Empirical error functions for monthly mean Arctic sea-ice drift
Empirical error functions for 6 different low-resolution Arctic sea-ice drift products are presented on monthly time-scales. To assess the error statistics of the Eulerian ice-drift products, we use high-resolution Lagrangian sea-ice drift obtained from synthetic aperture radar (SAR) images. We proc...
| Published in: | Journal of Geophysical Research: Oceans |
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| Main Authors: | , , , |
| Format: | Article in Journal/Newspaper |
| Language: | unknown |
| Published: |
2015
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| Subjects: | |
| Online Access: | https://epic.awi.de/id/eprint/42397/ https://doi.org/10.1002/2015JC011151 https://hdl.handle.net/10013/epic.49088 |
| Summary: | Empirical error functions for 6 different low-resolution Arctic sea-ice drift products are presented on monthly time-scales. To assess the error statistics of the Eulerian ice-drift products, we use high-resolution Lagrangian sea-ice drift obtained from synthetic aperture radar (SAR) images. We processed the Lagrangian drift to Eulerian drift vectors and used them as a reference for the error assessment. Unlike sea-ice buoy trajectory data traditionally used for that purpose, SAR offers a much larger number of data, which enables us to do a thorough assessment of the error statistics of the Eulerian products under different ice conditions. We find that the error statistics differ between the products and between the seasons. For some products the error is dependent on ice drift speed, while for others the error is rather dependent on ice concentration or on both. The summer ice drifts have roughly a two times larger error than the winter drifts, and show significant mean biases. The calculated empirical error functions allow us to derive uncertainty maps for the respective products. These maps can be used for model validation and data assimilation. |
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