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. 2020 Sep 22;11:4621. doi: 10.1038/s41467-020-18479-5

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© The Author(s) 2020

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 2 — Left panels show changes in mean Landsat NDVI_max [unitless] anomalies for the Arctic and each zone from 1985 to 2016 (a) and 2000 to 2016 (d). Middle panels show changes in mean summer warmth index [SWI; °C] anomalies from 1985 to 2016 (b) and 2000 to 2016 (e) derived from five temperature data sets. Right panels show the relationship between mean Arctic NDVI_max and SWI anomalies from 1985 to 2016 (c) and 2000 to 2016 (f). Spearman’s correlation coefficients (r_s) relating NDVI_max and SWI are provided for each period. Narrow error bands and whiskers depict 95% confidence intervals derived from Monte Carlo simulations (n = 10³). Note that while mean SWI time series are based on pan-Arctic data, the NDVI_max time series, and NDVI_max–SWI relationships are based on sites where Landsat data were available from 1985 to 2016 (a, c) and 2000 to 2016 (d, f), as shown in Fig. 1.