The mechanisms forcing variability in Southern Ocean sea ice and sea surface temperature from 600 years of a control climate coupled model integration are discussed. As in the observations, the ...leading mode of simulated variability exhibits a dipole pattern with positive anomalies in the Pacific sector associated with negative anomalies in the Atlantic. It is found that in the Pacific ocean circulation changes associated with variable wind forcing modify the ocean heat flux convergence and sea ice transport, resulting in sea surface temperature and sea ice anomalies. The Pacific ice and ocean anomalies persist over a number of years due to reductions in ocean shortwave absorption reinforcing the initial anomalies. In the Atlantic sector, no single process dominates in forcing the anomalies. Instead there are contributions from changing ocean and sea ice circulation and surface heat fluxes. While the absorbed solar radiation in the Atlantic is modified by the changing surface albedo, the anomalies are much shorter-lived than in the Pacific because the ocean circulation transports them northward, removing them from ice formation regions. Sea ice and ocean anomalies associated with the El Niño–Southern Oscillation and the Southern Annular Mode both exhibit a dipole pattern and contribute to the leading mode of ice and ocean variability.
Celotno besedilo
Dostopno za:
BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
As a part of the Arctic Ocean Model Intercomparison Project, results from 10 Arctic ocean/ice models are intercompared over the period 1970 through 1999. Models' monthly mean outputs are laterally ...integrated over two subdomains (Amerasian and Eurasian basins), then examined as functions of depth and time. Differences in such fields as averaged temperature and salinity arise from models' differences in parameterizations and numerical methods and from different domain sizes, with anomalies that develop at lower latitudes carried into the Arctic. A systematic deficiency is seen as AOMIP models tend to produce thermally stratified upper layers rather than the “cold halocline”, suggesting missing physics perhaps related to vertical mixing or to shelf‐basin exchanges. Flow fields pose a challenge for intercomparison. We introduce topostrophy, the vertical component of V×∇D where V is monthly mean velocity and ∇D is the gradient of total depth, characterizing the tendency to follow topographic slopes. Positive topostrophy expresses a tendency for cyclonic “rim currents”. Systematic differences of models' circulations are found to depend strongly upon assumed roles of unresolved eddies.
We use a subset of models from the coordinated experiment of the Arctic Ocean Model Intercomparison Project (AOMIP) to analyze differences in intensity and sense of rotation of Atlantic Water ...circulation. We focus on the interpretation of the potential vorticity (PV) balance. Results differ drastically for the Eurasian and the Amerasian Basins of the Arctic Ocean. We find indications that in the Eurasian Basin the lateral net flux of PV is a significant factor for the determination of the sense of rotation of Atlantic Water circulation on timescales beyond pentades. The main source of high PV causing cyclonic circulation in the Eurasian Basin is the Barents Sea, where the seasonal cycle of surface buoyancy fluxes forms stratified water that leaves the shelf and feeds the Atlantic Water Layer (AWL) in the Arctic Basins. However, in the Amerasian Basin vertical PV fluxes are the more important factor. These are closely related to wind field changes. We find an intense response of the AWL flow to wind forcing, approximated by the sea level pressure difference between the Bering Sea and the central Canadian Basin, which describes about half the variance of AWL flow of the Amerasian Basin. An experiment driven with a repeated atmospheric climatology exhibits an extreme case where a permanent high pressure system over the Beaufort Sea dominates the circulation in the Amerasian Basin, demonstrating the potential of the Beaufort Gyre to adjust in such a way as to suppress a cyclonic AWL flow in the Amerasian Basin. In more realistic cases the Beaufort Gyre still modulates the Amerasian Basin AWL circulation significantly.
Monthly sea levels from five Arctic Ocean Model Intercomparison Project (AOMIP) models are analyzed and validated against observations in the Arctic Ocean. The AOMIP models are able to simulate ...variability of sea level reasonably well, but several improvements are needed to reduce model errors. It is suggested that the models will improve if their domains have a minimum depth less than 10 m. It is also recommended to take into account forcing associated with atmospheric loading, fast ice, and volume water fluxes representing Bering Strait inflow and river runoff. Several aspects of sea level variability in the Arctic Ocean are investigated based on updated observed sea level time series. The observed rate of sea level rise corrected for the glacial isostatic adjustment at 9 stations in the Kara, Laptev, and East Siberian seas for 1954–2006 is estimated as 0.250 cm/yr. There is a well pronounced decadal variability in the observed sea level time series. The 5‐year running mean sea level signal correlates well with the annual Arctic Oscillation (AO) index and the sea level atmospheric pressure (SLP) at coastal stations and the North Pole. For 1954–2000 all model results reflect this correlation very well, indicating that the long‐term model forcing and model reaction to the forcing are correct. Consistent with the influences of AO‐driven processes, the sea level in the Arctic Ocean dropped significantly after 1990 and increased after the circulation regime changed from cyclonic to anticyclonic in 1997. In contrast, from 2000 to 2006 the sea level rose despite the stabilization of the AO index at its lowest values after 2000.
Sea ice concentration is a fundamental property of the Arctic ice‐ocean‐atmosphere system reflecting both dynamics and thermodynamics. Concentration integrates across space and time and is useful for ...characterizing both observed and numerically simulated systems. Concentration is reasonably well measured by remote sensing, and several high‐quality sea ice concentration data sets exist beginning with the satellite era. In this paper we examine the simulated sea ice concentration from nine ice‐ocean numerical models that are part of the coordinated experiments of the Arctic Ocean Model Intercomparison Project (AOMIP). Spatial patterns of means and differences between models and observations, and among models, are compared for a multiyear record and for the September sea ice minimum. Interannual variations are assessed on data with monthly climatology removed. As a proxy for the annual cycle of open water for each model, the total areas with concentration less than 10% are compared among models. Mean ice statistics are computed for grid points with greater than 1% and greater than 10% concentrations. The results show that the models have similar characteristics for the winter months when 100% cover is produced, and most models reproduce an observed minimum in sea ice concentration for 1990. The compared observational data sets use the NASA Team algorithm (Goddard Space Flight Center data, the adjusted or Walsh data, and the Hadley Centre data) and the Bootstrap algorithm. Variability in sea ice concentration is less among the four observational records than among models.
Employing results from a 0.4°, 40‐level fully global, coupled ocean–sea ice model, we investigated the role of physical processes emanating from atmosphere, ocean, and ice in the initiation, ...maintenance, and termination of a sensible heat polynya with a focus on the western Cosmonaut polynya that occurred during May–July 1999. The Cosmonaut polynya first appeared in early May 1999 in the form of an ice‐free embayment, transformed into an enclosed polynya on 5–9 July, and disappeared by late July, when the ice from the surrounding regions began to encircle the embayment. Except for the differences in ice concentrations, the time of appearance, size, and shape of the Cosmonaut polynya simulated by the model are in approximate agreement with the Special Sensor Microwave/Imager (SSM/I) observations. Between May and July 1999 the Cosmonaut Sea experienced two synoptic storms, both lasting ∼5 days. Followed by the passage of the first storm on 12–19 June, there was a remarkable growth in the size of the embayment by 21 × 103 km2. Associated with this, the sea surface temperature (SST) rose by 0.15°C, the upward heat flux jumped from 5 to 94 W m−2, and a net freshwater flux into the ocean increased by 2 cm d−1. By running the model simulation with a 20% wind speed increase, it is demonstrated that the twofold increase in SST and upward heat flux increased the embayment area by 15 × 103 km2 and decreased the ice concentration by approximately 10% from the control run. A similar, but somewhat weaker wind event that took place on 30 June to 10 July had less influence on the embayment area although the upward heat flux (65 W m−2) was comparable to the first event. By examining the vertical displacement of the −1.6°C isotherm depth prior to, during, and after these two storms, we demonstrate that the impetus provided by these storms was able to raise the −1.6°C isotherm depth by 30 m through wind‐driven mixing, making sufficient oceanic heat input from beneath the mixed layer available to prevent freezing and/or delay ice formation while ice in the adjacent regions continued to grow. A sudden shift in the ice drift direction from southwest to northeast (3 July) followed by the second storm, accompanied by large air‐sea temperature differences, caused the enclosure of the embayment, subsequent formation of the polynya, and its termination.
We have derived an analytic form of the thickness redistribution function, Ψ, and compressive strength of sea ice using variational principles. By using the technique of coarse‐graining vertical sea ...ice deformation, or ridging, in the momentum equation of the pack, we isolate frictional energy loss from potential energy gain in the collision of floes. The method accounts for macroporosity of ridge rubble, ϕR, and by including this in the state space of the pack, we expand the sea ice thickness distribution, g(h), to a bivariate distribution, g(h,ϕR). The effect of macroporosity is for the first time included in the large‐scale mass conservation and momentum equations of frozen oceans. We make assumptions that have simplified the problem, such as treating sea ice as a granular material in ridges, and assuming that bending moments associated with ridging are perturbations around an isostatic state. Regardless of these simplifications, the coarse‐grained ridge model is highly predictive of macroporosity and ridge shape. By ensuring that vertical sea ice deformation observes a variational principle both at the scale of individual ridges and over the pack as a whole, we can predict distributions of ridge shapes using equations that can be solved in Earth system models. Our method also offers the possibility of more accurate derivations of sea ice thickness from ice freeboard measured by space‐borne altimeters over polar oceans.
Key Points
We present a framework for sea ice ridging using variational calculus
The new framework accounts for the macroporosity of ice ridges and the nonconservation of energy in ridge formation
From the statistics of individual ridges, we derive the evolution of the sea ice thickness distribution for the entire pack
This work documents version two of the Department of Energy's Energy Exascale Earth System Model (E3SM). E3SMv2 is a significant evolution from its predecessor E3SMv1, resulting in a model that is ...nearly twice as fast and with a simulated climate that is improved in many metrics. We describe the physical climate model in its lower horizontal resolution configuration consisting of 110 km atmosphere, 165 km land, 0.5° river routing model, and an ocean and sea ice with mesh spacing varying between 60 km in the mid‐latitudes and 30 km at the equator and poles. The model performance is evaluated with Coupled Model Intercomparison Project Phase 6 Diagnosis, Evaluation, and Characterization of Klima simulations augmented with historical simulations as well as simulations to evaluate impacts of different forcing agents. The simulated climate has many realistic features of the climate system, with notable improvements in clouds and precipitation compared to E3SMv1. E3SMv1 suffered from an excessively high equilibrium climate sensitivity (ECS) of 5.3 K. In E3SMv2, ECS is reduced to 4.0 K which is now within the plausible range based on a recent World Climate Research Program assessment. However, a number of important biases remain including a weak Atlantic Meridional Overturning Circulation, deficiencies in the characteristics and spectral distribution of tropical atmospheric variability, and a significant underestimation of the observed warming in the second half of the historical period. An analysis of single‐forcing simulations indicates that correcting the historical temperature bias would require a substantial reduction in the magnitude of the aerosol‐related forcing.
Plain Language Summary
The U.S. Department of Energy recently released version two of its Energy Exascale Earth System Model (E3SM). E3SMv2 experienced a significant evolution in many of its model components (most notably the atmosphere and sea ice models), and its supporting software infrastructure. In this work, we document the computational performance of E3SMv2 and analyze its ability to reproduce the observed climate. To accomplish this, we utilize the standard Diagnosis and Evaluation and Characterization of Klima experiments augmented with historical simulations for the period 1850–2015. We find that E3SMv2 is nearly twice as fast as its predecessor and more accurately reproduces the observed climate in a number of metrics, most notably clouds and precipitation. We also find that the model's simulated response to increasing carbon dioxide (the equilibrium climate sensitivity) is much more realistic. Unfortunately, E3SMv2 underestimates the global mean surface temperature compared to observations during the second half of historical period. Using sensitivity experiments, where forcing agents (carbon dioxide, aerosols) are selectively disabled in the model, we determine that correcting this problem would require a strong reduction in the impact of aerosols.
Key Points
E3SMv2 is nearly twice as fast as E3SMv1 with a simulated climate that is improved in many metrics (e.g., precipitation and clouds)
Climate sensitivity is substantially lower with a more plausible equilibrium climate sensitivity of 4.0 K (compared to an unlikely value of 5.3 K in E3SMv1)
E3SMv2 underestimates the warming in the late historical period due to excessive aerosol‐related forcing
Quality control for community-based sea-ice model development Roberts, Andrew F.; Hunke, Elizabeth C.; Allard, Richard ...
Philosophical transactions of the Royal Society of London. Series A: Mathematical, physical, and engineering sciences,
09/2018, Letnik:
376, Številka:
2129
Journal Article
Recenzirano
A new collaborative organization for sea-ice model development, the CICE Consortium, has devised quality control procedures to maintain the integrity of its numerical codes’ physical representations, ...enabling broad participation from the scientific community in the Consortium’s open software development environment. Using output from five coupled and uncoupled configurations of the Los Alamos Sea Ice Model, CICE, we formulate quality control methods that exploit common statistical properties of sea-ice thickness, and test for significant changes in model results in a computationally efficient manner. New additions and changes to CICE are graded into four categories, ranging from bit-for-bit amendments to significant, answer-changing upgrades. These modifications are assessed using criteria that account for the high level of autocorrelation in sea-ice time series, along with a quadratic skill metric that searches for hemispheric changes in model answers across an array of different CICE configurations. These metrics also provide objective guidance for assessing new physical representations and code functionality.
This article is part of the theme issue ‘Modelling of sea-ice phenomena’.
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