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](Code)) and loading the data files ([.mat files](Data)) requires the pre-installation of [MATLAB](/https://de.mathworks.com/products/matlab.html). 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.
Monitoring Velocity Changes using Ambient Seismic Noise
SeisMIC (Seismological Monitoring using Interferometric Concepts) is a python software that emerged from the miic library. SeisMIC provides functionality to apply some concepts of seismic interferometry to different data of elastic waves. Its main use case is the monitoring of temporal changes in a mediums Green's Function (i.e., monitoring of temporal velocity changes).
SeisMIC will handle the whole workflow to create velocity-change time-series including: Downloading raw data, Adaptable preprocessing of the waveform data, Computating cross- and/or autocorrelation, Plotting tools for correlations, Database management of ambient seismic noise correlations, Adaptable postprocessing of correlations, Computation of velocity change (dv/v) time series, postprocessing of dv/v time series, plotting of dv/v time-series