Database of daily Lagrangian Arctic sea ice parcel drift tracks with coincident ice and atmospheric conditions
Since the early 2000s, sea ice has experienced an increased rate of decline in thickness and extent and is transitioning to a seasonal ice cover. This shift to thinner, seasonal ice in the ‘New Arctic’ is accompanied by a reshuffling of energy flows at the surface. Understanding of the magnitude and...
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| Format: | Article in Journal/Newspaper |
| Language: | unknown |
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2022
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| Online Access: | https://zenodo.org/record/7489397 https://doi.org/10.5281/zenodo.7489397 |
| Summary: | Since the early 2000s, sea ice has experienced an increased rate of decline in thickness and extent and is transitioning to a seasonal ice cover. This shift to thinner, seasonal ice in 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 daily sea ice parcel drift tracks produced in a Lagrangian framework. This dataset consists of daily time series of sea ice parcel locations, sea ice and snow conditions, and atmospheric states. Building on previous work, this dataset includes remotely sensed radiative and turbulent fluxes from which the surface energy budget can be calculated. 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. Results show ice parcels generally remain within 100 km of the corresponding buoy, with a mean distance of 82.6 km and median distance of 54 km. The sea ice mass balance buoys also provide recordings of sea ice thickness, snow depth, and air temperature and pressure which were compared to this database. Ice thickness and snow depth typically are less accurate when compared to the buoy point measurements than air temperature and pressure due to the high spatial variability of the former two quantities. The correlations between the ice parcel and buoy data are high, which highlights the reliability of this Lagrangian 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. Applications such as these may shed light on the ... |
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