.. 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_fcstCREDIT_GFS_obsGFS_6hrRealtime.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_fcstCREDIT_GFS_obsGFS_6hrRealtime.py: Grid-Stat, Stat-Analysis, Data-Ingest: CREDIT and GFS statistics and Data Download ================================================================================== model_applications/medium_range/GridStat_fcstCREDIT_GFS_obsGFS_6hrRealtime.conf .. GENERATED FROM PYTHON SOURCE LINES 9-13 .. contents:: :depth: 1 :local: :backlinks: none .. GENERATED FROM PYTHON SOURCE LINES 15-26 Scientific Objective -------------------- This use case is an example for verification within RAL to illustrate how to compare two models and also how to download data automatically. The use case was originally designed to be run in real-time using the now keyword in VALID_BEG and VALID_END. However, a specified date is used in this example for our automated testing. The case demonstrates how to run statistics comparing two models, NSF NCAR Community Research Earth Digital Intelligence Twin (CREDIT) and GFS for both the surface and upper air evaluation. Surface and upper air statistics are run separately since they are stored in separate observation files. .. GENERATED FROM PYTHON SOURCE LINES 28-32 Version Added ------------- METplus version 6.2 .. GENERATED FROM PYTHON SOURCE LINES 34-54 Datasets -------- **Forecast**: CREDIT ~0.28 degree model and GFS 0.25 degree model **Observation**: GFS Analysis **Climatology:** None **Location:** The CREDIT model 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. The GFS model data and GDAS observations are downloaded automatically. Make sure you have an internet connection. .. GENERATED FROM PYTHON SOURCE LINES 56-62 METplus Components ------------------ This use case calls DataIngest once, GridStat 4 times and StatAnalysis once. GridStat has 4 calls, 2 for the CREDIT model and 2 for the GFS using surface and upper air observations respectively. .. GENERATED FROM PYTHON SOURCE LINES 65-96 METplus Workflow ---------------- **Beginning time (VALID_BEG):** 2025-09-24 00Z **End time (VALID_END):** 2025-09-24 06Z **Increment between beginning and end times (VALID_INCREMENT):** 6 hours **Sequence of forecast leads to process (LEAD_SEQ):** 6, 12 The DataIngest and GridStat tools are run for each time, whereas StatAnalysis is run once. This example loops by valid time. It processes 2 lead times for 2 valid times with a total of 4 runs. The times are listed below. | **Init:** 2025-09-23_18Z | **Valid:** 2025-09-24_00Z | **Forecast lead:** 06 | **Init:** 2025-09-23_12Z | **Valid:** 2025-09-24_00Z | **Forecast lead:** 12 | **Init:** 2025-09-24_00Z | **Valid:** 2025-09-24_06Z | **Forecast lead:** 06 | **Init:** 2025-09-23_18Z | **Valid:** 2025-09-24_06Z | **Forecast lead:** 12 .. GENERATED FROM PYTHON SOURCE LINES 98-107 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, e.g. parm/use_cases/model_applications/medium_range/GridStat_fcstCREDIT_GFS_obsGFS_6hrRealtime.conf .. highlight:: bash .. literalinclude:: ../../../../parm/use_cases/model_applications/medium_range/GridStat_fcstCREDIT_GFS_obsGFS_6hrRealtime.conf .. GENERATED FROM PYTHON SOURCE LINES 110-129 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 .. dropdown:: StatAnalysisConfig_wrapped .. literalinclude:: ../../../../parm/met_config/STATAnalysisConfig_wrapped .. GENERATED FROM PYTHON SOURCE LINES 131-135 Python Embedding ---------------- This use case does not use Python embedding. .. GENERATED FROM PYTHON SOURCE LINES 137-141 User Scripting -------------- This user case does not call a user-defined script. .. GENERATED FROM PYTHON SOURCE LINES 143-152 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_fcstCREDIT_GFS_obsGFS_6hrRealtime.conf /path/to/user_system.conf See :ref:`running-metplus` for more information. .. GENERATED FROM PYTHON SOURCE LINES 154-203 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/medium_range/GridStat_fcstCREDIT_GFS_obsGFS_6hrRealtime.conf. There will be 3 directories, data_ingest which contains the downloaded data, grid_stat which contains the output statistics, and StatAnalysis which contains the aggregated statistics. The data_ingest directory will contain 2 subdirectories, GFS and GFS_analysis, each with the downloaded data. The data inside the GFS directory is sorted by model initialization time and contains both surface and upper air data. These files have the format, where II is the model initialzation hours and HHH is the lead time in hours: * gfs.tIIz.pgrb2.0p25.fHHH * gfs.tIIz.sfluxgrbfHHH.grib2 The GFS_analysis directory contains one subdirectory 20250924 with 4 files: * gfs.2025092400.pgrb2.0p25.anl * gfs.2025092406.pgrb2.0p25.anl * gfs_anal_2025092400.sfcanl.nc * gfs_anal_2025092406.sfcanl.nc Inside the grid_stat directory, there are also 2 subdirectories, CREDIT/6h and GFS. The files output to CREDIT/6h are also stored in subdirectories dated with model initialization time in the format of YYYYMMDDHH. These files have the following format, where the dates labeled are lead time, valid year, month, and day, and valid hour, minute, and second: * grid_stat_CREDIT_surface_HHMMSSL_YYYYMMDD_HHMMSSV.stat * grid_stat_CREDIT_upper_air_HHMMSSL_YYYYMMDD_HHMMSSV.stat The files output to the GFS directory are also stored in subdirectories dated with model initialization time in the format of YYYYMMDDHH. These files have the same format as above where the dates labeled are lead time, valid year, month, and day, and valid hour, minute, and second: * grid_stat_GFS_surface_HHMMSSL_YYYYMMDD_HHMMSSV.stat * grid_stat_GFS_upper_air_HHMMSSL_YYYYMMDD_HHMMSSV.stat The StatAnalysis directory contains 1 subdirectory (6h). Inside that directory are 4 output files: * CREDIT_GFS_2025092400_2025092406_allleads_allValidHours_CNT.stat * CREDIT_GFS_2025092400_2025092406_allleads_allValidHours_CTS.stat * GFS_GFS_2025092400_2025092406_allleads_allValidHours_CNT.stat * GFS_GFS_2025092400_2025092406_allleads_allValidHours_CTS.stat .. GENERATED FROM PYTHON SOURCE LINES 205-222 Keywords -------- .. note:: * DataIngestToolUseCase * GridStatToolUseCase * StatAnalysisToolUseCase * MediumRangeAppUseCase * NCAROrgUseCase * GRIB2FileUseCase * NetCDFFileUseCase Navigate to the :ref:`quick-search` page to discover other similar use cases. sphinx_gallery_thumbnail_path = '_static/medium_range-GridStat_fcstCREDIT_GFS_obsGFS_6hrRealtime.png' .. _sphx_glr_download_generated_model_applications_medium_range_GridStat_fcstCREDIT_GFS_obsGFS_6hrRealtime.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: GridStat_fcstCREDIT_GFS_obsGFS_6hrRealtime.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: GridStat_fcstCREDIT_GFS_obsGFS_6hrRealtime.py ` .. container:: sphx-glr-download sphx-glr-download-zip :download:`Download zipped: GridStat_fcstCREDIT_GFS_obsGFS_6hrRealtime.zip ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_