Notebooks for figures/tables generation

This section describe figure and tables creation notebooks, while notebooks related to creating a data versions dictionnary and to data management and processing are described there

The figures/tables creation notebooks are stored in directory ‘notebooks’;they are provided with expressive names; some details of their design show below, together with a link to their html rendering.

Most notebooks include both a compute phase and a figure plot phase, which can generally be activated separately

Notebooks for global change maps

Next notebooks all produce a multi-panel figure, except for the first two. Excpet for the first one, they all basically call function changes.change_figure_with_caching, which documentation is helpful for understanding details of the computation. The plot itself is done using function figures.change_figure()

  • basic : create a single map of the change in a variable between a reference period and a projection period. A hatching is superimposed, either after Knutti and Sedlacek 2013 robustness index (https://doi.org/10.1038/NCLIMATE1716) or AR6 ‘simple’ scheme
  • change_map_simple : same as basic, but allows for another set of hatching schemes: AR5, AR6 comprehensive and AR6 simple ‘simple’ scheme
  • those notebooks use a single projection experiment, but multiple variable or seasons:
    • change_map_4seasons : compute a 4 panels-figure for one variable where each panel shows the map of the change for a season and a single SSP. Used for AR6/WGI/fig8.14
    • change_map_1SSP_4vars : compute a 9 panels-figure where each panel shows the map of the change of one variable and a single SSP. Used for AR6/WGI/TS7-fig1
    • change_map_1SSP_9vars : compute a 9 panels-figure where each panel shows the map of the change of one variable and a single SSP. Used in AR6/WGI for a preliminary TS figure
  • while those one show 3 projection experiments:
    • change_map_3SSPs_2seasons: compute a 6 panels-figure for change for one variable and 2 seasons (columns) and 3 SSPs (rows). Used for AR6/WGI/fig 8.15
    • change_map_3SSPs_2vars: compute a 6 panels-figure for change for two variables (columns) and 3 SSPs (rows). Used for AR6/WGI/fig 8.17 and 8.18
    • change_map_3SSPs_3horizons : compute a 9 panels-figure for change for one variable, three time horizons (columns) and 3 SSPs (rows). Used in AR6/WGI for a preliminary TS figure
    • change_map_3SSPs_plus_ref : compute a 4 panels-figure for one variable with the reference (top left) and the change for 3 SSPs. Used for AR6/WGI/Box8.2 fig 1
  • and these one deal with warming levels :
    • change_map_1var_at_WL_1SSP_with_clim : compute a single panel figure showing the map of a single variable change for a given warming level and a single SSP, with superimposition of a few contours of the climatology of this variable in e.g. a control experiment. Used in AR6/WGI/fig8.21.
    • change_map_path_dependance : compute a 6 panels-figure showing the changes in some (raw or transformed) variable at two levels of warming, for a series of projection experiments, and their diff, for 2 seasons. Used for AR6/WGI/fig 8.25

Notebooks for plots/tables of rate of change vs warming level

  • A series of notebooks name ‘change_hybrid….’ allow for computing changes over regions, integrated over seasons and hybrid_seasons. What is called an hybrid season here is the union of pairs (region,season), which allow to define e.g. a ‘global winter’ by (DFJ, northern hemisphere) + (JJA, souther hemisphere). A number of regions are knwon by keyword (globe, land, NH, SH …)

    The change are computed with their direct or parametric dependance to the global warming level :

    • direct dependance means that, for each desired warming level, one computes for each model which is the central year corresponding to the warming level and then what is the change for that year in that model. These change values for the same warming level are then e.g. averaged across the models.
    • parametric dependance means that, for a given set of time periods, one computes for each model, on one side the global warming which is then averaged across models, and on the other side the change value, which is also avreaged across models; this provide a parametric dependency of the change to the global warming, where the paremeter is the time period

    In the course of incremental CAMMAC development, the following redundant notebooks were successively developped :

    • notebook change_hybrid_seasons only implements the parametric dependance scheme (it allows to compute changes for a series of time horizons) and has a companion notebooks change_hybrid_seasons_figure for creating a plot of the change time series. It was used for AR6/WGI figure 8.16.
    • notebook change_hybrid_seasons_dT is derived form previous notebook, but implements both schemes (so, it also allows to compute changes for a series of warming levels); it was actualy tested only using the direct dependance scheme (so, for warming levels). With its companion notebook change_hybrid_seasons_dT_figure, it was used for producing AR6/WGI figure Box TS 12; with its other companion notebook change_hybrid_seasons_dT_table, which allows to filter out models that do not reach a givel warming level, it was used for producing two panels for AR6/WGI figure Box TS X f3
    • notebook change_hybrid_seasons_must is derived from previous notebook but can also produces results in a tabular form; it was used in AR6/WGI for producing the data for tables 8.1 and 8.2, in CSV and text mode; it is the best basis for replacong the other computation notebooks but its output dictionnary may have a some differences with what is expected by the change_hybrid…_figure figure creation notebboks

  • change_rate_basins : compute a 6-to-9-panels figure of time evolution for three ensemble-statistics (e.g. mean and two percentiles) for two variables integrated over three basins, and for three SSPs. The variables are a combination of a geopysical variable (e.g. “mrro”) and a time statistics (“mean” or “std”). Few common notebooks parameters apply (see documentation in notebook itself). There are two companion Ncl scripts, automatically called for ploting the results, one for the case of three basins and two statistics (mean an standard deviation), the other for up to 9 basins and only the time mean ( change_rate_basins_1var and change_rate_basins_2vars)

Meridional profiles of zonal means

  • change_zonal_mean : compute a 6-panels figure of zonal mean for statistics of two variables (rows) and three SSPs (columns). The statistics are : ensemble mean and 5% percentiles, ensemble mean on land, and ensemble 5% percentiles of internal variability. Graphs have a color code matching the SSPs. There is a companion Ncl script for ploting the figure, change_zonal_mean.ncl, which is automaticallty called by the notebook