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Atmosphere 2018, 9(11), 437; https://doi.org/10.3390/atmos9110437

Precursors of September Arctic Sea-Ice Extent Based on Causal Effect Networks

1
Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
2
Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle, WA 98195, USA
3
Pacific Marine Environmental Laboratory, National Oceanic and Atmospheric Administration, Seattle, WA 98115, USA
4
Department of Atmospheric and Environmental Sciences, University at Albany, State University of New York, Albany, NY 12222, USA
5
State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
*
Authors to whom correspondence should be addressed.
Received: 1 October 2018 / Revised: 30 October 2018 / Accepted: 2 November 2018 / Published: 9 November 2018
(This article belongs to the Section Climatology and Meteorology)
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Abstract

Although standard statistical methods and climate models can simulate and predict sea-ice changes well, it is still very hard to distinguish some direct and robust factors associated with sea-ice changes from its internal variability and other noises. Here, with long-term observations (38 years from 1980 to 2017), we apply the causal effect networks algorithm to explore the direct precursors of September Arctic sea-ice extent by adjusting the maximal lead time from one to eight months. For lead time of more than three months, June downward longwave radiation flux in the Canadian Arctic Archipelago is the only one precursor. However, for lead time of 1–3 months, August sea-ice concentration in Western Arctic represents the strongest positive correlation with September sea-ice extent, while August sea-ice concentration factors in other regions have weaker influences on the marginal seas. Other precursors include August wind anomalies in the lower latitudes accompanied with an Arctic high pressure anomaly, which induces the sea-ice loss along the Eurasian coast. These robust precursors can be used to improve the seasonal predictions of Arctic sea ice and evaluate the climate models. View Full-Text
Keywords: precursors; causal effect networks; sea ice; Arctic precursors; causal effect networks; sea ice; Arctic
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Li, S.; Wang, M.; Bond, N.A.; Huang, W.; Wang, Y.; Xu, S.; Liu, J.; Wang, B.; Bai, Y. Precursors of September Arctic Sea-Ice Extent Based on Causal Effect Networks. Atmosphere 2018, 9, 437.

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