Articles | Volume 24, issue 5
https://doi.org/10.5194/hess-24-2817-2020
https://doi.org/10.5194/hess-24-2817-2020
Research article
 | 
29 May 2020
Research article |  | 29 May 2020

Emerging climate signals in the Lena River catchment: a non-parametric statistical approach

Eric Pohl, Christophe Grenier, Mathieu Vrac, and Masa Kageyama

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Latest update: 19 Jun 2024
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Short summary
Existing approaches to quantify the emergence of climate change require several user choices that make these approaches less objective. We present an approach that uses a minimum number of choices and showcase its application in the extremely sensitive, permafrost-dominated region of eastern Siberia. Designed as a Python toolbox, it allows for incorporating climate model, reanalysis, and in situ data to make use of numerous existing data sources and reduce uncertainties in obtained estimates.