; Melling, Humfrey; Ingram, R. Grant

    2004-06-01

    A numerical model of the evolving draft distribution of seasonal pack ice is driven by freezing and ice field compression in one dimension. Spatial transects of sea ice draft acquired during winter in the Beaufort Sea are used to evaluate the model. Histograms obtained by ice-profiling sonar on subsea moorings reveal changes in the draft distribution, while observations of ice velocity by Doppler sonar allow calculation of the strain to which the draft distribution is responding. Numerical diffusion in thermal ice growth is controlled using a remapping algorithm. Mechanical redistribution algorithms in common use generate much more deep ridged ice than is observed. Geometric constraints on ridge-keel development that reflect the finite extent of level floes available for ridge building and the true average shape of keels produce more realistic results. In the seasonal pack ice of the Beaufort Sea, 75% of all floes are too small to provide a volume of ice sufficient to construct a keel of draft equal to that commonly assumed in ice dynamics modeling. On average, the distribution of draft within keels has a negative exponential form, implying a cusped keel shape with more area on the thinner flanks than at the crest; models commonly assume a uniform redistribution of ice into a keel of triangular shape. Clearly, the spatial organization of ice within seasonal pack or, equivalently, the existence of ridges and floes should be an acknowledged factor in redistribution theory for pack ice thickness.

  13. Interdecadal changes in snow depth on Arctic sea ice

    Science.gov (United States)

    Webster, Melinda A.; Rigor, Ignatius G.; Nghiem, Son V.; Kurtz, Nathan T.; Farrell, Sinead L.; Perovich, Donald K.; Sturm, Matthew

    2014-08-01

    Snow plays a key role in the growth and decay of Arctic sea ice. In winter, it insulates sea ice from cold air temperatures, slowing sea ice growth. From spring to summer, the albedo of snow determines how much insolation is absorbed by the sea ice and underlying ocean, impacting ice melt processes. Knowledge of the contemporary snow depth distribution is essential for estimating sea ice thickness and volume, and for understanding and modeling sea ice thermodynamics in the changing Arctic. This study assesses spring snow depth distribution on Arctic sea ice using airborne radar observations from Operation IceBridge for 2009-2013. Data were validated using coordinated in situ measurements taken in March 2012 during the Bromine, Ozone, and Mercury Experiment (BROMEX) field campaign. We find a correlation of 0.59 and root-mean-square error of 5.8 cm between the airborne and in situ data. Using this relationship and IceBridge snow thickness products, we compared the recent results with data from the 1937, 1954-1991 Soviet drifting ice stations. The comparison shows thinning of the snowpack, from 35.1 ± 9.4 to 22.2 ± 1.9 cm in the western Arctic, and from 32.8 ± 9.4 to 14.5 ± 1.9 cm in the Beaufort and Chukchi seas. These changes suggest a snow depth decline of 37 ± 29% in the western Arctic and 56 ± 33% in the Beaufort and Chukchi seas. Thinning is negatively correlated with the delayed onset of sea ice freezeup during autumn.

  14. Radiative transfer in atmosphere-sea ice-ocean system

    Energy Technology Data Exchange (ETDEWEB)

    Jin, Z.; Stamnes, K.; Weeks, W.F. [Univ. of Alaska, Fairbanks, AK (United States); Tsay, S.C. [NASA Goddard Space Flight Center, Greenbelt, MD (United States)

    1996-04-01

    Radiative energy is critical in controlling the heat and mass balance of sea ice, which significantly affects the polar climate. In the polar oceans, light transmission through the atmosphere and sea ice is essential to the growth of plankton and algae and, consequently, to the microbial community both in the ice and in the ocean. Therefore, the study of radiative transfer in the polar atmosphere, sea ice, and ocean system is of particular importance. Lacking a properly coupled radiative transfer model for the atmosphere-sea ice-ocean system, a consistent study of the radiative transfer in the polar atmosphere, snow, sea ice, and ocean system has not been undertaken before. The radiative transfer processes in the atmosphere and in the ice and ocean have been treated separately. Because the radiation processes in the atmosphere, sea ice, and ocean depend on each other, this separate treatment is inconsistent. To study the radiative interaction between the atmosphere, clouds, snow, sea ice, and ocean, a radiative transfer model with consistent treatment of radiation in the coupled system is needed and is under development.

  15. Sea Ice Mapping using Unmanned Aerial Systems

    Science.gov (United States)

    Solbø, S.; Storvold, R.

    2011-12-01

    Mapping of sea ice extent and sea ice features is an important task in climate research. Since the arctic coastal and oceanic areas have a high probability of cloud coverage, aerial platforms are superior to satellite measurements for high-resolution optical measurements. However, routine observations of sea ice conditions present a variety of problems using conventional piloted aircrafts. Specially, the availability of suitable aircrafts for lease does not cover the demand in major parts of the arctic. With the recent advances in unmanned aerial systems (UAS), there is a high possibility of establishing routine, cost effective aerial observations of sea ice conditions in the near future. Unmanned aerial systems can carry a wide variety of sensors useful for characterizing sea-ice features. For instance, the CryoWing UAS, a system initially designed for measurements of the cryosphere, can be equipped with digital cameras, surface thermometers and laser altimeters for measuring freeboard of ice flows. In this work we will present results from recent CryoWing sea ice flights on Svalbard, Norway. The emphasis will be on data processing for stitching together images acquired with the non-stabilized camera payload, to form high-resolution mosaics covering large spatial areas. These data are being employed to map ice conditions; including ice and lead features and melt ponds. These high-resolution mosaics are also well suited for sea-ice mechanics, classification studies and for validation of satellite sea-ice products.

  16. First Results from the ASIBIA (Arctic Sea-Ice, snow, Biogeochemistry and Impacts on the Atmosphere) Sea-Ice Chamber

    Science.gov (United States)

    Frey, M. M.; France, J.; von Glasow, R.; Thomas, M.

    2015-12-01

    the coming years. The ASIBIA sea-ice facility is a key component of a 5-year ERC funded program with a long-term goal to develop parameterisations for local to global scale models based on experimental results.

  17. Improved method for sea ice age computation based on combination of sea ice drift and concentration

    Science.gov (United States)

    Korosov, Anton; Rampal, Pierre; Lavergne, Thomas; Aaboe, Signe

    2017-04-01

    Sea Ice Age is one of the components of the Sea Ice ECV as defined by the Global Climate Observing System (GCOS) [WMO, 2015]. It is an important climate indicator describing the sea ice state in addition to sea ice concentration (SIC) and thickness (SIT). The amount of old/thick ice in the Arctic Ocean has been decreasing dramatically [Perovich et al. 2015]. Kwok et al. [2009] reported significant decline in the MYI share and consequent loss of thickness and therefore volume. Today, there is only one acknowledged sea ice age climate data record [Tschudi, et al. 2015], based on Maslanik et al. [2011] provided by National Snow and Ice Data Center (NSIDC) [http://nsidc.org/data/docs/daac/nsidc0611-sea-ice-age/]. The sea ice age algorithm [Fowler et al., 2004] is using satellite-derived ice drift for Lagrangian tracking of individual ice parcels (12-km grid cells) defined by areas of sea ice concentration > 15% [Maslanik et al., 2011], i.e. sea ice extent, according to the NASA Team algorithm [Cavalieri et al., 1984]. This approach has several drawbacks. (1) Using sea ice extent instead of sea ice concentration leads to overestimation of the amount of older ice. (2) The individual ice parcels are not advected uniformly over (long) time. This leads to undersampling in areas of consistent ice divergence. (3) The end product grid cells are assigned the age of the oldest ice parcel within that cell, and the frequency distribution of the ice age is not taken into account. In addition, the base sea ice drift product (https://nsidc.org/data/docs/daac/nsidc0116_icemotion.gd.html) is known to exhibit greatly reduced accuracy during the summer season [Sumata et al 2014, Szanyi, 2016] as it only relies on a combination of sea ice drifter trajectories and wind-driven "free-drift" motion during summer. This results in a significant overestimate of old-ice content, incorrect shape of the old-ice pack, and lack of information about the ice age distribution within the grid cells. We

  18. Quantification of ikaite in Antarctic sea ice

    Directory of Open Access Journals (Sweden)

    M. Fischer

    2012-02-01

    Full Text Available Calcium carbonate precipitation in sea ice can increase pCO2 during precipitation in winter and decrease pCO2 during dissolution in spring. CaCO3 precipitation in sea ice is thought to potentially drive significant CO2 uptake by the ocean. However, little is known about the quantitative spatial and temporal distribution of CaCO3 within sea ice. This is the first quantitative study of hydrous calcium carbonate, as ikaite, in sea ice and discusses its potential significance for the carbon cycle in polar oceans. Ice cores and brine samples were collected from pack and land fast sea ice between September and December 2007 during an expedition in the East Antarctic and another off Terre Adélie, Antarctica. Samples were analysed for CaCO3, Salinity, DOC, DON, Phosphate, and total alkalinity. A relationship between the measured parameters and CaCO3 precipitation could not be observed. We found calcium carbonate, as ikaite, mostly in the top layer of sea ice with values up to 126 mg ikaite per liter melted sea ice. This potentially represents a contribution between 0.12 and 9 Tg C to the annual carbon flux in polar oceans. The horizontal distribution of ikaite in sea ice was heterogenous. We also found the precipitate in the snow on top of the sea ice.

  19. Arctic Landfast Sea Ice 1953-1998

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The files in this data set contain landfast sea ice data (monthly means) gathered from both Russian Arctic and Antarctic Research Institute (AARI) and Canadian Ice...

  20. Controls on Arctic sea ice from first-year and multi-year survival rates

    Energy Technology Data Exchange (ETDEWEB)

    Hunke, Jes [Los Alamos National Laboratory

    2009-01-01

    The recent decrease in Arctic sea ice cover has transpired with a significant loss of multi year 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 we develop a reduced model for Arctic sea ice with which we investigate how the survivability of first year and multi year ice control the mean state, variability, and trends in ice area and volume.

  1. Microwave signature of sea-ice for GCOM-W1/AMSR2

    Science.gov (United States)

    Naoki, K.; Nishio, F.; Yoshikawa, M.

    2011-12-01

    The lowest Arctic sea-ice cover has been recorded in September 2007. After that, though it has increased in 2008 and 2009, it has decreased again in 2010. The factor of the sea-ice change is researched in various fields. Monitoring of a thin sea-ice thickness is important as these researches because the sea-ice thickness has influences for the heat budget. However the retrieval of thin sea-ice thickness is difficult because thin sea-ice brightness temperature (TB) depends on the salinity and temperature, and there exist the snow over the thin sea-ice. In order to know the relationship between sea-ice TB and sea-ice parameters, we observed thin sea-ice TB using Polarimetric Scanning Radiometer (PSR) and measured ice thickness by ship. The effect of sea-ice parameters on the TB was examined by model. The brightness temperature of the thin sea-ice was observed using PSR on board an aircraft in the Okhotsk on February 7, 2003. The sea-ice thickness was measured from the icebreaker synchronizing with the aircraft. The TB calculated the variation at the sea-ice with/without of the snow, thickness, and the density of the snow. The calculated result was consistent with the observed one in the 18GHz-Hpol. We show the snow density influenced the increased brightness temperature.

  2. Impact of sea ice initialization on sea ice and atmosphere prediction skill on seasonal timescales

    Science.gov (United States)

    Guemas, V.; Chevallier, M.; Déqué, M.; Bellprat, O.; Doblas-Reyes, F.

    2016-04-01

    We present a robust assessment of the impact of sea ice initialization from reconstructions of the real state on the sea ice and atmosphere prediction skill. We ran two ensemble seasonal prediction experiments from 1979 to 2012 : one using realistic sea ice initial conditions and another where sea ice is initialized from a climatology, with two forecast systems. During the melting season in the Arctic Ocean, sea ice forecasts become skilful with sea ice initialization until 3-5 months ahead, thanks to the memory held by sea ice thickness. During the freezing season in both the Arctic and Antarctic Oceans, sea ice forecasts are skilful for 7 and 2 months, respectively, with negligible differences between the two experiments, the memory being held by the ocean heat content. A weak impact on the atmosphere prediction skill is obtained.

  3. Evaluation of the sea ice proxy IP against observational and diatom proxy data in the SW Labrador Sea

    DEFF Research Database (Denmark)

    Weckström, K.; Andersen, M.L.; Kuijpers, A.

    2013-01-01

    The recent rapid decline in Arctic sea ice cover has increased the need to improve the accuracy of the sea ice component in climate models and to provide detailed long-term sea ice concentration records, which are only available via proxy data. Recently, the highly branched isoprenoid IP25...... established sea ice proxy (sea ice diatom abundance in sediments) in the South-West (SW) Labrador Sea. Furthermore, our study location at the southern margin of Arctic sea ice drift provided a new environmental setting in which to further test the novel PIP25 index. Our two study sites are located North......-East (NE) and South-East (SE) of Newfoundland where box cores covering the last ca 100-150 years were collected. IP25 concentrations are nearly an order of magnitude higher and sea ice diatoms more abundant in sediments from NE of Newfoundland, where sea ice prevails 2-4 months per year compared...

  4. The microwave scattering characteristics of sea ice in the Bohai Sea

    Institute of Scientific and Technical Information of China (English)

    LIU Meijie; DAI Yongshou; ZHANG Jie; ZHANG Xi; MENG Junmin; ZHU Xiuqin; YIN Yalei

    2016-01-01

    Microwave remote sensing has become the primary means for sea-ice research, and has been supported by a great deal of field experiments and theoretical studies regarding sea-ice microwave scattering. However, these studies have been barely carried in the Bohai Sea. The sea-ice microwave scattering mechanism was first developed for the thin sea ice with slight roughness in the Bohai Sea in the winter of 2012, and included the backscattering coefficients which were measured on the different conditions of three bands (L, C and X), two polarizations (HH and VV), and incident angles of 20° to 60°, using a ground-based scatterometer and the synchronous physical parameters of the sea-ice temperature, density, thickness, salinity, and so on. The theoretical model of the sea-ice electromagnetic scattering is obtained based on these physical parameters. The research regarding the sea-ice microwave scattering mechanism is carried out through two means, which includes the comparison between the field microwave scattering data and the simulation results of the theoretical model, as well as the feature analysis of the four components of the sea-ice electromagnetic scattering. It is revealed that the sea-ice microwave scattering data and the theoretical simulation results vary in the same trend with the incident angles. Also, there is a visible variant in the sensitivity of every component to the different bands. For example, the C and X bands are sensitive to the top surface, the X band is sensitive to the scatterers, and the L and C bands are sensitive to the bottom surface, and so on. It is suggested that the features of the sea-ice surfaces and scatterers can be retrieved by the further research in the future. This experiment can provide an experimental and theoretical foundation for research regarding the sea-ice microwave scattering characteristics in the Bohai Sea.

  5. An improved bathymetry compilation for the Bellingshausen Sea, Antarctica, to inform ice-sheet and ocean models

    Directory of Open Access Journals (Sweden)

    A. G. C. Graham

    2011-02-01

    Full Text Available The southern Bellingshausen Sea (SBS is a rapidly-changing part of West Antarctica, where oceanic and atmospheric warming has led to the recent basal melting and break-up of the Wilkins ice shelf, the dynamic thinning of fringing glaciers, and sea-ice reduction. Accurate sea-floor morphology is vital for understanding the continued effects of each process upon changes within Antarctica's ice sheets. Here we present a new bathymetric grid for the SBS compiled from shipborne multibeam echo-sounder, spot-sounding and sub-ice measurements. The 1-km grid is the most detailed compilation for the SBS to-date, revealing large cross-shelf troughs, shallow banks, and deep inner-shelf basins that continue inland of coastal ice shelves. The troughs now serve as pathways which allow warm deep water to access the ice sheet in the SBS. Our dataset highlights areas still lacking bathymetric constraint, as well as regions for further investigation, including the likely routes of palaeo-ice streams. The new compilation is a major improvement upon previous grids and will be a key dataset for incorporating into simulations of ocean circulation, ice-sheet change and history. It will also serve forecasts of ice stability and future sea-level contributions from ice loss in West Antarctica, required for the next IPCC assessment report in 2013.

  6. An improved bathymetry compilation for the Bellingshausen Sea, Antarctica, to inform ice-sheet and ocean models

    Directory of Open Access Journals (Sweden)

    A. G. C. Graham

    2010-10-01

    Full Text Available The southern Bellingshausen Sea (SBS is a rapidly-changing part of West Antarctica, where oceanic and atmospheric warming has led to the recent basal melting and break-up of the Wilkins ice shelf, the dynamic thinning of fringing glaciers, and sea-ice reduction. Accurate sea-floor morphology is vital for understanding the continued effects of each process upon changes within Antarctica's ice sheets. Here we present a new bathymetric grid for the SBS compiled from shipborne echo-sounder, spot-sounding and sub-ice measurements. The 1-km grid is the most detailed compilation for the SBS to-date, revealing large cross-shelf troughs, shallow banks, and deep inner-shelf basins that continue inland of coastal ice shelves. The troughs now serve as pathways which allow warm deep water to access the ice fronts in the SBS. Our dataset highlights areas still lacking bathymetric constraint, as well as regions for further investigation, including the likely routes of palaeo-ice streams. The new compilation is a major improvement upon previous grids and will be a key dataset for incorporating into simulations of ocean circulation, ice-sheet change and history. It will also serve forecasts of ice stability and future sea-level contributions from ice loss in West Antarctica, required for the next IPCC assessment report in 2013.

  7. Sea Ice Thickness, Freeboard, and Snow Depth products from Operation IceBridge Airborne Data

    Science.gov (United States)

    Kurtz, N. T.; Farrell, S. L.; Studinger, M.; Galin, N.; Harbeck, J. P.; Lindsay, R.; Onana, V. D.; Panzer, B.; Sonntag, J. G.

    2013-01-01

    The study of sea ice using airborne remote sensing platforms provides unique capabilities to measure a wide variety of sea ice properties. These measurements are useful for a variety of topics including model evaluation and improvement, assessment of satellite retrievals, and incorporation into climate data records for analysis of interannual variability and long-term trends in sea ice properties. In this paper we describe methods for the retrieval of sea ice thickness, freeboard, and snow depth using data from a multisensor suite of instruments on NASA's Operation IceBridge airborne campaign. We assess the consistency of the results through comparison with independent data sets that demonstrate that the IceBridge products are capable of providing a reliable record of snow depth and sea ice thickness. We explore the impact of inter-campaign instrument changes and associated algorithm adaptations as well as the applicability of the adapted algorithms to the ongoing IceBridge mission. The uncertainties associated with the retrieval methods are determined and placed in the context of their impact on the retrieved sea ice thickness. Lastly, we present results for the 2009 and 2010 IceBridge campaigns, which are currently available in product form via the National Snow and Ice Data Center

  8. Variability and Trends in Sea Ice Extent and Ice Production in the Ross Sea

    Science.gov (United States)

    Comiso, Josefino; Kwok, Ronald; Martin, Seelye; Gordon, Arnold L.

    2011-01-01

    Salt release during sea ice formation in the Ross Sea coastal regions is regarded as a primary forcing for the regional generation of Antarctic Bottom Water. Passive microwave data from November 1978 through 2008 are used to examine the detailed seasonal and interannual characteristics of the sea ice cover of the Ross Sea and the adjacent Bellingshausen and Amundsen seas. For this period the sea ice extent in the Ross Sea shows the greatest increase of all the Antarctic seas. Variability in the ice cover in these regions is linked to changes in the Southern Annular Mode and secondarily to the Antarctic Circumpolar Wave. Over the Ross Sea shelf, analysis of sea ice drift data from 1992 to 2008 yields a positive rate of increase in the net ice export of about 30,000 sq km/yr. For a characteristic ice thickness of 0.6 m, this yields a volume transport of about 20 cu km/yr, which is almost identical, within error bars, to our estimate of the trend in ice production. The increase in brine rejection in the Ross Shelf Polynya associated with the estimated increase with the ice production, however, is not consistent with the reported Ross Sea salinity decrease. The locally generated sea ice enhancement of Ross Sea salinity may be offset by an increase of relatively low salinity of the water advected into the region from the Amundsen Sea, a consequence of increased precipitation and regional glacial ice melt.

  9. The impact of the Arctic Sea Ice retreat on extratropical cyclones and anticyclones over Northern Eurasia: atmospheric model simulations

    Science.gov (United States)

    Akperov, Mirseid; Semenov, Vladimir; Mokhov, Igor; Lupo, Antony

    2015-04-01

    The Arctic region has been warming more than twice as fast as the other parts of the world during the last few decades. The rapid Arctic warming is accompanied with the dramatic change of Arctic sea ice cover. Recently, it has been suggested that such climatic changes might have led to the increase of anomalous weather events in winter over Northern Eurasia. One example is anomalous cold winters over Northern Eurasia associated with atmospheric blocking events. However, a large uncertainty remains concerning robustness of the observed relationship and associated mechanisms of impact. The main goal of this research is to explore the connection between the declining Arctic sea ice (most strongly expressed in the Barents-Kara Seas region) in the cold season and the change of cyclonic and anti-cyclonic activity over Northern Eurasia using simulations with atmospheric general circulation model (AGCM). The simulations were performed with the ECHAM5 AGCM using identical sea surface temperature climatology but different sea ice concentrations (SIC) for the periods corresponding to the high (1966-1969), low (1990-1995) and very low (2005-2012) SIC regimes in the Arctic as well as for the mean climatological SIC for 1971-2000. The duration of each simulation was 50 years. For the regimes with high and very low SIC, a statistically significant increase in the number of long-living anticyclones (with lifetime of more than 5 days) over Northern Eurasia was found. Long-living cyclones exhibited different changes in their number depending on their intensity. The analysis of the spatial patterns of cyclonic and anti-cyclonic activity over Eurasia was performed. We found an increase of the frequency of cyclones over the central region of the European part of Russia (EPR) and anticyclones over the northern region of the EPR for the regimes with a high sea ice concentration in the Arctic. For the regime with very low SIC the shift of the frequency of cyclones and anticyclones towards

  10. Modelling radiative transfer through ponded first-year Arctic sea ice with a plane-parallel model

    Directory of Open Access Journals (Sweden)

    T. Taskjelle

    2017-09-01

    Full Text Available Under-ice irradiance measurements were done on ponded first-year pack ice along three transects during the ICE12 expedition north of Svalbard. Bulk transmittances (400–900 nm were found to be on average 0.15–0.20 under bare ice, and 0.39–0.46 under ponded ice. Radiative transfer modelling was done with a plane-parallel model. While simulated transmittances deviate significantly from measured transmittances close to the edge of ponds, spatially averaged bulk transmittances agree well. That is, transect-average bulk transmittances, calculated using typical simulated transmittances for ponded and bare ice weighted by the fractional coverage of the two surface types, are in good agreement with the measured values. Radiative heating rates calculated from model output indicates that about 20 % of the incident solar energy is absorbed in bare ice, and 50 % in ponded ice (35 % in pond itself, 15 % in the underlying ice. This large difference is due to the highly scattering surface scattering layer (SSL increasing the albedo of the bare ice.

  11. SMOS sea ice product: Operational application and validation in the Barents Sea marginal ice zone

    DEFF Research Database (Denmark)

    Kaleschke, Lars; Tian-Kunze, Xiangshan; Maaß, Nina

    2016-01-01

    Brightness temperatures at 1.4. GHz (L-band) measured by the Soil Moisture and Ocean Salinity (SMOS) Mission have been used to derive the thickness of sea ice. The retrieval method is applicable only for relatively thin ice and not during the melting period. Hitherto, the availability of ground...... truth sea ice thickness measurements for validation of SMOS sea ice products was mainly limited to relatively thick ice. The situation has improved with an extensive field campaign in the Barents Sea during an anomalous ice edge retreat and subsequent freeze-up event in March 2014. A sea ice forecast...... system for ship route optimisation has been developed and was tested during this field campaign with the ice-strengthened research vessel RV Lance. The ship cruise was complemented with coordinated measurements from a helicopter and the research aircraft Polar 5. Sea ice thickness was measured using...

  12. On large outflows of Arctic sea ice into the Barents Sea

    Science.gov (United States)

    Kwok, Ron; Maslowski, Wieslaw; Laxon, Seymour W.

    2005-01-01

    Winter outflows of Arctic sea ice into the Barents Sea are estimated using a 10-year record of satellite ice motion and thickness. The mean winter volume export through the Svalbard/Franz Josef Land passage is 40 km3, and ranges from -280 km3 to 340 km3. A large outflow in 2003 is preconditioned by an unusually high concentration of thick perennial ice over the Nansen Basin at the end of the 2002 summer. With a deep atmospheric low situated over the eastern Barents Sea in winter, the result is an increased export of Arctic ice. The Oct-Mar ice area flux, at 110 x 10 to the third power km3, is not only unusual in magnitude but also remarkable in that >70% of the area is multiyear ice; the ice volume flux at340 km3 is almost one-fifth of the ice flux through the Fram Strait. Another large outflow of Arctic sea ice through this passage, comparable to that in 2003, is found in 1996. This southward flux of sea ice represents one of two major sources of freshwater in the Barents Sea; the other is the eastward flux of water via the Norwegian Coastal Current. The possible consequences of variable freshwater input on the Barents Sea hydrography and its impact on transformation of Atlantic Water en route to the Arctic Ocean are examined with a 25-year coupled ice-ocean model.

  13. Skill improvement of dynamical seasonal Arctic sea ice forecasts

    Science.gov (United States)

    Krikken, Folmer; Schmeits, Maurice; Vlot, Willem; Guemas, Virginie; Hazeleger, Wilco

    2016-05-01

    We explore the error and improve the skill of the outcome from dynamical seasonal Arctic sea ice reforecasts using different bias correction and ensemble calibration methods. These reforecasts consist of a five-member ensemble from 1979 to 2012 using the general circulation model EC-Earth. The raw model reforecasts show large biases in Arctic sea ice area, mainly due to a differently simulated seasonal cycle and long term trend compared to observations. This translates very quickly (1-3 months) into large biases. We find that (heteroscedastic) extended logistic regressions are viable ensemble calibration methods, as the forecast skill is improved compared to standard bias correction methods. Analysis of regional skill of Arctic sea ice shows that the Northeast Passage and the Kara and Barents Sea are most predictable. These results show the importance of reducing model error and the potential for ensemble calibration in improving skill of seasonal forecasts of Arctic sea ice.

  14. On the characteristics of sea ice divergence/convergence in the Southern Beaufort Sea

    Directory of Open Access Journals (Sweden)

    J. V. Lukovich

    2014-07-01

    Full Text Available An understanding of spatial gradients in sea ice motion, or deformation, is essential to understanding of ocean-sea-ice-atmosphere interactions and realistic representations of sea ice in models used for the purposes of prediction. This is particularly true for the southern Beaufort Sea, where significant offshore hydrocarbon resource development increases the risk of oil and other contaminants dispersing into the marginal ice zone. In this study, sea ice deformation is examined through evaluation of ice beacon triplets from September to November 2009 in the southern Beaufort Sea (SBS, defined according to distance from the coastline on deployment. Results from this analysis illustrate that ice beacon triplets in the SBS demonstrate spatiotemporal differences in their evolution at the periphery and interior of the ice pack. The time rate of change in triplet area highlights two intervals of enhanced divergence and convergence in fall, 2009. Investigation of sea ice and atmospheric conditions during these intervals shows that until mid-September, all triplets respond to northerly flow, while during the second interval of enhanced divergence/convergence in October only one triplet responds to persistent northeasterly flow due to its proximity to the ice edge, in contrast to triplets located at the interior of the pack. Differences in sea ice deformation and dispersion near the pack ice edge and interior are further demonstrated in the behavior of triplets B and C in late October/early November. The results from this analysis highlight differences in dispersion and deformation characteristics based on triplet proximity to the southernmost ice edge and coastline, with implications for modeling studies pertaining to sea ice dynamics and dispersion.

  15. Multisensor Analyzed Sea Ice Extent - Northern Hemisphere (MASIE-NH)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Multisensor Analyzed Sea Ice Extent Northern Hemisphere (MASIE-NH) products provide measurements of daily sea ice extent and sea ice edge boundary for the...

  16. Global warming releases microplastic legacy frozen in Arctic Sea ice

    Science.gov (United States)

    Obbard, Rachel W.; Sadri, Saeed; Wong, Ying Qi; Khitun, Alexandra A.; Baker, Ian; Thompson, Richard C.

    2014-06-01

    When sea ice forms it scavenges and concentrates particulates from the water column, which then become trapped until the ice melts. In recent years, melting has led to record lows in Arctic Sea ice extent, the most recent in September 2012. Global climate models, such as that of Gregory et al. (2002), suggest that the decline in Arctic Sea ice volume (3.4% per decade) will actually exceed the decline in sea ice extent, something that Laxon et al. (2013) have shown supported by satellite data. The extent to which melting ice could release anthropogenic particulates back to the open ocean has not yet been examined. Here we show that Arctic Sea ice from remote locations contains concentrations of microplastics at least two orders of magnitude greater than those that have been previously reported in highly contaminated surface waters, such as those of the Pacific Gyre. Our findings indicate that microplastics have accumulated far from population centers and that polar sea ice represents a major historic global sink of man-made particulates. The potential for substantial quantities of legacy microplastic contamination to be released to the ocean as the ice melts therefore needs to be evaluated, as do the physical and toxicological effects of plastics on marine life.

  17. Physically-based Ice Thickness and Surface Roughness Retrievals over Rough Deformed Sea Ice

    Science.gov (United States)

    Li, Li; Gaiser, Peter; Allard, Richard; Posey, Pamela; Hebert, David; Richter-Menge, Jacqueline; Polashenski, Christopher; Claffey, Keran

    2016-04-01

    The observations of sea ice thickness and ice surface roughness are critical for our understanding of the state of the changing Arctic. Currently, the Radar and/or LiDAR data of sea ice freeboard are used to infer sea ice thickness via isostasy. The underlying assumption is that the LiDAR signal returns at the air/snow interface and radar signal at the snow/ice interface. The elevations of these interfaces are determined based on LiDAR/Radar return waveforms. However, the commonly used threshold-based surface detection techniques are empirical in nature and work well only over level/smooth sea ice. Rough sea ice surfaces can modify the return waveforms, resulting in significant Electromagnetic (EM) bias in the estimated surface elevations, and thus large errors in the ice thickness retrievals. To understand and quantify such sea ice surface roughness effects, a combined EM rough surface and volume scattering model was developed to simulate radar returns from the rough sea ice 'layer cake' structure. A waveform matching technique was also developed to fit observed waveforms to a physically-based waveform model and subsequently correct the roughness induced EM bias in the estimated freeboard. This new EM Bias Corrected (EMBC) algorithm was able to better retrieve surface elevations and estimate the surface roughness parameter simultaneously. Both the ice thickness and surface roughness retrievals are validated using in-situ data. For the surface roughness retrievals, we applied this EMBC algorithm to co-incident LiDAR/Radar measurements collected during a Cryosat-2 under-flight by the NASA IceBridge missions. Results show that not only does the waveform model fit very well to the measured radar waveform, but also the roughness parameters derived independently from the LiDAR and radar data agree very well for both level and deformed sea ice. For sea ice thickness retrievals, validation based on in-situ data from the coordinated CRREL/NRL field campaign demonstrates

  18. Remote sensing of sea ice: advances during the DAMOCLES project

    Directory of Open Access Journals (Sweden)

    G. Heygster

    2012-12-01

    Full Text Available In the Arctic, global warming is particularly pronounced so that we need to monitor its development continuously. On the other hand, the vast and hostile conditions make in situ observation difficult, so that available satellite observations should be exploited in the best possible way to extract geophysical information. Here, we give a résumé of the sea ice remote sensing efforts of the European Union's (EU project DAMOCLES (Developing Arctic Modeling and Observing Capabilities for Long-term Environmental Studies. In order to better understand the seasonal variation of the microwave emission of sea ice observed from space, the monthly variations of the microwave emissivity of first-year and multi-year sea ice have been derived for the frequencies of the microwave imagers like AMSR-E (Advanced Microwave Scanning Radiometer on EOS and sounding frequencies of AMSU (Advanced Microwave Sounding Unit, and have been used to develop an optimal estimation method to retrieve sea ice and atmospheric parameters simultaneously. In addition, a sea ice microwave emissivity model has been used together with a thermodynamic model to establish relations between the emissivities from 6 GHz to 50 GHz. At the latter frequency, the emissivity is needed for assimilation into atmospheric circulation models, but is more difficult to observe directly. The size of the snow grains on top of the sea ice influences both its albedo and the microwave emission. A method to determine the effective size of the snow grains from observations in the visible range (MODIS is developed and demonstrated in an application on the Ross ice shelf. The bidirectional reflectivity distribution function (BRDF of snow, which is an essential input parameter to the retrieval, has been measured in situ on Svalbard during the DAMOCLES campaign, and a BRDF model assuming aspherical particles is developed. Sea ice drift and deformation is derived from satellite observations with the scatterometer

  19. On using numerical sea-ice prediction and indigenous observations to improve operational sea-ice forecasts during spring in the bering sea

    Science.gov (United States)

    Deemer, Gregory Joseph

    Impacts of a rapidly changing climate are amplified in the Arctic. The most notorious change has come in the form of record-breaking summertime sea-ice retreat. Larger areas of open water and a prolonged ice-free season create opportunity for some industries, but bring new challenges to indigenous populations that rely on sea-ice cover for subsistence. Observed and projected increases in maritime activities require accurate sea-ice forecasts on the weather timescale, which are currently lacking. Motivated by this need, this study explores how new modeling developments and local-scale observations can contribute to improving sea-ice forecasts. The Arctic Cap Nowcast/Forecast System, a research sea-ice forecast model developed by the U.S. Navy, is evaluated for forecast skill. Forecasts of ice concentration, thickness, and drift speed produced by the model from April through June 2011 in the Bering Sea were investigated to determine how the model performs relative to persistence and climatology. Results show that model forecasts can outperform forecasts based on climatology or persistence. However, predictive skill is less consistent during powerful, synoptic-scale events and near the Bering Slope. Forecast case studies in Western Alaska were presented. Community-based observations from recognized indigenous sea-ice experts have been analyzed to gauge the prospect of using local observations in the operational sea-ice monitoring and prediction process. Local observations were discussed in the context of cross-validating model guidance, data sources used in operational ice monitoring, and public sea-ice information products issued by the U.S. National Weather Service. Instrumentation for observing sea-ice and weather at the local scale was supplied to key observers. The instrumentation shows utility in the field and may help translate the context of indigenous observations and provide ground-truth data for use by forecasters.

  20. Measurement of sea ice and icebergs topography using satellite imagery

    Science.gov (United States)

    Zakharov, I.; Power, D.; Prasad, S.

    2016-12-01

    Sea ice topography represents geospatial information on the three-dimensional geometrical attributes of the ice surface including height and shape of various ice features. The features interest consist of deformed (pressure ridges, rubbles and hummocks) and level sea ice as well as glacial ice. Sea ice topography is important for scientific research and climate studies because it helps characterise ice volume and thickness and it influences the near-surface atmospheric transport by impacting the drag coefficients. It also represents critical information to marine operational applications, such as ships navigation and risks assessment for offshore infrastructures. The several methods were used to measure sea ice topography from a single satellite image as well as multiple images. The techniques based on the single image, acquired by optical or synthetic aperture radar (SAR) satellites, derive the height and shape information from shadow and shading. Optical stereo images acquired by very high resolution (0.5 m) satellites were used to extract highly detailed digital elevation model (DEM). SAR imagery allowed extraction of DEM using stereo-radargrammetry and interferometry. The images from optical satellites WorldView, Pleiades, GeoEye, Spot, and Landsat-8 were used to measure topography of sea ice deformation features and glacial ice including icebergs and ice islands. These features were mapped in regions of the Central Arctic, Baffin Bay and the coast of Greenland. SAR imagery including interferometric TanDEM-X data and full polarimetric Radarsat-2 were used to extract ridge frequency and measure spatial parameters of glacial features. The accuracy was evaluated by comparison of the results from different methods demonstrating their strengths and limitations. Ridge height and frequency were also compared with the high resolution results from the Los Alamos sea ice model (CICE), regionally implemented for Baffin Bay and the Labrador Sea.

  1. Sea ice growth rates from tide-driven visible banding

    Science.gov (United States)

    Turner, Kate E.; Smith, Inga J.; Tison, Jean-Louis; Verbeke, Véronique; McGuinness, Mark; Ingham, Malcolm; Vennell, Ross; Trodahl, Joe

    2017-06-01

    In this paper, periodic tide-current-driven banding in a sea-ice core is demonstrated as a measure of the growth rate of first-year sea ice at congelation-ice depths. The study was performed on a core from the eastern McMurdo Sound, exploiting the well-characterized tidal pattern at the site. It points the way to a technique for determining early-season ice growth rates from late-season cores, in areas where under ice currents are known to be tidally dominated and the ice is landfast, thus providing data for a time of year when thin ice prevents direct thickness (and therefore growth rate) measurements. The measured results were compared to the growth-versus-depth predicted by a thermodynamic model.Plain Language SummaryIt is currently very difficult to measure sea-ice growth rates, due to the danger of traveling on thin ice early in the growing season. This paper introduces the use of tidal patterns to determine sea-ice growth rates at the end of the growing season, when ice cores can be taken. The technique utilizes the visible light and dark bands that are often present in sea ice near land, and are driven by changes in the tidal current beneath the ice. As well as being important for climate research, this method could contribute to the understanding biological ecosystems within the ice, by providing a method to date depths in an ice core where particular organisms are observed or samples taken.

  2. Estimating Greenland ice sheet surface mass balance contribution to future sea level rise using the regional atmospheric climate model MAR

    Directory of Open Access Journals (Sweden)

    X. Fettweis

    2012-08-01

    Full Text Available We report future projections of Surface Mass Balance (SMB over the Greenland ice sheet (GrIS obtained with the regional climate model MAR, forced by the outputs of three CMIP5 General Circulation Models (GCMs when considering two different warming scenarios (RCP 4.5 and RCP 8.5. The GCMs selected in this study have been chosen according to their ability to simulate the current climate over Greenland. Our results indicate that in a warmer climate (i the mass gained due to increased precipitation over GrIS does not compensate the mass lost through increased run-off; (ii the surface melt increases non-linearly with rising temperatures due to the positive feedback between surface albedo and melt, associated with the expansion of bare ice zones which, in addition, decreases the ice sheet refreezing capacity; (iii most of the precipitation is expected to fall as rainfall in summer, which further increases surface melt; (iv no considerable change is expected on the length of the melting season, since heavier winter snowfall dampens the melt increase at the end of spring; (v the increase of meltwater run-off versus temperature anomalies is dependent of the GCM-forced MAR ability to simulate the current climate; (vi the MAR-simulated SMB changes can be approximated using the annual accumulated snowfall and summer 600 hPa temperature increase simulated by the forcing GCMs. In view of the large range in the CMIP5 future projections for the same future scenario, the GCM-based SMB approximations allow us to estimate what future projections are most likely within the CMIP5 multi-model ensemble. In 2100, the ensemble mean projects a sea level rise, resulting from a GrIS SMB decrease, estimated to be +4 ± 2 cm and +9 ± 4 cm for the RCP 4.5 and RCP 8.5 scenarios, respectively. The GrIS SMB should remain positive with respect to RCP 4.5 scenario and becomes negative around 2070 in the case of the RCP 8.5 scenario since a global warming >+3 °C is needed

  3. Linking the northern hemisphere sea-ice reduction trend and the quasi-decadal arctic sea-ice oscillation

    Energy Technology Data Exchange (ETDEWEB)

    Wang, J. [University of Alaska Fairbanks, International Arctic Research Center, Alaska (United States); Ikeda, M. [Hokkaido University, Graduate School of Environmental Earth Science, Sapporo (Japan); Zhang, S. [University of Alaska Fairbanks Fairbanks, Department of Mathematical Sciences, Alaska (United States); Gerdes, R. [Alfred-Wegener Institute for Polar Research, Bremerhaven (Germany)

    2005-02-01

    The nature of the reduction trend and quasi-decadal oscillation in Northern Hemisphere sea-ice extent is investigated. The trend and oscillation that seem to be two separate phenomena have been found in data. This study examines a hypothesis that the Arctic sea-ice reduction trend in the last three decades amplified the quasi-decadal Arctic sea-ice oscillation (ASIO) due to a positive ice/ocean-albedo feedback, based on data analysis and a conceptual model proposed by Ikeda et al. The theoretical, conceptual model predicts that the quasi-decadal oscillation is amplified by the thinning sea-ice, leading to the ASIO, which is driven by the strong positive feedback between the atmosphere and ice-ocean systems. Such oscillation is predicted to be out-of-phase between the Arctic Basin and the Nordic Seas with a phase difference of 3{pi}/4, with the Nordic Seas leading the Arctic. The wavelet analysis of the sea ice data reveals that the quasi-decadal ASIO occurred actively since the 1970s following the trend starting in the 1960s (i.e., as sea-ice became thinner and thinner), as the atmosphere experienced quasi-decadal oscillations during the last century. The wavelet analysis also confirms the prediction of such out-of-phase feature between these two basins, which varied from 0.62{pi} in 1960 to 0.25{pi} in 1995. Furthermore, a coupled ice-ocean general circulation model (GCM) was used to simulate two scenarios, one without the greenhouse gas warming and the other having realistic atmospheric forcing along with the warming that leads to sea-ice reduction trend. The quasi-decadal ASIO is excited in the latter case compared to the no-warming case. The wavelet analyses of the simulated ice volume were also conducted to derive decadal ASIO and similar phase relationship between the Arctic Ocean and the Nordic Seas. An independent data source was used to confirm such decadal oscillation in the upper layer (or freshwater) thickness, which is consistent with the model

  4. Greenland Ice Sheet response to mid-Pliocene summer Arctic sea ice-free conditions

    Science.gov (United States)

    Koenig, S. J.; DeConto, R.; Pollard, D.

    2011-12-01

    A critical uncertainty in future predictions of climate and sea level is the response of the cryosphere. Proxy reconstructions for the mid-Pliocene Arctic Ocean (~ 3 Ma) are indicative of summer Arctic ice-free conditions and higher than modern sea surface temperatures, conditions that are analogous to projections for the end of the 21st century. We implement available mid-Pliocene boundary conditions into a fully-coupled Global Circulation Model with interactive vegetation. We use a 3-D thermo-mechanical ice sheet-shelf model to simulate the equilibrated response of the Greenland Ice Sheet (GIS) to the combined effect of reduced sea ice conditions and increased sea surface temperatures during the mid-Pliocene Warm Period. Reductions in Arctic sea ice are shown to enhance ocean/land-to-atmosphere fluxes, increasing heat and moisture transport in the high latitudes. In particular, changes in the North Atlantic exert a strong influence on the storm track and seasonal temperatures and precipitation over Greenland. Despite increased precipitation, warmer temperatures generally reduce snow mass balance. As a result, an initial present-day ice sheet forced by Pliocene climate undergoes rapid melting, limiting the ice sheet to the only highest elevations in South and East Greenland. Once the ice sheet is lost, local surface characteristics and associated feedbacks dominates Greenland climate, precluding the regrowth of the ice sheet. Depending on the initial state of the ice sheet, the equilibrated ice sheet loss is equivalent to between 5.8 to 6.4 m of sea level. We assess the sensitivity of the GIS to Pliocene forcing and internal feedbacks, adding to the understanding of land-ice sea-ice hysteresis in a world warmer than today.

  5. Fram Strait Spring Ice Export and September Arctic Sea Ice

    Science.gov (United States)

    Smedsrud, Lars H.; Halvorsen, Mari H.; Stroeve, Julienne; Zhang, Rong; Kloster, Kjell

    2016-04-01

    The Arctic Basin exports between 600 000 - 1 million km² of it's sea ice cover southwards through Fram Strait each year, comparing to about 10% of the ice covered area inside the basin. During winter ice export results in growth of new and relatively thin ice inside the basin, while during summer or spring export contributes directly to open water further north. A new updated time series from 1935 to 2014 of Fram Strait sea ice area export shows that the long-term annual mean export is about 880,000 km², with large annual and decadal variability and no long-term trend over the past 80 years. Nevertheless, the last decade has witnessed increased annual ice export, with several years having annual ice export exceed 1 million km². Evaluating the trend onwards from 1979, when satellite based sea ice coverage became more readily available, reveals an increase in annual export of about +6% per decade. This increase is caused by higher southward ice drift speeds due to stronger southward geostrophic winds, largely explained by increasing surface pressure over Greenland. Spring and summer area export increased more (+11% per decade) than in autumn and winter. Contrary to the last decade the 1950 - 1970 period had low export during spring and summer, and mid-September sea ice extent was consistently higher than both before and after these decades. We thus find that export anomalies during spring have a clear influence on the following September sea ice extent in general, and that for the recent decade the export may be partially responsible for the accelerating decline in Arctic sea ice extent.

  6. Albedo parametrization and reversibility of sea ice decay

    Science.gov (United States)

    Müller-Stoffels, M.; Wackerbauer, R.

    2012-02-01

    The Arctic's sea ice cover has been receding rapidly in recent years, and global climate models typically predict a further decline over the next century. It is an open question whether a possible loss of Arctic sea ice is reversible. We study the stability of Arctic model sea ice in a conceptual, two-dimensional energy-based regular network model of the ice-ocean layer that considers ARM's longwave radiative budget data and SHEBA albedo measurements. Seasonal ice cover, perennial ice and perennial open water are asymptotic states accessible by the model. We show that the shape of albedo parameterization near the melting temperature differentiates between reversible continuous sea ice decrease under atmospheric forcing and hysteresis behavior. Fixed points induced solely by the surface energy budget are essential for understanding the interaction of surface energy with the radiative forcing and the underlying body of ice/water, particularly close to a bifurcation point. Future studies will explore ice edge stability and reversibility in this lattice model, generalized to a latitudinal transect with spatiotemporal lateral atmospheric heat transfer and high spatial resolution.

  7. Albedo parametrization and reversibility of sea ice decay

    Directory of Open Access Journals (Sweden)

    M. Müller-Stoffels

    2012-02-01

    Full Text Available The Arctic's sea ice cover has been receding rapidly in recent years, and global climate models typically predict a further decline over the next century. It is an open question whether a possible loss of Arctic sea ice is reversible. We study the stability of Arctic model sea ice in a conceptual, two-dimensional energy-based regular network model of the ice-ocean layer that considers ARM's longwave radiative budget data and SHEBA albedo measurements. Seasonal ice cover, perennial ice and perennial open water are asymptotic states accessible by the model. We show that the shape of albedo parameterization near the melting temperature differentiates between reversible continuous sea ice decrease under atmospheric forcing and hysteresis behavior. Fixed points induced solely by the surface energy budget are essential for understanding the interaction of surface energy with the radiative forcing and the underlying body of ice/water, particularly close to a bifurcation point. Future studies will explore ice edge stability and reversibility in this lattice model, generalized to a latitudinal transect with spatiotemporal lateral atmospheric heat transfer and high spatial resolution.

  8. Observations of Recent Arctic Sea Ice Volume Loss and Its Impact on Ocean-Atmosphere Energy Exchange and Ice Production

    Science.gov (United States)

    Kurtz, N. T.; Markus, T.; Farrell, S. L.; Worthen, D. L.; Boisvert, L. N.

    2011-01-01

    Using recently developed techniques we estimate snow and sea ice thickness distributions for the Arctic basin through the combination of freeboard data from the Ice, Cloud, and land Elevation Satellite (ICESat) and a snow depth model. These data are used with meteorological data and a thermodynamic sea ice model to calculate ocean-atmosphere heat exchange and ice volume production during the 2003-2008 fall and winter seasons. The calculated heat fluxes and ice growth rates are in agreement with previous observations over multiyear ice. In this study, we calculate heat fluxes and ice growth rates for the full distribution of ice thicknesses covering the Arctic basin and determine the impact of ice thickness change on the calculated values. Thinning of the sea ice is observed which greatly increases the 2005-2007 fall period ocean-atmosphere heat fluxes compared to those observed in 2003. Although there was also a decline in sea ice thickness for the winter periods, the winter time heat flux was found to be less impacted by the observed changes in ice thickness. A large increase in the net Arctic ocean-atmosphere heat output is also observed in the fall periods due to changes in the areal coverage of sea ice. The anomalously low sea ice coverage in 2007 led to a net ocean-atmosphere heat output approximately 3 times greater than was observed in previous years and suggests that sea ice losses are now playing a role in increasing surface air temperatures in the Arctic.

  9. On the measure of sea ice area from sea ice concentration data sets

    Science.gov (United States)

    Boccolari, Mauro; Parmiggiani, Flavio

    2015-10-01

    The measure of sea ice surface variability provides a fundamental information on the climatology of the Arctic region. Sea ice extension is conventionally measured by two parameters, i.e. Sea Ice Extent (SIE) and Sea Ice Area (SIA), both parameters being derived from Sea Ice Concentration (SIC) data sets. In this work a new parameter (CSIA) is introduced, which takes into account only the compact sea-ice, which is defined as the sea-ice having concentration at least equal the 70%. Aim of this study is to compare the performances of the two parameters, SIA and CSIA, in analyzing the trends of three monthly time-series of the whole Arctic region. The SIC data set used in this study was produced by the Institute of Environmental Physics of the University of Bremen and covers the period January 2003 - December 2014, i.e. the period in which the data set is built using the new AMSR passive microwave sensor.

  10. Ice–ocean coupled computations for sea-ice prediction to support ice navigation in Arctic sea routes

    Directory of Open Access Journals (Sweden)

    Liyanarachchi Waruna Arampath De Silva

    2015-11-01

    Full Text Available With the recent rapid decrease in summer sea ice in the Arctic Ocean extending the navigation period in the Arctic sea routes (ASR, the precise prediction of ice distribution is crucial for safe and efficient navigation in the Arctic Ocean. In general, however, most of the available numerical models have exhibited significant uncertainties in short-term and narrow-area predictions, especially in marginal ice zones such as the ASR. In this study, we predict short-term sea-ice conditions in the ASR by using a mesoscale eddy-resolving ice–ocean coupled model that explicitly treats ice floe collisions in marginal ice zones. First, numerical issues associated with collision rheology in the ice–ocean coupled model (ice–Princeton Ocean Model [POM] are discussed and resolved. A model for the whole of the Arctic Ocean with a coarser resolution (about 25 km was developed to investigate the performance of the ice–POM model by examining the reproducibility of seasonal and interannual sea-ice variability. It was found that this coarser resolution model can reproduce seasonal and interannual sea-ice variations compared to observations, but it cannot be used to predict variations over the short-term, such as one to two weeks. Therefore, second, high-resolution (about 2.5 km regional models were set up along the ASR to investigate the accuracy of short-term sea-ice predictions. High-resolution computations were able to reasonably reproduce the sea-ice extent compared to Advanced Microwave Scanning Radiometer–Earth Observing System satellite observations because of the improved expression of the ice–albedo feedback process and the ice–eddy interaction process.

  11. Massive phytoplankton blooms under Arctic sea ice.

    Science.gov (United States)

    Arrigo, Kevin R; Perovich, Donald K; Pickart, Robert S; Brown, Zachary W; van Dijken, Gert L; Lowry, Kate E; Mills, Matthew M; Palmer, Molly A; Balch, William M; Bahr, Frank; Bates, Nicholas R; Benitez-Nelson, Claudia; Bowler, Bruce; Brownlee, Emily; Ehn, Jens K; Frey, Karen E; Garley, Rebecca; Laney, Samuel R; Lubelczyk, Laura; Mathis, Jeremy; Matsuoka, Atsushi; Mitchell, B Greg; Moore, G W K; Ortega-Retuerta, Eva; Pal, Sharmila; Polashenski, Chris M; Reynolds, Rick A; Schieber, Brian; Sosik, Heidi M; Stephens, Michael; Swift, James H

    2012-06-15

    Phytoplankton blooms over Arctic Ocean continental shelves are thought to be restricted to waters free of sea ice. Here, we document a massive phytoplankton bloom beneath fully consolidated pack ice far from the ice edge in the Chukchi Sea, where light transmission has increased in recent decades because of thinning ice cover and proliferation of melt ponds. The bloom was characterized by high diatom biomass and rates of growth and primary production. Evidence suggests that under-ice phytoplankton blooms may be more widespread over nutrient-rich Arctic continental shelves and that satellite-based estimates of annual primary production in these waters may be underestimated by up to 10-fold.

  12. Record Arctic Sea Ice Loss in 2007

    Science.gov (United States)

    2007-01-01

    This image of the Arctic was produced from sea ice observations collected by the Advanced Microwave Scanning Radiometer (AMSR-E) Instrument on NASA's Aqua satellite on September 16, overlaid on the NASA Blue Marble. The image captures ice conditions at the end of the melt season. Sea ice (white, image center) stretches across the Arctic Ocean from Greenland to Russia, but large areas of open water were apparent as well. In addition to record melt, the summer of 2007 brought an ice-free opening though the Northwest Passage that lasted several weeks. The Northeast Passage did not open during the summer of 2007, however, as a substantial tongue of ice remained in place north of the Russian coast. According to the National Snow and Ice Data Center (NSIDC), on September 16, 2007, sea ice extent dropped to 4.13 million square kilometers (1.59 million square miles)--38 percent below average and 24 percent below the 2005 record.

  13. Dependence of NAO variability on coupling with sea ice

    Science.gov (United States)

    Strong, Courtenay; Magnusdottir, Gudrun

    2011-05-01

    The variance of the North Atlantic Oscillation index (denoted N) is shown to depend on its coupling with area-averaged sea ice concentration anomalies in and around the Barents Sea (index denoted B). The observed form of this coupling is a negative feedback whereby positive N tends to produce negative B, which in turn forces negative N. The effects of this feedback in the system are examined by modifying the feedback in two modeling frameworks: a statistical vector autoregressive model ( F VAR) and an atmospheric global climate model ( F CAM) customized so that sea ice anomalies on the lower boundary are stochastic with adjustable sensitivity to the model's evolving N. Experiments show that the variance of N decreases nearly linearly with the sensitivity of B to N, where the sensitivity is a measure of the negative feedback strength. Given that the sea ice concentration field has anomalies, the variance of N goes down as these anomalies become more sensitive to N. If the sea ice concentration anomalies are entirely absent, the variance of N is even smaller than the experiment with the most sensitive anomalies. Quantifying how the variance of N depends on the presence and sensitivity of sea ice anomalies to N has implications for the simulation of N in global climate models. In the physical system, projected changes in sea ice thickness or extent could alter the sensitivity of B to N, impacting the within-season variability and hence predictability of N.

  14. Measurements of sea ice proxies from Antarctic coastal shallow cores

    Science.gov (United States)

    Maffezzoli, Niccolò; Vallelonga, Paul; Spolaor, Andrea; Barbante, Carlo; Frezzotti, Massimo

    2015-04-01

    Despite its close relationship with climate, the climatic impact of sea ice remains only partially understood: an indication of this is the Arctic sea ice which is declining at a faster rate than models predict. Thus, the need for reliable sea ice proxies is of crucial importance. Among the sea ice proxies that can be extracted from ice cores, interest has recently been shown in the halogens Iodine (I) and Bromine (Br) (Spolaor, A., et al., 2013a, 2013b). The production of sea ice is a source of Sodium and Bromine aerosols through frost flower crystal formation and sublimation of salty blowing snow, while Iodine is emitted by the algae living underneath sea ice. We present here the results of Na, Br and I measurements in Antarctic shallow cores, drilled during a traverse made in late 2013 - early 2014 from Talos Dome (72° 00'S, 159°12'E) to GV7 (70° 41'S, 158° 51'E) seeking for sea ice signature. The samples were kept frozen until the analyses, that were carried out by Sector Field Mass Spectroscopy Inductive Coupled Plasma (SFMS-ICP): special precautions and experimental steps were adopted for the detection of such elements. The coastal location of the cores allows a clear signal from the nearby sea ice masses. The multiple cores are located about 50 km from each other and can help us to infer the provenance of the sea ice that contributed to the proxy signature. Moreover, by simultaneously determining other chemical elements and compounds in the snow, it is possible to determine the relative timing of their deposition, thus helping us to understand their processes of emission and deposition.

  15. Regional Changes in the Sea Ice Cover and Ice Production in the Antarctic

    Science.gov (United States)

    Comiso, Josefino C.

    2011-01-01

    Coastal polynyas around the Antarctic continent have been regarded as sea ice factories because of high ice production rates in these regions. The observation of a positive trend in the extent of Antarctic sea ice during the satellite era has been intriguing in light of the observed rapid decline of the ice extent in the Arctic. The results of analysis of the time series of passive microwave data indicate large regional variability with the trends being strongly positive in the Ross Sea, strongly negative in the Bellingshausen/Amundsen Seas and close to zero in the other regions. The atmospheric circulation in the Antarctic is controlled mainly by the Southern Annular Mode (SAM) and the marginal ice zone around the continent shows an alternating pattern of advance and retreat suggesting the presence of a propagating wave (called Antarctic Circumpolar Wave) around the circumpolar region. The results of analysis of the passive microwave data suggest that the positive trend in the Antarctic sea ice cover could be caused primarily by enhanced ice production in the Ross Sea that may be associated with more persistent and larger coastal polynyas in the region. Over the Ross Sea shelf, analysis of sea ice drift data from 1992 to 2008 yields a positive rate-of-increase in the net ice export of about 30,000 km2 per year. For a characteristic ice thickness of 0.6 m, this yields a volume transport of about 20 km3/year, which is almost identical, within error bars, to our estimate of the trend in ice production. In addition to the possibility of changes in SAM, modeling studies have also indicated that the ozone hole may have a role in that it causes the deepening of the lows in the western Antarctic region thereby causing strong winds to occur offthe Ross-ice shelf.

  16. Spring Snow Depth on Arctic Sea Ice using the IceBridge Snow Depth Product (Invited)

    Science.gov (United States)

    Webster, M.; Rigor, I. G.; Nghiem, S. V.; Kurtz, N. T.; Farrell, S. L.

    2013-12-01

    Snow has dual roles in the growth and decay of Arctic sea ice. In winter, it insulates sea ice from colder air temperatures, slowing its growth. From spring into summer, the albedo of snow determines how much insolation is transmitted through the sea ice and into the underlying ocean, ultimately impacting the progression of the summer ice melt. Knowing the snow thickness and distribution are essential for understanding and modeling sea ice thermodynamics and the surface heat budget. Therefore, an accurate assessment of the snow cover is necessary for identifying its impacts in the changing Arctic. This study assesses springtime snow conditions on Arctic sea ice using airborne snow thickness measurements from Operation IceBridge (2009-2012). The 2012 data were validated with coordinated in situ measurements taken in March 2012 during the BRomine, Ozone, and Mercury EXperiment field campaign. We find a statistically significant correlation coefficient of 0.59 and RMS error of 5.8 cm. The comparison between the IceBridge snow thickness product and the 1937, 1954-1991 Soviet drifting ice station data suggests that the snow cover has thinned by 33% in the western Arctic and 44% in the Beaufort and Chukchi Seas. A rudimentary estimation shows that a thinner snow cover in the Beaufort and Chukchi Seas translates to a mid-December surface heat flux as high as 81 W/m2 compared to 32 W/m2. The relationship between the 2009-2012 thinner snow depth distribution and later sea ice freeze-up is statistically significant, with a correlation coefficient of 0.59. These results may help us better understand the surface energy budget in the changing Arctic, and may improve our ability to predict the future state of the sea ice cover.

  17. Global Fiducials Program - Arctic Buoy Sea Ice Studies

    Science.gov (United States)

    Wilson, E. M.; Wilds, S. R.; Friesen, B. A.; Sloan, J. L.

    2012-12-01

    The U.S. Geological Survey has utilized remotely sensed imagery to analyze Arctic Sea Ice since 1997, and has collected and created thousands of Literal Image Derived Products (LIDPS) at one meter resolution for public distribution. From 1997-2012, six static sea ice sites located in the Arctic Basin were selected and added to the Global Fiducial Library (GFL), to create an annual series of geographically referenced images to allow scientists to study seasonal changes in Arctic ice. In early 2009, a scientific group known as MEDEA (Measurements of Earth Data for Environmental Analysis) requested additional collections to track ice floe movements during the course of an entire summer (April through September), to better understand seasonal changes in the Arctic Sea Ice. In order to track and capture the same ice cover over time, USGS adopted a methodology to utilize buoys deployed at various locations across the Arctic by the International Arctic Buoy Program. The data buoys record and transmit hourly GPS positions, along with meteorologic and climatologic data associated with the sea ice in which they are anchored. Repeated imaging of the ice cover is guided by the data buoy GPS to help estimate travel direction and speed of the ice cover. Imagery is referenced by the MEDEA scientists to study ice fracture patterns, sea ice ridge heights, ice cover percentages, seasonal development and coverage of melt ponds, evolution of ice concentrations, floe size distribution, lateral melting, and other variables that are used for input to refine and develop climate models. These same ice floe images have been added to the GFL for various buoy locations from 2009 through 2011, and are being acquired for the 2012 summer season.

  18. Estimating the Greenland ice sheet surface mass balance contribution to future sea level rise using the regional atmospheric climate model MAR

    NARCIS (Netherlands)

    Fettweis, X.; Franco, B.; Tedesco, M.; van Angelen, J.H.; Lenaerts, J.T.M.; van den Broeke, M.R.; Gallée, H.

    2013-01-01

    To estimate the sea level rise (SLR) originating from changes in surface mass balance (SMB) of the Greenland ice sheet (GrIS), we present 21st century climate projections obtained with the regional climate model MAR (Mod`ele Atmosph´erique R´egional), forced by output of three CMIP5 (Coupled Model I

  19. Can regional climate engineering save the summer Arctic sea ice?

    Science.gov (United States)

    Tilmes, S.; Jahn, Alexandra; Kay, Jennifer E.; Holland, Marika; Lamarque, Jean-Francois

    2014-02-01

    Rapid declines in summer Arctic sea ice extent are projected under high-forcing future climate scenarios. Regional Arctic climate engineering has been suggested as an emergency strategy to save the sea ice. Model simulations of idealized regional dimming experiments compared to a business-as-usual greenhouse gas emission simulation demonstrate the importance of both local and remote feedback mechanisms to the surface energy budget in high latitudes. With increasing artificial reduction in incoming shortwave radiation, the positive surface albedo feedback from Arctic sea ice loss is reduced. However, changes in Arctic clouds and the strongly increasing northward heat transport both counteract the direct dimming effects. A 4 times stronger local reduction in solar radiation compared to a global experiment is required to preserve summer Arctic sea ice area. Even with regional Arctic dimming, a reduction in the strength of the oceanic meridional overturning circulation and a shut down of Labrador Sea deep convection are possible.

  20. Correlated Energy Exchange in Drifting Sea Ice

    Directory of Open Access Journals (Sweden)

    A. Chmel

    2011-01-01

    Full Text Available The ice floe speed variations were monitored at the research camp North Pole 35 established on the Arctic ice pack in 2008. A three-month time series of measured speed values was used for determining changes in the kinetic energy of the drifting ice floe. The constructed energy distributions were analyzed by methods of nonextensive statistical mechanics based on the Tsallis statistics for open nonequilibrium systems, such as tectonic formations and drifting sea ice. The nonextensivity means the nonadditivity of externally induced energy changes in multicomponent systems due to dynamic interrelation of components having no structural links. The Tsallis formalism gives one an opportunity to assess the correlation between ice floe motions through a specific parameter, the so-called parameter of nonextensivity. This formalistic assessment of the actual state of drifting pack allows one to forecast some important trends in sea ice behavior, because the level of correlated dynamics determines conditions for extended mechanical perturbations in ice pack. In this work, we revealed temporal fluctuations of the parameter of nonextensivity and observed its maximum value before a large-scale sea ice fragmentation (faulting of consolidated sea ice. The correlation was not detected in fragmented sea ice where long-range interactions are weakened.

  1. Trajectories of arctic sea ice under anthropogenic warming scenarios

    Science.gov (United States)

    Zhang, J.; Steele, M.; Schweiger, A. J.

    2010-12-01

    A series of numerical experiments are conducted to study the possible trajectories of arctic sea ice in response to varying levels of future anthropogenic warming and climate variability using a sea ice-ocean model. A summer ice-free Arctic Ocean is likely by the mid-2040s if arctic surface air temperature (SAT) increases 4C by 2050 and climate variability is similar to the past relatively warm two decades. Summer ice volume decreases to very low levels (10-37% of the 1978-2009 summer mean) as early as 2025 and remains low in the following years, while summer ice extent continues to fluctuate annually. The rate of annual mean ice volume decrease relaxes approaching 2050. The causes of the reduced ice volume loss are examined.

  2. Arctic sea-ice ridges—Safe heavens for sea-ice fauna during periods of extreme ice melt?

    Science.gov (United States)

    Gradinger, Rolf; Bluhm, Bodil; Iken, Katrin

    2010-01-01

    The abundances and distribution of metazoan within-ice meiofauna (13 stations) and under-ice fauna (12 stations) were investigated in level sea ice and sea-ice ridges in the Chukchi/Beaufort Seas and Canada Basin in June/July 2005 using a combination of ice coring and SCUBA diving. Ice meiofauna abundance was estimated based on live counts in the bottom 30 cm of level sea ice based on triplicate ice core sampling at each location, and in individual ice chunks from ridges at four locations. Under-ice amphipods were counted in situ in replicate ( N=24-65 per station) 0.25 m 2 quadrats using SCUBA to a maximum water depth of 12 m. In level sea ice, the most abundant ice meiofauna groups were Turbellaria (46%), Nematoda (35%), and Harpacticoida (19%), with overall low abundances per station that ranged from 0.0 to 10.9 ind l -1 (median 0.8 ind l -1). In level ice, low ice algal pigment concentrations (3 m where abundances were up to 42-fold higher compared with level ice. We propose that the summer ice melt impacted meiofauna and under-ice amphipod abundance and distribution through (a) flushing, and (b) enhanced salinity stress at thinner level sea ice (less than 3 m thickness). We further suggest that pressure ridges, which extend into deeper, high-salinity water, become accumulation regions for ice meiofauna and under-ice amphipods in summer. Pressure ridges thus might be crucial for faunal survival during periods of enhanced summer ice melt. Previous estimates of Arctic sea ice meiofauna and under-ice amphipods on regional and pan-Arctic scales likely underestimate abundances at least in summer because they typically do not include pressure ridges.

  3. Diagnostic sea ice predictability in the pan-Arctic and U.S. Arctic regional seas

    Science.gov (United States)

    Cheng, Wei; Blanchard-Wrigglesworth, Edward; Bitz, Cecilia M.; Ladd, Carol; Stabeno, Phyllis J.

    2016-11-01

    This study assesses sea ice predictability in the pan-Arctic and U.S. Arctic regional (Bering, Chukchi, and Beaufort) seas with a purpose of understanding regional differences from the pan-Arctic perspective and how predictability might change under changing climate. Lagged correlation is derived using existing output from the Community Earth System Model Large Ensemble (CESM-LE), Pan-Arctic Ice-Ocean Modeling and Assimilation System, and NOAA Coupled Forecast System Reanalysis models. While qualitatively similar, quantitative differences exist in Arctic ice area lagged correlation in models with or without data assimilation. On regional scales, modeled ice area lagged correlations are strongly location and season dependent. A robust feature in the CESM-LE is that the pan-Arctic melt-to-freeze season ice area memory intensifies, whereas the freeze-to-melt season memory weakens as climate warms, but there are across-region variations in the sea ice predictability changes with changing climate.

  4. The Importance of Snow Distribution on Sea Ice

    Science.gov (United States)

    Butler, B.; Polashenski, C.; Divine, D.; King, J.; Liston, G. E.; Nicolaus, M.; Rösel, A.

    2015-12-01

    Snow's insulating and reflective properties substantially influence Arctic sea ice growth and decay. A particularly important, but under-appreciated, aspect of snow on sea ice is its fine-scale spatial distribution. Snow redistribution into dunes and drifts controls the effective thermal conductivity of a snowpack and dictates the locations of melt pond formation, exerting considerable control over ice mass balance. The effective thermal conductivity of snow distributions created on sea ice, for example, is often considerably greater than a uniform snowpack of equivalent mean thickness. During the N-ICE 2015 campaign north of Svalbard, we studied snow distributions across multiple ice types and the impacts these have on thermal fluxes and ice mass balance. We used terrestrial LiDAR to observe the snow surface topography over km2 areas, conducted many thousands of manual snow depth measurements, and collected hundreds of observations of the snow physical properties in snow pits. We find that the wind driven redistribution of snow can alter the net effect of a constant snow cover volume on ice mass balance as strongly as inter-annual variability in the amount and timing of snowfall. Further comparison with snow depth distributions from field campaigns in other parts of the Arctic highlights regional and inter-annual differences in snow distribution. We quantify the impact of this variability on ice mass balance and demonstrate the need for considering snow distributions and redistribution processes in sea ice models.

  5. Sensitivity of ocean circulation and sea-ice conditions to loss of West Antarctic ice shelves and ice sheet

    Science.gov (United States)

    Bougamont, Marion; Hunke, Elizabeth C.; Tulaczyk, Slawek

    We use a global coupled ocean-sea ice model to test the hypothesis that the disintegration of the West Antarctic ice sheet (WAIS), or just its ice shelves, may modify ocean circulation and sea-ice conditions in the Southern Ocean. We compare the results of three model runs: (1) a control run with a standard (modern) configuration of landmask in West Antarctica, (2) a no-shelves run with West Antarctic ice shelves removed and (3) a no-WAIS run. In the latter two runs, up to a few million square kilometres of new sea surface area opens to sea-ice formation, causing the volume and extent of Antarctic sea-ice cover to increase compared with the control run. In general, near-surface waters are cooler around Antarctica in the no-shelves and no-WAIS model runs than in the control run, while warm intermediate and deep waters penetrate further south, increasing poleward heat transport. Varying regional responses to the imposed changes in landmask configuration are determined by the fact that Antarctic polynyas and fast ice develop in different parts of the model domain in each run. Model results suggest that changes in the extent of WAIS may modify oceanographic conditions in the Southern Ocean.

  6. How sea ice could be the cold beating heart of European weather

    Science.gov (United States)

    Margrethe Ringgaard, Ida; Yang, Shuting; Hesselbjerg Christensen, Jens; Kaas, Eigil

    2017-04-01

    The possibility that the ongoing rapid demise of Arctic sea ice may instigate abrupt changes is, however, not tackled by current research in general. Ice cores from the Greenland Ice Sheet (GIS) show clear evidence of past abrupt warm events with up to 15 degrees warming in less than a decade, most likely triggered by rapid disappearance of Nordic Seas sea ice. At present, both Arctic Sea ice and the GIS are in strong transformation: Arctic sea-ice cover has been retreating during most of the satellite era and in recent years, Arctic sea ice experienced a dramatic reduction and the summer extent was in 2012 and 2016 only half of the 1979-2000 average. With such dramatic change in the current sea ice coverage as a point of departure, several studies have linked reduction in wintertime sea ice in the Barents-Kara seas to cold weather anomalies over Europe and through large scale tele-connections to regional warming elsewhere. Here we aim to investigate if, and how, Arctic sea ice impacts European weather, i.e. if the Arctic sea ice works as the 'cold heart' of European weather. To understand the effects of the sea ice reduction on the full climate system, a fully-coupled global climate model, EC-Earth, is used. A new energy-conserving method for assimilating sea ice using the sensible heat flux is implemented in the coupled climate model and compared to the traditional, non-conserving, method of assimilating sea ice. Using this new method, experiments are performed with reduced sea ice cover in the Barents-Kara seas under both warm and cold conditions in Europe. These experiments are used to evaluate how the Arctic sea ice modulates European winter weather under present climate conditions with a view towards favouring both relatively cold and warm conditions.

  7. Antarctic last interglacial isotope peak in response to sea ice retreat not ice-sheet collapse.

    Science.gov (United States)

    Holloway, Max D; Sime, Louise C; Singarayer, Joy S; Tindall, Julia C; Bunch, Pete; Valdes, Paul J

    2016-08-16

    Several studies have suggested that sea-level rise during the last interglacial implies retreat of the West Antarctic Ice Sheet (WAIS). The prevalent hypothesis is that the retreat coincided with the peak Antarctic temperature and stable water isotope values from 128,000 years ago (128 ka); very early in the last interglacial. Here, by analysing climate model simulations of last interglacial WAIS loss featuring water isotopes, we show instead that the isotopic response to WAIS loss is in opposition to the isotopic evidence at 128 ka. Instead, a reduction in winter sea ice area of 65±7% fully explains the 128 ka ice core evidence. Our finding of a marked retreat of the sea ice at 128 ka demonstrates the sensitivity of Antarctic sea ice extent to climate warming.

  8. Airborne Passive Microwave Measurements from the AMISA 2008 Science Campaign for Modeling of Arctic Sea Ice Heating

    Science.gov (United States)

    Zucker, M. L.; Gasiewski, A. J.; CenterEnvironmental Technology

    2011-12-01

    While climate changes in the Arctic are occurring more rapidly than anywhere else on Earth model-based predictions of sea ice extent are at once both more optimistic than the data suggest and exhibit a high degree of variability. It is believed that this high level of uncertainty is the result of an inadequate quantitative understanding of surface heating mechanisms, which in large part is due to a lack of high spatial resolution data on boundary layer and surface energy processes during melt and freezeup. In August 2008 the NASA Arctic Mechanisms of Interactions between the Surface and Atmosphere (AMISA) campaign, in conjunction with the Swedish-led Arctic Summer Cloud-Ocean Study (ASCOS) conducted coordinated high spatial resolution measurements of geophysical parameters in the Arctic relevant to atmospheric-sea ice interaction. The IPY-approved AMISA campaign used airborne radiometers, including the Polarimetric Scanning Radiometer (PSR) system, a suite of L-band to V-band fixed-beam radiometers for cloud liquid and water vapor measurement, short and longwave radiation sensors, meteorological parameters from cloud size distribution probes, GPS dropsondes, and aerosol sensors. Calibration of the PSR is achieved through periodic observations of stable references such as thermal blackbody targets and noise diodes. A combination of methods using both infrequent external thermal blackbody views and brief frequent internal noise sources has proven practical for airborne systems such as the PSR and is proposed for spaceborne systems such as GeoMAS. Once radiometric data is calibrated it is then rasterized into brightness temperature images which are then geo-located and imported into Google EarthTM. An example brightness temperature map from the AMISA 2008 campaign is included in this abstract. The analysis of this data provides a basis for the development of a heat flux model needed to decrease the uncertainly in weather and climate predictions within the Arctic. In

  9. Environmental predictors of ice seal presence in the Bering Sea.

    Science.gov (United States)

    Miksis-Olds, Jennifer L; Madden, Laura E

    2014-01-01

    Ice seals overwintering in the Bering Sea are challenged with foraging, finding mates, and maintaining breathing holes in a dark and ice covered environment. Due to the difficulty of studying these species in their natural environment, very little is known about how the seals navigate under ice. Here we identify specific environmental parameters, including components of the ambient background sound, that are predictive of ice seal presence in the Bering Sea. Multi-year mooring deployments provided synoptic time series of acoustic and oceanographic parameters from which environmental parameters predictive of species presence were identified through a series of mixed models. Ice cover and 10 kHz sound level were significant predictors of seal presence, with 40 kHz sound and prey presence (combined with ice cover) as potential predictors as well. Ice seal presence showed a strong positive correlation with ice cover and a negative association with 10 kHz environmental sound. On average, there was a 20-30 dB difference between sound levels during solid ice conditions compared to open water or melting conditions, providing a salient acoustic gradient between open water and solid ice conditions by which ice seals could orient. By constantly assessing the acoustic environment associated with the seasonal ice movement in the Bering Sea, it is possible that ice seals could utilize aspects of the soundscape to gauge their safe distance to open water or the ice edge by orienting in the direction of higher sound levels indicative of open water, especially in the frequency range above 1 kHz. In rapidly changing Arctic and sub-Arctic environments, the seasonal ice conditions and soundscapes are likely to change which may impact the ability of animals using ice presence and cues to successfully function during the winter breeding season.

  10. Environmental predictors of ice seal presence in the Bering Sea.

    Directory of Open Access Journals (Sweden)

    Jennifer L Miksis-Olds

    Full Text Available Ice seals overwintering in the Bering Sea are challenged with foraging, finding mates, and maintaining breathing holes in a dark and ice covered environment. Due to the difficulty of studying these species in their natural environment, very little is known about how the seals navigate under ice. Here we identify specific environmental parameters, including components of the ambient background sound, that are predictive of ice seal presence in the Bering Sea. Multi-year mooring deployments provided synoptic time series of acoustic and oceanographic parameters from which environmental parameters predictive of species presence were identified through a series of mixed models. Ice cover and 10 kHz sound level were significant predictors of seal presence, with 40 kHz sound and prey presence (combined with ice cover as potential predictors as well. Ice seal presence showed a strong positive correlation with ice cover and a negative association with 10 kHz environmental sound. On average, there was a 20-30 dB difference between sound levels during solid ice conditions compared to open water or melting conditions, providing a salient acoustic gradient between open water and solid ice conditions by which ice seals could orient. By constantly assessing the acoustic environment associated with the seasonal ice movement in the Bering Sea, it is possible that ice seals could utilize aspects of the soundscape to gauge their safe distance to open water or the ice edge by orienting in the direction of higher sound levels indicative of open water, especially in the frequency range above 1 kHz. In rapidly changing Arctic and sub-Arctic environments, the seasonal ice conditions and soundscapes are likely to change which may impact the ability of animals using ice presence and cues to successfully function during the winter breeding season.

  11. Atmospheric Response to Variations in Arctic Sea Ice Conditions

    Science.gov (United States)

    Bhatt, U.; Alexander, M.; Walsh, J.; Timlin, M.; Miller, J.

    2001-12-01

    While it is generally accepted that changes in air temperature and circulation determine sea ice conditions, it is not understood how the atmosphere is influenced by changes in sea ice. We employ the NCAR CCM 3.6 with specified ice extent and sea surface temperatures (sst). The overarching question addressed in this study is: how do variations in sea ice influence the atmosphere? We are particularly interested in the summer time response to highlight this unique aspect of this research. A control experiment has been integrated for 55 years by repeating the mean annual cycle of observed sea ice extent (either 0% or 100% ice cover) and sst, based on the period 1979-99. Sets of 50 member ensemble experiments were constructed by integrating the CCM from October to April using climatological sst (same as control) and observed sea ice extent from the winters of 1982-83 (ice maximum) and 1995-96 (ice minimum). Similar summertime sensitivity experiments were performed using ice extent conditions from April to October during 1982 (maximum) and 1995 (minimum). While responses were found both in winter and summer, the results described below refer to the summer of 1995. A set of 50 ensembles was also integrated for the summer of 1995 using sea ice concentration instead of extent. During the summer of 1995, negative sea ice anomalies were particularly large in the Siberian Arctic. Sea ice reductions result in increased surface and air temperatures and enhanced latent, sensible, and longwave fluxes out of the ocean. However, the net heat flux out of the ocean decreases because the changes are dominated by increased absorption of solar radiation over the low-albedo ocean. Cloud feedbacks are important in the Arctic and the downwelling solar at the surface decreases. The total cloud amount decreases due to reductions in low level clouds, however, convective cloud amounts increased. The net cloud radiative (shortwave and longwave) forcing is smaller in the experiment than the

  12. The impact of regional Arctic sea ice loss on atmospheric circulation and the NAO

    Science.gov (United States)

    Anker Pedersen, Rasmus; Cvijanovic, Ivana; Langen, Peter Lang; Vinther, Bo

    2016-04-01

    Reduction of the Arctic sea ice cover can affect the atmospheric circulation, and thus impact the climate beyond the Arctic. The atmospheric response may, however, vary with the geographical location of sea ice loss. The atmospheric sensitivity to the location of sea ice loss is studied using a general circulation model in a configuration that allows combination of a prescribed sea ice cover and an active mixed layer ocean. This hybrid setup makes it possible to simulate the isolated impact of sea ice loss and provides a more complete response compared to experiments with fixed sea surface temperatures. Three investigated sea ice scenarios with ice loss in different regions all exhibit substantial near-surface warming which peaks over the area of ice loss. The maximum warming is found during winter, delayed compared to the maximum sea ice reduction. The wintertime response of the mid-latitude atmospheric circulation shows a non-uniform sensitivity to the location of sea ice reduction. While all three scenarios exhibit decreased zonal winds related to high-latitude geopotential height increases, the magnitudes and locations of the anomalies vary between the simulations. Investigation of the North Atlantic Oscillation reveals a high sensitivity to the location of the ice loss. The northern center of action exhibits clear shifts in response to the different sea ice reductions. Sea ice loss in the Atlantic and Pacific sectors of the Arctic cause westward and eastward shifts, respectively.

  13. Assimilation of ice and water observations from SAR imagery to improve estimates of sea ice concentration

    Directory of Open Access Journals (Sweden)

    K. Andrea Scott

    2015-09-01

    Full Text Available In this paper, the assimilation of binary observations calculated from synthetic aperture radar (SAR images of sea ice is investigated. Ice and water observations are obtained from a set of SAR images by thresholding ice and water probabilities calculated using a supervised maximum likelihood estimator (MLE. These ice and water observations are then assimilated in combination with ice concentration from passive microwave imagery for the purpose of estimating sea ice concentration. Due to the fact that the observations are binary, consisting of zeros and ones, while the state vector is a continuous variable (ice concentration, the forward model used to map the state vector to the observation space requires special consideration. Both linear and non-linear forward models were investigated. In both cases, the assimilation of SAR data was able to produce ice concentration analyses in closer agreement with image analysis charts than when assimilating passive microwave data only. When both passive microwave and SAR data are assimilated, the bias between the ice concentration analyses and the ice concentration from ice charts is 19.78%, as compared to 26.72% when only passive microwave data are assimilated. The method presented here for the assimilation of SAR data could be applied to other binary observations, such as ice/water information from visual/infrared sensors.

  14. Influence of sea ice on Arctic precipitation.

    Science.gov (United States)

    Kopec, Ben G; Feng, Xiahong; Michel, Fred A; Posmentier, Eric S

    2016-01-05

    Global climate is influenced by the Arctic hydrologic cycle, which is, in part, regulated by sea ice through its control on evaporation and precipitation. However, the quantitative link between precipitation and sea ice extent is poorly constrained. Here we present observational evidence for the response of precipitation to sea ice reduction and assess the sensitivity of the response. Changes in the proportion of moisture sourced from the Arctic with sea ice change in the Canadian Arctic and Greenland Sea regions over the past two decades are inferred from annually averaged deuterium excess (d-excess) measurements from six sites. Other influences on the Arctic hydrologic cycle, such as the strength of meridional transport, are assessed using the North Atlantic Oscillation index. We find that the independent, direct effect of sea ice on the increase of the percentage of Arctic sourced moisture (or Arctic moisture proportion, AMP) is 18.2 ± 4.6% and 10.8 ± 3.6%/100,000 km(2) sea ice lost for each region, respectively, corresponding to increases of 10.9 ± 2.8% and 2.7 ± 1.1%/1 °C of warming in the vapor source regions. The moisture source changes likely result in increases of precipitation and changes in energy balance, creating significant uncertainty for climate predictions.

  15. The effects of additional black carbon on the albedo of Arctic sea ice: variation with sea ice type and snow cover

    Directory of Open Access Journals (Sweden)

    A. A. Marks

    2013-07-01

    Full Text Available The response of the albedo of bare sea ice and snow-covered sea ice to the addition of black carbon is calculated. Visible light absorption and light-scattering cross-sections are derived for a typical first-year and multi-year sea ice with both "dry" and "wet" snow types. The cross-sections are derived using data from a 1970s field study that recorded both reflectivity and light penetration in Arctic sea ice and snow overlying sea ice. The variation of absorption cross-section over the visible wavelengths suggests black carbon is the dominating light-absorbing impurity. The response of first-year and multi-year sea ice albedo to increasing black carbon, from 1 to 1024 ng g−1, in a top 5 cm layer of a 155 cm-thick sea ice was calculated using a radiative-transfer model. The albedo of the first-year sea ice is more sensitive to additional loadings of black carbon than the multi-year sea ice. An addition of 8 ng g−1 of black carbon causes a decrease to 98.7% of the original albedo for first-year sea ice compared to a decrease to 99.7% for the albedo of multi-year sea ice, at a wavelength of 500 nm. The albedo of sea ice is surprisingly unresponsive to additional black carbon up to 100 ng g−1 . Snow layers on sea ice may mitigate the effects of black carbon in sea ice. Wet and dry snow layers of 0.5, 1, 2, 5 and 10 cm depth were added onto the sea ice surface. The albedo of the snow surface was calculated whilst the black carbon in the underlying sea ice was increased. A layer of snow 0.5 cm thick greatly diminishes the effect of black carbon in sea ice on the surface albedo. The albedo of a 2–5 cm snow layer (less than the e-folding depth of snow is still influenced by the underlying sea ice, but the effect of additional black carbon in the sea ice is masked.

  16. The microwave emissivity variability of snow covered first-year sea ice from late winter to early summer: a model study

    Directory of Open Access Journals (Sweden)

    S. Willmes

    2013-12-01

    Full Text Available Satellite observations of microwave brightness temperatures between 19 GHz and 85 GHz are the main data source for operational sea-ice monitoring. However, the sea ice microwave emissivity is subject to pronounced seasonal variations and shows significant hemispheric contrasts that mainly arise from differences in the rate and strength of snow metamorphism and melt. We use the thermodynamic snow model SNTHERM and the microwave emission model MEMLS to identify the contribution of regional patterns in atmospheric energy fluxes to surface emissivity variations on Arctic and Antarctic sea ice between 2000 and 2009. The obtained emissivity data reveal a pronounced seasonal cycle with a large regional variability. The emissivity variability increases from winter to early summer and is more pronounced in the Antarctic. In the pre-melt period (January–May, July–November the variations in surface microwave emissivity due to diurnal, regional and inter-annual variability of atmospheric forcing reach up to 3.4%, 4.3%, and 9.7% for 19 GHz, 37 GHz and 85 GHz channels, respectively. Small but significant emissivity trends can be observed in the Weddell Sea during November and December as well as in Fram Strait during February. The obtained emissivity data lend themselves for an assessment of sea-ice concentration and snow-depth algorithm accuracies.

  17. Uncertainty quantification of Antarctic contribution to sea-level rise using the fast Elementary Thermomechanical Ice Sheet (f.ETISh) model

    Science.gov (United States)

    Bulthuis, Kevin; Arnst, Maarten; Pattyn, Frank; Favier, Lionel

    2017-04-01

    Uncertainties in sea-level rise projections are mostly due to uncertainties in Antarctic ice-sheet predictions (IPCC AR5 report, 2013), because key parameters related to the current state of the Antarctic ice sheet (e.g. sub-ice-shelf melting) and future climate forcing are poorly constrained. Here, we propose to improve the predictions of Antarctic ice-sheet behaviour using new uncertainty quantification methods. As opposed to ensemble modelling (Bindschadler et al., 2013) which provides a rather limited view on input and output dispersion, new stochastic methods (Le Maître and Knio, 2010) can provide deeper insight into the impact of uncertainties on complex system behaviour. Such stochastic methods usually begin with deducing a probabilistic description of input parameter uncertainties from the available data. Then, the impact of these input parameter uncertainties on output quantities is assessed by estimating the probability distribution of the outputs by means of uncertainty propagation methods such as Monte Carlo methods or stochastic expansion methods. The use of such uncertainty propagation methods in glaciology may be computationally costly because of the high computational complexity of ice-sheet models. This challenge emphasises the importance of developing reliable and computationally efficient ice-sheet models such as the f.ETISh ice-sheet model (Pattyn, 2015), a new fast thermomechanical coupled ice sheet/ice shelf model capable of handling complex and critical processes such as the marine ice-sheet instability mechanism. Here, we apply these methods to investigate the role of uncertainties in sub-ice-shelf melting, calving rates and climate projections in assessing Antarctic contribution to sea-level rise for the next centuries using the f.ETISh model. We detail the methods and show results that provide nominal values and uncertainty bounds for future sea-level rise as a reflection of the impact of the input parameter uncertainties under

  18. Arctic Sea Ice Simulation in the PlioMIP Ensemble

    Science.gov (United States)

    Howell, Fergus W.; Haywood, Alan M.; Otto-Bliesner, Bette L.; Bragg, Fran; Chan, Wing-Le; Chandler, Mark A.; Contoux, Camille; Kamae, Youichi; Abe-Ouchi, Ayako; Rosenbloom, Nan A.; Stepanek, Christian; Zhang, Zhongshi

    2016-01-01

    Eight general circulation models have simulated the mid-Pliocene warm period (mid-Pliocene, 3.264 to 3.025 Ma) as part of the Pliocene Modelling Intercomparison Project (PlioMIP). Here, we analyse and compare their simulation of Arctic sea ice for both the pre-industrial period and the mid-Pliocene. Mid-Pliocene sea ice thickness and extent is reduced, and the model spread of extent is more than twice the pre-industrial spread in some summer months. Half of the PlioMIP models simulate ice-free conditions in the mid-Pliocene. This spread amongst the ensemble is in line with the uncertainties amongst proxy reconstructions for mid-Pliocene sea ice extent. Correlations between mid-Pliocene Arctic temperatures and sea ice extents are almost twice as strong as the equivalent correlations for the pre-industrial simulations. The need for more comprehensive sea ice proxy data is highlighted, in order to better compare model performances.

  19. Halocarbons associated with Arctic sea ice

    OpenAIRE

    Atkinson, Helen M.; Hughes, Claire; Shaw, Marvin J.; Roscoe, Howard K.; Carpenter, Lucy J.; Liss, Peter S.

    2014-01-01

    Short-lived halocarbons were measured in Arctic sea-ice brine, seawater and air above the Greenland and Norwegian seas (∼81°N, 2 to 5°E) in mid-summer, from a melting ice floe at the edge of the ice pack. In the ice floe, concentrations of C2H5I, 2-C3H7I and CH2Br2 showed significant enhancement in the sea ice brine, of average factors of 1.7, 1.4 and 2.5 times respectively, compared to the water underneath and after normalising to brine volume. Concentrations of mono-iodocarbons in air are t...

  20. Arctic Tides from GPS on sea-ice

    DEFF Research Database (Denmark)

    Kildegaard Rose, Stine; Skourup, Henriette; Forsberg, René

    2013-01-01

    The presence of sea-ice in the Arctic Ocean plays a significant role in the Arctic climate. Sea-ice dampens the ocean tide amplitude with the result that global tidal models perform less accurately in the polar regions. This paper presents, a kinematic processing of global positioning system (GPS......) placed on sea-ice, at six different sites north of Greenland for the preliminary study of sea surface height (SSH), and tidal analysis to improve tide models in the Central Arctic. The GPS measurements are compared with the Arctic tide model AOTIM-5, which assimilates tide-gauges and altimetry data....... The results show coherence between the GPS buoy measurements, and the tide model. Furthermore, we have proved that the reference ellipsoid of WGS84, can be interpolated to the tidal defined zero level by applying geophysical corrections to the GPS data....

  1. Arctic Autumn Air-Ice-Ocean Interactions Resulting from Recent Sea-ice Decline

    Science.gov (United States)

    Persson, Ola; Blomquist, Byron; Fairall, Christopher; Guest, Peter; Stammerjohn, Sharon; Rainville, Luc; Thomson, Jim; Smith, Madison; Tjernström, Michael; Solomon, Amy

    2017-04-01

    The recent decline in Arctic sea-ice extent has produced large areas of open water in September that were previously ice covered. Autumn air-ice-ocean interactions in these regions are now characterized by ice-edge or marginal ice zone (MIZ) processes rather than by primarily air-ice refreezing processes. This study will utilize field program measurements to illustrate this change in processes, provide examples of new processes, and to quantify changes in energy fluxes resulting from some of the key processes. Observations from SHEBA (1998) and near the North Pole during ASCOS (2008) are used to illustrate freeze-up over existing sea ice ("old Arctic" processes) while observations from ACSE (2014), Mirai (2014), and Sea State (2015), supplemented with mesoscale model output, are used to illustrate "new Arctic" processes. In the "old Arctic", energy budgets show that freeze-up over remaining end-of-season sea ice occurred in late August, primarily because of the high albedo of the ice enhanced by snowfall events. In the "new Arctic" with extensive open water, summertime upper-ocean heating, formation of atmospheric ice-edge fronts, atmospheric thermal circulations, formation of thin new ice, ocean waves, and upper-ocean mixing all play a role in the autumn freeze-up process. These new processes also significantly impact the temporal extent and magnitude of the ocean heat loss to the atmosphere during this critical season from September to November, and possibly beyond. The magnitude of this heat loss plays an important role in various hypotheses regarding the impact of Arctic sea-ice loss on mid-latitude atmospheric circulations. While these hypotheses will not be discussed, the observations directly provide estimates of heat loss magnitudes in the "old Arctic" and the "new Arctic", thereby quantifying changes in heat loss, which can then be used to assess the accuracy of the various models and reanalyses.

  2. Periodic fluctuations in deep water formation due to sea ice

    CERN Document Server

    Saha, Raj

    2015-01-01

    During the last ice age several quasi-periodic abrupt warming events took place. Known as Dansgaard-Oeschger (DO) events their effects were felt globally, although the North Atlantic experienced the largest temperature anomalies. Paleoclimate data shows that the fluctuations often occurred right after massive glacial meltwater releases in the North Atlantic and in bursts of three or four with progressively decreasing strengths. In this study a simple dynamical model of an overturning circulation and sea ice is developed with the goal of understanding the fundamental mechanisms that could have caused the DO events. Interaction between sea ice and the overturning circulation in the model produces self-sustained oscillations. Analysis and numerical experiments reveal that the insulating effect of sea ice causes the ocean to periodically vent out accumulated heat in the deep ocean into the atmosphere. Subjecting the model to idealized freshwater forcing mimicking Heinrich events causes modulation of the natural p...

  3. Numerical prediction with `DMDF` model of pack ice motion in the Okhotsk sea; DMDF model ni yoru Okhotsk kai ryuhyo undo no suchi yosoku

    Energy Technology Data Exchange (ETDEWEB)

    Matsuzawa, T.; Yamaguchi, H.; Suzuki, S.; Kato, H. [The University of Tokyo (Japan); Rheem, C. [The University of Tokyo, Tokyo (Japan). Institute of Industrial Science

    1996-12-31

    A simulation was performed on pack ice motion in the Okhotsk Sea in winter by using the distributed mass/discrete floe (DMDF) method that carries out a dynamic numerical calculation of pack ice motion. Several kinds of cases were compared and calculated. As a result, effectiveness was verified on a DMDF model with boundary conditions which are relatively large in range and complex in nature. At the same time, it was possible to estimate part of the characteristics of pack ice motion in this sea area. The numerical calculation used the floe distribution on February 1, 1994 as the initial condition, and performed calculations on conditions until February 8 giving considerations on meteorological and hydrographic data. As a result, the calculation result showed the same movements as those in the observed ice conditions. If an ocean current is hypothesized steady, the calculation is affected more than necessarily by the ocean current, and it derives a result departed from reality. From these findings, it was elucidated that floe motions are governed mainly by wind; and in making a numerical modeling, a consideration including composition with the ocean current is necessary. Shear stress of wind has its acting direction displaced from the wind direction because of effect of the Corioli`s force. 6 refs., 13 figs., 2 tabs.

  4. Primary production calculations for sea ice from bio-optical observations in the Baltic Sea

    Directory of Open Access Journals (Sweden)

    Susann Müller

    2016-09-01

    Full Text Available Abstract Bio-optics is a powerful approach for estimating photosynthesis rates, but has seldom been applied to sea ice, where measuring photosynthesis is a challenge. We measured absorption coefficients of chromophoric dissolved organic matter (CDOM, algae, and non-algal particles along with solar radiation, albedo and transmittance at four sea-ice stations in the Gulf of Finland, Baltic Sea. This unique compilation of optical and biological data for Baltic Sea ice was used to build a radiative transfer model describing the light field and the light absorption by algae in 1-cm increments. The maximum quantum yields and photoadaptation of photosynthesis were determined from 14C-incorporation in photosynthetic-irradiance experiments using melted ice. The quantum yields were applied to the radiative transfer model estimating the rate of photosynthesis based on incident solar irradiance measured at 1-min intervals. The calculated depth-integrated mean primary production was 5 mg C m–2 d–1 for the surface layer (0–20 cm ice depth at Station 3 (fast ice and 0.5 mg C m–2 d–1 for the bottom layer (20–57 cm ice depth. Additional calculations were performed for typical sea ice in the area in March using all ice types and a typical light spectrum, resulting in depth-integrated mean primary production rates of 34 and 5.6 mg C m–2 d–1 in surface ice and bottom ice, respectively. These calculated rates were compared to rates determined from 14C incorporation experiments with melted ice incubated in situ. The rate of the calculated photosynthesis and the rates measured in situ at Station 3 were lower than those calculated by the bio-optical algorithm for typical conditions in March in the Gulf of Finland by the bio-optical algorithm. Nevertheless, our study shows the applicability of bio-optics for estimating the photosynthesis of sea-ice algae.

  5. Arctic and Southern Ocean Sea Ice Concentrations

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Monthly sea ice concentration for Arctic (1901 to 1995) and Southern oceans (1973 to 1990) were digitized on a standard 1-degree grid (cylindrical projection) to...

  6. Sea ice thickness analyses for the Bohai Sea using MODIS thermal infrared imagery

    Institute of Scientific and Technical Information of China (English)

    ZENG Tao; SHI Lijian; MARKO Makynen; CHENG Bin; ZOU Juhong; ZHANG Zhiping

    2016-01-01

    Level ice thickness distribution pattern in the Bohai Sea in the winter of 2009–2010 was investigated in this paper using MODIS night-time thermal infrared imagery. The cloud cover in the imagery was masked out manually. Level ice thickness was calculated using MODIS ice surface temperature and an ice surface heat balance equation. Weather forcing data was from the European Centre for Medium-Range Weather Forecasts (ECMWF) analyses. The retrieved ice thickness agreed reasonable well within situ observations from two off-shore oil platforms. The overall bias and the root mean square error of the MODIS ice thickness are –1.4 cm and 3.9 cm, respectively. The MODIS results under cold conditions (air temperature < –10°C) also agree with the estimated ice growth from Lebedev and Zubov models. The MODIS ice thickness is sensitive to the changes of the sea ice and air temperature, in particular when the sea ice is relatively thin. It is less sensitive to the wind speed. Our method is feasible for the Bohai Sea operational ice thickness analyses during cold freezing seasons.

  7. Floating ice-algal aggregates below melting arctic sea ice.

    Science.gov (United States)

    Assmy, Philipp; Ehn, Jens K; Fernández-Méndez, Mar; Hop, Haakon; Katlein, Christian; Sundfjord, Arild; Bluhm, Katrin; Daase, Malin; Engel, Anja; Fransson, Agneta; Granskog, Mats A; Hudson, Stephen R; Kristiansen, Svein; Nicolaus, Marcel; Peeken, Ilka; Renner, Angelika H H; Spreen, Gunnar; Tatarek, Agnieszka; Wiktor, Jozef

    2013-01-01

    During two consecutive cruises to the Eastern Central Arctic in late summer 2012, we observed floating algal aggregates in the melt-water layer below and between melting ice floes of first-year pack ice. The macroscopic (1-15 cm in diameter) aggregates had a mucous consistency and were dominated by typical ice-associated pennate diatoms embedded within the mucous matrix. Aggregates maintained buoyancy and accumulated just above a strong pycnocline that separated meltwater and seawater layers. We were able, for the first time, to obtain quantitative abundance and biomass estimates of these aggregates. Although their biomass and production on a square metre basis was small compared to ice-algal blooms, the floating ice-algal aggregates supported high levels of biological activity on the scale of the individual aggregate. In addition they constituted a food source for the ice-associated fauna as revealed by pigments indicative of zooplankton grazing, high abundance of naked ciliates, and ice amphipods associated with them. During the Arctic melt season, these floating aggregates likely play an important ecological role in an otherwise impoverished near-surface sea ice environment. Our findings provide important observations and measurements of a unique aggregate-based habitat during the 2012 record sea ice minimum year.

  8. Climate change and ice hazards in the Beaufort Sea

    Directory of Open Access Journals (Sweden)

    D. G. Barber

    2014-03-01

    Full Text Available Abstract Recent reductions in the summer extent of sea ice have focused the world’s attention on the effects of climate change. Increased CO2-derived global warming is rapidly shrinking the Arctic multi-year ice pack. This shift in ice regimes allows for increasing development opportunities for large oil and gas deposits known to occur throughout the Arctic. Here we show that hazardous ice features remain a threat to stationary and mobile infrastructure in the southern Beaufort Sea. With the opening up of the ice pack, forecasting of high-frequency oscillations or local eddy-driven ice motion will be a much more complex task than modeling average ice circulation. Given the observed reduction in sea ice extent and thickness this rather counterintuitive situation, associated with a warming climate, poses significant hazards to Arctic marine oil and gas development and marine transportation. Accurate forecasting of hazardous ice motion will require improved real-time surface wind and ocean current forecast models capable of ingesting local satellite-derived wind data and/or local, closely-spaced networks of anemometers and improved methods of determining high-frequency components of surface ocean current fields ‘up-stream’ from drilling and extraction operations.

  9. A spongy icing model for aircraft icing

    Institute of Scientific and Technical Information of China (English)

    Li Xin; Bai Junqiang; Hua Jun; Wang Kun; Zhang Yang

    2014-01-01

    Researches have indicated that impinging droplets can be entrapped as liquid in the ice matrix and the temperature of accreting ice surface is below the freezing point. When liquid entrapment by ice matrix happens, this kind of ice is called spongy ice. A new spongy icing model for the ice accretion problem on airfoil or aircraft has been developed to account for entrapped liquid within accreted ice and to improve the determination of the surface temperature when enter-ing clouds with supercooled droplets. Different with conventional icing model, this model identifies icing conditions in four regimes:rime, spongy without water film, spongy with water film and glaze. By using the Eulerian method based on two-phase flow theory, the impinging droplet flow was investigated numerically. The accuracy of the Eulerian method for computing the water collection efficiency was assessed, and icing shapes and surface temperature distributions predicted with this spongy icing model agree with experimental results well.

  10. A spongy icing model for aircraft icing

    Directory of Open Access Journals (Sweden)

    Li Xin

    2014-02-01

    Full Text Available Researches have indicated that impinging droplets can be entrapped as liquid in the ice matrix and the temperature of accreting ice surface is below the freezing point. When liquid entrapment by ice matrix happens, this kind of ice is called spongy ice. A new spongy icing model for the ice accretion problem on airfoil or aircraft has been developed to account for entrapped liquid within accreted ice and to improve the determination of the surface temperature when entering clouds with supercooled droplets. Different with conventional icing model, this model identifies icing conditions in four regimes: rime, spongy without water film, spongy with water film and glaze. By using the Eulerian method based on two-phase flow theory, the impinging droplet flow was investigated numerically. The accuracy of the Eulerian method for computing the water collection efficiency was assessed, and icing shapes and surface temperature distributions predicted with this spongy icing model agree with experimental results well.

  11. SENTINEL-1 RESULTS: SEA ICE OPERATIONAL MONITORING

    DEFF Research Database (Denmark)

    Toudal Pedersen, Leif; Saldo, Roberto; Fenger-Nielsen, Rasmus

    2015-01-01

    In the present paper we demonstrate the capabilities of the Sentinel-1 SAR data for operational sea-ice and iceberg monitoring. Most of the examples are drawn from the Copernicus Marine Environmental Monitoring Service (CMEMS) production.......In the present paper we demonstrate the capabilities of the Sentinel-1 SAR data for operational sea-ice and iceberg monitoring. Most of the examples are drawn from the Copernicus Marine Environmental Monitoring Service (CMEMS) production....

  12. Autonomous Sea-Ice Thickness Survey

    Science.gov (United States)

    2016-06-01

    measurements , assesses the merits of au- tonomous surveys relative to manual ones, and describes potential future applications. DISCLAIMER: The contents...estimated that, compared with borehole measurements , their errors averaged 0.05 m for 2 m of level sea ice. They attributed most of the...average errors of 6% or 0.12 m for 2 m of ice, although their measurements included deformed and ridged ice that probably increased average errors

  13. Radar Backscatter Study of Sea Ice.

    Science.gov (United States)

    1980-02-01

    in controlling the "state" of the ice ( temperatura and salinity) are shown in Figure 4.3-79. The salinity profile is a typical irregular c-shaped...the University of Kansas to provide well- controlled systematic studies to relate radar backscatter return to sea ice and to pin down some of the...34..,. : . - " ... ,. -.. .... .. .. ... ,,, ... ... _ ., ’.. . . , 72. Profiles of the parameters most important in controlling the "state" of the ice (temperature and salinity

  14. Trends in sea-ice variability on the way to an ice-free Arctic

    CERN Document Server

    Bathiany, Sebastian; Williamson, Mark S; Lenton, Timothy M; Scheffer, Marten; van Nes, Egbert; Notz, Dirk

    2016-01-01

    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 that is ice-free during the whole year. To this end, we apply a model hierarchy consisting of two box models and one comprehensive Earth system model. We find a consistent and robust decrease of the ice volume's annual relaxation time before summer ice is lost because thinner ice can adjust more quickly to perturbations. Thereafter, the relaxation time increases, mainly because the system becomes dominated by the ocean wa...

  15. Remote sensing of sea ice: advances during the DAMOCLES project

    Directory of Open Access Journals (Sweden)

    G. Heygster

    2012-01-01

    Full Text Available In the Arctic, global warming is particularly pronounced so that we need to monitor its development continuously. On the other hand, the vast and hostile conditions make in situ observation difficult, so that available satellite observations should be exploited in the best possible way to extract geophysical information. Here, we give a résumé of the sea ice remote sensing efforts of the EU project DAMOCLES (Developing Arctic Modeling and Observing Capabilities for Long-term Environmental Studies. The monthly variation of the microwave emissivity of first-year and multiyear sea ice has been derived for the frequencies of the microwave imagers like AMSR-E and sounding frequencies of AMSU, and has been used to develop an optimal estimation method to retrieve sea ice and atmospheric parameters simultaneously. A sea ice microwave emissivity model has been used together with a thermodynamic model to establish relations between the emisivities at 6 GHz and 50 GHz. At the latter frequency, the emissivity is needed for assimilation into atmospheric circulation models, but more difficult to observe directly. A method to determine the effective size of the snow grains from observations in the visible range (MODIS is developed and applied. The bidirectional reflectivity distribution function (BRDF of snow, which is an essential input parameter to the retrieval, has been measured in situ on Svalbard during the DAMOCLES campaign, and a BRDF model assuming aspherical particles is developed. Sea ice drift and deformation is derived from satellite observations with the scatterometer ASCAT (62.5 km grid spacing, with visible AVHRR observations (20 km, with the synthetic aperture radar sensor ASAR (10 km, and a multi-sensor product (62.5 km with improved angular resolution (Continuous Maximum Cross Correlation, CMCC method is presented. CMCC is also used to derive the sea ice deformation, important for formation of sea ice leads (diverging deformation and

  16. Coordinated Mapping of Sea Ice Deformation Features with Autonomous Vehicles

    Science.gov (United States)

    Maksym, T.; Williams, G. D.; Singh, H.; Weissling, B.; Anderson, J.; Maki, T.; Ackley, S. F.

    2016-12-01

    Decreases in summer sea ice extent in the Beaufort and Chukchi Seas has lead to a transition from a largely perennial ice cover, to a seasonal ice cover. This drives shifts in sea ice production, dynamics, ice types, and thickness distribution. To examine how the processes driving ice advance might also impact the morphology of the ice cover, a coordinated ice mapping effort was undertaken during a field campaign in the Beaufort Sea in October, 2015. Here, we present observations of sea ice draft topography from six missions of an Autonomous Underwater Vehicle run under different ice types and deformation features observed during autumn freeze-up. Ice surface features were also mapped during coordinated drone photogrammetric missions over each site. We present preliminary results of a comparison between sea ice surface topography and ice underside morphology for a range of sample ice types, including hummocked multiyear ice, rubble fields, young ice ridges and rafts, and consolidated pancake ice. These data are compared to prior observations of ice morphological features from deformed Antarctic sea ice. Such data will be useful for improving parameterizations of sea ice redistribution during deformation, and for better constraining estimates of airborne or satellite sea ice thickness.

  17. Corrigendum to insights on past and future sea-ice evolution from combining observations and models [Glob. Planet. Change (2015) 119-132

    Science.gov (United States)

    Stroeve, Julienne; Notz, Dirk

    2016-09-01

    The authors regret a misleading comparison for the modeled and observed sensitivity of Arctic sea ice to global-mean temperature change. The reference observational value from Mahlstein and Knutti (2012) that we used for comparison with the CMIP5 climate models is actually unsuitable for our purpose. This is because the value of observed sensitivity given by Mahlstein and Knutti (2012) is (1) based on sea-ice area rather than extent, and (2) only considers the period to 2007. In our study, we used extent and analyzed the sensitivity through 2014. An updated analysis based on NASA GISS Surface Temperature data (GISTEMP, http://data.giss.nasa.gov/gistemp/) and the NASA-Team sea-ice extent until 2014 gives a larger observed sensitivity of - 4.42 km2 sea-ice loss per degree of global warming. This is about twice the rate simulated by the models, and about twice the estimate of Mahlstein and Knutti (2012) that we used previously.

  18. The interaction between sea ice and salinity-dominated ocean circulation: implications for halocline stability and rapid changes of sea ice cover

    Science.gov (United States)

    Jensen, Mari F.; Nilsson, Johan; Nisancioglu, Kerim H.

    2016-11-01

    Changes in the sea ice cover of the Nordic Seas have been proposed to play a key role for the dramatic temperature excursions associated with the Dansgaard-Oeschger events during the last glacial. In this study, we develop a simple conceptual model to examine how interactions between sea ice and oceanic heat and freshwater transports affect the stability of an upper-ocean halocline in a semi-enclosed basin. The model represents a sea ice covered and salinity stratified Nordic Seas, and consists of a sea ice component and a two-layer ocean. The sea ice thickness depends on the atmospheric energy fluxes as well as the ocean heat flux. We introduce a thickness-dependent sea ice export. Whether sea ice stabilizes or destabilizes against a freshwater perturbation is shown to depend on the representation of the diapycnal flow. In a system where the diapycnal flow increases with density differences, the sea ice acts as a positive feedback on a freshwater perturbation. If the diapycnal flow decreases with density differences, the sea ice acts as a negative feedback. However, both representations lead to a circulation that breaks down when the freshwater input at the surface is small. As a consequence, we get rapid changes in sea ice. In addition to low freshwater forcing, increasing deep-ocean temperatures promote instability and the disappearance of sea ice. Generally, the unstable state is reached before the vertical density difference disappears, and the temperature of the deep ocean do not need to increase as much as previously thought to provoke abrupt changes in sea ice.

  19. Sea-level response to melting of Antarctic ice shelves on multi-centennial timescales with the fast Elementary Thermomechanical Ice Sheet model (f.ETISh v1.0)

    Science.gov (United States)

    Pattyn, Frank

    2017-08-01

    The magnitude of the Antarctic ice sheet's contribution to global sea-level rise is dominated by the potential of its marine sectors to become unstable and collapse as a response to ocean (and atmospheric) forcing. This paper presents Antarctic sea-level response to sudden atmospheric and oceanic forcings on multi-centennial timescales with the newly developed fast Elementary Thermomechanical Ice Sheet (f.ETISh) model. The f.ETISh model is a vertically integrated hybrid ice sheet-ice shelf model with vertically integrated thermomechanical coupling, making the model two-dimensional. Its marine boundary is represented by two different flux conditions, coherent with power-law basal sliding and Coulomb basal friction. The model has been compared to existing benchmarks. Modelled Antarctic ice sheet response to forcing is dominated by sub-ice shelf melt and the sensitivity is highly dependent on basal conditions at the grounding line. Coulomb friction in the grounding-line transition zone leads to significantly higher mass loss in both West and East Antarctica on centennial timescales, leading to 1.5 m sea-level rise after 500 years for a limited melt scenario of 10 m a-1 under freely floating ice shelves, up to 6 m for a 50 m a-1 scenario. The higher sensitivity is attributed to higher ice fluxes at the grounding line due to vanishing effective pressure. Removing the ice shelves altogether results in a disintegration of the West Antarctic ice sheet and (partially) marine basins in East Antarctica. After 500 years, this leads to a 5 m and a 16 m sea-level rise for the power-law basal sliding and Coulomb friction conditions at the grounding line, respectively. The latter value agrees with simulations by DeConto and Pollard (2016) over a similar period (but with different forcing and including processes of hydrofracturing and cliff failure). The chosen parametrizations make model results largely independent of spatial resolution so that f.ETISh can potentially be

  20. Canadian Ice Service Arctic Regional Sea Ice Charts in SIGRID-3 Format

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Canadian Ice Service (CIS) produces digital Arctic regional sea ice charts for marine navigation, climate research, and input to the Global Digital Sea Ice Data...

  1. Arctic and Antarctic sea ice and climate

    Science.gov (United States)

    Barreira, S.

    2014-12-01

    Principal Components Analysis in T-Mode Varimax rotated was performed on Antarctic and Arctic monthly sea ice concentration anomalies (SICA) fields for the period 1979-2014, in order to investigate which are the main spatial characteristics of sea ice and its relationship with atmospheric circulation. This analysis provides 5 patterns of sea ice for inter-spring period and 3 patterns for summer-autumn for Antarctica (69,2% of the total variance) and 3 different patterns for summer-autumn and 3 for winter-spring season for the Arctic Ocean (67,8% of the total variance).Each of these patterns has a positive and negative phase. We used the Monthly Polar Gridded Sea Ice Concentrations database derived from satellite information generated by NASA Team algorithm. To understand the links between the SICA and climate trends, we extracted the mean pressure and, temperature field patterns for the months with high loadings (positive or negative) of the sea ice patterns that gave distinct atmospheric structures associated with each one. For Antarctica, the first SICA spatial winter-spring pattern in positive phase shows a negative SICA centre over the Drake Passage and north region of Bellingshausen and Weddell Seas together with another negative SICA centre over the East Indian Ocean. Strong positive centres over the rest of the Atlantic and Indian Oceans basins and the Amundsen Sea are also presented. A strong negative pressure anomaly covers most of the Antarctic Continent centered over the Bellingshausen Sea accompanied by three positive pressure anomalies in middle-latitudes. During recent years, the Arctic showed persistent associations of sea-ice and climate patterns principally during summer. Our strongest summer-autumn pattern in negative phase showed a marked reduction on SICA over western Arctic, primarily linked to an overall increase in Arctic atmospheric temperature most pronounced over the Beaufort, Chukchi and East Siberian Seas, and a positive anomaly of

  2. Modeling seasonal velocity variability and assessing the influence of glacial hydrology and sea-ice buttressing at the Belcher Glacier, Arctic Canada

    Science.gov (United States)

    Pimentel, S.; Flowers, G. E.; Boon, S.; Clavano, W.; Copland, L.; Danielson, B.; Duncan, A.; Kavanaugh, J. L.; Sharp, M. J.; van Wychen, W. D.

    2011-12-01

    Seasonal ice dynamics on marine outlet glaciers can be influenced by the effects of both glacial hydrology and sea-ice buttressing. In summer surface meltwater finds its way through crevasses and moulins into the subglacial drainage system thereby modulating the extent of glacier sliding. Whereas in winter sea-ice build-up in front of the glacier terminus provides a buttressing effect exerting a back stress on the glacier ice. In this study we seek to distinguish between contributions from these two processes at a large fast-flowing tidewater-terminating Arctic glacier. The Belcher Glacier is the largest outlet glacier of the Devon Island Ice Cap in the Canadian high-Arctic. We employ the use of a hydrologically coupled higher-order ice-flow model together with field data collected in 2008 and 2009. Model output is compared against surface GPS observations as well as remotely sensed velocities derived using speckle tracking methods on Radarsat-2 imagery. Five major drainage sub-catchments have been identified on the Belcher and a melt model is used to generate daily surface runoff for each sub-catchment. The observed timing of lake drainage and moulin openings in each sub-catchment allow a seasonal timeseries of meltwater inputs to the subglacial drainage system to be constructed. Model simulations for 2008 and 2009 forced with this meltwater input timeseries are presented. Model responses to tidal forcing and changes in sea-ice back stress at the terminus are examined and compared alongside hydrologically driven accelerations.

  3. Observed Arctic sea-ice loss directly follows anthropogenic CO2 emission

    Science.gov (United States)

    Notz, Dirk; Stroeve, Julienne

    2016-11-01

    Arctic sea ice is retreating rapidly, raising prospects of a future ice-free Arctic Ocean during summer. Because climate-model simulations of the sea-ice loss differ substantially, we used a robust linear relationship between monthly-mean September sea-ice area and cumulative carbon dioxide (CO2) emissions to infer the future evolution of Arctic summer sea ice directly from the observational record. The observed linear relationship implies a sustained loss of 3 ± 0.3 square meters of September sea-ice area per metric ton of CO2 emission. On the basis of this sensitivity, Arctic sea ice will be lost throughout September for an additional 1000 gigatons of CO2 emissions. Most models show a lower sensitivity, which is possibly linked to an underestimation of the modeled increase in incoming longwave radiation and of the modeled transient climate response.

  4. Empirical sea ice thickness retrieval during the freeze up period from SMOS high incident angle observations

    OpenAIRE

    Huntemann, M.; G. Heygster; Kaleschke, L.; T. Krumpen; M. Mäkynen; M. Drusch

    2014-01-01

    Sea ice thickness information is important for sea ice modelling and ship operations. Here a method to detect the thickness of sea ice up to 50 cm during the freeze-up season based on high incidence angle observations of the Soil Moisture and Ocean Salinity (SMOS) satellite working at 1.4 GHz is suggested. By comparison of thermodynamic ice growth data with SMOS brightness temperatures, a high correlation to intensity and an anticorrelation to the difference bet...

  5. Spatial-temporal characters of Antarctic sea ice variation

    Institute of Scientific and Technical Information of China (English)

    Ma Lijuan; Lu Longhua; Bian Lingen

    2004-01-01

    Using sea ice concentration dataset covering the period of 1968-2002 obtained from the Hadley Center of UK, this paper investigates characters of Antarctic sea ice variations .The finding demonstrates that the change of mean sea-ice extent is almost consistent with that of sea-ice area, so sea-ice extent can be chosen to go on this research. The maximum and the minimum of Antarctic sea ice appear in September and February respectively. The maximum and the maximal variation of sea ice appear in Weddell Sea and Ross Sea, while the minimum and the minimal variation of sea-ice appear in Antarctic Peninsula. In recent 35 years, as a whole, Antarctic sea ice decreased distinctly. Moreover, there are 5 subdivision characteristic regions considering their different variations. Hereinto, the sea-ice extent of Weddell Sea and Ross Sea regions extends and area increases, while the sea-ice extent of the other three regions contracts and area decreases. They are all of obvious 2-4 years and 5-7 years significant oscillation periods. It is of significance for further understanding the sea-ice-air interaction in Antarctica region and discussing the relationship between sea-ice variation and atmospheric circulation.

  6. The Holocene thermal maximum in the Nordic Seas: the impact of Greenland Ice Sheet melt and other forcings in a coupled atmosphere-sea ice-ocean model

    NARCIS (Netherlands)

    Blaschek, M.; Renssen, H.

    2012-01-01

    The relatively warm early Holocene climate in the Nordic Seas, known as the Holocene Thermal Maximum (HTM), is often associated with an orbitally forced summer insolation maximum at 10 ka BP. The spatial and temporal response recorded in proxy data in the North Atlantic and the Nordic Seas reveal a

  7. Ice-sheet modelling characteristics in sea-level-based temperature reconstructions over the last glacial cycle

    NARCIS (Netherlands)

    Wilschut, F.; Bintanja, R.; van de Wal, R.S.W.

    2006-01-01

    A widely used method for investigating palaeotemperatures is to analyze local proxy records (e.g. ice cores or deep-sea sediment cores). The interpretation of these records is often not straightforward, and global or hemispheric means cannot be deduced from local estimates because of large spatial v

  8. Response of passive microwave sea ice concentration algorithms to thin ice

    DEFF Research Database (Denmark)

    Heygster, Georg; Huntemann, Marcus; Ivanova, Natalia;

    2014-01-01

    The influence of sea ice thickness brightness temperatures and ice concentrations retrieved from passive microwave observations is quantified, using horizontally homogeneous sea ice thickness retrievals from ESA's SMOS sensor observations at high incidence angles. Brightness temperatures are infl......The influence of sea ice thickness brightness temperatures and ice concentrations retrieved from passive microwave observations is quantified, using horizontally homogeneous sea ice thickness retrievals from ESA's SMOS sensor observations at high incidence angles. Brightness temperatures...

  9. Is Ice-Rafted Sediment in a North Pole Marine Record Evidence for Perennial Sea-ice Cover?

    Science.gov (United States)

    Tremblay, L.B.; Schmidt, G.A.; Pfirman, S.; Newton, R.; DeRepentigny, P.

    2015-01-01

    Ice-rafted sediments of Eurasian and North American origin are found consistently in the upper part (13 Ma BP to present) of the Arctic Coring Expedition (ACEX) ocean core from the Lomonosov Ridge, near the North Pole (approximately 88 degrees N). Based on modern sea-ice drift trajectories and speeds, this has been taken as evidence of the presence of a perennial sea-ice cover in the Arctic Ocean from the middle Miocene onwards. However, other high latitude land and marine records indicate a long-term trend towards cooling broken by periods of extensive warming suggestive of a seasonally ice-free Arctic between the Miocene and the present. We use a coupled sea-ice slab-ocean model including sediment transport tracers to map the spatial distribution of ice-rafted deposits in the Arctic Ocean. We use 6 hourly wind forcing and surface heat fluxes for two different climates: one with a perennial sea-ice cover similar to that of the present day and one with seasonally ice-free conditions, similar to that simulated in future projections. Model results confirm that in the present-day climate, sea ice takes more than 1 year to transport sediment from all its peripheral seas to the North Pole. However, in a warmer climate, sea-ice speeds are significantly faster (for the same wind forcing) and can deposit sediments of Laptev, East Siberian and perhaps also Beaufort Sea origin at the North Pole. This is primarily because of the fact that sea-ice interactions are much weaker with a thinner ice cover and there is less resistance to drift. We conclude that the presence of ice-rafted sediment of Eurasian and North American origin at the North Pole does not imply a perennial sea-ice cover in the Arctic Ocean, reconciling the ACEX ocean core data with other land and marine records.

  10. Using Sea Ice Age as a Proxy for Sea Ice Thickness

    Science.gov (United States)

    Stroeve, J. C.; Tschudi, M. A.; Maslanik, J. A.

    2014-12-01

    Since the beginning of the modern satellite record starting in October 1978, the Arctic sea ice cover has been shrinking, with the largest changes observed at the end of the melt season in September. Through 2013, the September ice extent has declined at a rate of -14.0% dec-1, or -895,300 km2 dec-1. The seven lowest September extents in the satellite record have all occurred in the past seven years. This reduction in ice extent is accompanied by large reductions in winter ice thicknesses that are primarily explained by changes in the ocean's coverage of multiyear ice (MYI). Using the University of Colorado ice age product developed by J. Maslanik and C. Fowler, and currently produced by M. Tschudi we present recent changes in the distribution of ice age from the mid 1980s to present. The CU ice age product is based on (1) the use of ice motion to track areas of sea ice and thus estimate how long the ice survives within the Arctic, and (2) satellite imagery of sea ice concentration to determine when the ice disappears. Age is assigned on a yearly basis, with the age incremented by one year if the ice survives summer melt and stays within the Arctic domain. Age is counted from 1 to 10 years, with all ice older than 10 years assigned to the "10+" age category. The position of the ice is calculated on weekly time steps on NSIDC's 12.5-km EASE-grid. In the mid-1980s, MYI accounted for 70% of total winter ice extent, whereas by the end of 2012 it had dropped to less than 20%. This reflects not only a change in ice type, but also a general thinning of the ice pack, as older ice tends to be thicker ice. Thus, with older ice being replaced by thinner first-year ice, the ice pack is more susceptible to melting out than it was in 1980's. It has been suggested that ice age may be a useful proxy for long-term changes in ice thickness. To assess the relationship between ice age and thickness, and how this may be changing over time, we compare the ice age fields to several

  11. A Low Order Theory of Arctic Sea Ice Stability

    CERN Document Server

    Moon, W

    2011-01-01

    We analyze the stability of a low-order coupled sea ice and climate model and extract the essential physics governing the time scales of response as a function of greenhouse gas forcing. Under present climate conditions the stability is controlled by longwave radiation driven heat conduction. However, as greenhouse gas forcing increases and the ice cover decays, the destabilizing influence of ice-albedo feedback acts on equal footing with longwave stabilization. Both are seasonally out of phase and as the system warms towards a seasonal ice state these effects, which underlie the bifurcations between climate states, combine to extend the intrinsic relaxation time scale from ~ 2 yr to 5 yr.

  12. Windows in Arctic sea ice: Light transmission and ice