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Volume 8, issue 6
The Cryosphere, 8, 2409–2418, 2014
https://doi.org/10.5194/tc-8-2409-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
The Cryosphere, 8, 2409–2418, 2014
https://doi.org/10.5194/tc-8-2409-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 23 Dec 2014

Research article | 23 Dec 2014

Ice and AIS: ship speed data and sea ice forecasts in the Baltic Sea

U. Löptien1 and L. Axell2 U. Löptien and L. Axell
  • 1GEOMAR Helmholtz Centre for Ocean Research, Düsternbrooker Weg 20, 24105 Kiel, Germany
  • 2Swedish Meteorological and Hydrological Institute, Folkborgsvägen 17, 601 76 Norrköping, Sweden

Abstract. The Baltic Sea is a seasonally ice-covered marginal sea located in a densely populated area in northern Europe. Severe sea ice conditions have the potential to hinder the intense ship traffic considerably. Thus, sea ice fore- and nowcasts are regularly provided by the national weather services. Typically, the forecast comprises several ice properties that are distributed as prognostic variables, but their actual usefulness is difficult to measure, and the ship captains must determine their relative importance and relevance for optimal ship speed and safety ad hoc.

The present study provides a more objective approach by comparing the ship speeds, obtained by the automatic identification system (AIS), with the respective forecasted ice conditions. We find that, despite an unavoidable random component, this information is useful to constrain and rate fore- and nowcasts. More precisely, 62–67% of ship speed variations can be explained by the forecasted ice properties when fitting a mixed-effect model. This statistical fit is based on a test region in the Bothnian Sea during the severe winter 2011 and employs 15 to 25 min averages of ship speed.

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Short summary
The Baltic Sea is a seasonally ice-covered marginal sea in central northern Europe. In wintertime, on-time shipping depends crucially on sea ice forecasts. Among the forecasting tools heavily applied are numerical models, which suffer from a lack of calibration data because relevant ice properties are difficult (and costly) to monitor. We developed an innovative and inexpensive approach, by using ship speed observations obtained by the automatic identification system (AIS) to asses such models.
The Baltic Sea is a seasonally ice-covered marginal sea in central northern Europe. In...
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