Transient Climate Response to Cumulative CO2 Emissions (TCRE)#

Calculate Transient Climate Response to Cumulative CO2 Emissions (TCRE).

Description#

This diagnostics calculates the Transient Climate Response to Cumulative CO2 Emissions (TCRE) and produces relevant plots.

Author#

Manuel Schlund (DLR, Germany)

Configuration options in recipe#

calc_tcre_period: list of int, optional (default: [90, 110])

Period considered to calculate TCRE. This needs to be a sequence of two integers, where the first integer defines the start and the second integer the end of a slice. TCRE is calculated by averaging over a subarray of the temperature change array which is determined by this slice. For example, if the input data are annual means, the values here correspond to the years (measured from simulation start) over which the temperature change is averaged (by default from years 90 to 110).

exp_control: str, optional (default: ‘esm-piControl’)

Name of the control experiment.

exp_target: str, optional (default: ‘esm-flat10’)

Name of the target experiment.

figure_kwargs: dict, optional

Optional keyword arguments for matplotlib.pyplot.figure(). By default, uses constrained_layout: true.

gridline_kwargs: dict, optional

Optional keyword arguments for grid lines. By default, color: lightgrey, alpha: 0.5 are used. Use gridline_kwargs: false to not show grid lines.

groupby_facet: str, optional (default: ‘dataset’)

Facet used to group datasets. TCRE is calculated for each group element individually.

legend_kwargs: dict, optional

Optional keyword arguments for matplotlib.pyplot.legend(). Use legend_kwargs: false to not show legends.

matplotlib_rc_params: dict, optional

Optional matplotlib.RcParams used to customize matplotlib plots. Options given here will be passed to matplotlib.rc_context() and used for all plots produced with this diagnostic.

plot_kwargs: dict, optional

Optional keyword arguments for iris.plot.plot(). Dictionary keys are elements identified by groupby_facet or default, e.g., CMIP6 if groupby_facet: project or CESM2 if groupby_facet: dataset. Dictionary values are dictionaries used as keyword arguments for iris.plot.plot().

pyplot_kwargs: dict, optional

Optional calls to functions of matplotlib.pyplot. Dictionary keys are functions of matplotlib.pyplot. Dictionary values are used as argument(s) for these functions (if values are dictionaries, these are interpreted as keyword arguments; otherwise a single argument is assumed).

savefig_kwargs: dict, optional

Optional keyword arguments for matplotlib.pyplot.savefig(). By default, uses bbox_inches: tight, dpi: 300, orientation: landscape.

seaborn_settings: dict, optional

Options for seaborn.set_theme() (affects all plots). By default, uses style: ticks.

var_emissions: str, optional (default: ‘cumulative_fco2antt’)

Short name of the variable describing the cumulative anthropogenic CO2 emissions. This must be the name of the variable given in the recipe. Note that using the cumulative_sum() preprends cumulative_ to this name.

var_temperature: str, optional (default: ‘tas’)

Short name of the variable describing the temperature change. This must be the name of the variable given in the recipe.