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Multiple ensemble diagnostic regression (MDER) for constraining future austral jet position#

Overview#

Wenzel et al. (2016) use multiple ensemble diagnostic regression (MDER) to constrain the CMIP5 future projection of the summer austral jet position with several historical process-oriented diagnostics and respective observations.

The following plots are reproduced:

  • Absolute correlation between the target variable and the diagnostics.

  • Scatterplot between the target variable and the MDER-calculated linear combination of diagnostics.

  • Boxplot of RMSE for the unweighted multi-model mean and the (MDER) weighted multi-model mean of the target variable in a pseudo-reality setup.

  • Time series of the target variable for all models, observations and MDER predictions.

  • Errorbar plots for all diagnostics.

  • Scatterplots between the target variable and all diagnostics.

Available recipes and diagnostics#

Recipes are stored in recipes/

  • recipe_wenzel16jclim.yml

Diagnostics are stored in diag_scripts/

  • austral_jet/asr.ncl

  • austral_jet/main.ncl

  • mder/absolute_correlation.ncl

  • mder/regression_stepwise.ncl

  • mder/select_for_mder.ncl

User settings in recipe#

  1. Preprocessor

    • extract_region: Region extraction.

    • extract_levels: Pressure level extraction.

    • area_statistics: Spatial average calculations.

  2. Script austral_jet/asr.ncl

    • season, str: Season.

    • average_ens, bool, optional (default: False): Average over all given ensemble members of a climate model.

    • wdiag, array of str, optional: Names of the diagnostic for MDER output. Necessary when MDER output is desired.

    • wdiag_title, array of str, optional: Names of the diagnostic in plots.

  3. Script austral_jet/main.ncl

    • styleset, str: Style set used for plotting the multi-model plots.

    • season, str: Season.

    • average_ens, bool, optional (default: False): Average over all given ensemble members of a climate model.

    • rsondes, array of str, optional: Additional observations used in the plot but not for MDER output.

    • rsondes_file, array of str, optional: Paths to the additional observations Necessary when rsondes is given.

    • rsondes_yr_min, int, optional: Minimum year for additional observations. Necessary when rsondes is given.

    • rsondes_yr_max, int, optional: Maximum year for additional observations. Necessary when rsondes is given.

    • wdiag, array of str, optional: Names of the diagnostic for MDER output. Necessary when MDER output is desired.

    • wdiag_title, array of str, optional: Names of the diagnostic in plots.

    • derive_var, str, optional: Derive variables using NCL functions. Must be one of "tpp", "mmstf".

    • derive_latrange, array of float, optional: Latitude range for variable derivation. Necessary if derive_var is given.

    • derive_lev, float, optional: Pressure level (given in Pa) for variable derivation. Necessary if derive_var is given.

  4. Script mder/absolute_correlation.ncl

    • p_time, array of int: Start years for future projections.

    • p_step, int: Time range for future projections (in years).

    • scal_time, array of int: Time range for base period (in years) for anomaly calculations used when calc_type = "trend".

    • time_oper, str: Operation used in NCL time_operation function.

    • time_opt, str: Option used in NCL time_operation function.

    • calc_type, str: Calculation type for the target variable. Must be one of "trend", "pos", "int".

    • domain, str: Domain tag for provenance tracking.

    • average_ens, bool, optional (default: False): Average over all given ensemble members of a climate model.

    • region, str, optional: Region used for area aggregation. Necessary if input of target variable is multidimensional.

    • area_oper, str, optional: Operation used in NCL area_operation function. Necessary if multidimensional is given.

    • plot_units, str, optional (attribute for variable_info): Units for the target variable used in the plots.

  5. Script mder/regression_stepwise.ncl

    • p_time, array of int: Start years for future projections.

    • p_step, int: Time range for future projections (in years).

    • scal_time, array of int: Time range for base period (in years) for anomaly calculations used when calc_type = "trend".

    • time_oper, str: Operation used in NCL time_operation function.

    • time_opt, str: Option used in NCL time_operation function.

    • calc_type, str: Calculation type for the target variable. Must be one of "trend", "pos", "int".

    • domain, str: Domain tag for provenance tracking.

    • average_ens, bool, optional (default: False): Average over all given ensemble members of a climate model.

    • smooth, bool, optional (default: False): Smooth time period with 1-2-1 filter.

    • iter, int, optional: Number of iterations for smoothing. Necessary when smooth is given.

    • cross_validation_mode, bool, optional (default: False): Perform cross-validation.

    • region, str, optional: Region used for area aggregation. Necessary if input of target variable is multidimensional.

    • area_oper, str, optional: Operation used in NCL area_operation function. Necessary if multidimensional is given.

    • plot_units, str, optional (attribute for variable_info): Units for the target variable used in the plots.

  6. Script mder/select_for_mder.ncl

    • wdiag, array of str: Names of the diagnostic for MDER output. Necessary when MDER output is desired.

    • domain, str: Domain tag for provenance tracking.

    • ref_dataset, str: Style set used for plotting the multi-model plots.

    • average_ens, bool, optional (default: False): Average over all given ensemble members of a climate model.

    • derive_var, str, optional: Derive variables using NCL functions. Must be one of "tpp", "mmstf".

Variables#

  • ta (atmos, monthly, longitude, latitude, pressure level, time)

  • uajet (atmos, monthly, time)

  • va (atmos, monthly, longitude, latitude, pressure level, time)

  • ps (atmos, monthly, longitude, latitude, time)

  • asr (atmos, monthly, longitude, latitude, time)

Observations and reformat scripts#

  • ERA-Intermin (ta, uajet, va, ps)

  • CERES-EBAF (asr)

References#

  • Wenzel, S., V. Eyring, E.P. Gerber, and A.Y. Karpechko: Constraining Future Summer Austral Jet Stream Positions in the CMIP5 Ensemble by Process-Oriented Multiple Diagnostic Regression. J. Climate, 29, 673–687, doi:10.1175/JCLI-D-15-0412.1, 2016.

Example plots#

../_images/CMPI5_uajet-pos_rcp45_20ystep_FIG1.png

Fig. 126 Time series of the the target variable (future austral jet position in the RCP 4.5 scenario) for the CMIP5 ensemble, observations, unweighted multi-model mean projections and (MDER) weighted multi-model mean projections.#

../_images/CMPI5_uajet-pos_rcp45_20ystep_FIG2b.png

Fig. 127 Scatterplot of the target variable (future austral jet position in the RCP 4.5 scenario) vs. the MDER-determined linear combination of diagnostics for the CMIP5 ensemble.#

../_images/CMPI5_uajet-pos_rcp45_20ystep_FIG3.png

Fig. 128 Boxplot for the RMSE of the target variable for the unweighted and (MDER) weighted multi-model mean projections in a pseudo-reality setup.#

../_images/ta_trop250_ta_DJF_trend.png

Fig. 129 Trends in tropical DJF temperature at 250hPa for different CMIP5 models and observations.#

../_images/uajet_H-SH_c.png

Fig. 130 Scatterplot of the target variable (future austral jet position in the RCP 4.5 scenario) vs. a single diagnostic, the historical location of the Southern hemisphere Hadley cell boundary for the CMIP5 ensemble.#

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