Some useful applications of Climate Statistics using Python.
This repository should cover most of the celebrated methods of Climatology and is destined both for students and professionals. Each notebook is associated, or at least should be, with a script properly said just as eigenvalues and eigenvectors are, which can be used as a 'hands-on' introduction or anything you might want - including especially using for research purposes.
Feel free to make any modifications you find necessary but please, leave the original parts of the script headings there (you might add anything you want as well). This is also an ongoing and completely independent project, which means I'm not getting paid for this. However, you can pay me a beer anytime.
If you want to help with suggestions, critics or anything else feel free to send me an e-mail at hagi.willy[at]gmail.com. And if the content of this repository helps you to get some results for your future publications or any kind of work, please
don't forget to tell me. I'd like to know it!
Currently, the available content is:
1 - An Introduction to Classes with Radiation Laws.
2 - An Introduction to Cartopy Plotting with Xarray.
3 - Monthly Averaging, Anomalies and Climate Indices.
4 - Seasonal Analysis with Xarray.
5 - Autocorrelation Function and Correlogram.
6 - Linear Correlations and Statistical Significance.
7 - Composite Analysis.
8 - Empirical Orthogonal Functions.
9 - Wavelet Transform.
10 - Wavelet Filtering.
11 - Cross-Wavelet Spectrum and Wavelet Coherence.