Scientific Data (Feb 2023)

Database of daily Lagrangian Arctic sea ice parcel drift tracks with coincident ice and atmospheric conditions

  • Sean Horvath,
  • Linette Boisvert,
  • Chelsea Parker,
  • Melinda Webster,
  • Patrick Taylor,
  • Robyn Boeke,
  • Steven Fons,
  • J. Scott Stewart

DOI
https://doi.org/10.1038/s41597-023-01987-6
Journal volume & issue
Vol. 10, no. 1
pp. 1 – 16

Abstract

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Abstract Since the early 2000s, sea ice has experienced an increased rate of decline in thickness, extent and age. This new regime, coined the ‘New Arctic’, is accompanied by a reshuffling of energy flows at the surface. Understanding of the magnitude and nature of this reshuffling and the feedbacks therein remains limited. A novel database is presented that combines satellite observations, model output, and reanalysis data with sea ice parcel drift tracks in a Lagrangian framework. This dataset consists of daily time series of sea ice parcel locations, sea ice and snow conditions, and atmospheric states, including remotely sensed surface energy budget terms. Additionally, flags indicate when sea ice parcels travel within cyclones, recording cyclone intensity and distance from the cyclone center. The quality of the ice parcel database was evaluated by comparison with sea ice mass balance buoys and correlations are high, which highlights the reliability of this database in capturing the seasonal changes and evolution of sea ice. This database has multiple applications for the scientific community; it can be used to study the processes that influence individual sea ice parcel time series, or to explore generalized summary statistics and trends across the Arctic.