.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "generated/model_applications/climate/MODE_fcstCESM_obsGPCP_AsianMonsoonPrecip.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_climate_MODE_fcstCESM_obsGPCP_AsianMonsoonPrecip.py: MODE: CESM and GPCP Asian Monsoon Precipitation ============================================================================ model_applications/climate/MODE_fcstCESM_obsGPCP_AsianMonsoonPrecip.conf .. GENERATED FROM PYTHON SOURCE LINES 9-13 .. contents:: :depth: 1 :local: :backlinks: none .. GENERATED FROM PYTHON SOURCE LINES 15-22 Scientific Objective -------------------- To evaluate the CESM model daily precipitation against the GPCP daily precipitation over the Indian Monsoon region to obtain object based output statistics. This was developed as part of the NCAR System for Integrated Modeling of the Atmosphere (SIMA) project. .. GENERATED FROM PYTHON SOURCE LINES 24-28 Version Added ------------- METplus version 3.1 .. GENERATED FROM PYTHON SOURCE LINES 30-47 Datasets -------- **Forecast**: CESM Daily Precipitation **Observation**: GPCP Daily Precipitation **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 49-54 METplus Components ------------------ This use case runs mode to create object based statistics on daily precipitation data from the CESM model and observations from the GPCP. .. GENERATED FROM PYTHON SOURCE LINES 56-82 METplus Workflow ---------------- **Beginning time (INIT_BEG):** 2014060100 **End time (INIT_END):** 2014060200 **Increment between beginning and end times (INIT_INCREMENT):** 1 day **Sequence of forecast leads to process (LEAD_SEQ):** 24, 48 The mode tool is run for each time. This example loops by model initialization time. It processes two initialization times and two lead times for each for a total of 4 valid times, listed below. | **Valid:** 2014-06-02_0Z | **Forecast lead:** 24 | **Valid:** 2014-06-03_0Z | **Forecast lead:** 48 | **Init:** 2014-06-03_0Z | **Forecast lead:** 24 | **Init:** 2014-06-04_0Z | **Forecast lead:** 48 .. GENERATED FROM PYTHON SOURCE LINES 85-94 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, parm/use_cases/model_applications/climate/MODE_fcstCESM_obsGPCP_AsianMonsoonPrecip.conf .. highlight:: bash .. literalinclude:: ../../../../parm/use_cases/model_applications/climate/MODE_fcstCESM_obsGPCP_AsianMonsoonPrecip.conf .. GENERATED FROM PYTHON SOURCE LINES 96-113 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` .. note:: See the :ref:`MODE MET Configuration` section of the User's Guide for more information on the environment variables used in the file below: .. dropdown:: MODEConfig_wrapped .. highlight:: bash .. literalinclude:: ../../../../parm/met_config/MODEConfig_wrapped .. GENERATED FROM PYTHON SOURCE LINES 115-119 Python Embedding ---------------- This use case does not use Python embedding. .. GENERATED FROM PYTHON SOURCE LINES 121-126 User Scripting -------------- This use case does not use additional scripts. However, a sample NCL script to plot the output is available on the `Sample Analysis Scripts `_ page. .. 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/climate/MODE_fcstCESM_obsGPCP_AsianMonsoonPrecip.conf /path/to/user_system.conf See :ref:`running-metplus` for more information. .. GENERATED FROM PYTHON SOURCE LINES 139-206 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/climate/CESM_MODE and will contain the following files:: * 2014_06_01_000000/mode_000000L_20140602_000000V_000000A_R1_T1_cts.txt * 2014_06_01_000000/mode_000000L_20140602_000000V_000000A_R1_T1_obj.nc * 2014_06_01_000000/mode_000000L_20140602_000000V_000000A_R1_T1_obj.txt * 2014_06_01_000000/mode_000000L_20140602_000000V_000000A_R1_T1.ps * 2014_06_01_000000/mode_000000L_20140602_000000V_000000A_R1_T2_cts.txt * 2014_06_01_000000/mode_000000L_20140602_000000V_000000A_R1_T2_obj.nc * 2014_06_01_000000/mode_000000L_20140602_000000V_000000A_R1_T2_obj.txt * 2014_06_01_000000/mode_000000L_20140602_000000V_000000A_R1_T2.ps * 2014_06_01_000000/mode_000000L_20140603_000000V_000000A_R1_T1_cts.txt * 2014_06_01_000000/mode_000000L_20140603_000000V_000000A_R1_T1_obj.nc * 2014_06_01_000000/mode_000000L_20140603_000000V_000000A_R1_T1_obj.txt * 2014_06_01_000000/mode_000000L_20140603_000000V_000000A_R1_T1.ps * 2014_06_01_000000/mode_000000L_20140603_000000V_000000A_R1_T2_cts.txt * 2014_06_01_000000/mode_000000L_20140603_000000V_000000A_R1_T2_obj.nc * 2014_06_01_000000/mode_000000L_20140603_000000V_000000A_R1_T2_obj.txt * 2014_06_01_000000/mode_000000L_20140603_000000V_000000A_R1_T2.ps * 2014_06_02_000000/mode_000000L_20140603_000000V_000000A_R1_T1_cts.txt * 2014_06_02_000000/mode_000000L_20140603_000000V_000000A_R1_T1_obj.nc * 2014_06_02_000000/mode_000000L_20140603_000000V_000000A_R1_T1_obj.txt * 2014_06_02_000000/mode_000000L_20140603_000000V_000000A_R1_T1.ps * 2014_06_02_000000/mode_000000L_20140603_000000V_000000A_R1_T2_cts.txt * 2014_06_02_000000/mode_000000L_20140603_000000V_000000A_R1_T2_obj.nc * 2014_06_02_000000/mode_000000L_20140603_000000V_000000A_R1_T2_obj.txt * 2014_06_02_000000/mode_000000L_20140603_000000V_000000A_R1_T2.ps * 2014_06_02_000000/mode_000000L_20140604_000000V_000000A_R1_T1_cts.txt * 2014_06_02_000000/mode_000000L_20140604_000000V_000000A_R1_T1_obj.nc * 2014_06_02_000000/mode_000000L_20140604_000000V_000000A_R1_T1_obj.txt * 2014_06_02_000000/mode_000000L_20140604_000000V_000000A_R1_T1.ps * 2014_06_02_000000/mode_000000L_20140604_000000V_000000A_R1_T2_cts.txt * 2014_06_02_000000/mode_000000L_20140604_000000V_000000A_R1_T2_obj.nc * 2014_06_02_000000/mode_000000L_20140604_000000V_000000A_R1_T2_obj.txt * 2014_06_02_000000/mode_000000L_20140604_000000V_000000A_R1_T2.ps For the netCDF file, 18 variable fields are present (not including the lat/lon fields). Those variables are:: * fcst_raw(lat, lon) * fcst_obj_raw(lat, lon) * fcst_obj_id(lat, lon) * fcst_clus_id(lat, lon) * obs_raw(lat, lon) * obs_obj_raw(lat, lon) * obs_obj_id(lat, lon) * obs_clus_id(lat, lon) * fcst_conv_radius * obs_conv_radius * fcst_conv_threshold(fcst_thresh_length) * obs_conv_threshold(obs_thresh_length) * fcst_variable(fcst_variable_length) * obs_variable(obs_variable_length) * fcst_level(fcst_level_length) * obs_level(obs_level_length) * fcst_units(fcst_units_length) * obs_units(obs_units_length) .. GENERATED FROM PYTHON SOURCE LINES 208-222 Keywords --------- .. note:: * MODEToolUseCase * ClimateAppUseCase * NetCDFFileUseCase * NCAROrgUseCase Navigate to the :ref:`quick-search` page to discover other similar use cases. .. _sphx_glr_download_generated_model_applications_climate_MODE_fcstCESM_obsGPCP_AsianMonsoonPrecip.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: MODE_fcstCESM_obsGPCP_AsianMonsoonPrecip.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: MODE_fcstCESM_obsGPCP_AsianMonsoonPrecip.py ` .. container:: sphx-glr-download sphx-glr-download-zip :download:`Download zipped: MODE_fcstCESM_obsGPCP_AsianMonsoonPrecip.zip ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_