Tutorials
Welcome to the tutorial section. Here you will find examples in the form of Jupyter notebooks that you can either download from the GitLab repository or this documentation website.
Please keep the architecture as follow:
your_wmsan_dir/
|-- notebooks/
| └── body_waves/
│ ├── amplification_coeff.ipynb
│ └── microseismic_sources.ipynb
│ └── rayleigh_waves/
│ ├── amplification_coeff.ipynb
│ ├── microseismic_sources.ipynb
│ ├── spectrograms.ipynb
│ ├── rayleigh_source.ipynb
│ └── synthetic_CCF.ipynb
│ └── wmsan_to_noisi.ipynb
│ └── temporal_variations.ipynb
|-- data/
│ ├── C.nc
│ ├── cP.nc
│ ├── cS.nc
│ ├── longuet_higgins.txt
│ ├── stations_pair.txt
│ └── ww3.07121700.dpt
Additionnal files can be found on the GitLab repository except for synthetic cross-correlations AxiSEM archive which is hosted on Zenodo.
Site Effect - Amplification Coefficients
Secondary microseisms generation results from the interaction of oceanic waves of similar periods travelling in opposite directions, see SANS. When the resulting standing pressure field hits the seafloor interface, seismic waves can be emitted and travelling through the crust. Therefore the bathymetry and frequency content at source location has an impact on observed seismic waves. Site effect or amplification coefficient allow to quantify this transmition to the crust.
Equivalent Vertical Force - Source Maps
Once the site effect is quantified, let's make source distribution maps based on the WW3 outputs which can be compared to seismic data based source maps (e.g., SANS, backprojection, ...).
Temporal Variations
If you want to see the temporal evolution of the source intensity in a specific area check out this example (dv/v series comparison, clustering occurence, ...).
Synthetic Cross-correlation Functions
To compute synthetic cross-correlations with a WW3 model based source distribution.
WMSAN to noisi
To use the equivalent vertical force as a starting model for noisi.
Synthetic Spectrograms
To compute synthetic spectrograms, following an example from Ardhuin et al. (2011) and using a data comparison from Stutzmann et al. (2012).