Empirical error functions for monthly mean Arctic sea‐ice drift. Issue 11 (19th November 2015) - Sumata, Hiroshi; Gerdes, Rüdiger; Kauker, Frank; Karcher, Michael
Abstract: Empirical error functions for six 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 enable 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 2 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. Key Points: Empirical error functions are formulated based on error statistics of ice drift products High‐resolution SAR data are processed to provide reference data for the error assessment Deduced error and bias functions are directly applicable to model validation and data assimilation