ArticleScientific data2024
A dataset of the daily edge of each polynya in the Antarctic.
Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
2 citing papers in PubMed.
- Reconstruction of Antarctic sea ice thickness from sparse satellite laser altimetry data via deep learning.Scientific data · 2025Article
- A dataset of the daily edge of each polynya in the Antarctic.Scientific data · 2024Article
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Authors and funding
6 authors.
Funding
Abstract
Polynyas play a critical role in the formation of Antarctic Bottom Water and the enhancement of polar primary productivity. Accurate and exhaustive identification of Antarctic polynyas is fundamental to advancing in-depth research. However, due to methodological limitations, previous studies paid more attention to frequent polynyas and infrequent polynyas have not been investigated much despite that they could be vulnerable to climate change. Inspired by a cyclone tracking algorithm, we develop a novel method to overcome challenges identifying all types of polynyas satisfying spatiotemporal criteria and tracing their daily evolution, extracting from an extensive amount of sea ice concentration data. Based on it, we establish a dataset called "Daily Edge of Each Polynya in Antarctica" (DEEP-AA). Validation against remote sensing and ship-based observations confirms DEEP-AA's reliability. Compared to existing maps, the DEEP-AA identifies a threefold number of polynyas and reveals the seasonal area recovery of infrequent polynyas is earlier than frequent ones.
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Registered trials
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