Journal metrics

Journal metrics

  • IF value: 4.524 IF 4.524
  • IF 5-year value: 5.558 IF 5-year 5.558
  • CiteScore value: 4.84 CiteScore 4.84
  • SNIP value: 1.425 SNIP 1.425
  • SJR value: 3.034 SJR 3.034
  • IPP value: 4.65 IPP 4.65
  • h5-index value: 52 h5-index 52
  • Scimago H index value: 55 Scimago H index 55
The Cryosphere, 11, 2265-2281, 2017
https://doi.org/10.5194/tc-11-2265-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
29 Sep 2017
Sea ice assimilation into a coupled ocean–sea ice model using its adjoint
Nikolay V. Koldunov1,2,3, Armin Köhl1, Nuno Serra1, and Detlef Stammer1 1Institut für Meereskunde, Centrum für Erdsystemforschung und Nachhaltigkeit, Universität Hamburg, Hamburg, Germany
2MARUM – Center for Marine Environmental Sciences, Bremen, Germany
3AWI – Alfred Wegener Institute for Polar and Marine Research, Bremerhaven, Germany
Abstract. Satellite sea ice concentrations (SICs), together with several ocean parameters, are assimilated into a regional Arctic coupled ocean–sea ice model covering the period of 2000–2008 using the adjoint method. There is substantial improvement in the representation of the SIC spatial distribution, in particular with respect to the position of the ice edge and to the concentrations in the central parts of the Arctic Ocean during summer months. Seasonal cycles of total Arctic sea ice area show an overall improvement. During summer months, values of sea ice extent (SIE) integrated over the model domain become underestimated compared to observations, but absolute differences of mean SIE to the data are reduced in nearly all months and years. Along with the SICs, the sea ice thickness fields also become closer to observations, providing added value by the assimilation. Very sparse ocean data in the Arctic, corresponding to a very small contribution to the cost function, prevent sizable improvements of assimilated ocean variables, with the exception of the sea surface temperature.

Citation: Koldunov, N. V., Köhl, A., Serra, N., and Stammer, D.: Sea ice assimilation into a coupled ocean–sea ice model using its adjoint, The Cryosphere, 11, 2265-2281, https://doi.org/10.5194/tc-11-2265-2017, 2017.
Publications Copernicus
Download
Short summary
The paper describes one of the first attempts to use the so-called adjoint data assimilation method to bring Arctic Ocean model simulations closer to observation, especially in terms of the sea ice. It is shown that after assimilation the model bias in simulating the Arctic sea ice is considerably reduced. There is also additional improvement in the sea ice thickens representation that is not assimilated directly.
The paper describes one of the first attempts to use the so-called adjoint data assimilation...
Share