Closed pawelbielski closed 4 years ago
pierretoussing
commented
4 years ago "Plot the derived (and postprocessed) QBO index (at 30 hPa) together with reference, and other versions you derived (70 hPa, Singapore, etc.) for the whole period" done in 3_deriving_QBO
pawelbielski
commented
4 years ago Comments on 3_deriving_QBO.ipynb:
[x] The x axis in both plots is a month number. It is not interpretable. Switching it to years would make more sense.
[x] The plots are not easy to interpret, because there is much going on there. Think of additional representation that would make it easier to see the differences between different versions of QBO. Maybe zooming in in one part would do.
[x] Please specify what do you mean by reference QBO found on the Internet. This will not be clear enough for our climate scientists
pawelbielski
commented
4 years ago Everything is good. As soon as #10 is cleared, this issue can be closed.
pierretoussing
commented
4 years ago After #10, the data is now deseasonalized before the QBO is derived.
Once the QBO index is derived and postprocessed as described in #2 , prepare the jupyter notebook with the results that are the most relevant for climate scientists. This will be the basis for our meeting with them soon.
Plot the Pearson and Mutual information between derived QBO and all other points at the height 30 hPa
[x] for the whole period (just one map)
[x] for the whole period, but for every month separately (12 maps)
[x] for the whole period, but only for the winter months combined (1 map for all three: December, January, February)
[x] Make sure that the jupyter notebook is well structured and meaningfuly annotated with markdown. Think of it as a presentation in form of a notebook. Your main focus should be on plots and their annotations and readability.
After feedback from climate scientists we will decide on the next steps that could be:
how to incorporate the height to the analysis
how to incorporate different time scales
how to improve the visualization for better interpretability