Incorporation of the C-GOLDSTEIN efficient climate model into the GENIE framework: &quot;eb_go_gs&quot; configurations of GENIE

Abstract. A computationally efficient, intermediate complexity ocean-atmosphere-sea ice model (C-GOLDSTEIN) has been incorporated into the Grid ENabled Integrated Earth system modelling (GENIE) framework. This involved decoupling of the three component modules that were re-coupled in a modular way, to allow replacement with alternatives and coupling of further components within the framework. The climate model described here (referred to as "eb_go_gs" for short) is the most basic version of GENIE in which atmosphere, ocean and sea ice all play an active role. Among improvements on the original C-GOLDSTEIN model, latitudinal grid resolution is generalized to allow a wider range of surface grids to be used. The ocean, atmosphere and sea-ice components of the "eb_go_gs" configuration of GENIE are individually described, along with details of their coupling. The setup and results from simulations using four different meshes are presented. The four alternative meshes comprise the widely-used 36 × 36 equal-area-partitioning of the Earth surface with 16 depth layers in the ocean, a version in which horizontal and vertical resolution are doubled, a setup matching the horizontal resolution of the dynamic atmospheric component available in the GENIE framework, and a setup with enhanced resolution in high-latitude areas. Results are presented for a spin-up experiment with a baseline parameter set and wind forcing typically used for current studies in which "eb_go_gs" is coupled with the ocean biogeochemistry module of GENIE, as well as for an experiment with a modified parameter set, revised wind forcing, and additional cross-basin transport pathways (Indonesian and Bering Strait throughflows). The latter experiment is repeated with the four mesh variants, with common parameter settings throughout, except for time-step length. Selected state variables and diagnostics are compared in two regards: (i) between simulations at lowest resolution that are obtained with the baseline and modified configurations, predominantly in order to evaluate the revision of the wind forcing, the modification of some key parameters, and the effect of additional transport pathways across the Arctic Ocean and the Indonesian Archipelago; (ii) between simulations with the four meshes, in order to explore various effects of mesh choice.

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Causality and Evolution of Summer Polynyas off the Coast of Northern Greenland

10.5194/egusphere-egu2020-6076 ◽

2020 ◽

Author(s):

Younjoo Lee ◽

Wieslaw Maslowski ◽

Robert Osinski ◽

Jaclyn Clement Kinney ◽

Anthony Craig ◽

...

Keyword(s):

Sea Ice ◽

Climate Model ◽

National Laboratory ◽

Arctic Region ◽

Open Water ◽

Horizontal Resolution ◽

The Arctic ◽

Northern Coast ◽

Infiltration Capacity ◽

Land Hydrology

The summer polynya along the northern coast of Greenland has been observed only six months later after the winter polynya in 2018, which has prompted concerns about the stability of some of the thickest sea-ice in the Arctic region. This study combines retrospective remotely sensed sea-ice measurements with results from the Regional Arctic System Model (RASM) to examine the causes, effect, and evolution of open-water areas/polynyas in the region.RASM is a limited-domain, fully-coupled climate model, consisting of the atmosphere (Weather Research and Forecasting, WRF3.7), ocean (Los Alamos National Laboratory Parallel Ocean Program, POP2), sea-ice (Community Sea Ice Model, CICE5), land hydrology (Variable Infiltration Capacity, VIC4) and streamflow routing (RVIC) components. The ocean and sea-ice models are configured with the horizontal resolution of 1/12-degree with 45 vertical levels and 5 sea-ice thickness categories, respectively. The atmosphere and land hydrology components are set up on a 50-km grid with 40-vertical levels and 3-soil layers, respectively. The Climate Forecast System Reanalysis (CFSR) and version 2 (CFSv2) output are used as boundary conditions for dynamic downscaling.Analysis of the sea-ice conditions off the coast of northern Greenland revealed that RASM, in agreement with satellite measurements, has simulated five summer polynya events, i.e. in August of 1984, 1985, 2002, 2004 and 2018, over the 39-year period (1980-2018). All these events were primarily dynamically forced, with the thermodynamic forcing playing the secondary, yet still important role. While the thermodynamically driven sea-ice melting exhibited a relatively little year-to-year variability, between 87 km3 and 115 km3, its relative contribution to the total sea-ice loss increased by 2.5 times, from 16% in 1984 to 40% in 2018. This implies that with continuing thinning of sea-ice, increasingly less mechanical forcing may be required to generate and maintain a polynya or open water north of Greenland in summers to come. &#160;

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Observations and Simulations of Meteorological Conditions over Arctic Thick Sea Ice in Late Winter during the Transarktika 2019 Expedition

Atmosphere ◽

10.3390/atmos12020174 ◽

2021 ◽

Vol 12 (2) ◽

pp. 174

Author(s):

Günther Heinemann ◽

Sascha Willmes ◽

Lukas Schefczyk ◽

Alexander Makshtas ◽

Vasilii Kustov ◽

...

Keyword(s):

Sea Ice ◽

Climate Models ◽

Climate Model ◽

Regional Climate ◽

Open Water ◽

The Arctic ◽

Late Winter ◽

Good Representation ◽

Hourly Temperature ◽

Ice Model

The parameterization of ocean/sea-ice/atmosphere interaction processes is a challenge for regional climate models (RCMs) of the Arctic, particularly for wintertime conditions, when small fractions of thin ice or open water cause strong modifications of the boundary layer. Thus, the treatment of sea ice and sub-grid flux parameterizations in RCMs is of crucial importance. However, verification data sets over sea ice for wintertime conditions are rare. In the present paper, data of the ship-based experiment Transarktika 2019 during the end of the Arctic winter for thick one-year ice conditions are presented. The data are used for the verification of the regional climate model COSMO-CLM (CCLM). In addition, Moderate Resolution Imaging Spectroradiometer (MODIS) data are used for the comparison of ice surface temperature (IST) simulations of the CCLM sea ice model. CCLM is used in a forecast mode (nested in ERA5) for the Norwegian and Barents Seas with 5 km resolution and is run with different configurations of the sea ice model and sub-grid flux parameterizations. The use of a new set of parameterizations yields improved results for the comparisons with in-situ data. Comparisons with MODIS IST allow for a verification over large areas and show also a good performance of CCLM. The comparison with twice-daily radiosonde ascents during Transarktika 2019, hourly microwave water vapor measurements of first 5 km in the atmosphere and hourly temperature profiler data show a very good representation of the temperature, humidity and wind structure of the whole troposphere for CCLM.

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Mechanisms for and Predictability of a Drastic Reduction in the Arctic Sea Ice: APPOSITE Data with Climate Model MIROC

Journal of Climate ◽

10.1175/jcli-d-18-0195.1 ◽

2019 ◽

Vol 32 (5) ◽

pp. 1361-1380 ◽

Cited By ~ 3

Author(s):

J. Ono ◽

H. Tatebe ◽

Y. Komuro

Keyword(s):

Sea Ice ◽

Climate Model ◽

Arctic Sea Ice ◽

The Arctic ◽

Ensemble Prediction ◽

Forecast Errors ◽

Drastic Reduction ◽

Sea Ice Concentration ◽

Sea Ice Extent ◽

Arctic Sea

Abstract The mechanisms for and predictability of a drastic reduction in the Arctic sea ice extent (SIE) are investigated using the Model for Interdisciplinary Research on Climate (MIROC) version 5.2. Here, a control (CTRL) with forcing fixed at year 2000 levels and perfect-model ensemble prediction (PRED) experiments are conducted. In CTRL, three (model years 51, 56, and 57) drastic SIE reductions occur during a 200-yr-long integration. In year 56, the sea ice moves offshore in association with a positive phase of the summer Arctic dipole anomaly (ADA) index and melts due to heat input through the increased open water area, and the SIE drastically decreases. This provides the preconditioning for the lowest SIE in year 57 when the Arctic Ocean interior is in a warm state and the spring sea ice volume has a large negative anomaly due to drastic ice reduction in the previous year. Although the ADA is one of the key mechanisms behind sea ice reduction, it does not always cause a drastic reduction. Our analysis suggests that wind direction favoring offshore ice motion is a more important factor for drastic ice reduction events. In years experiencing drastic ice reduction events, the September SIE can be skillfully predicted in PRED started from July, but not from April. This is because the forecast errors for the July sea level pressure and those for the sea ice concentration and sea ice thickness along the ice edge are large in PRED started from April.

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Atmospheric teleconnection processes linking winter air stagnation and haze extremes in China with regional Arctic sea ice decline

10.5194/acp-2019-1023 ◽

2019 ◽

Author(s):

Yufei Zou ◽

Yuhang Wang ◽

Zuowei Xie ◽

Hailong Wang ◽

Philip J. Rasch

Keyword(s):

Sea Ice ◽

Climate Model ◽

Teleconnection Pattern ◽

Arctic Sea Ice ◽

The Arctic ◽

Transient Eddy ◽

Regional Ventilation ◽

Atmospheric Teleconnection ◽

Upper Troposphere ◽

Arctic Sea

Abstract. Recent studies suggested significant impacts of boreal cryosphere changes on wintertime air stagnation and haze pollution extremes in China. However, the underlying mechanism of such a teleconnection relationship remains unclear. Here we used the Whole Atmosphere Community Climate Model (WACCM) to investigate dynamic processes leading to atmospheric circulation and air stagnation responses to Arctic sea ice changes. We conducted four climate sensitivity experiments by perturbing sea ice concentrations (SIC) and corresponding sea surface temperature (SST) in autumn and early winter over the whole Arctic and three sub-regions in the climate model. The results indicate different responses in the general circulation and regional ventilation to the region-specific Arctic changes, with the largest increase of both the probability (by 120 %) and the intensity (by 32 %) of air stagnation extreme events being found in the experiment driven by SIC and SST changes over the Pacific sector of the Arctic (the East Siberian and Chukchi Seas). The increased air stagnation extreme events are mainly driven by an amplified hemispheric-scale atmospheric teleconnection pattern that resembles the negative phase of the Eurasian (EU) pattern. Dynamical diagnostics suggest that convergence of transient eddy forcing in the vicinity of Scandinavia in winter is largely responsible for the amplification of the teleconnection pattern. Transient eddy vorticity fluxes dominate the transient eddy forcing and produce a barotropic anticyclonic anomaly near Scandinavia and wave-train propagation across Eurasia to the downstream regions in East Asia. The piecewise potential vorticity inversion analysis reveals that this long-range atmospheric teleconnection of the Arctic origin takes place primarily in the middle and upper troposphere. The anomalous ridge over East Asia in the middle and upper troposphere worsens regional ventilation conditions by weakening monsoon northwesterlies and enhancing temperature inversion near the surface, leading to more and stronger air stagnation and pollution extremes over eastern China in winter. Ensemble projections based on the state-of-the-art climate models in the Coupled Model Intercomparison Project Phase 6 (CMIP6) corroborate this teleconnection relationship between high-latitude environmental changes and middle-latitude weather extremes, though the tendency and magnitude vary considerably among each participating model.

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Achieving realistic Arctic-midlatitude teleconnections in a climate model through stochastic process representation

10.5194/wcd-2021-61 ◽

2021 ◽

Author(s):

Kristian Strommen ◽

Stephan Juricke

Keyword(s):

Sea Ice ◽

Climate Models ◽

Climate Model ◽

Arctic Sea Ice ◽

Stochastic Perturbations ◽

Model Studies ◽

Process Representation ◽

Arctic Sea ◽

Ocean Atmosphere ◽

Winter Circulation

Abstract. The extent to which interannual variability in Arctic sea ice influences the midlatitude circulation has been extensively debated. While observational data supports the existence of a teleconnection between November sea ice in the Barents-Kara region and the subsequent winter circulation, climate models do not consistently reproduce such a link, with only very weak inter-model consensus. We show, using the EC-Earth3 climate model, that while a deterministic ensemble of coupled simulations shows no evidence of such a teleconnection, the inclusion of stochastic parameterizations to the ocean and sea ice component of EC-Earth3 results in the emergence of a robust teleconnection comparable in magnitude to that observed. We show that this can be accounted for entirely by an improved ice-ocean-atmosphere coupling due to the stochastic perturbations. In particular, the inconsistent signal in existing climate model studies may be due to model biases in surface coupling, with stochastic parameterizations being one possible remedy.

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Mechanisms causing reduced Arctic sea ice loss in a coupled climate model

The Cryosphere Discussions ◽

10.5194/tcd-6-2653-2012 ◽

2012 ◽

Vol 6 (4) ◽

pp. 2653-2687 ◽

Cited By ~ 1

Author(s):

A. E. West ◽

A. B. Keen ◽

H. T. Hewitt

Keyword(s):

Sea Ice ◽

Climate Model ◽

Historical Record ◽

Arctic Sea Ice ◽

The Arctic ◽

Slight Reduction ◽

Coupled Climate Model ◽

Arctic Sea ◽

Ensembles Project ◽

Arctic Sea Ice Loss

Abstract. The fully-coupled climate model HadGEM1 produces one of the most accurate simulations of the historical record of Arctic sea ice seen in the IPCC AR4 multi-model ensemble. In this study, we examine projections of sea ice decline out to 2030, produced by two ensembles of HadGEM1 with natural and anthropogenic forcings included. These ensembles project a significant slowing of the rate of ice loss to occur after 2010, with some integrations even simulating a small increase in ice area. We use an energy budget of the Arctic to examine the causes of this slowdown. A negative feedback effect by which rapid reductions in ice thickness north of Greenland reduce ice export is found to play a major role. A slight reduction in ocean-to-ice heat flux in the relevant period, caused by changes in the MOC and subpolar gyre in some integrations, is also found to play a part. Finally, we assess the likelihood of a slowdown occurring in the real world due to these causes.

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Version 2 of the EUMETSAT OSI SAF and ESA CCI Sea Ice Concentration Climate Data Records

10.5194/tc-2018-127 ◽

2018 ◽

Cited By ~ 2

Author(s):

Thomas Lavergne ◽

Atle Macdonald Sørensen ◽

Stefan Kern ◽

Rasmus Tonboe ◽

Dirk Notz ◽

...

Keyword(s):

Sea Ice ◽

Satellite Data ◽

Grid Point ◽

Ice Cover ◽

Quantitative Information ◽

Horizontal Resolution ◽

Climate Data ◽

Time Step ◽

Sea Ice Concentration ◽

Ice Concentration

Abstract. We introduce the OSI-450, the SICCI-25km and the SICCI-50km climate data records of gridded global sea-ice concentration. These three records are derived from passive microwave satellite data and offer three distinct advantages compared to existing records: First, all three records provide quantitative information on uncertainty and possibly applied filtering at every grid point and every time step. Second, they are based on dynamic tie points, which capture the time evolution of surface characteristics of the ice cover and accommodate potential calibration differences between satellite missions. Third, they are produced in the context of sustained services offering committed extension, documentation, traceability, and user support. The three records differ in the underlying satellite data (SMMR & SSM/I & SSMIS or AMSR-E & AMSR2), in the imaging frequency channels (37 GHz and either 6 GHz or 19 GHz), in their horizontal resolution (25 km or 50 km) and in the time period they cover. We introduce the underlying algorithms and provide an initial evaluation. We find that all three records compare well with independent estimates of sea-ice concentration both in regions with very high sea-ice concentration and in regions with very low sea-ice concentration. We hence trust that these records will prove helpful for a better understanding of the evolution of the Earth's sea-ice cover.

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Response of the Atlantic Thermohaline Circulation to Increased Atmospheric CO2 in a Coupled Model

Journal of Climate ◽

10.1175/jcli3208.1 ◽

2004 ◽

Vol 17 (21) ◽

pp. 4267-4279 ◽

Cited By ~ 39

Author(s):

Aixue Hu ◽

Gerald A. Meehl ◽

Warren M. Washington ◽

Aiguo Dai

Keyword(s):

Sea Ice ◽

Heat Transport ◽

North Atlantic ◽

Thermohaline Circulation ◽

Climate Model ◽

Coupled Model ◽

The Arctic ◽

Labrador Sea ◽

Upper Ocean ◽

Gin Seas

Abstract Changes in the thermohaline circulation (THC) due to increased CO2 are important in future climate regimes. Using a coupled climate model, the Parallel Climate Model (PCM), regional responses of the THC in the North Atlantic to increased CO2 and the underlying physical processes are studied here. The Atlantic THC shows a 20-yr cycle in the control run, qualitatively agreeing with other modeling results. Compared with the control run, the simulated maximum of the Atlantic THC weakens by about 5 Sv (1 Sv ≡ 106 m3 s−1) or 14% in an ensemble of transient experiments with a 1% CO2 increase per year at the time of CO2 doubling. The weakening of the THC is accompanied by reduced poleward heat transport in the midlatitude North Atlantic. Analyses show that oceanic deep convective activity strengthens significantly in the Greenland–Iceland–Norway (GIN) Seas owing to a saltier (denser) upper ocean, but weakens in the Labrador Sea due to a fresher (lighter) upper ocean and in the south of the Denmark Strait region (SDSR) because of surface warming. The saltiness of the GIN Seas are mainly caused by an increased salty North Atlantic inflow, and reduced sea ice volume fluxes from the Arctic into this region. The warmer SDSR is induced by a reduced heat loss to the atmosphere, and a reduced sea ice flux into this region, resulting in less heat being used to melt ice. Thus, sea ice–related salinity effects appear to be more important in the GIN Seas, but sea ice–melt-related thermal effects seem to be more important in the SDSR region. On the other hand, the fresher Labrador Sea is mainly attributed to increased precipitation. These regional changes produce the overall weakening of the THC in the Labrador Sea and SDSR, and more vigorous ocean overturning in the GIN Seas. The northward heat transport south of 60°N is reduced with increased CO2, but increased north of 60°N due to the increased flow of North Atlantic water across this latitude.

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PARASO, a circum-Antarctic fully-coupled ice-sheet - ocean - sea-ice - atmosphere - land model involving f.ETISh1.7, NEMO3.6, LIM3.6, COSMO5.0 and CLM4.5

10.5194/gmd-2021-315 ◽

2021 ◽

Author(s):

Charles Pelletier ◽

Thierry Fichefet ◽

Hugues Goosse ◽

Konstanze Haubner ◽

Samuel Helsen ◽

...

Keyword(s):

Sea Ice ◽

Climate Model ◽

Regional Climate ◽

Ice Sheet ◽

Horizontal Resolution ◽

Fine Tuning ◽

Polar Regions ◽

Surface Mass ◽

The Impact ◽

Fully Coupled

Abstract. We introduce PARASO, a novel five-component fully-coupled regional climate model over an Antarctic circumpolar domain covering the full Southern Ocean. The state-of-the-art models used are f.ETISh1.7 (ice sheet), NEMO3.6 (ocean), LIM3.6 (sea ice), COSMO5.0 (atmosphere) and CLM4.5 (land), which are here run at an horizontal resolution close to 1/4°. One key-feature of this tool resides in a novel two-way coupling interface for representing ocean – ice-sheet interactions, through explicitly resolved ice-shelf cavities. The impact of atmospheric processes on the Antarctic ice sheet is also conveyed through computed COSMO-CLM – f.ETISh surface mass exchanges. In this technical paper, we briefly introduce each model's configuration and document the developments that were carried out in order to establish PARASO. The new offline-based NEMO – f.ETISh coupling interface is thoroughly described. Our developments also include a new surface tiling approach to combine open-ocean and sea-ice covered cells within COSMO, which was required to make this model relevant in the context of coupled simulations in polar regions. We present results from a 2000–2001 coupled two-year experiment. PARASO is numerically stable and fully operational. The 2-year simulation conducted without fine tuning of the model reproduced the main expected features, although remaining systematic biases provide perspectives for further adjustment and development.

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Gridded Arctic sea ice concentration reconstruction for the first half of the 20th century based on different proxy data

10.5194/egusphere-egu21-3106 ◽

2021 ◽

Author(s):

Vladimir Semenov ◽

Tatiana Matveeva

Keyword(s):

Sea Ice ◽

20Th Century ◽

Climate Model ◽

Surface Air Temperature ◽

Arctic Sea Ice ◽

The Arctic ◽

Sea Ice Concentration ◽

The North ◽

Arctic Sea ◽

Ice Concentration

Global warming in the recent decades has been accompanied by a rapid recline of the Arctic sea ice area most pronounced in summer (10% per decade). To understand the relative contribution of external forcing and natural variability to the modern and future sea ice area changes, it is necessary to evaluate a range of long-term variations of the Arctic sea ice area in the period before a significant increase in anthropogenic emissions of greenhouse gases into the atmosphere. Available observational data on the spatiotemporal dynamics of Arctic sea ice until 1950s are characterized by significant gaps and uncertainties. In the recent years, there have appeared several reconstructions of the early 20th century Arctic sea ice area that filled the gaps by analogue methods or utilized combined empirical data and climate model&#8217;s output. All of them resulted in a stronger that earlier believed negative sea ice area anomaly in the 1940s concurrent with the early 20th century warming (ETCW) peak. In this study, we reconstruct the monthly average gridded sea ice concentration (SIC) in the first half of the 20th century using the relationship between the spatiotemporal features of SIC variability, surface air temperature over the Northern Hemisphere extratropical continents, sea surface temperature in the North Atlantic and North Pacific, and sea level pressure. In agreement with a few previous results, our reconstructed data also show a significant negative anomaly of the Arctic sea ice area in the middle of the 20th century, however with some 15% to 30% stronger amplitude, about 1.5 million km2 in September and 0.7 million km2 in March. The reconstruction demonstrates a good agreement with regional Arctic sea ice area data when available and suggests that ETWC in the Arctic has been accompanied by a concurrent sea ice area decline of a magnitude that have been exceeded only in the beginning of the 21st century.

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