scholarly journals Modeling of iceberg drift in the marginal ice zone of the Barents Sea

2019 ◽  
Vol 88 ◽  
pp. 210-222 ◽  
Author(s):  
A. Marchenko ◽  
N. Diansky ◽  
V. Fomin
2006 ◽  
Vol 59 (1-2) ◽  
pp. 1-24 ◽  
Author(s):  
Paul Wassmann ◽  
Dag Slagstad ◽  
Christian Wexels Riser ◽  
Marit Reigstad

2008 ◽  
Vol 55 (20-21) ◽  
pp. 2245-2256 ◽  
Author(s):  
Anna Pasternak ◽  
Elena Arashkevich ◽  
Marit Reigstad ◽  
Paul Wassmann ◽  
Stig Falk-Petersen

2015 ◽  
Vol 15 (19) ◽  
pp. 26609-26660 ◽  
Author(s):  
A. D. Elvidge ◽  
I. A. Renfrew ◽  
A. I. Weiss ◽  
I. M. Brooks ◽  
T. A. Lachlan-Cope ◽  
...  

Abstract. Comprehensive aircraft observations are used to characterise surface roughness over the Arctic marginal ice zone (MIZ) and consequently make recommendations for the parameterization of surface momentum exchange in the MIZ. These observations were gathered in the Barents Sea and Fram Strait from two aircraft as part of the Aerosol–Cloud Coupling And Climate Interactions in the Arctic (ACCACIA) project. They represent a doubling of the total number of such aircraft observations currently available over the Arctic MIZ. The eddy covariance method is used to derive estimates of the 10 m neutral drag coefficient (CDN10) from turbulent wind velocity measurements, and a novel method using albedo and surface temperature is employed to derive ice fraction. Peak surface roughness is found at ice fractions in the range 0.6 to 0.8 (with a mean interquartile range in CDN10 of 1.25 to 2.85 × 10−3). CDN10 as a function of ice fraction is found to be well approximated by the negatively skewed distribution provided by a leading parameterization scheme (Lüpkes et al., 2012) tailored for sea ice drag over the MIZ in which the two constituent components of drag – skin and form drag – are separately quantified. Current parameterization schemes used in the weather and climate models are compared with our results and the majority are found to be physically unjustified and unrepresentative. The Lüpkes et al. (2012) scheme is recommended in a computationally simple form, with adjusted parameter settings. A good agreement is found to hold for subsets of the data from different locations despite differences in sea ice conditions. Ice conditions in the Barents Sea, characterised by small, unconsolidated ice floes, are found to be associated with higher CDN10 values – especially at the higher ice fractions – than those of Fram Strait, where typically larger, smoother floes are observed. Consequently, the important influence of sea ice morphology and floe size on surface roughness is recognised, and improvement in the representation of this in parameterization schemes is suggested for future study.


ARCTIC ◽  
1996 ◽  
Vol 49 (1) ◽  
Author(s):  
George L. Hunt ◽  
Vidar Bakken ◽  
Fridtjof Mehlum

2008 ◽  
Vol 55 (20-21) ◽  
pp. 2330-2339 ◽  
Author(s):  
Tobias Tamelander ◽  
Marit Reigstad ◽  
Haakon Hop ◽  
Michael L. Carroll ◽  
Paul Wassmann

2009 ◽  
Vol 26 (10) ◽  
pp. 2216-2227 ◽  
Author(s):  
Intissar Keghouche ◽  
Laurent Bertino ◽  
Knut Arild Lisæter

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.


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