""" UserScript and SeriesAnalysis: Compute Zonal Mean Bias and Create Plots for Temperature and Wind ================================================================================================ model_applications/s2s_stratosphere/UserScript_fcstGFS_obsERA_StratosphereBias.py """ ############################################################################## # .. contents:: # :depth: 1 # :local: # :backlinks: none ############################################################################## # Scientific Objective # -------------------- # # Many common modes of variability in the troposphere have stratospheric teleconnection # pathways. Thus, the stratosphere can be a source of predictability for surface weather. # However, the predictive skill gained from the stratosphere can be limited by biases in # the representation of these stratospheric processes. This use case investigates # stratospheric biases in temperature and wind. Model biases are plotted for a month time # period based on latitude and pressure between 100 and 1 hPa. # # In addition, this use case also demonstrates how to read semi-structured grids into # MET. Specifically zonal mean data (on a grid of latitude and pressure) is read into # Series-Analysis in the second step of this use case. ############################################################################## # Version Added # ------------- # # METplus version 6.0 ############################################################################## # Datasets # -------- # # **Forecast:** GFS 24 hour forecasts for February 2018 # # **Observation:** ERA reanalysis for February 2018 # # **Climatology:** None # # **Location:** All of the input data required for this use case can be # found in a sample data tarball. Each use case category will have # one or more sample data tarballs. It is only necessary to download # the tarball with the use case’s dataset and not the entire collection # of sample data. Click here to access the METplus releases page and download sample data # for the appropriate release: https://github.com/dtcenter/METplus/releases # This tarball should be unpacked into the directory that you will # set the value of INPUT_BASE. See :ref:`running-metplus` section for more information. ############################################################################## # METplus Components # ------------------ # # This use case calls UserScript first, Series-Analysis, and then UserScript # a second time. METcalcpy, METplotpy, and METdataio are needed for this use case to run. # The METcalcpy scripts accessed include the following: # # * metcalcpy/pre_processing/directional_means.py # # The METplotpy scripts accessed include the following: # # * metplotpy/stratosphere_diagnostics/stratosphere_plots.py # # The METdataio scripts accessed include the following: # # * METreadnc/util/read_netcdf.py ############################################################################## # METplus Workflow # ---------------- # # **Beginning time (INIT_BEG):** 02-01-2018 # # **End time (INIT_END):** 02-28-2018 # # **Increment between beginning and end times (INIT_INCREMENT):** 30 days # # **Sequence of forecast leads to process (LEAD_SEQ):** 24 hours # # This use case does not loop. The two calls to UserScript are run once. Series- # Analysis is also run once. The first call to UserScript runs zonal_mean_driver.py. # This script computes zonal and meridional mean data from the directional_means program in # METplotpy. Then, Series-Analysis is run on the zonal mean output to compute # continuous statistics. Finally, the second call to UserScript runs bias_plot_driver.py # which creates bias plots for temperature and wind. # # METcalcpy 3.0.0 or higher, METplotpy 3.0.0 or higher, and METdataio 2.1 or higher are needed # for this use case. ############################################################################## # METplus Configuration # --------------------- # # METplus first loads all of the configuration files found in parm/metplus_config, # then it loads any configuration files passed to METplus via the command line, # i.e. parm/use_cases/model_applications/s2s_stratosphere/UserScript_fcstGFS_obsERA_StratosphereBias.conf # # .. highlight:: bash # .. literalinclude:: ../../../../parm/use_cases/model_applications/s2s_stratosphere/UserScript_fcstGFS_obsERA_StratosphereBias.conf ############################################################################# # MET Configuration # --------------------- # # METplus sets environment variables based on user settings in the METplus configuration file. # See :ref:`How METplus controls MET config file settings` for more details. # # **YOU SHOULD NOT SET ANY OF THESE ENVIRONMENT VARIABLES YOURSELF! THEY WILL BE OVERWRITTEN BY METPLUS WHEN IT CALLS THE MET TOOLS!** # # If there is a setting in the MET configuration file that is currently not supported by METplus you'd like to control, please refer to: # :ref:`Overriding Unsupported MET config file settings` # # .. dropdown:: SeriesAnalysisConfig_wrapped # # .. literalinclude:: ../../../../parm/met_config/SeriesAnalysisConfig_wrapped ############################################################################## # Python Embedding # ---------------- # # This use case uses a Python embedding script to read in the semi-structured zonal mean data to Series-Analysis. Inputs to # this script include the filename to be read in, variable name, and the axis over which the mean is taken. The script # returns a numpy array containing the zonal mean data (semi-structured grid). # # .. dropdown:: read_met_axis_mean.py # # .. highlight:: bash # .. literalinclude:: ../../../../parm/use_cases/model_applications/s2s_stratosphere/UserScript_fcstGFS_obsERA_StratosphereBias/read_met_axis_mean.py ############################################################################## # User Scripting # -------------- # # This use case runs both zonal_mean_driver.py and bias_plot_driver.py. The zonal mean driver takes an input netCDF # file and the time variable. Then it computes zonal and meridional means for u and T from directional_means.py in # METcalcpy. It writes the zonal mean data to output netCDF files. # # The bias plot driver reads output netCDF files from Series-Analysis and creates plots of the bias over # latitude and pressure level. Inputs to both of the Python scripts can be found in the [user_env_vars] # section of the UserScript_fcstGFS_obsERA_StratosphereBias.conf file # # .. dropdown:: parm/use_cases/model_applications/s2s_stratosphere/UserScript_fcstGFS_obsERA_StratosphereBias/zonal_mean_driver.py # # .. highlight:: python # .. literalinclude:: ../../../../parm/use_cases/model_applications/s2s_stratosphere/UserScript_fcstGFS_obsERA_StratosphereBias/zonal_mean_driver.py # # .. dropdown:: parm/use_cases/model_applications/s2s_stratosphere/UserScript_fcstGFS_obsERA_StratosphereBias/bias_plot_driver.py # # .. highlight:: python # .. literalinclude:: ../../../../parm/use_cases/model_applications/s2s_stratosphere/UserScript_fcstGFS_obsERA_StratosphereBias/bias_plot_driver.py ############################################################################## # Running METplus # --------------- # # Pass the use case configuration file to the run_metplus.py script along with any # user-specific system configuration files if desired:: # # run_metplus.py /path/to/METplus/parm/use_cases/model_applications/s2s_stratosphere/UserScript_fcstGFS_obsERA_StratosphereBias.conf /path/to/user_system.conf # # See :ref:`running-metplus` for more information. ############################################################################## # Expected Output # --------------- # # A successful run will output the following both to the screen and to the logfile:: # # INFO: METplus has successfully finished running. # # Refer to the value set for **OUTPUT_BASE** to find where the output data was generated. # Output for this use case will be found in # {OUTPUT_BASE}/model_applications/s2s_stratosphere/UserScript_fcstGFS_obsERA_StratospherePolar # The output includes the netCDF zonal mean files for the forecast and observations, netCDF output # from Series-Analysis, and bias plots. There are two bias plots output:: # # * plots/GFS_ERA_ME_2018_02_zonal_mean_T.png # * plots/GFS_ERA_ME_2018_02_zonal_mean_U.png # # The statistics output from Series-Analysis output is two netCDF files, one for temperature and one for wind:: # # * SeriesAnalysis/zonal_mean_T_stats_2018_02.nc # * SeriesAnalysis/zonal_mean_U_stats_2018_02.nc # # There are 7 variable fields present in the Series-Analysis output netCDF files (not # including the lat/lon fields). Those variables are:: # # * level(level) # * n_series # * series_cnt_TOTAL(lat, level) # * series_cnt_ME(lat, level) # * series_cnt_RMSE(lat, level) # * series_cnt_FBAR(lat, level) # * series_cnt_OBAR(lat, level) # # Text files with a listing of the files input to Series-Analysis are also output:: # # * SeriesAnalysis/series_analysis_files_fcst_init_ALL_valid_ALL_lead_ALL.txt # * SeriesAnalysis/series_analysis_files_obs_init_ALL_valid_ALL_lead_ALL.txt # # The zonal mean output includes 28 files for the forecast # and observations, one for each day. The file format for February 1 is:: # # * FCST/FCST_zonal_mean_U_T_20180201_000000.nc # * OBS/OBS_zonal_mean_U_T_20180201_000000.nc # # There are 4 variable fields present in the zonal mean netCDF file (not including the # latitude and pressure fields). Those variables are:: # # * time # * u(pres, latitude) # * T(pres, latitude) # * lead_time ############################################################################## # Keywords # -------- # # .. note:: # # * UserScriptUseCase # * S2SAppUseCase # * S2SStratosphereAppUseCase # * UserScriptUseCase # * SeriesAnalysisUseCase # * METdataioUseCase # * METcalcpyUseCase # * METplotpyUseCase # # Navigate to the :ref:`quick-search` page to discover other similar use cases. # # # # sphinx_gallery_thumbnail_path = '_static/s2s_stratosphere-UserScript_fcstGFS_obsERA_StratosphereBias.png'