.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "generated/model_applications/s2s/TCGen_fcstGFSO_obsBDECKS_GDF_TDF.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_s2s_TCGen_fcstGFSO_obsBDECKS_GDF_TDF.py: TCGen: Genesis Density Function (GDF) and Track Density Function (TDF) ====================================================================== model_applications/s2s/TCGen_fcstGFSO_obsBDECKS_GDF_TDF.conf .. GENERATED FROM PYTHON SOURCE LINES 9-13 .. contents:: :depth: 1 :local: :backlinks: none .. GENERATED FROM PYTHON SOURCE LINES 15-59 Scientific Objective -------------------- Tropocal cyclone (TC) genesis density function (GDF) and track density function (TDF) are designed to quantitatively evaluate geographic distributions of TC activities including TC genesis frequency and subsequent TC tracks. Spatial patterns of long-term averaged GDF or TDF on the regional or global scale are particularly useful to evaluate TC forecasts against those derived from an observational best-track dataset, such as IBTrACS or ATCF B-decks, from a climate perspective. The metrics can help assess the forecast biases (under- or over-prediction) of TC formations or TC vortices around particular locations in a numerical model. For demonstration purposes, only cyclone tracker output and b-decks data for 2016 are used. The following settings are used in the use case, all of which are configurable in the METplus configuration file (see below). Forecast genesis event criteria: | Minimum forecast lead: 48h | Maximum forecast lead: 120h | Maximum velocity threshold: >= 16.5 m/s | Minimum TC duration: 24h | Observed genesis event criteria: | Minimum TC duration: 24h | Maximum velocity threshold: >= 17.0 m/s | Minimum TC Category: TD | Matching settings: | Genesis matching window: +/- 24h | Early genesis matching window: -120h | Late genesis matching window: +120h | Genesis hit scoring window: +/- 24h | Early genesis hit scoring window: -120h | Late genesis hit scoring window: +120h | Matching and Scoring radius: 555 km | In addition to the above settings, normalization is performed on the metrics by the number of years included in the dataset (in this example, just one), and the total number of model forecasts valid at the time of an observed genesis event. The latter can also be thought of as the total number of chances that the model had to forecast a genesis event. .. GENERATED FROM PYTHON SOURCE LINES 61-65 Version Added ------------- METplus version 4.1 .. GENERATED FROM PYTHON SOURCE LINES 67-90 Datasets -------- Both forecast and observation datasets for this use case must adhere to the ATCF format. **Forecast:** GFDL Cyclone Tracker output configured for "genesis mode" for the FV3GFS model. This configuration used an experimental GFSv15 physics package, and had a horizontal grid spacing of ~25 km with 64 vertical levels. **Observation:** Global ATCF B-decks files from the National Hurricane Center (NHC) and Joint Typhoon Warning Center (JTWC) **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 92-107 Software Versions ----------------- This use case was developed with specific versions of various software and Python packages. Any deviation from these versions may require re-configuration or adaptation to reproduce the results shown. Names and version numbers:: python-3.6.3 cartopy-0.18.0 matplotlib-3.1.2 MET-10.0.0 METplus-4.0.0 METplotpy-1.0.0 .. GENERATED FROM PYTHON SOURCE LINES 109-116 METplus Components ------------------ This use case utilizes the MET TCGen tool to generate matched pairs of TC genesis, and then uses Python Embedding to compute the TDF and GDF metrics and create graphics for the year 2016. .. GENERATED FROM PYTHON SOURCE LINES 118-135 METplus Workflow ---------------- **Beginning time (INIT_BEG):** 2016 **End time (INIT_END):** None **Increment between beginning and end times (INIT_INCREMENT):** None **Sequence of forecast leads to process (LEAD_SEQ):** None The following tools are used for each run time: TCGen, Python The TCGen tool is designed to be provided a single file pair or a directory containing a list of files, rather than loop over valid or initialization times. Thus, a single year is used in the METplus configuration file and wildcard symbols are provided to gather all the tracker and genesis input files at each input directory. .. GENERATED FROM PYTHON SOURCE LINES 137-143 METplus Configuration --------------------- .. highlight:: bash .. literalinclude:: ../../../../parm/use_cases/model_applications/s2s/TCGen_fcstGFSO_obsBDECKS_GDF_TDF.conf .. GENERATED FROM PYTHON SOURCE LINES 145-159 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:: TCGenConfig_wrapped .. literalinclude:: ../../../../parm/met_config/TCGenConfig_wrapped .. GENERATED FROM PYTHON SOURCE LINES 161-174 Python Embedding ---------------- This use case uses a Python embedding script to create output graphics. .. dropdown:: parm/use_cases/model_applications/s2s/TCGen_fcstGFSO_obsBDECKS_GDF_TDF/UserScript_fcstGFSO_obsBDECKS_GDF_TDF.py .. highlight:: python .. literalinclude:: ../../../../parm/use_cases/model_applications/s2s/TCGen_fcstGFSO_obsBDECKS_GDF_TDF/UserScript_fcstGFSO_obsBDECKS_GDF_TDF.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 176-180 User Scripting -------------- User Scripting is not used in this use case. .. GENERATED FROM PYTHON SOURCE LINES 182-191 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/TCGen_fcstGFSO_obsBDECKS_GDF_TDF.conf /path/to/user_system.conf See :ref:`running-metplus` for more information. .. GENERATED FROM PYTHON SOURCE LINES 193-212 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 from TCGen for this use case will be found in model_applications/s2s/TCGen_fcstGFSO_obsBDECKS_GDF_TDF/TCGen (relative to **OUTPUT_BASE**) For each month and year there will be five files written:: * tc_gen_2016_pairs.nc * tc_gen_2016_genmpr.txt * tc_gen_2016_ctc.txt * tc_gen_2016_cts.txt * tc_gen_2016.stat .. GENERATED FROM PYTHON SOURCE LINES 214-228 Keywords -------- .. note:: * TCGenToolUseCase * S2SAppUseCase * UserScriptUseCase * METplotpyUseCase Navigate to the :ref:`quick-search` page to discover other similar use cases. .. GENERATED FROM PYTHON SOURCE LINES 228-230 .. code-block:: Python # .. _sphx_glr_download_generated_model_applications_s2s_TCGen_fcstGFSO_obsBDECKS_GDF_TDF.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: TCGen_fcstGFSO_obsBDECKS_GDF_TDF.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: TCGen_fcstGFSO_obsBDECKS_GDF_TDF.py ` .. container:: sphx-glr-download sphx-glr-download-zip :download:`Download zipped: TCGen_fcstGFSO_obsBDECKS_GDF_TDF.zip ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_