Determining the form drag contribution to the total stress of the atmospheric flow over ridged sea ice

1983 ◽  
Vol 88 (C7) ◽  
pp. 4524 ◽  
Author(s):  
Sylvain M. Joffre
Keyword(s):  
Sea Ice ◽  
Total Stress ◽  
Form Drag ◽  
Atmospheric Flow

scholarly journals Implementation of a simple thermodynamic sea ice scheme, SICE version 1.0-38h1, within the ALADIN–HIRLAM numerical weather prediction system version 38h1

2018 ◽  
Vol 11 (8) ◽  
pp. 3347-3368 ◽  
Author(s):  
Yurii Batrak ◽  
Ekaterina Kourzeneva ◽  
Mariken Homleid
Keyword(s):  
Sea Ice ◽  
Numerical Weather Prediction ◽  
Mean Absolute Error ◽  
Weather Prediction ◽  
Absolute Error ◽  
The Arctic ◽  
Polar Regions ◽  
Form Drag ◽  
Numerical Weather ◽  
Ice Surface Temperature

Abstract. Sea ice is an important factor affecting weather regimes, especially in polar regions. A lack of its representation in numerical weather prediction (NWP) systems leads to large errors. For example, in the HARMONIE–AROME model configuration of the ALADIN–HIRLAM NWP system, the mean absolute error in 2 m temperature reaches 1.5 ∘C after 15 forecast hours for Svalbard. A possible reason for this is that the sea ice properties are not reproduced correctly (there is no prognostic sea ice temperature in the model). Here, we develop a new simple sea ice scheme (SICE) and implement it in the ALADIN–HIRLAM NWP system in order to improve the forecast quality in areas influenced by sea ice. The new parameterization is evaluated using HARMONIE–AROME experiments covering the Svalbard and Gulf of Bothnia areas for a selected period in March–April 2013. It is found that using the SICE scheme improves the forecast, decreasing the value of the 2 m temperature mean absolute error on average by 0.5 ∘C in areas that are influenced by sea ice. The new scheme is sensitive to the representation of the form drag. The 10 m wind speed bias increases on average by 0.4 m s−1 when the form drag is not taken into account. Also, the performance of SICE in March–April 2013 and December 2015–December 2016 was studied by comparing modelling results with the sea ice surface temperature products from MODIS and VIIRS. The warm bias (of approximately 5 ∘C) of the new scheme is indicated for areas of thick ice in the Arctic. Impacts of the SICE scheme on the modelling results and possibilities for future improvement of sea ice representation in the ALADIN–HIRLAM NWP system are discussed.

scholarly journals Impact of Variable Atmospheric and Oceanic Form Drag on Simulations of Arctic Sea Ice*

2014 ◽  
Vol 44 (5) ◽  
pp. 1329-1353 ◽  
Author(s):  
Michel Tsamados ◽  
Daniel L. Feltham ◽  
David Schroeder ◽  
Daniela Flocco ◽  
Sinead L. Farrell ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Form Drag ◽  
Drag Coefficients ◽  
Arctic Sea ◽  
The Arctic Ocean ◽  
Range Of Values

Abstract Over Arctic sea ice, pressure ridges and floe and melt pond edges all introduce discrete obstructions to the flow of air or water past the ice and are a source of form drag. In current climate models form drag is only accounted for by tuning the air–ice and ice–ocean drag coefficients, that is, by effectively altering the roughness length in a surface drag parameterization. The existing approach of the skin drag parameter tuning is poorly constrained by observations and fails to describe correctly the physics associated with the air–ice and ocean–ice drag. Here, the authors combine recent theoretical developments to deduce the total neutral form drag coefficients from properties of the ice cover such as ice concentration, vertical extent and area of the ridges, freeboard and floe draft, and the size of floes and melt ponds. The drag coefficients are incorporated into the Los Alamos Sea Ice Model (CICE) and show the influence of the new drag parameterization on the motion and state of the ice cover, with the most noticeable being a depletion of sea ice over the west boundary of the Arctic Ocean and over the Beaufort Sea. The new parameterization allows the drag coefficients to be coupled to the sea ice state and therefore to evolve spatially and temporally. It is found that the range of values predicted for the drag coefficients agree with the range of values measured in several regions of the Arctic. Finally, the implications of the new form drag formulation for the spinup or spindown of the Arctic Ocean are discussed.

Observed Atmospheric Coupling between Barents Sea Ice and the Warm-Arctic Cold-Siberian Anomaly Pattern

2016 ◽  
Vol 29 (2) ◽  
pp. 495-511 ◽  
Author(s):  
Svetlana A. Sorokina ◽  
Camille Li ◽  
Justin J. Wettstein ◽  
Nils Gunnar Kvamstø
Keyword(s):  
Sea Ice ◽  
Large Scale ◽  
Barents Sea ◽  
Winter Season ◽  
Surface Air Temperature ◽  
Turbulent Heat Flux ◽  
Turbulent Heat ◽  
Atmospheric Variability ◽  
Atmospheric Flow ◽  
Anomaly Pattern

Abstract The decline in Barents Sea ice has been implicated in forcing the “warm-Arctic cold-Siberian” (WACS) anomaly pattern via enhanced turbulent heat flux (THF). This study investigates interannual variability in winter [December–February (DJF)] Barents Sea THF and its relationship to Barents Sea ice and the large-scale atmospheric flow. ERA-Interim and observational data from 1979/80 to 2011/12 are used. The leading pattern (EOF1: 33%) of winter Barents Sea THF variability is relatively weakly correlated (r = 0.30) with Barents Sea ice and appears to be driven primarily by atmospheric variability. The sea ice–related THF variability manifests itself as EOF2 (20%, r = 0.60). THF EOF2 is robust over the entire winter season, but its link to the WACS pattern is not. However, the WACS pattern emerges consistently as the second EOF (20%) of Eurasian surface air temperature (SAT) variability in all winter months. When Eurasia is cold, there are indeed weak reductions in Barents Sea ice, but the associated THF anomalies are on average negative, which is inconsistent with the proposed direct atmospheric response to sea ice variability. Lead–lag correlation analyses on shorter time scales support this conclusion and indicate that atmospheric variability plays an important role in driving observed variability in Barents Sea THF and ice cover, as well as the WACS pattern.

Parameterization of an Iceberg Drift Model in the Barents Sea

2009 ◽  
Vol 26 (10) ◽  
pp. 2216-2227 ◽  
Author(s):  
Intissar Keghouche ◽  
Laurent Bertino ◽  
Knut Arild Lisæter
Keyword(s):  
Sea Ice ◽  
Barents Sea ◽  
Reanalysis Data ◽  
Ocean Model ◽  
Form Drag ◽  
Drag Coefficients ◽  
Drag Forces ◽  
Drift Model ◽  
The Barents Sea ◽  
Iceberg Drift

Abstract The problem of parameter estimation is examined for an iceberg drift model of the Barents Sea. The model is forced by atmospheric reanalysis data from ECMWF and ocean and sea ice variables from the Hybrid Coordinate Ocean Model (HYCOM). The model is compared with four observed iceberg trajectories from April to July 1990. The first part of the study focuses on the forces that have the strongest impact on the iceberg trajectories, namely, the oceanic, atmospheric, and Coriolis forces. The oceanic and atmospheric form drag coefficients are optimized for three different iceberg geometries. As the iceberg mass increases, the optimal form drag coefficients increase linearly. A simple balance between the drag forces and the Coriolis force explains this behavior. The ratio between the oceanic and atmospheric form drag coefficients is similar in all experiments, although there are large uncertainties on the iceberg geometries. Two iceberg trajectory simulations have precisions better than 20 km during two months of drift. The trajectory error for the two other simulations is less than 25 km during the first month of drift but increases rapidly to over 70 km afterward. The second part of the study focuses on the sea ice parameterization. The sea ice conditions east of Svalbard in winter 1990 were too mild to exhibit any sensitivity to the sea ice parameters.

scholarly journals Form drag on pressure ridges and drag coefficient in the northwestern Weddell Sea, Antarctica, in winter

2013 ◽  
Vol 54 (62) ◽  
pp. 133-138
Author(s):  
Tan Bing ◽  
Lu Peng ◽  
Li Zhijun ◽  
Li Runling
Keyword(s):  
Sea Ice ◽  
Drag Coefficient ◽  
Roughness Length ◽  
Weddell Sea ◽  
Neutral Stability ◽  
Form Drag ◽  
Laser Altimeter ◽  
Dominant Component ◽  
Elevation Data ◽  
Ice Surfaces

AbstractSurface elevation data for sea ice in the northwesternty - Weddell Sea, Antarctica, collected by a helicopter-borne laser altimeter during the Winter Weddell Outflow Study 2006, were used to estimate the form drag on pressure ridges and its contribution to the total wind drag, and the air-ice drag coefficient at a reference height of 10 m under neutral stability conditions (Cdn(10)). This was achieved by partitioning the total wind drag into two components: form drag on pressure ridges and skin drag over rough sea-ice surfaces. The results reveal that for the compacted ice field, the contribution of form drag on pressure ridges to the total wind drag increases with increasing ridging intensity Ri (where Ri is the ratio of mean ridge height to spacing), while the contribution decreases with increasing roughness length. There is also an increasing trend in the air-ice drag coefficient Cdn(10) as ridging intensity Ri increases. However, as roughness length increases, Cdn(10) increases at lower ridging intensities (Ri < 0.023) but decreases at lower ridging intensities (0.023 < Ri < 0.05). These opposing trends are mainly caused by the dominance of the form drag on pressure ridges and skin drag over rough ice surfaces. Generally, the form drag becomes dominant only when the ridging intensity is sufficiently large, while the skin drag is the dominant component at relatively larger ridging intensities. These results imply that a large value of Cdn(10) is caused not only by the form drag on pressure ridges, but also by the skin drag over rough ice surfaces. Additionally, the estimated drag coefficients are consistent with reported measurements in the northwestern Weddell Sea, further demonstrating the feasibility of the drag partition model.

scholarly journals The simulation of Antarctic sea ice in the Hadley Centre Climate Model (HadCM3)

2001 ◽  
Vol 33 ◽  
pp. 585-591 ◽  
Author(s):  
John Turner ◽  
William Connolley ◽  
Doug Cresswell ◽  
Steven Harangozo
Keyword(s):  
Sea Ice ◽  
Satellite Data ◽  
General Circulation ◽  
Climate Model ◽  
Phase Error ◽  
Regional Scale ◽  
Circulation Model ◽  
Ocean General Circulation Model ◽  
Atmospheric Flow ◽  
Antarctic Sea Ice

AbstractAn assessment is presented of the extent and variability of Antarctic sea ice in the non-flux-corrected version of the Hadley Centre’s coupled atmosphere-ocean general circulation model (HadCM3). The results are based on a 100 year segment of a long control run of the model with the sea ice being compared to ice extents and concentrations derived from passive microwave satellite data. Over the year as a whole, the model ice extent (the area with >15% ice concentration) is 91% of that determined from satellite imagery, but, not surprisingly, the regional-scale distribution differs from the observed. Throughout the year there is too much ice near 90° E, which is believed to be present as a result of incorrect ocean currents near Kerguelen. In contrast to the satellite data, there is too little ice to the west of the Antarctic Peninsula as a result of anomalously northerly atmospheric flow, compared to observations. During the winter the sea-ice concentrations in the model are too high, possibly as a result of the simple representation of the sea ice, which does not simulate complex dynamical interactions within the pack. The annual cycle of sea-ice advance/retreat in the model has a phase error, with the winter sea-ice maximum extent being too late by about 1 month.

scholarly journals Implementation of a simple thermodynamic sea ice scheme, SICE version 1.0-38h1, within the ALADIN-HIRLAM numerical weather prediction system version 38h1

2018 ◽  
Author(s):  
Yurii Batrak ◽  
Ekaterina Kourzeneva ◽  
Mariken Homleid
Keyword(s):  
Sea Ice ◽  
Numerical Weather Prediction ◽  
Mean Absolute Error ◽  
Weather Prediction ◽  
Absolute Error ◽  
The Arctic ◽  
Polar Regions ◽  
Form Drag ◽  
Numerical Weather ◽  
General Evaluation

Abstract. Sea ice is an important factor affecting weather regimes, especially in polar regions. A lack of its representation in numerical weather prediction (NWP) systems leads to large errors. For example, in the HARMONIE-AROME model configuration of the ALADIN-HIRLAM NWP system, the mean absolute error in 2 metre temperature reaches 1.5 °C after 15 forecast hours for Svalbard. A possible reason for that is that the sea ice properties are not reproduced correctly (there is no prognostic sea ice temperature in the model). Here, we develop a new SImple sea iCE scheme (SICE) and implement it into the ALADIN-HIRLAM NWP system in order to improve the quality of its forecasts in areas influenced by sea ice. General evaluation of the new parameterization is performed within HARMONIE-AROME by experiments covering the Svalbard and Gulf of Bothnia areas for a selected period in March–April 2013. It is found that using the SICE scheme improves the forecast, decreasing the value of the 2 metre temperature mean absolute error on average by 0.5 °C in areas that are influenced by sea ice. The new scheme is sensitive to the representation of the form drag: it may increase the 10 metre wind speed bias on average by 0.4 m s−1 when the form drag is not taken into account. Also, the modelling results are compared with the sea ice surface temperature observations from MODIS. The warm bias (of approximately 5 °C) of the new scheme is indicated for the areas of thick ice in the Arctic. Impacts of the SICE scheme on the modelling results and possibilities for future improvement of sea ice representation in the ALADIN-HIRLAM NWP system are discussed.

scholarly journals Warm and moist atmospheric flow caused a record minimum July sea ice extent of the Arctic in 2020

2021 ◽  
Author(s):  
Yu Liang ◽  
Haibo Bi ◽  
Haijun Huang ◽  
Ruibo Lei ◽  
Xi Liang ◽  
...  
Keyword(s):  
Sea Ice ◽  
Large Scale ◽  
Extreme Event ◽  
Longwave Radiation ◽  
Decisive Role ◽  
High Energy ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Atmospheric Flow ◽  
Downward Longwave Radiation

Abstract. The satellite observations unveiled that the July sea ice extent of the Arctic shrank to the lowest value in 2020 since 1979, with a major ice retreat in the Eurasian shelf seas including Kara, Laptev, and East Siberian Seas. Based on the ERA-5 reanalysis products, we explored the impacts of warm and moist air-mass transport on this extreme event. The results reveal that anomalously high energy and moisture converged into these regions in the spring months (April to June) of 2020, leading to a burst of high moisture content and warming within the atmospheric column. The convergence is accompanied by local enhanced downward longwave radiation and turbulent fluxes, which is favorable for initiating an early melt onset in the areas with severe ice loss. Once the melt begins, solar radiation played a decisive role in leading to further sea ice depletion due to ice-albedo positive feedback. The typical trajectories of the synoptic cyclones that occurred on the Eurasian side in spring 2020 agree well with the path of atmospheric flow. Assessments suggest that variations in characteristics of the spring cyclones are conducive to the severe melt of sea ice. We argue that large-scale atmospheric circulation and synoptic cyclones act in concert to trigger the exceptional poleward transport of total energy and moisture from April to June to cause this new record minimum of sea ice extent in the following July.

Importance of variable neutral drag coefficients for ocean-ice and air-ice fluxes in polar regions

2021 ◽  
Author(s):  
Jean Sterlin ◽  
Thierry Fichefet ◽  
Francois Massonnet ◽  
Michel Tsamados
Keyword(s):  
Surface Roughness ◽  
Sea Ice ◽  
Surface Fluxes ◽  
The Arctic ◽  
Climate Modelling ◽  
Form Drag ◽  
Drag Coefficients ◽  
Ice Surface ◽  
Melt Ponds ◽  
Ice Surface Roughness

&lt;p&gt;Sea ice features a variety of obstacles to the flow of air and seawater at its top and bottom surfaces. Sea ice ridges, floe edges, ice surface roughness and melt ponds, lead to a form drag that interacts dynamically with the air-ice and ocean-ice fluxes of heat and momentum. In most climate models, surface fluxes of heat and momentum are calculated by bulk formulas using constant drag coefficients over sea ice, to reflect the mean surface roughness of the interfaces with the atmosphere and ocean. However, such constant drag coefficients do not account for the subgrid-scale variability of the sea ice surface roughness. To study the effect of form drag over sea ice on air-ice-ocean fluxes, we have implemented a formulation that estimates drag coefficients in ice-covered areas comprising the effect of sea ice ridges, floe edges and melt ponds, and ice surface skin (Tsamados et al., 2013) into the NEMO3.6-LIM3 global coupled ice-ocean model. In this work, we thoroughly analyse the impacts of this improvement on the model performance in both the Arctic and Antarctic. A particular attention is paid to the influence of this modification on the air-ice-ocean fluxes of heat and momentum, and the characteristics of the oceanic surface layers. We also formulate an assessment of the importance of variable drag coefficients over sea ice for the climate modelling community.&lt;/p&gt;

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