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. 2017 Apr 27;7:1228. doi: 10.1038/s41598-017-01306-1

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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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(a) 1 day 50 year rainfall maxima (in mm) for 23 cities across India assuming stationary conditions, (b) same as (a) but for 1 day 100 year rainfall maxima, (c) percentage bias in 1 day 50 year rainfall maxima considering stationary and nonstationary conditions, (d) same as (c) but for 1 day 100 year, (e) same as (c) but mean and standard deviation in percentage bias for different climatic zones and (f) same as (d) but for 1 day 100 year rainfall. DPT and T850 were used as covariate to account nonstationary conditions. Percentage change $(= \frac{N S - S}{N S} \times 100)$ in 1 day 50–100 year rainfall maxima were estimated using the stationary (S) and nonstationary (NS) conditions. Return values were estimated using ismev package in “R”. The figure was developed using the Generic Mapping Tools (GMT, https://www.soest.hawaii.edu/gmt/).