scholarly journals Impact of sea‐ice model complexity on the performance of an unstructured‐mesh sea‐ice/ocean model under different atmospheric forcings

2021 ◽  
Author(s):  
L. Zampieri ◽  
F. Kauker ◽  
J. Fröhle ◽  
H. Sumata ◽  
E. C. Hunke ◽  
...  
Keyword(s):  
Sea Ice ◽  
Unstructured Mesh ◽  
Ocean Model ◽  
Model Complexity ◽  
Atmospheric Forcings ◽  
Ice Model

scholarly journals Impact of sea-ice model complexity on the performance of an unstructured-mesh sea-ice/ocean model under different atmospheric forcings

2020 ◽  
Author(s):  
Lorenzo Zampieri ◽  
Frank Kauker ◽  
Jörg Fröhle ◽  
Hiroshi Sumata ◽  
Elizabeth C Hunke ◽  
...  
Keyword(s):  
Sea Ice ◽  
Unstructured Mesh ◽  
Ocean Model ◽  
Model Complexity ◽  
Atmospheric Forcings ◽  
Ice Model

scholarly journals Arctic sea-ice diffusion from observed and simulated Lagrangian trajectories

2016 ◽  
Vol 10 (4) ◽  
pp. 1513-1527 ◽  
Author(s):  
Pierre Rampal ◽  
Sylvain Bouillon ◽  
Jon Bergh ◽  
Einar Ólason
Keyword(s):  
Sea Ice ◽  
Ocean Model ◽  
Arctic Sea Ice ◽  
Diffusion Analysis ◽  
Modeling Systems ◽  
Sea Ice Drift ◽  
Simulated Motion ◽  
Transport And Diffusion ◽  
Passive Tracers ◽  
Ice Model

Abstract. We characterize sea-ice drift by applying a Lagrangian diffusion analysis to buoy trajectories from the International Arctic Buoy Programme (IABP) dataset and from two different models: the standalone Lagrangian sea-ice model neXtSIM and the Eulerian coupled ice–ocean model used for the TOPAZ reanalysis. By applying the diffusion analysis to the IABP buoy trajectories over the period 1979–2011, we confirm that sea-ice diffusion follows two distinct regimes (ballistic and Brownian) and we provide accurate values for the diffusivity and integral timescale that could be used in Eulerian or Lagrangian passive tracers models to simulate the transport and diffusion of particles moving with the ice. We discuss how these values are linked to the evolution of the fluctuating displacements variance and how this information could be used to define the size of the search area around the position predicted by the mean drift. By comparing observed and simulated sea-ice trajectories for three consecutive winter seasons (2007–2011), we show how the characteristics of the simulated motion may differ from or agree well with observations. This comparison illustrates the usefulness of first applying a diffusion analysis to evaluate the output of modeling systems that include a sea-ice model before using these in, e.g., oil spill trajectory models or, more generally, to simulate the transport of passive tracers in sea ice.

scholarly journals Finite-Element Sea Ice Model (FESIM), version 2

2015 ◽  
Vol 8 (2) ◽  
pp. 855-896 ◽  
Author(s):  
S. Danilov ◽  
Q. Wang ◽  
R. Timmermann ◽  
N. Iakovlev ◽  
D. Sidorenko ◽  
...  
Keyword(s):  
Finite Element ◽  
Sea Ice ◽  
Piecewise Linear ◽  
Ocean Model ◽  
Triangular Meshes ◽  
Flux Corrected Transport ◽  
Improved Stability ◽  
Ice Model ◽  
Number Of Iterations

Abstract. The Finite-Element Sea-Ice Model, used as a component of the Finite-Element Sea ice Ocean Model, is presented. Version 2 includes the elastic-viscous-plastic (EVP) and viscous-plastic (VP) solvers and employs a flux corrected transport algorithm to advect the ice and snow mean thicknesses and concentration. The EVP part also includes a modified approach proposed recently by Bouillon et al., which is characterized by an improved stability compared to the standard EVP approach. The model is formulated on unstructured triangular meshes. It assumes a collocated placement of ice velocities, mean thicknesses and concentration at mesh vertices, and relies on a piecewise-linear (P1) continuous elements. Simple tests for the modified EVP and VP solvers are presented to show that they may produce very close results provided the number of iterations is sufficiently high.

scholarly journals The Finite-volumE Sea ice–Ocean Model (FESOM2)

2016 ◽  
Author(s):  
Sergey Danilov ◽  
Dmitry Sidorenko ◽  
Qiang Wang ◽  
Thomas Jung
Keyword(s):  
Sea Ice ◽  
Ocean Circulation ◽  
Unstructured Mesh ◽  
Circulation Model ◽  
Ocean Model ◽  
Arbitrary Lagrangian Eulerian ◽  
Major Step ◽  
Vertical Coordinate ◽  
Intercomparison Project ◽  
Mesh Models

Abstract. Version 2 of the unstructured-mesh sea ice – ocean circulation model FESOM is presented. It builds upon FESOM1.4 (Wang et al., 2014, Geosci. Mod. Dev., 7, 663–693) but differs by its dynamical core (finite volumes instead of finite elements) and is formulated using the Arbitrary Lagrangian Eulerian (ALE) vertical coordinate, which increases model flexibility. The model inherits the framework and sea ice model from the previous version, which minimizes the efforts needed from a user to switch from one version to the other. The ocean states simulated with FESOM1.4 and FESOM2.0 driven by CORE-II forcing are compared on a mesh used for CORE-II intercomparison project. Additionally the performance on an eddy-permitting mesh with uniform resolution is discussed. The new version improves numerical efficiency of FESOM in terms of CPU time by at least three times while retaining its fidelity in simulating sea ice and ocean. From this it is argued that FESOM2.0 provides a major step forward in establishing unstructured-mesh models as valuable tools in climate research.

scholarly journals On The Interannual Variability Of A Diagnostic Ice-Ocean Model

1990 ◽  
Vol 14 ◽  
pp. 339-339
Author(s):  
W.D Hibler ◽  
Peter Ranelli
Keyword(s):  
Sea Ice ◽  
Interannual Variability ◽  
Ocean Circulation ◽  
Model Simulation ◽  
Coupled Model ◽  
Ocean Model ◽  
The Arctic ◽  
Time Interval ◽  
Ice Drift ◽  
Ice Model

Sea-ice drift and dynamics can significantly affect the exchanges of heat between the atmosphere and ocean and salt fluxes into the ocean. The ice drift and dynamics, in turn, can be modified by the ocean circulation. This is especially true of the ice margin location whose seasonal characteristics are largely controlled by the substantial oceanic heat flux in the Greenland Sea due to convective overturning.A useful framework to analyze the interannual variability of ice–ocean interaction effects relevant to climatic change is the diagnostic ice–ocean model developed by Hibler and Bryan (1987). In this model, the oceanic temperature and salinity is weakly relaxed (except in the upper layer of the ocean which is essentially driven by the ice dynamic-thermodynamic sea-ice model) to climatological temperature and salinity data. This procedure allows seasonal and interannual variability to be simulated while still preventing the baroclinic characteristics of the ocean circulation from gradually drifting off into a total model defined state. However, in the work of Hibler and Bryan only the seasonal equilibrium characteristics of this model with the same forcing repeated year after year have been considered.In order to begin to examine the interannual behavior of this model, we have carried out a three-year simulation for the Arctic Greenland and Norwegian seas over the time period 1981–83. (The geographical region is essentially the same as used by Hibler and Bryan.) This three year simulation is carried out after an initial two year spin up using the 1981 atmospheric forcing data. For comparison purposes, an ice model simulation with only a fixed depth mixed layer was also carried out over this time interval.The results of these two simulations are analyzed with special attention to the ice margin characteristics in the Greenland and Norwegian seas to determine the role of ocean circulation on the variability there. The ice margin results are also compared to the variability in the northward transports of heat through the Faero-Shetland passage which in the fully-coupled model are calculated rather than specified.

scholarly journals On The Interannual Variability Of A Diagnostic Ice-Ocean Model

1990 ◽  
Vol 14 ◽  
pp. 339
Author(s):  
W.D Hibler ◽  
Peter Ranelli
Keyword(s):  
Sea Ice ◽  
Interannual Variability ◽  
Ocean Circulation ◽  
Model Simulation ◽  
Coupled Model ◽  
Ocean Model ◽  
The Arctic ◽  
Time Interval ◽  
Ice Drift ◽  
Ice Model

Sea-ice drift and dynamics can significantly affect the exchanges of heat between the atmosphere and ocean and salt fluxes into the ocean. The ice drift and dynamics, in turn, can be modified by the ocean circulation. This is especially true of the ice margin location whose seasonal characteristics are largely controlled by the substantial oceanic heat flux in the Greenland Sea due to convective overturning. A useful framework to analyze the interannual variability of ice–ocean interaction effects relevant to climatic change is the diagnostic ice–ocean model developed by Hibler and Bryan (1987). In this model, the oceanic temperature and salinity is weakly relaxed (except in the upper layer of the ocean which is essentially driven by the ice dynamic-thermodynamic sea-ice model) to climatological temperature and salinity data. This procedure allows seasonal and interannual variability to be simulated while still preventing the baroclinic characteristics of the ocean circulation from gradually drifting off into a total model defined state. However, in the work of Hibler and Bryan only the seasonal equilibrium characteristics of this model with the same forcing repeated year after year have been considered. In order to begin to examine the interannual behavior of this model, we have carried out a three-year simulation for the Arctic Greenland and Norwegian seas over the time period 1981–83. (The geographical region is essentially the same as used by Hibler and Bryan.) This three year simulation is carried out after an initial two year spin up using the 1981 atmospheric forcing data. For comparison purposes, an ice model simulation with only a fixed depth mixed layer was also carried out over this time interval. The results of these two simulations are analyzed with special attention to the ice margin characteristics in the Greenland and Norwegian seas to determine the role of ocean circulation on the variability there. The ice margin results are also compared to the variability in the northward transports of heat through the Faero-Shetland passage which in the fully-coupled model are calculated rather than specified.

Experiences with a coupled global model

1989 ◽  
Vol 329 (1604) ◽  
pp. 275-288 ◽  
Keyword(s):  
Sea Ice ◽  
General Circulation ◽  
Degrees Of Freedom ◽  
Coupled Model ◽  
General Circulation Models ◽  
Ocean Model ◽  
Atmosphere Model ◽  
Component Models ◽  
Ice Model ◽  
The Tropical Pacific

General circulation models of the atmosphere have been used to investigate the climate response to factors such as the changing concentration of CO 2 . Their usefulness is restricted by the need to specify the sea surface temperature. Partial solutions to this problem exist, such as adding a model of the ocean mixed layer to the atmosphere model, but these cannot simulate the response of the ocean heat transport to changes in the atmospheric circulation. Only a coupled atmosphere—ocean-sea-ice model can represent the mechanisms that determine the climate on time scales of decades. A coupled atmosphere-ocean-sea-ice model has been developed at the Meteorological Office. This paper describes the ocean and sea-ice components of that model and some of the characteristics of the ocean model when driven by observed fluxes of heat, fresh water, and momentum during a long spin-up experiment. Aspects of a four-year integration of the coupled model are discussed. Many factors contribute to the simulation of the coupled model. Not only are the characteristics of the component models present, but the additional degrees of freedom introduced by the removal of fixed boundary conditions at the ocean surface also introduce new features into the simulation. Particular features that result from the interaction of the models used in the simulations described in this paper include a feedback between the sea-ice model and the simulations of the atmosphere model at high latitudes, and a warming of the tropical Pacific.

scholarly journals The Finite Element Sea ice-Ocean Model (FESOM): formulation of an unstructured-mesh ocean general circulation model

2013 ◽  
Vol 6 (3) ◽  
pp. 3893-3976 ◽  
Author(s):  
Q. Wang ◽  
S. Danilov ◽  
D. Sidorenko ◽  
R. Timmermann ◽  
C. Wekerle ◽  
...  
Keyword(s):  
Finite Element ◽  
Sea Ice ◽  
General Circulation Model ◽  
General Circulation ◽  
Unstructured Mesh ◽  
Circulation Model ◽  
Ocean General Circulation Model ◽  
Ocean Model ◽  
Climate Modelling ◽  
Ocean General Circulation

Abstract. 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 it provides an excellent platform for further developments required to advance the field of climate modelling on unstructured meshes.

scholarly journals Evaluation of global ocean–sea-ice model simulations based on the experimental protocols of the Ocean Model Intercomparison Project phase 2 (OMIP-2)

2020 ◽  
Author(s):  
Hiroyuki Tsujino ◽  
L. Shogo Urakawa ◽  
Stephen M. Griffies ◽  
Gokhan Danabasoglu ◽  
Alistair J. Adcroft ◽  
...  
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Ocean Model ◽  
Sea Surface ◽  
Global Ocean ◽  
Phase 2 ◽  
Model Intercomparison ◽  
Model Simulations ◽  
Intercomparison Project ◽  
Ice Model

Abstract. We present a new framework for global ocean–sea-ice model simulations based on phase 2 of the Ocean Model Intercomparison Project (OMIP-2), making use of the JRA55-do atmospheric dataset. We motivate the use of OMIP-2 over the framework for the first phase of OMIP (OMIP-1), previously referred to as the Coordinated Ocean–ice Reference Experiments (CORE), via the evaluation of OMIP-1 and OMIP-2 simulations from eleven (11) state-of-the-science global ocean–sea-ice models. In the present evaluation, multi-model means are calculated separately for the OMIP-1 and OMIP-2 simulations and overall performances are assessed considering metrics commonly used by ocean modelers. Many features are very similar between OMIP-1 and OMIP-2 simulations, and yet we also identify key improvements in transitioning from OMIP-1 to OMIP-2. For example, the sea surface temperature of the OMIP-2 simulations reproduce the observed global warming during the 1980s and 1990s, as well as the warming hiatus in the 2000s and the more recent accelerated warming, which were absent in OMIP-1, noting that OMIP-1 forcing stopped in 2009. A negative bias in the sea-ice concentration in summer of both hemispheres in OMIP-1 is significantly reduced in OMIP-2. The overall reproducibility of both seasonal and interannual variations in sea surface temperature and sea surface height (dynamic sea level) is improved in OMIP-2. Many of the remaining common model biases may be attributed either to errors in representing important processes in ocean–sea-ice models, some of which are expected to be reduced by using finer horizontal and/or vertical resolutions, or to shared biases in the atmospheric forcing. In particular, further efforts are warranted to reduce remaining biases in OMIP-2 such as those related to the erroneous representation of deep and bottom water formations and circulations. We suggest that such problems can be resolved through collaboration between those developing models (including parameterizations) and forcing datasets.

Sign in / Sign up

Export Citation Format

Share Document