Sea ice sensitivity to the parameterisation of open water area

Wang, Zeliang; Lu, Youyu; Wright, Daniel G.; Dupont, Frédéric

doi:10.1080/1755876x.2010.11020113

Cited by 12 publications

(12 citation statements)

References 12 publications

(8 reference statements)

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“…Wang et al . [] also demonstrated a direct impact of h 0 on the simulated sea ice volume from LIM2. In the single‐ice category model, this parameter compensates for the absence of a multithickness redistribution scheme.…”

Section: Methodsmentioning

confidence: 58%

“…An important sensitivity to the parameter specifying the thickness of newly formed sea ice (hereafter h 0 ) was found in simulations made with LIM2. Wang et al [2010] also demonstrated a direct impact of h 0 on the simulated sea ice volume from LIM2. In the single-ice category model, this parameter compensates for the absence of a multithickness redistribution scheme.…”

Section: Simulation Domain and Setupmentioning

confidence: 75%

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Arctic sea ice and freshwater sensitivity to the treatment of the atmosphere‐ice‐ocean surface layer

Roy¹,

Chevallier

Smith³

et al. 2015

JGR Oceans

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Global simulations are presented focusing on the atmosphere-ice-ocean (AIO) surface layer (SL) in the Arctic. Results are produced using an ocean model (NEMO) coupled to two different sea ice models: the Louvain-La-Neuve single-category model (LIM2) and the Los Alamos multicategory model (CICE4). A more objective way to adjust the sea ice-ocean drag is proposed compared to a coefficient tuning approach. The air-ice drag is also adjusted to be more consistent with the atmospheric forcing data set. Improving the AIO SL treatment leads to more realistic results, having a significant impact on the sea ice volume trend, sea ice thickness, and the Arctic freshwater (FW) budget. The physical mechanisms explaining this sensitivity are studied. Improved sea ice drift speeds result in less sea ice accumulation in the Beaufort Sea, correcting a typical ice thickness bias. Sea ice thickness and drag parameters affect how atmospheric stress is transferred to the ocean, thereby influencing Ekman transport and FW retention in the Beaufort Gyre (BG). Increasing sea ice-ocean roughness reduces sea ice growth in winter by reducing ice deformation and lead fractions in the BG. It also increases the total Arctic FW content by reducing sea ice export through Fram Strait. Similarly, increasing air-ice roughness increases the total Arctic FW content by increasing FW retention in the BG.

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Section: Methodsmentioning

confidence: 58%

Section: Simulation Domain and Setupmentioning

confidence: 75%

Arctic sea ice and freshwater sensitivity to the treatment of the atmosphere‐ice‐ocean surface layer

Roy¹,

Chevallier

Smith³

et al. 2015

JGR Oceans

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“…Previous versions of NEMO have been extensively tested and applied in Canada for global, basin and regional applications (Holloway and Wang, 2009;Zhu et al, 2009;Wang et al, 2010;Lu et al, 2014).…”

Section: Ocean Componentmentioning

confidence: 99%

“…The VP solver performs 20 outer loops (the default is two) with a linear residual at convergence of 1 × 10 −6 or a maximum of 550 iterations. It should be noted here that NEMO-LIM2 users can tune the total ice extent and volume by adjusting the parameter hiccrit (Wang et al, 2010), a characteristic thickness that is used to determine changes in open water area during ice growth. Nonetheless, overestimation of the total ice extent or volume is often reported in NEMO-related publications (Massonnet et al, 2011;Blockley et al, 2014), likely related to the use of a too-large value of the aforementioned parameter for given configuration and forcing.…”

Section: Lim2 and Cice Parametersmentioning

confidence: 99%

A high-resolution ocean and sea-ice modelling system for the Arctic and North Atlantic oceans

et al. 2015

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Abstract. As part of the CONCEPTS (Canadian Operational Network of Coupled Environmental PredicTion Systems) initiative, a high-resolution (1/12 • ) ice-ocean regional model is developed covering the North Atlantic and the Arctic oceans. The long-term objective is to provide Canada with short-term ice-ocean predictions and hazard warnings in ice-infested regions. To evaluate the modelling component (as opposed to the analysis -or data-assimilation -component, which is not covered in this contribution), a series of hindcasts for the period 2003-2009 is carried out, forced at the surface by the Canadian GDPS reforecasts (Smith et al., 2014). These hindcasts test how the model represents upper ocean characteristics and ice cover. Each hindcast implements a new aspect of the modelling or the ice-ocean coupling. Notably, the coupling to the multi-category ice model CICE is tested. The hindcast solutions are then assessed using a verification package under development, including in situ and satellite ice and ocean observations. The conclusions are as follows: (1) the model reproduces reasonably well the time mean, variance and skewness of sea surface height; (2) the model biases in temperature and salinity show that while the mean properties follow expectations, the Pacific Water signature in the Beaufort Sea is weaker than observed; (3) the modelled freshwater content of the Arctic agrees well with observational estimates; (4) the distribution and volume of the sea ice are shown to be improved in the latest hindcast due to modifications to the drag coefficients and to some degree to the ice thickness distribution available in CICE; (5) nonetheless, the model still overestimates the ice drift and ice thickness in the Beaufort Gyre.

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“…The thermodynamic component also accounts for creation of new ice in the open water and at the ice bottom, creation of snow ice at the top of the ice pack, and melting at the upper and lower interfaces of the ice pack. When the net heat is lost from the ocean to the atmosphere in open water, lateral accretion of sea ice occurs with a characteristic depth scale h 0 , which has been set between 0.3 and 1.0 m in previous modeling studies [ Wang et al ., ]. In this study, a relatively smaller value of h 0 = 0.05 m is used to reduce underestimations of sea ice concentrations in the model.…”

Section: Model Setup and Forcingmentioning

confidence: 99%

Formation and distribution of sea ice in the Gulf of St. Lawrence: A process‐oriented study using a coupled ocean‐ice model

Urrego-Blanco

Jiang

2014

JGR Oceans

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A coupled ocean-ice model for the eastern Canadian shelf is used to examine main physical processes affecting sea ice conditions in the Gulf of St. Lawrence (GSL) and adjacent waters. The coupled model is based on NEMO and uses OPA9 as the ocean circulation component and LIM2 as the ice model. The coupled model is forced by atmospheric reanalysis fields produced by Large and Yeager (2004). The model results are used to examine the roles of thermodynamics and dynamics on sea ice distributions and patterns of ice production and melting, and the influence of ice capping on the circulation in the study region. Analysis of model results indicates that local production of sea ice is important in shallower areas over the northern and western GSL. Equatorward advection of sea ice from the St. Lawrence Estuary is affected significantly by the Gaspe Current. An index is used to quantify the relative importance of thermodynamic and dynamics of sea ice in the GSL. It is found that both thermodynamics and dynamics are important over most of the GSL, except for waters around Anticosti Island, in the southeastern Gulf, and over the eastern Scotian Shelf, where dynamics (or sea ice movements) are the most important mechanism for the presence of sea ice. The study also demonstrates that ice capping significantly reduces the strength of the winter circulation in the GSL.

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Sea ice sensitivity to the parameterisation of open water area

Cited by 12 publications

References 12 publications

Arctic sea ice and freshwater sensitivity to the treatment of the atmosphere‐ice‐ocean surface layer

Arctic sea ice and freshwater sensitivity to the treatment of the atmosphere‐ice‐ocean surface layer

A high-resolution ocean and sea-ice modelling system for the Arctic and North Atlantic oceans

Formation and distribution of sea ice in the Gulf of St. Lawrence: A process‐oriented study using a coupled ocean‐ice model

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