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. 2017 Jul 19;7:5811. doi: 10.1038/s41598-017-05373-2

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© The Author(s) 2017

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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Spatial maps of model relative biases in predicting the magnitude of precipitation anomalies for the five extreme droughts of 1983 (a1 to a4), 1998 (b1 to b4), 2005 (c1 to c4), 2010 (d1 to d4), and 2016 (e1 to e4). The areas where magnitude of the observed negative standardized anomalies of precipitation is lower than 1.0 are masked out in order to only focus on regions that experience intense drought. Here, the least-square fit is implemented over the entire analysis period (1982–2017) to equally account for all five extreme droughts when deriving the regression coefficients of the multivariate linear model. Seasonal cycles for each year start from September of the previous year (e.g. SON 2004 for 2005 seasonal cycle). Figures created with: The NCAR Command Language (Version 6.3.0) [Software]. (2016). Boulder, Colorado: UCAR/NCAR/CISL/TDD. http://dx.doi.org/10.5065/D6WD3XH5.