Timeseries for Arctic-Midlatitude Teleconnections

Overview

The recipe produces the timeseries of selected variables to study Arctic-midlatitude teleconnections for further application of Causal Model Evaluation (CME) described in Galytska et al. (2023).

The output of the recipe consists of the .nc files named after the data source (e.g. ERA5, ACCESS-CM2.nc etc.). Each file contains the area-weighted spatial average of climatological monthly anomalies of selected variables. The recipe also applies the CVDP package.

Available recipes and diagnostics

Recipes are stored in esmvaltool/recipes/

• recipe_galytska23jgr.yml

Diagnostics are stored in esmvaltool/diag_scripts/

• galytska23/select_variables_for_tigramite.py

• cvdp/cvdp_wrapper.py

User settings in recipe

1. Preprocessor

   • anomalies (period: monthly): Calculate anomalies for selected variables

   • regrid (target_grid: 1x1): Linear regridding of all datasets to the uniform grid

   • area_statistics (operation: mean): Calculate mean over defined regions

2. Script <select_variables_for_tigramite.py>

   none

3. Script <cvdp_wrapper.py>

   none

4. Script <cvdp/cvdp/driver.ncl>

   • modular (modular: True): Run the diagnostics that is selected in modular_list

   • modular_list (modular_list: psl.nam_nao): Calculate only NAO diagnostics

Variables

• zg (atmos, monthly mean, longitude latitude time)

• tas (atmos, monthly mean, longitude latitude time)

• psl (atmos, monthly mean, longitude latitude time)

• va (atmos, monthly mean, longitude latitude time)

• ta (atmos, monthly mean, longitude latitude time)

• sic/siconc (seaice, monthly mean, longitude latitude time)

• ts (atmos, monthly mean, longitude latitude time)

• pr (atmos, monthly mean, longitude latitude time)

Observations and reformat scripts

• ERA5 (pr, psl, ta, tas, ts, va, zg - ERA5 data can be used via the native6 project)

• HadISST - (sic - esmvaltool/cmorizers/data/formatters/datasets/hadisst.ncl)

References

• Galytska, E., Weigel, K., Handorf, D., Jaiser, R., Köhler, R. H., Runge, J., & Eyring, V.: Causal model evaluation of Arctic-midlatitude teleconnections in CMIP6. Authorea Preprints. https://doi.org/10.1002/essoar.10512569.1.

• Copernicus Climate Change Service (C3S), 2017: ERA5: Fifth generation of ECMWF atmospheric reanalyses of the global climate, edited, Copernicus Climate Change Service Climate Data Store (CDS). https://cds.climate.copernicus.eu/cdsapp#!/home

• http://www.cesm.ucar.edu/working_groups/CVC/cvdp/

Example plots

Fig. 225 Monthly mean temperature anomalies in the Arctic (65°–90°N) from observations and selected CMIP6 models during 1980-2021.