24. Stratosphere plots

24.1. Description

The stratosphere_plots.py script contains the plotting portion for three Stratosphere use cases. One use case creates a ME plot in latitude and pressure, another which creates ME and RMSE plots for lead time and pressure, and a third which creates two phase diagrams and a time series of U for at 50mb and 30mb. The three METplus use cases, illustrate how to use these plotting scripts for zonal mean biases , creating bias and RMSE for polar cap temperature and polar vortex U and creating phase diagrams and time series for QBO

These files are used by the image comparison test:

  • GFS_ERA_ME_2018_02_zonal_mean_T.png: Run “plot_zonal_bias” in stratosphere_plots.py.py to create this plot.

  • GFS_ERA_ME_2018_02_zonal_mean_U.png: Run “plot_zonal_bias” in stratosphere_plots.py to create this plot.

  • ME_2018_02_polar_cap_T.png: Run “plot_polar_bias” in stratosphere_plots.py to create this plot.

  • ME_2018_02_polar_vortex_U.png: Rn “plot_polar_bias” in stratosphere_plots.py to create this plot.

  • RMSE_2018_02_polar_cap_T.png: Run “plot_polar_rmse” in stratosphere_plots.py to create this plot.

  • RMSE_2018_02_polar_vortex_U.png: Run “plot_polar_rmse” in stratosphere_plots.py to create this plot.

  • ERA_GFS_QBO_circuits.png: Run “plot_qbo_phase_circuits” in stratosphere_plots.py to create this plot.

  • ERA5_QBO_PhaseSpace.png: Run “plot_qbo_phase_space” in stratosphere_plots.py to create this plot.

  • ERA_GFS_timeseries_30mb_u_201710_201802.png: Run “plot_u_timeseries” in stratosphere_plots.py to create this plot.

  • ERA_GFS_timeseries_50mb_u_201710_201802.png: Run “plot_u_timeseries” in stratosphere_plots.py to create this plot.

24.2. Required Packages

  • Python

  • Matplotlib

  • metcalcpy (see Section 1.1.4)

  • metdataio

  • numpy

  • xarray

  • pandas

  • cmocean

  • pyyaml

24.3. How to Use

Import stratosphere_plots into the script:

from stratosphere_plots import plot_zonal_bias,plot_polar_bias,plot_polar_rmse, plot_qbo_phase_circuits,plot_qbo_phase_space,plot_u_timeseries

24.3.1. For plot_zonal_bias

In the code, generate the following as numpy arrays (except outfile, ptitle, and plevs).

lats: A numpy array of the latitude values under consideration.

levels: A numpy array of the pressure level values under consideration.

bias: A numpy array containing the bias.

obar: A numpy array of the size wrnum containing the frequency of occurrence of each cluster.

outfile: The full path and filename of the output plot file, a .png version will be written.

ptitle: A string containing the title of the plot.

plevs: A list containing integers of the contour levels used in plotting the obs climatology.

24.3.2. For plot_polar_bias

In the code, generate the following as numpy arrays (except outfile, ptitle, and plevs).

leads: A numpy array containing the forecast lead times.

levels: A numpy array of the pressure level values under consideration.

pdata: A numpy array containing the bias.

outfile: The full path and filename of the output plot file, a .png version will be written.

ptitle: A string containing the title of the plot.

plevs: A list containing floats of the contour levels used in plotting.

24.3.3. For plot_polar_rmse

In the code, generate the following as numpy arrays (except outfile, ptitle, and plevs).

leads: A numpy array containing the forecast lead times.

levels: A numpy array of the pressure level values under consideration.

pdata: A numpy array containing the RMSE.

outfile: The full path and filename of the output plot file, a .png version will be written.

ptitle: A string containing the title of the plot.

plevs: A list containing floats of the contour levels used in plotting.

24.3.4. For plot_qbo_phase_circuits

In the code, generate the following as numpy arrays (except inits, periods, and outfile).

inits: A listing of datetimes that are the start date for each plot.

periods: An integer containing the number of days to plot from the inits.

rean_qbo_pcs: An xarray dataarray containing the projected daily zonal winds for the observations.

rfcst_qbo_pcs: An xarray dataarray containing the projected daily zonal winds for the model.

outfile: The full path and filename of the output plot file, a .png version will be written.

24.3.5. For plot_qbo_phase_space

In the code, generate the following as numpy arrays (except ptitle and outfile).

rean_qbo_pcs: An xarray dataarray containing the projected daily zonal winds.

eofs: An xarray dataarray containing the EOFs.

ptitle: A string containing the title of the plot.

outfile: The full path and filename of the output plot file, a .png version will be written.

24.3.6. For plot_u_timeseries

In the code, generate the following as numpy arrays (except ptitle and outfile).

obs_dt: A numpy array of datetimes for the observations.

obs_u: A numpy array containing U wind values for the observations.

fcst_dt: A numpy array of datetimes for the forecasts.

fcst_u: A numpy array containing U wind values for the forecasts.

ptitle: A string containing the title of the plot.

outfile: The full path and filename of the output plot file, a .png version will be written.

Invoke the plotting functions:

plot_zonal_bias(lats,levels,bias,obar,outfile,ptitle,plevs)

plot_polar_bias(leads,levels,pdata,outfile,ptitle,plevs)

plot_polar_rmse(leads,levels,pdata,outfile,ptitle,plevs)

plot_qbo_phase_circuits(inits,periods,rean_qbo_pcs,rfcst_qbo_pcs,outfile)

plot_qbo_phase_space(rean_qbo_pcs,eofs,ptitle,outfile)

plot_u_timeseries(obs_dt,obs_u,fcst_dt,fcst_u,ptitle,outfile)

The output will be .png version of all requested plots and will be located based on what was specified (path and name) in the outfile.