EGU23-11483
https://doi.org/10.5194/egusphere-egu23-11483
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

The Sea Ice Drift Forecast Experiment (SIDFEx): Introduction and applications

Valentin Ludwig1, Helge Gößling1, and the SIDFEx Team*
Valentin Ludwig and Helge Gößling and the SIDFEx Team
  • 1Alfred Wegener Institute, Climate Dynamics, Bremen, Germany (valentin.ludwig@awi.de)
  • *A full list of authors appears at the end of the abstract

We introduce the Sea Ice Drift Forecast Experiment (SIDFEx) database. SIDFEx is a collection of close to 180,000 lagrangian drift forecasts for the trajectories of specified assets (mostly buoys) on the Arctic and Antarctic sea ice, at lead times from daily to seasonal scale and mostly daily resolution. The forecasts are based on systems with varying degrees of complexity, ranging from free-drift forecasts to forecasts by fully coupled dynamical general circulation models. Combining several independent forecasts allows us to construct a best-guess consensus forecast, with a seamless transition from systems with lead times of up to 10 days to systems with seasonal lead times. The forecasts are generated by 13 research groups using 23 distinct forecasting systems and sent operationally to the Alfred-Wegener-Institute, where they are archived and evaluated. Many systems send forecasts in near-real time.

One key purpose when starting SIDFEx in 2017 was to find the optimal starting position for the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC). Over the years, more applications evolved: During MOSAiC, the SIDFEx forecasts were used for ordering high-resolution TerraSAR-X images in advance, with a hit rate of 80%. During the Endurance22 expedition, we supported the onboard team with near-real time forecasts, contributing to the success of the mission. Currently, we evaluate drift forecasts for several buoys of the MOSAiC Distributed Network (DN). We know that there is skill in predicting the location of single buoys. Now, we extend this to studying the deformation of the polygon spanned by the DN buoys. Deformation is derived from the spatial velocity derivatives of the buoy array. We find low correlation coefficients between the deformation in the models and the observed deformation for a small-scale DN configuration, but larger and significant correlations around 0.7 for larger configurations and an Arctic-wide buoy array.

SIDFEx Team:

Helge F. Goessling (1), Axel Schweiger (2), Valentin Ludwig (1), Laurent Bertino (3), Ed Blockley (4), Frédéric Dupont (5), Wendy Ermold (2), Rüdiger Gerdes (1), Robert Grumbine (6), Yukie Hata (5), Jennifer Hutchings (7), Antonia A. Jost (1), Frank Kauker (1), Thomas Krumpen (1), Jean-François Lemieux (5), François Massonnet (8), Bill Merryfield (5), E. Joseph Metzger (9), Malte Müller (10), Marcel Nicolaus (1), Cyril Palerme (10), Michael W. Phelps (9,11), Thomas Rackow (1,12), Till A. S. Rasmussen (13), Simon F. Reifenberg (1), Ignatius Rigor (2), Suman Singha (13,14), Amy Solomon (15,16), Nick Szapiro (17), Steffen Tietsche (12), Jinlun Zhang (2)

How to cite: Ludwig, V. and Gößling, H. and the SIDFEx Team: The Sea Ice Drift Forecast Experiment (SIDFEx): Introduction and applications, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-11483, https://doi.org/10.5194/egusphere-egu23-11483, 2023.

Supplementary materials

Supplementary material file