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

Chevallier, Matthieu; Smith, G. C. Moore; Dupont, Frédéric; Lemieux, Jean‐François; Forget, Gaël; Fujii, Yosuke; Hernández, Fabrice; Msadek, Rym; Peterson, K. Andrew; Storto, Andrea; Toyoda, Takahiro; Valdivieso, Maria; Vernières, Guillaume; Zuo, Hao; Balmaseda, Magdalena; Chang, Yehui; Ferry, Nicolas; Garric, Gilles; Haines, Keith; Keeley, Sarah; Kovach, Robin; Kuragano, Tsurane; Masina, Simona; Tang, Yongming; Tsujino, Hiroyuki; Wang, Xiaochun

doi:10.1007/s00382-016-2985-y

Cited by 114 publications

(136 citation statements)

References 86 publications

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“…3a, c, e). A similar positive sea-ice velocity bias was reported by (Chevallier et al, 2015), who analysed 14 ocean-ice reanalysis products. This discrepancy might be a result of a too high air-sea momentum flux driving the ice too fast and, on the shelf regions, due to the lack of a fast-ice parameterisation.…”

Section: Sea-ice Driftsupporting

confidence: 84%

“…For example, papers of the CORE-II virtual special issue of the Ocean Modelling Journal, such as Danabasoglu et al (2014Danabasoglu et al ( , 2016; Downes et al (2015); Farneti et al (2015); Griffies et al (2014); Wang et al (2016a, b), and of the ORA-IP special issue of the Climate Dynamics Journal, such as Chevallier et al (2015), are particularly relevant for this study. As the majority of CORE-II and ORA-IP ocean model configurations, our grid configuration (ORCA1) does not resolve ocean eddies.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, Chevallier et al (2015) analysed the Arctic sea ice in a set of ocean reanalyses to assess how the assimilation of observations affects the sea-ice characteristics. In addition to observational data, we use these ocean-ice model assessments as a benchmark when analysing our simulation performance.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2017

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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.

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Section: Sea-ice Driftsupporting

confidence: 84%

Section: Introductionmentioning

confidence: 99%

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

et al. 2017

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“…The proposed reanalysis is unique compared to other reanalysis products (see Table 1 of Chevallier et al, 2016). It proposes a long high-resolution dynamical reconstruction of the ocean and sea ice, and assimilates a complete set of observations available in the Arctic region with an advanced ensemble data assimilation method and with strongly coupled data assimilation between ocean and sea ice.…”

Section: Summary and Discussionmentioning

confidence: 99%

Quality assessment of the TOPAZ4 reanalysis in the Arctic over the period 1991–2013

Xie¹,

Bertino²,

Counillon³

et al. 2017

Ocean Sci.

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Abstract. Long dynamical atmospheric reanalyses are widely used for climate studies, but data-assimilative reanalyses of ocean and sea ice in the Arctic are less common. TOPAZ4 is a coupled ocean and sea ice data assimilation system for the North Atlantic and the Arctic that is based on the HYCOM ocean model and the ensemble Kalman filter data assimilation method using 100 dynamical members. A 23-year reanalysis has been completed for the period 1991-2013 and is the multi-year physical product in the Copernicus Marine Environment Monitoring Service (CMEMS) Arctic Marine Forecasting Center (ARC MFC). This study presents its quantitative quality assessment, compared to both assimilated and unassimilated observations available in the whole Arctic region, in order to document the strengths and weaknesses of the system for potential users. It is found that TOPAZ4 performs well with respect to near-surface ocean variables, but some limitations appear in the interior of the ocean and for ice thickness, where observations are sparse. In the course of the reanalysis, the skills of the system are improving as the observation network becomes denser, in particular during the International Polar Year. The online bias estimation successfully maintains a low bias in our system. In addition, statistics of the reduced centered random variables (RCRVs) confirm the reliability of the ensemble for most of the assimilated variables. Occasional discontinuities of these statistics are caused by the changes of the input data sets or the data assimilation settings, but the statistics remain otherwise stable throughout the reanalysis, regardless of the density of observations. Furthermore, no data type is severely less dispersed than the others, even though the lack of consistently reprocessed observation time series at the beginning of the reanalysis has proven challenging. IntroductionThe Arctic Ocean plays an important role in the global climate system, where the sea ice at the interface between atmosphere and ocean regulates the fluxes of heat, moisture and momentum. The recent warming of the Arctic and the change of its water cycle has been linked to the following manifestations: a significant reduction and thinning of the sea ice cover (Johannessen et al., 2004;Shimada et al., 2006;Rothrock et al., 2008;Kwok and Rothrock, 2009), more freshwater in the Arctic in the 2000s (Haine et al., 2015) and more mobility and faster deformations of the Arctic sea ice (Rampal et al., 2009;Spreen et al., 2011). The interpretation of such changes is severely hampered by the sparseness of the concerned observations, which should not be improved dramatically in the near future. It can be assisted by free-running model simulations, but those are usually hampered by mislocations of ice edge and certain water masses. One possibility is to study surrogate locations where similar processes are assumed to take place. Another solution is to correct the dynamical model by assimilating observations available over relevant timescales.The latter activities thu...

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“…First results reveal consistency with respect to sea ice concentration, which is primarily due to the constraints in surface temperature imposed by atmospheric forcing and ocean data assimilation. However, estimates of Arctic sea-ice volume suffer from large uncertainties, and the ensemble mean does not seem to be a robust estimate (Chevallier et al 2017). On average, ocean reanalyses tend to have a relatively low heat transport to the Arctic through Fram Strait and, as a result, cooler than the observed 25 Atlantic water layer.…”

Section: Linkages Between the Marine Arctic And Eurasian Continentmentioning

confidence: 99%

Towards the Marine Arctic Component of the Pan-Eurasian Experiment

Vihma

Uotila

Sandven³

et al. 2018

Preprint

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Abstract. The Arctic marine climate system is changing rapidly, seen as warming of the ocean and atmosphere, decline of sea ice cover, increase in river discharge, acidification of the ocean, and changes in marine ecosystems. Socio-economic activities 20 in the coastal and marine Arctic are simultaneously changing. This calls for establishment of a marine Arctic component of the Pan-Eurasian Experiment (MA-PEEX). There is a need for more in-situ observations on the marine atmosphere, sea ice, and ocean, but increasing the amount of such observations is a pronounced technological and logistical challenge. The SMEAR (Station Measuring Ecosystem-Atmosphere Relations) concept can be applied in coastal and archipelago stations, but in the Arctic Ocean it will probably be more cost-effective to further develop a strongly distributed marine observation network 25 based on autonomous buoys, moorings, Autonomous Underwater Vehicles (AUV), and Unmanned Aerial Vehicles (UAV).These have to be supported by research vessel and aircraft campaigns, as well as various coastal observations, including community-based ones. Major manned drifting stations may occasionally serve comparable to terrestrial SMEAR Flagship stations. To best utilize the observations, atmosphere-ocean reanalyses need to be further developed. To well integrate MA-PEEX with the existing terrestrial/atmospheric PEEX, focus is needed on the river discharge and associated fluxes, coastal 30 processes, as well as atmospheric transports in and out of the marine Arctic. More observations and research are also needed on the specific socio-economic challenges and opportunities in the marine and coastal Arctic, and on their interaction with changes in the climate and environmental system. MA-PEEX will promote international collaboration, sustainable marine Atmos. Chem. Phys. Discuss., https://doi

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

Cited by 114 publications

References 86 publications

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

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

Quality assessment of the TOPAZ4 reanalysis in the Arctic over the period 1991–2013

Towards the Marine Arctic Component of the Pan-Eurasian Experiment

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