4.3 Article

Model experiments on snow and ice thermodynamics in the Arctic Ocean with CHINARE 2003 data

Journal

JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS
Volume 113, Issue C9, Pages -

Publisher

AMER GEOPHYSICAL UNION
DOI: 10.1029/2007JC004654

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Funding

  1. EC-funded project DAMOCLES [18509]
  2. Sixth Framework Program, by DFG [LU 818/1-1]
  3. Natural Science Foundation of China [40233032, 40376006]

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Snow and ice thermodynamics over the Arctic Ocean were simulated applying a one-dimensional model. A number of numerical experiments in synoptic (10 days in early autumn) and seasonal (May-September) scales were carried out to investigate the impact of external forcing, snow physics, and the model resolution: the number of layers in both snow and ice ranged from 3 to 40. The model forcing was based on in situ observations carried out in 2003 during the Chinese National Arctic Research Expedition (CHINARE) as well as on forecasts and analyses of the European Centre for Medium-Range Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction (NCEP)/ National Center for Atmospheric Research (NCAR). The model results were compared against the results of the ECMWF and NCEP/ NCAR sea ice schemes. The ECMWF operational precipitation forecasts yielded realistic seasonal snowfall, while the precipitation in NCEP/ NCAR reanalysis was unrealistically large. A good result on snow thickness evolution also strongly depended on the accuracy of modeled snowmelt. A time-dependent surface albedo parameterization was critical for the seasonal evolution of snow and ice thickness. Application of 15-20 model levels in snow and ice is recommended as it (1) ensured good reproduction of the vertical snow/ ice temperature profile also when solar radiation was large, (2) decreased the sensitivity of snow and ice mass balance to changes in surface albedo, (3) enabled the calculation of subsurface melting of snow and ice, and (4) reasonably reproduced the superimposed ice formation and onset of ice melt. In autumn, however, the accuracy of atmospheric forcing was more important than the model resolution.

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