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Hyo-Seok Park, Sukyoung Lee, Seok-Woo Son, Steven B. Feldstein, and Yu Kosaka

.5°. To cross-check our findings from the ERAI, we also analyzed data from the Japanese 25-year Reanalysis Project (JRA-25; Onogi et al. 2007 ) produced by the Japan Meteorological Agency and the Central Research Institute of Electric Power Industry, Japan. The JRA-25 global model has a spectral resolution of T106 and 40 vertical layers with the top at 0.4 hPa. Arctic sea ice concentration data are from the U.S. National Snow and Ice Data Center (NSIDC) where the NASA Team algorithm ( Swift and

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Ariaan Purich, Matthew H. England, Wenju Cai, Yoshimitsu Chikamoto, Axel Timmermann, John C. Fyfe, Leela Frankcombe, Gerald A. Meehl, and Julie M. Arblaster

experiments We utilize passive microwave sea ice concentration (SIC) processed using the National Snow and Ice Data Center (NSIDC) bootstrap algorithm ( Comiso and Nishio 2008 ; Meier et al. 2015 ) and SST from the Hadley Centre Sea Ice and Sea Surface Temperature dataset (HadISST; Rayner et al. 2003 ). We also assess SIC processed using the NASA team algorithm, as it is possible that spurious trends are present in the bootstrap algorithm dataset ( Eisenman et al. 2014 ) and results are found to be

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Bradley P. Goodwin, Ellen Mosley-Thompson, Aaron B. Wilson, Stacy E. Porter, and M. Roxana Sierra-Hernandez

) begin in 1947 and from Rothera (67.5°S, 68.1°W; 32 m MSL) begin in 1976. h. Changepoint analysis A key challenge in changepoint analysis is the ability to detect multiple changes within a given time series or sequence. The changepoints in the time series of the 11-yr running correlations between A n and the Fogt SAM index were calculated using the R changepoint package presented by Killick and Eckley (2014) . The pruned exact linear time algorithm was used to identify times when a change occurred

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