Arctic sea‐ice evolution as modeled by Max Planck Institute for Meteorology's Earth system model

Notz, Dirk; Haumann, F. Alexander; Haak, Helmuth; Jungclaus, Johann; Marotzke, Jochem

doi:10.1002/jame.20016

Cited by 122 publications

(149 citation statements)

References 49 publications

Supporting

Mentioning

137

Contrasting

Unclassified

Order By: Relevance

“…This sensitivity of coupled ice-ocean models to the atmospheric forcing dataset was also found by both Hunke and Holland (2007) and Notz et al (2013). In the Notz et al (2013) study, the simulated September ice volume was less than half as much using ERA-Interim forcing compared to using NCEP-R1 forcing in part because the model was not fully adjusted to the different biases of each dataset. As a result the trend in September ice volume was also very different, 22.6 3 10 3 km 3 decade 21 for the NCEP-R1 forcing compared to a much weaker trend in the run with thinner ice, 21.6 3 10 3 km 3 decade 21 for the ERA-Interim forcing.…”

Section: Forcing An Ice-ocean Modelmentioning

confidence: 57%

“…Additionally, Notz et al (2013) found much different mean sea ice volume and volume trends in the Max Planck Institute Earth System Model using NCEP-R1 or ECMWF Interim Re-Analysis (ERA-Interim) forcing. These studies illustrate how important it is to consider the relative merits of reanalysis datasets for forcing an ice-ocean model.…”

Section: Introductionmentioning

confidence: 95%

“…A notable application of this class of models is the production of retrospective time series of sea ice thickness and volume (e.g., Zhang and Rothrock 2003;Hunke and Holland 2007;Lindsay et al 2009;Schweiger at al. 2011;Notz et al 2013). Observations for these ice variables are typically too sparse in time and space to allow an analysis for climate purposes and the use of atmospheric reanalysis data allows the reconstructions of the ice and ocean state.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Evaluation of Seven Different Atmospheric Reanalysis Products in the Arctic*

et al. 2014

View full text Add to dashboard Cite

Atmospheric reanalyses depend on a mix of observations and model forecasts. In data-sparse regions such as the Arctic, the reanalysis solution is more dependent on the model structure, assumptions, and data assimilation methods than in data-rich regions. Applications such as the forcing of ice-ocean models are sensitive to the errors in reanalyses. Seven reanalysis datasets for the Arctic region are compared over the 30-yr period 1981-2010: National Centers for Environmental Prediction (NCEP)-National Center for Atmospheric Research Reanalysis 1 (NCEP-R1) and NCEP-U.S. Department of Energy Reanalysis 2 (NCEP-R2), Climate Forecast System Reanalysis (CFSR), Twentieth-Century Reanalysis (20CR), Modern-Era Retrospective Analysis for Research and Applications (MERRA), ECMWF Interim Re-Analysis (ERA-Interim), and Japanese 25-year Reanalysis Project (JRA-25). Emphasis is placed on variables not observed directly including surface fluxes and precipitation and their trends. The monthly averaged surface temperatures, radiative fluxes, precipitation, and wind speed are compared to observed values to assess how well the reanalysis data solutions capture the seasonal cycles. Three models stand out as being more consistent with independent observations: CFSR, MERRA, and ERA-Interim. A coupled ice-ocean model is forced with four of the datasets to determine how estimates of the ice thickness compare to observed values for each forcing and how the total ice volume differs among the simulations. Significant differences in the correlation of the simulated ice thickness with submarine measurements were found, with the MERRA products giving the best correlation (R 5 0.82). The trend in the total ice volume in September is greatest with MERRA (24.1 3 10 3 km 3 decade 21 ) and least with CFSR (22.7 3 10 3 km 3 decade 21 ).

show abstract

Section: Forcing An Ice-ocean Modelmentioning

confidence: 57%

Section: Introductionmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Evaluation of Seven Different Atmospheric Reanalysis Products in the Arctic*

et al. 2014

View full text Add to dashboard Cite

show abstract

“…The LIM models have a distinct cold bias in the North Atlantic and in the Greenland Sea. These cold biases are related to the common atmospheric ERA-Interim-based forcing, which is known to have a cold anomaly over the Fram Strait-Svalbard region (Notz et al, 2013). In the Norwegian and Barents Seas, LIM models' surfaces are warmer than PHC3, while their differences to WOA13 are relatively small.…”

Section: Arctic Surface Temperaturementioning

confidence: 98%

Comparing sea ice, hydrography and circulation between NEMO3.6 LIM3 and LIM2

et al. 2017

View full text Add to dashboard Cite

Abstract. A set of hindcast simulations with the new version 3.6 of the Nucleus for European Modelling of the Ocean (NEMO) ocean-ice model in the ORCA1 configuration and forced by the DRAKKAR Forcing Set version 5.2 (DFS5.2) atmospheric data was performed from 1958 to 2012. Simulations differed in their sea-ice component: the old standard version Louvain-la-Neuve Sea Ice Model (LIM2) and its successor LIM3. Main differences between these sea-ice models are the parameterisations of sub-grid-scale sea-ice thickness distribution, ice deformation, thermodynamic processes, and sea-ice salinity. Our main objective was to analyse the response of the ocean-ice system sensitivity to the change in sea-ice physics. Additional sensitivity simulations were carried out for the attribution of observed differences between the two main simulations.In the Arctic, NEMO-LIM3 compares better with observations by realistically reproducing the sea-ice extent decline during the last few decades due to its multi-category sea-ice thickness. In the Antarctic, NEMO-LIM3 more realistically simulates the seasonal evolution of sea-ice extent than NEMO-LIM2. In terms of oceanic properties, improvements are not as evident, although NEMO-LIM3 reproduces a more realistic hydrography in the Labrador Sea and in the Arctic Ocean, including a reduced cold temperature bias of the Arctic Intermediate Water at 250 m. In the extra-polar regions, the oceanographic conditions of the two NEMO-LIM versions remain relatively similar, although they slowly drift apart over decades. This drift is probably due to a stronger deep water formation around Antarctica in LIM3.

show abstract

“…Virtually all modern sea ice models use either the VP or EVP formulation, combined with a thermodynamics model (e.g. Semtner, 1976;Bitz and Lipscomb, 1999;Vancoppenolle et al, 2009;Turner and Hunke, 2015) and variously detailed subgrid-scale parameterisations (for commonly used large-scale sea ice models as for instance CICE , LIM3 (Vancoppenolle et al, 2009), MITgcm (Adcroft et al, 2016) or MPI-ESM (Notz et al, 2013)). …”

Section: P Rampal Et Al: Nextsim: a New Lagrangian Sea Ice Modelmentioning

confidence: 99%

neXtSIM: a new Lagrangian sea ice model

et al. 2016

View full text Add to dashboard Cite

Abstract. The Arctic sea ice cover has changed drastically over the last decades. Associated with these changes is a shift in dynamical regime seen by an increase of extreme fracturing events and an acceleration of sea ice drift. The highly non-linear dynamical response of sea ice to external forcing makes modelling these changes and the future evolution of Arctic sea ice a challenge for current models. It is, however, increasingly important that this challenge be better met, both because of the important role of sea ice in the climate system and because of the steady increase of industrial operations in the Arctic. In this paper we present a new dynamical/thermodynamical sea ice model called neXtSIM that is designed to address this challenge. neXtSIM is a continuous and fully Lagrangian model, whose momentum equation is discretised with the finite-element method. In this model, sea ice physics are driven by the combination of two core components: a model for sea ice dynamics built on a mechanical framework using an elasto-brittle rheology, and a model for sea ice thermodynamics providing damage healing for the mechanical framework. The evaluation of the model performance for the Arctic is presented for the period September 2007 to October 2008 and shows that observed multiscale statistical properties of sea ice drift and deformation are well captured as well as the seasonal cycles of ice volume, area, and extent. These results show that neXtSIM is an appropriate tool for simulating sea ice over a wide range of spatial and temporal scales.

show abstract

Arctic sea‐ice evolution as modeled by Max Planck Institute for Meteorology's Earth system model

Cited by 122 publications

References 49 publications

Evaluation of Seven Different Atmospheric Reanalysis Products in the Arctic*

Evaluation of Seven Different Atmospheric Reanalysis Products in the Arctic*

Comparing sea ice, hydrography and circulation between NEMO3.6 LIM3 and LIM2

neXtSIM: a new Lagrangian sea ice model

Contact Info

Product

Resources

About