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. 2022 Oct 27;13:6416. doi: 10.1038/s41467-022-34221-9

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© The Author(s) 2022

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. 4 — a–d show the wavelet coherence between PC1 of reconstructed streamflow and four large-scale climate patterns, i.e., El Niño Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), and Indian Ocean Dipole (IOD) that significantly affect PC1 of reconstructed streamflow. Wavelet coherence analysis between PC2 of reconstructed streamflow and the four large-scale climate patterns is shown in e–h. Solid black contours enclose the statistically significant coherence at a 5% significance level of the white noise process. White lines represent the cone of influence. Color bar represents coherence ranges from low (blue) to high (red). With different lengths of paleoclimate records, the wavelet coherence analysis between leading PCs and different climate indices is based on their overlapping periods.