.. _recipe_ecs_scatter: Emergent constraints for equilibrium climate sensitivity ======================================================== Overview -------- Calculates equilibrium climate sensitivity (ECS) versus 1) S index, D index and lower tropospheric mixing index (LTMI); similar to fig. 5 from Sherwood et al. (2014) 2) southern ITCZ index and tropical mid-tropospheric humidity asymmetry index; similar to fig. 2 and 4 from Tian (2015) 3) covariance of shortwave cloud reflection (Brient and Schneider, 2016) 4) climatological Hadley cell extent (Lipat et al., 2017) 5) temperature variability metric; similar to fig. 2 from Cox et al. (2018) 6) total cloud fraction difference between tropics and mid-latitudes; similar to fig. 3 from Volodin (2008) 7) response of marine boundary layer cloud (MBLC) fraction changes to sea surface temperature (SST); similar to fig. 3 of Zhai et al. (2015) 8) Cloud shallowness index (Brient et al., 2016) 9) Error in vertically-resolved tropospheric zonal average relative humidity (Su et al., 2014) The results are displayed as scatterplots. .. note:: The recipe ``recipe_ecs_scatter.yml`` requires pre-calulation of the equilibrium climate sensitivites (ECS) for all models. The ECS values are calculated with recipe_ecs.yml. The netcdf file containing the ECS values (path and filename) is specified by diag_script_info@ecs_file. Alternatively, the netcdf file containing the ECS values can be generated with the cdl-script $diag_scripts/emergent_constraints/ecs_cmip.cdl (recommended method): 1) save script given at the end of this recipe as ecs_cmip.cdl 2) run command: ncgen -o ecs_cmip.nc ecs_cmip.cdl 3) copy ecs_cmip.nc to directory given by diag_script_info@ecs_file (e.g. $diag_scripts/emergent_constraints/ecs_cmip.nc) Available recipes and diagnostics --------------------------------- Recipes are stored in recipes/ * recipe_ecs_scatter.yml * recipe_ecs_constraints.yml Diagnostics are stored in diag_scripts * emergent_constraints/ecs_scatter.ncl: calculate emergent constraints for ECS * emergent_constraints/ecs_scatter.py: calculate further emergent constraints for ECS * emergent_constraints/single_constraint.py: create scatterplots for emergent constraints * climate_metrics/psi.py: calculate temperature variabililty metric (Cox et al., 2018) User settings in recipe ----------------------- .. _ecs_scatter.ncl: * Script emergent_constraints/ecs_scatter.ncl *Required settings (scripts)* * diag: emergent constraint to calculate ("itczidx", "humidx", "ltmi", "covrefl", "shhc", "sherwood_d", "sherwood_s") * ecs_file: path and filename of netCDF containing precalculated ECS values (see note above) *Optional settings (scripts)* * calcmm: calculate multi-model mean (True, False) * legend_outside: plot legend outside of scatterplots (True, False) * output_diag_only: Only write netcdf files for X axis (True) or write all plots (False) * output_models_only: Only write models (no reference datasets) to netcdf files (True, False) * output_attributes: Additonal attributes for all output netcdf files * predef_minmax: use predefined internal min/max values for axes (True, False) * styleset: "CMIP5" (if not set, diagnostic will create a color table and symbols for plotting) * suffix: string to add to output filenames (e.g."cmip3") *Required settings (variables)* * reference_dataset: name of reference data set *Optional settings (variables)* none *Color tables* none * Script emergent_constraints/ecs_scatter.py See :ref:`here`. * Script emergent_constraints/single_constraint.py See :ref:`here`. * Script climate_metrics/psi.py See :ref:`here`. Variables --------- * cl (atmos, monthly mean, longitude latitude level time) * clt (atmos, monthly mean, longitude latitude time) * pr (atmos, monthly mean, longitude latitude time) * hur (atmos, monthly mean, longitude latitude level time) * hus (atmos, monthly mean, longitude latitude level time) * rsdt (atmos, monthly mean, longitude latitude time) * rsut (atmos, monthly mean, longitude latitude time) * rsutcs (atmos, monthly mean, longitude latitude time) * rtnt or rtmt (atmos, monthly mean, longitude latitude time) * ta (atmos, monthly mean, longitude latitude level time) * tas (atmos, monthly mean, longitude latitude time) * tasa (atmos, monthly mean, longitude latitude time) * tos (atmos, monthly mean, longitude latitude time) * ts (atmos, monthly mean, longitude latitude time) * va (atmos, monthly mean, longitude latitude level time) * wap (atmos, monthly mean, longitude latitude level time) * zg (atmos, monthly mean, longitude latitude time) Observations and reformat scripts --------------------------------- .. note:: (1) Obs4mips data can be used directly without any preprocessing. (2) See headers of reformat scripts for non-obs4MIPs data for download instructions. * AIRS (obs4MIPs): hus, husStderr * AIRS-2-0 (obs4MIPs): hur * CERES-EBAF (obs4MIPs): rsdt, rsut, rsutcs * ERA-Interim (OBS6): hur, ta, va, wap * GPCP-SG (obs4MIPs): pr * HadCRUT4 (OBS): tasa * HadISST (OBS): ts * MLS-AURA (OBS6): hur * TRMM-L3 (obs4MIPs): pr, prStderr References ---------- * Brient, F., and T. Schneider, J. Climate, 29, 5821-5835, doi:10.1175/JCLIM-D-15-0897.1, 2016. * Brient et al., Clim. Dyn., 47, doi:10.1007/s00382-015-2846-0, 2016. * Cox et al., Nature, 553, doi:10.1038/nature25450, 2018. * Gregory et al., Geophys. Res. Lett., 31, doi:10.1029/2003GL018747, 2004. * Lipat et al., Geophys. Res. Lett., 44, 5739-5748, doi:10.1002/2017GL73151, 2017. * Sherwood et al., nature, 505, 37-42, doi:10.1038/nature12829, 2014. * Su, et al., J. Geophys. Res. Atmos., 119, doi:10.1002/2014JD021642, 2014. * Tian, Geophys. Res. Lett., 42, 4133-4141, doi:10.1002/2015GL064119, 2015. * Volodin, Izvestiya, Atmospheric and Oceanic Physics, 44, 288-299, doi:10.1134/S0001433808030043, 2008. * Zhai, et al., Geophys. Res. Lett., 42, doi:10.1002/2015GL065911, 2015. Example plots ------------- .. _fig_ec_ecs_1: .. figure:: /recipes/figures/emergent_constraints/ltmi.png :align: center Lower tropospheric mixing index (LTMI; Sherwood et al., 2014) vs. equilibrium climate sensitivity from CMIP5 models. .. _fig_ec_ecs_2: .. figure:: /recipes/figures/emergent_constraints/shhc.png :align: center Climatological Hadley cell extent (Lipat et al., 2017) vs. equilibrium climate sensitivity from CMIP5 models. .. _fig_ec_ecs_3: .. figure:: /recipes/figures/emergent_constraints/humidx.png :align: center Tropical mid-tropospheric humidity asymmetry index (Tian, 2015) vs. equilibrium climate sensitivity from CMIP5 models. .. _fig_ec_ecs_4: .. figure:: /recipes/figures/emergent_constraints/itczidx.png :align: center Southern ITCZ index (Tian, 2015) vs. equilibrium climate sensitivity from CMIP5 models. .. _fig_ec_ecs_5: .. figure:: /recipes/figures/emergent_constraints/covrefl.png :align: center Covariance of shortwave cloud reflection (Brient and Schneider, 2016) vs. equilibrium climate sensitivity from CMIP5 models. .. _fig_ec_ecs_6: .. figure:: /recipes/figures/emergent_constraints/volodin.png :align: center Difference in total cloud fraction between tropics (28°S - 28°N) and Southern midlatitudes (56°S - 36°S) (Volodin, 2008) vs. equilibrium climate sensitivity from CMIP5 models.