.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "generated/model_applications/precipitation/PointStat_fcstURMA_obsCOCORAHS_ASCIIprecip.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_precipitation_PointStat_fcstURMA_obsCOCORAHS_ASCIIprecip.py: PointStat: Compare community observed precipitation to model forecasts ====================================================================== model_applications/precipitation/PointStat_fcstURMA_obsCOCORAHS_ASCIIprecip.conf .. GENERATED FROM PYTHON SOURCE LINES 9-13 .. contents:: :depth: 1 :local: :backlinks: none .. GENERATED FROM PYTHON SOURCE LINES 15-21 Scientific Objective -------------------- This use case ingests a CoCoRaHS csv file, a new dataset that utilizes community reporting of precipitation amounts. Numerous studies have shown that a community approach to weather observations not only covers areas that lack traditional verification datasets, but is also remarkably quality controlled. Utilizing Python embedding, this use case taps into a new vital observation dataset and compares it to a 24 hour precipitation accumulation forecast. .. GENERATED FROM PYTHON SOURCE LINES 23-27 Version Added ------------- METplus version 5.0 .. GENERATED FROM PYTHON SOURCE LINES 29-46 Datasets -------- **Forecast:** 24 UnRestricted Mesoscale Analysis (URMA) 1 hour precipitation accumulation files **Observations:** CoCoRaHS, the Community Collaborative Rain, Hail, and Snow Network **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 48-54 METplus Components ------------------ This use case calls a Python script in ASCII2NC for the observation dataset. PCPCombine is called for a user-defined summation of the forecast accumulation fields. Finally, PointStat processes the forecast and observation fields, and outputs the requested line types. .. GENERATED FROM PYTHON SOURCE LINES 56-78 METplus Workflow ---------------- **Beginning time (VALID_BEG):** 2022091423 **End time (VALID_END):** 2022091423 **Increment between beginning and end times (VALID_INCREMENT):** 1M **Sequence of forecast leads to process (LEAD_SEQ):** 24H 1 csv file of multiple valid observation times is passed to ASCII2NC via Python embedding, resulting in a netCDF output. 24 forecast files, each composed of 1 hour precipitation accumulation forecasts, is summarized via PCPCombine. The following boundary times are used for the forecast summation times: | **Valid Beg:** 2022-09-14 at 00z | **Valid End:** 2022-09-14 at 23z The observation data point span the same times as the 24 hour forecast accumulation summation. Finally, PointStat is used to compare the two new fields (point data in netCDF and precipitation accumulation over 24 hours). Because the Valid Time used in configuration file is set to one time (2022-09-14 at 23z) and the precipitation accumulation valid time is set to this same time, the observation window spans across the entire 2022-09-14 24 hour timeframe. .. GENERATED FROM PYTHON SOURCE LINES 80-90 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/precipitation/PointStat_fcstURMA_obsCOCORAHS_ASCIIprecip.conf .. highlight:: bash .. literalinclude:: ../../../../parm/use_cases/model_applications/precipitation/PointStat_fcstURMA_obsCOCORAHS_ASCIIprecip.conf .. GENERATED FROM PYTHON SOURCE LINES 92-111 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:: Ascii2NcConfig_wrapped .. literalinclude:: ../../../../parm/met_config/Ascii2NcConfig_wrapped .. dropdown:: PointStatConfig_wrapped .. literalinclude:: ../../../../parm/met_config/PointStatConfig_wrapped .. GENERATED FROM PYTHON SOURCE LINES 113-117 Python Embedding ---------------- This use case does not use Python embedding. .. GENERATED FROM PYTHON SOURCE LINES 119-123 User Scripting -------------- User Scripting is not used in this use case. .. GENERATED FROM PYTHON SOURCE LINES 125-134 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/precipitation/PointStat_fcstURMA_obsCOCORAHS_ASCIIprecip.conf /path/to/user_system.conf See :ref:`running-metplus` for more information. .. GENERATED FROM PYTHON SOURCE LINES 136-167 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 3 folders(relative to **OUTPUT_BASE**). Those folders are: * ASCII2NC * PCPCombine * PointStat The ASCII2NC folder will contain one file from the ASCII2NC tool call: * precip_20220914_summary.nc The PCPCombine folder will also contain one file, from the PCPCombine call: * fcst_24hr_precip.nc The final folder, PointStat, contains all of the following output from the PointStat call: * point_stat_000000L_20220914_230000V_cnt.txt * point_stat_000000L_20220914_230000V_ctc.txt * point_stat_000000L_20220914_230000V_cts.txt * point_stat_000000L_20220914_230000V_mcts.txt * point_stat_000000L_20220914_230000V.stat .. GENERATED FROM PYTHON SOURCE LINES 169-185 Keywords -------- .. note:: * PointStatToolUseCase * ASCII2NCToolUseCase * PCPCombineToolUseCase * PythonEmbeddingFileUseCase * PrecipitationAppUseCase * NETCDFFileUseCase Navigate to the :ref:`quick-search` page to discover other similar use cases. .. _sphx_glr_download_generated_model_applications_precipitation_PointStat_fcstURMA_obsCOCORAHS_ASCIIprecip.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: PointStat_fcstURMA_obsCOCORAHS_ASCIIprecip.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: PointStat_fcstURMA_obsCOCORAHS_ASCIIprecip.py ` .. container:: sphx-glr-download sphx-glr-download-zip :download:`Download zipped: PointStat_fcstURMA_obsCOCORAHS_ASCIIprecip.zip ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_