Code for Methane Flux Data

DOI

This repository contains the codes produced for the article "Long-term observations reveal rise in early summer methane emissions from Siberian tundra" by Norman Rößger, Torsten Sachs, Christian Wille, Julia Boike and Lars Kutzbach.

In the article, the authors report an increasing trend of methane emissions for June and July at a permafrost site in Siberia (Lena River Delta). Using the longest set of observational methane flux data in the Arctic, the authors demonstrate that the continuous warming has begun to trigger the projected enhancement of methane release in Arctic permafrost ecosystems.

This software is written in MATLAB. Running the codes (.m files) and loading the data files (.mat files) requires the pre-installation of MATLAB. IMPORTANT: The repository only contains dummy data. The data that is needed to run the code can be requested by Torsten Sachs and Christian Wille (contact authors). Although the scripts and the data files have been tested for newer versions of MATLAB (>= MATLAB R2017a). The code might also run in older versions of MATLAB, but this has not been tested.

Identifier
DOI https://doi.org/10.5880/GFZ.1.4.2022.010
Related Identifier https://doi.org/10.1038/s41558-022-01512-4
Metadata Access http://doidb.wdc-terra.org/oaip/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:doidb.wdc-terra.org:7629
Provenance
Creator Rößger, Norman; Sachs, Torsten ORCID logo; Wille, Christian ORCID logo; Boike, Julia ORCID logo; Kutzbach, Lars ORCID logo
Publisher GFZ Data Services
Contributor Rößger, Norman; Sachs, Torsten; Wille, Christian; Boike, Julia; Kutzbach, Lars
Publication Year 2022
Rights European Union Public Licence 1.2 (C) 2022 the authors and Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences; https://opensource.org/licenses/EUPL-1.2
OpenAccess true
Contact Sachs, Torsten (GFZ German Research Centre for Geosciences, Potsdam, Germany); Wille, Christian (GFZ German Research Centre for Geosciences, Potsdam, Germany)
Representation
Resource Type Dataset
Discipline Chemistry; Natural Sciences
Spatial Coverage (126.446W, 72.364S, 126.534E, 72.391N); Samoylov, Lena River Delta, Siberia, Russia