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. 2018 May 22;5:180086. doi: 10.1038/sdata.2018.86

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Copyright © 2018, The Author(s)

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/ The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files made available in this article.

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Correlation between the data assimilation-based PDSI reconstruction and the PDSI reconstructions of the drought atlases from the years 1500–2000: the North American drought atlas (NADA)^14,51, the Old World drought atlas (OWDA)¹⁵, the Monsoon Asia drought atlas (MADA)⁵², the Mexican drought atlas (MXDA)⁵³, and the Australia and New Zealand drought atlas (ANZDA)⁵⁴. Correlations are computed using the JJA reconstruction for NADA, OWDA, MADA, and MXDA and the DJF reconstruction for ANZDA. Prior to computing the correlations, the drought atlases were interpolated to the land surface grid of the CESM LME model simulation used in the data assimilation-based reconstruction presented here.