ENSO CLIVAR metrics - reproducing background climatology and ENSO characteristics#
Overview#
Reproducing some ENSO metrics from the [CLIVAR package](https://pcmdi.llnl.gov/pmp-preliminary-results/interactive_plot/portrait_plot/enso_metric/enso_metrics_interactive_portrait_plots_v20231121.html)
Available recipes and diagnostics#
Recipes are stored in esmvaltool/recipes/
ref/recipe_enso_characteristics.yml
ref/recipe_enso_basicclimatology.yml
Diagnostics are stored in esmvaltool/diag_scripts/enso_metrics/
enso_diag1metrics.py: metrics for basic ENSO characteristics.
climatology_diagnostic1.py: metrics for background climatology.
climatology_diagnosticlevel2.py: creating map plots for background climatology.
User settings in recipe#
Variables#
tos (Omon, monthly)
areacello (Ofx)
pr (Amon, monthly)
ts (Amon, monthly)
tauu (Amon, monthly)
Observations and reformat scripts#
GPCP-SG
TROPFLUX
References#
Example plots#

Fig. 345 Bias in the zonal structure of zonal wind stress (Taux) in the equatorial Pacific (5°S-5°N averaged), showing mainly trade winds bias (usually a decreased circulation in the central Pacific and an increased circulation in the western Pacific)#

Fig. 346 Bias of time-mean precipitation (PR) in the equatorial Pacific, showing mainly the double intertropical convergence zone (ITCZ) bias. The left and right maps show respectively the reference and the model#

Fig. 347 Ratio of winter over spring’s standard deviation of sea surface temperature anomalies (SSTA) in the central equatorial Pacific (Niño3.4 averaged), showing the seasonal timing of SSTA. All models are on the same line.#

Fig. 348 Temporal structure of sea surface temperature anomalies (SSTA) in the central equatorial Pacific (Niño3.4 averaged), showing the temporal evolution of SSTA associated with ENSO. Observation is dashed black line.#