Articles | Volume 24, issue 5
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

Data sets

CRUNCEP Version 7 – Atmospheric Forcing Data for the Community Land Model N. Viovy

ecmwf-api-client ECMWF – European Centre for Medium-Range Weather Forecasts

Model code and software

ToE_tools: A non-parametric method to calculate the Time of Emergence of climate signals E. Pohl

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.