.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "generated/model_applications/medium_range/GridStat_fcstGEFS_obsCADB_BinaryObsPOE.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note :ref:`Go to the end ` to download the full example code. .. rst-class:: sphx-glr-example-title .. _sphx_glr_generated_model_applications_medium_range_GridStat_fcstGEFS_obsCADB_BinaryObsPOE.py: GridStat: Use binary observation field to verify percentile forecast ==================================================================== model_applications/medium_range/GridStat_fcstGEFS_obsCADB_BinaryObsPOE.conf .. GENERATED FROM PYTHON SOURCE LINES 9-13 .. contents:: :depth: 1 :local: :backlinks: none .. GENERATED FROM PYTHON SOURCE LINES 15-24 Scientific Objective -------------------- Evaluation of a Probability of Exceedence (POE) field presents several difficulties. Some of these include a fitting verification statistic to report on, choosing a meaningful percentile field, and more. This use case was the culmination of attempting to verify a POE field for extreme temperature (defined as the 85th percentile) in METplus. In order to provide a streamlined process that didn't require vast reworkings of the MET tools, the observation field was converted to binary: 0s indicating a non-85th percentile temperature was observed, and a 1 indicating the opposite. Those observations are compared to the chosen forecast percentile and the HSS_EC becomes the main statistical focus, as the new hss_ec_value feature allowed the use case to more closely replicate in-house verificaiton that already existed. A final note that because the POE forecast file is a non-standard netCDF, Python Embedding was used to extract the desired field .. GENERATED FROM PYTHON SOURCE LINES 26-30 Version Added ------------- METplus version 5.1 .. GENERATED FROM PYTHON SOURCE LINES 32-50 Datasets -------- **Forecast:** NOAA Global Ensemble Forecast System (GEFS) 85th percentile of maximum temperature **Observations:** NOAA Climate Prediction Center Climate Assessment Data Base (CADB) converted into a binary field relative to the 85th percentile **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. .. GENERATED FROM PYTHON SOURCE LINES 52-57 METplus Components ------------------ This use case calls a Python script to extract the user-defined percentile forecast. METplus then verifies it against a binary observation field in GridStat and returns the requested line type outputs. .. GENERATED FROM PYTHON SOURCE LINES 59-76 METplus Workflow ---------------- **Beginning time (INIT_BEG):** 20220522 **End time (INIT_END):** 20220522 **Increment between beginning and end times (INIT_INCREMENT):** 12H **Sequence of forecast leads to process (LEAD_SEQ):** 8d The following boundary time is used for the entire script: | **Init Beg:** 2022-05-22 | **Init End:** 2022-05-22 There is only one time processed for the use case. .. GENERATED FROM PYTHON SOURCE LINES 78-88 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/medium_range/GridStat_fcstGEFS_obsCADB_BinaryObsPOE.conf .. highlight:: bash .. literalinclude:: ../../../../parm/use_cases/model_applications/medium_range/GridStat_fcstGEFS_obsCADB_BinaryObsPOE.conf .. GENERATED FROM PYTHON SOURCE LINES 90-105 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:: GridStatConfig_wrapped .. literalinclude:: ../../../../parm/met_config/GridStatConfig_wrapped .. GENERATED FROM PYTHON SOURCE LINES 107-120 Python Embedding ---------------- This use case calls a Python script to parse the user-requested percentile from the forecast dataset. This is controlled in the forecast VAR1 variable setting and is provided in: .. dropdown:: parm/use_cases/model_applications/medium_range/GridStat_fcstGEFS_obsCADB_BinaryObsPOE/Tmax_fcst_embedded.py .. highlight:: python .. literalinclude:: ../../../../parm/use_cases/model_applications/medium_range/GridStat_fcstGEFS_obsCADB_BinaryObsPOE/Tmax_fcst_embedded.py For more information on the basic requirements to utilize Python Embedding in METplus, please refer to the MET User’s Guide section on `Python embedding `_. .. GENERATED FROM PYTHON SOURCE LINES 122-126 User Scripting -------------- User Scripting is not used in this use case. .. GENERATED FROM PYTHON SOURCE LINES 128-137 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/medium_range/GridStat_fcstGEFS_obsCADB_BinaryObsPOE.conf /path/to/user_system.conf See :ref:`running-metplus` for more information. .. GENERATED FROM PYTHON SOURCE LINES 139-154 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 the use case will be found in model_applications/POE_tmax (relative to **OUTPUT_BASE**). The following files should exist: * grid_stat_1920000L_20220530_000000V_ctc.txt * grid_stat_1920000L_20220530_000000V_cts.txt * grid_stat_1920000L_20220530_000000V.stat .. GENERATED FROM PYTHON SOURCE LINES 156-170 Keywords -------- .. note:: * GridStatUseCase * PythonEmbeddingFileUseCase * MediumRangeAppUseCase * NETCDFFileUseCase Navigate to the :ref:`quick-search` page to discover other similar use cases. .. _sphx_glr_download_generated_model_applications_medium_range_GridStat_fcstGEFS_obsCADB_BinaryObsPOE.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: GridStat_fcstGEFS_obsCADB_BinaryObsPOE.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: GridStat_fcstGEFS_obsCADB_BinaryObsPOE.py ` .. container:: sphx-glr-download sphx-glr-download-zip :download:`Download zipped: GridStat_fcstGEFS_obsCADB_BinaryObsPOE.zip ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_