willyhagi / climate-data-science Goto Github PK
View Code? Open in Web Editor NEWClimate Data Science and Earth Observation with Python.
License: MIT License
Climate Data Science and Earth Observation with Python.
License: MIT License
In "Wavelet Transform",TC98 says explicitly that "this red-noise was estimated from( α1+√α2) /2 where α1and α2 are the lag-1 and lag-2 autocorrelations of the Niño3 SST". So this is NOT a constant value, valid for each and every time series, but one which must be estimated. when α2<0,α=?, how to compute it? Thank you!
Hi Willy, many thanks for your interesting article on TDS.
Unfortunately your Notebook does not work "out of the box", which will leave novices/students not getting to the gist of your good work,
May I propose that you add the list of required conda install(s) (for a standard anaconda installation). Here's what I did to get your notebook running:
conda install -c intake intake
conda install xarray dask netCDF4 bottleneck
conda install -c conda-forge proplot
conda install -c conda-forge intake-esm
conda install -c conda-forge cartopy
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