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Co-authored-by: Kathryn Newman <knewman@seneca.rap.ucar.edu> Co-authored-by: j-opatz <59586397+j-opatz@users.noreply.github.com> Co-authored-by: Lisa Goodrich <lisag@ucar.edu> Co-authored-by: Julie Prestopnik <jpresto@seneca.rap.ucar.edu> Co-authored-by: johnhg <johnhg@ucar.edu> Co-authored-by: George McCabe <23407799+georgemccabe@users.noreply.github.com> Co-authored-by: Mrinal Biswas <biswas@ucar.edu> Co-authored-by: Julie Prestopnik <jpresto@ucar.edu> Co-authored-by: Christina Kalb <kalb@mohawk.rap.ucar.edu> Co-authored-by: Hank Fisher <fisherh@seneca.rap.ucar.edu> Co-authored-by: jprestop <jpresto@ucar.edu> Co-authored-by: cristianastan2 <cstan@gmu.edu> Co-authored-by: John Halley Gotway <johnhg@ucar.edu> Co-authored-by: bikegeek <minnawin@ucar.edu> Co-authored-by: Hank Fisher <fisherh@ucar.edu> Co-authored-by: j-opatz <jopatz@ucar.edu> Co-authored-by: Christina Kalb <kalb@ucar.edu> Co-authored-by: lisagoodrich <33230218+lisagoodrich@users.noreply.github.com> Co-authored-by: Howard Soh <hsoh@seneca.rap.ucar.edu> Co-authored-by: Molly Smith <molly.b.smith@noaa.gov> Co-authored-by: hsoh-u <hsoh@ucar.edu> Co-authored-by: bikegeek <3753118+bikegeek@users.noreply.github.com> Co-authored-by: Will Mayfield <59745143+willmayfield@users.noreply.github.com>
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...cases/model_applications/data_assimilation/StatAnalysis_fcstGFS_HofX_obsIODAv2_PyEmbed.py
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""" | ||
StatAnalysis: IODAv2 | ||
=========================================================================== | ||
model_applications/data_assimilation/StatAnalysis_fcstGFS_HofX_obsIODAv2_PyEmbed.conf | ||
""" | ||
|
||
########################################### | ||
# Scientific Objective | ||
# -------------------- | ||
# | ||
# This use case demonstrates the Stat-Analysis tool and ingestion of HofX NetCDF files | ||
# that have been output from the Joint Effort for Data assimilation Integration (JEDI) | ||
# data assimilation system. JEDI uses IODA version 2 formatted files, which are NetCDF files | ||
# with certain requirements of variables and naming conventions. These files | ||
# hold observations to be assimilated into forecasts, in this case taken from the JEDI software | ||
# test data, which contained a small number of Global observation-forecast pairs | ||
# derived from the hofx application. | ||
# | ||
# UFO is a component of HofX, which maps the background forecast to observation space | ||
# to form O minus B pairs. The HofX application of JEDI takes the input IODAv2 files and | ||
# adds an additional variable which is the forecast value as interpolated to the | ||
# observation location. These HofX files are used as input to form Matched Pair (MPR) | ||
# formatted lists via Python embedding. In this case, Stat-Analysis then performs an aggregate_stat | ||
# job and outputs statistics in an ascii file. | ||
# | ||
# This use case adopts the IODAv2 formatted NetCDF files, which replace the previous variable | ||
# formatting scheme to make use of NetCDF groups. | ||
|
||
############################################################################## | ||
# Datasets | ||
# -------- | ||
# | ||
# | ||
# | **Data source:** JEDI HofX output files in IODAv2 format | ||
# | ||
# | **Location:** All of the input data required for this use case can be found in the met_test sample data tarball. Click here to the METplus releases page and download sample data for the appropriate release: https://github.com/dtcenter/METplus/releases | ||
# | The tarball should be unpacked into the directory that you will set the value of INPUT_BASE. See `Running METplus`_ section for more information. | ||
# | | ||
|
||
############################################################################## | ||
# METplus Components | ||
# ------------------ | ||
# | ||
# This use case utilizes the METplus StatAnalysis wrapper to search for | ||
# files that are valid for the given case and generate a command to run | ||
# the MET tool stat_analysis. | ||
|
||
############################################################################## | ||
# METplus Workflow | ||
# ---------------- | ||
# | ||
# StatAnalysis is the only tool called in this example. It processes the following | ||
# run times: | ||
# | ||
# | **Valid:** 2018-04-15_00Z | ||
# | **Forecast lead:** 0 hour | ||
# | | ||
|
||
############################################################################## | ||
# 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 | ||
# with the -c option, i.e. -c parm/use_cases/model_applications/data_assimilation/StatAnalysis_fcstGFS_HofX_obsIODAv2_PyEmbed.conf | ||
# | ||
# .. highlight:: bash | ||
# .. literalinclude:: ../../../../parm/use_cases/model_applications/data_assimilation/StatAnalysis_fcstGFS_HofX_obsIODAv2_PyEmbed.conf | ||
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############################################################################## | ||
# MET Configuration | ||
# ----------------- | ||
# | ||
# METplus sets environment variables based on user settings in the METplus configuration file. | ||
# See :ref:`How METplus controls MET config file settings<metplus-control-met>` 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<met-config-overrides>` | ||
# | ||
# .. note:: See the :ref:`StatAnalysis MET Configuration<stat-analysis-met-conf>` section of the User's Guide for more information on the environment variables used in the file below: | ||
# | ||
# .. highlight:: bash | ||
# .. literalinclude:: ../../../../parm/met_config/STATAnalysisConfig_wrapped | ||
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############################################################################## | ||
# Python Embedding | ||
# ---------------- | ||
# | ||
# This use case uses a Python embedding script to read input data | ||
# | ||
# parm/use_cases/model_applications/data_assimilation/StatAnalysis_fcstGFS_HofX_obsIODAv2_PyEmbed/read_iodav2_mpr.py | ||
# | ||
# .. highlight:: python | ||
# .. literalinclude:: ../../../../parm/use_cases/model_applications/data_assimilation/StatAnalysis_fcstGFS_HofX_obsIODAv2_PyEmbed/read_iodav2_mpr.py | ||
# | ||
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############################################################################## | ||
# Running METplus | ||
# --------------- | ||
# | ||
# It is recommended to run this use case by: | ||
# | ||
# Passing in StatAnalysis_fcstGFS_HofX_obsIODAv2_PyEmbed.conf then a user-specific system configuration file:: | ||
# | ||
# run_metplus.py -c /path/to/StatAnalysis_fcstGFS_HofX_obsIODAv2_PyEmbed.conf -c /path/to/user_system.conf | ||
# | ||
# The following METplus configuration variables must be set correctly to run this example.: | ||
# | ||
# * **INPUT_BASE** - Path to directory where sample data tarballs are unpacked (See Datasets section to obtain tarballs). | ||
# * **OUTPUT_BASE** - Path where METplus output will be written. This must be in a location where you have write permissions | ||
# * **MET_INSTALL_DIR** - Path to location where MET is installed locally | ||
# | ||
# Example User Configuration File:: | ||
# | ||
# [dir] | ||
# INPUT_BASE = /path/to/sample/input/data | ||
# OUTPUT_BASE = /path/to/output/dir | ||
# MET_INSTALL_DIR = /path/to/met-X.Y | ||
# | ||
# **NOTE:** All of these items must be found under the [dir] section. | ||
# | ||
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||
|
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############################################################################## | ||
# 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 StatAnalysis_IODAv2 (relative to **OUTPUT_BASE**) | ||
# and will contain the following file: | ||
# | ||
# * dump.out | ||
|
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############################################################################## | ||
# Keywords | ||
# -------- | ||
# | ||
# .. note:: | ||
# | ||
# * StatAnalysisToolUseCase | ||
# * PythonEmbeddingFileUseCase | ||
# * DataAssimilationUseCase | ||
# | ||
# Navigate to the :ref:`quick-search` page to discover other similar use cases. | ||
# | ||
# | ||
# sphinx_gallery_thumbnail_path = '_static/data_assimilation-StatAnalysis_fcstGFS_HofX_obsIODAv2_PyEmbed.png' |
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docs/use_cases/model_applications/unstructured_grids/README.rst
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Unstructured Grids | ||
------------------ | ||
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Unstructured grids used by models for numerical weather prediction. |
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...es/model_applications/unstructured_grids/StatAnalysis_fcstLFRIC_UGRID_obsASCII_PyEmbed.py
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""" | ||
StatAnalysis: UGRID | ||
=========================================================================== | ||
model_applications/unstructured_grids/StatAnalysis_fcstLFRIC_UGRID_obsASCII_PyEmbed.conf | ||
""" | ||
|
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########################################### | ||
# Scientific Objective | ||
# -------------------- | ||
# | ||
# This use case demonstrates the use of python embedding to ingest and perform | ||
# verification on an unstructured grid. This foregoes the need to interpolate | ||
# to a regular grid as a step in the verification process, thereby avoiding | ||
# any incurred interpolation error in the process. | ||
# | ||
# In particular, this use case ingests a UK MET Office LFRic forecast file in | ||
# NetCDF format, which resides in the UGRID format of the cubed-sphere. The python | ||
# library Iris was developed to perform analysis on various UGRID formats, and is | ||
# employed here to ingest the file as well as perform direct interpolation | ||
# from the native forecast grid to observation locations, thereby forming matched | ||
# pairs to pass to stat_analysis. In order to perform the interpolation using a | ||
# nearest-neighbors approach, the geovista python package is also used to form a | ||
# KD tree to be used in identifying the interpolation points to be used. This | ||
# package is located at https://github.com/bjlittle/geovista/ and can be installed | ||
# from a development version. It is also required to install the pyvista python | ||
# package. ASCII files containing observations are also ingested. | ||
# | ||
# The python embedding script itself performs the interpolation in time, and | ||
# for this use case thins the observation data in order to reduce the run time. | ||
# It is also noted that the observations for this use case were fabricated and | ||
# correlated observation-forecast pairs are not expected. | ||
# | ||
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############################################################################## | ||
# Datasets | ||
# -------- | ||
# | ||
# | ||
# | **Data source:** UK MET Office LFRic forecast files in UGRID NetCDF format and observations in ASCII format | ||
# | ||
# | **Location:** All of the input data required for this use case can be found in the met_test sample data tarball. Click here to the METplus releases page and download sample data for the appropriate release: https://github.com/dtcenter/METplus/releases | ||
# | The tarball should be unpacked into the directory that you will set the value of INPUT_BASE. See `Running METplus`_ section for more information. | ||
# | | ||
|
||
############################################################################## | ||
# METplus Components | ||
# ------------------ | ||
# | ||
# This use case utilizes the METplus StatAnalysis wrapper to search for | ||
# files that are valid for the given case and generate a command to run | ||
# the MET tool stat_analysis. | ||
|
||
############################################################################## | ||
# METplus Workflow | ||
# ---------------- | ||
# | ||
# StatAnalysis is the only tool called in this example. It processes the following | ||
# run times: | ||
# | ||
# | **Valid:** 2021-05-05_00Z | ||
# | **Forecast lead:** 12 hour | ||
# | | ||
|
||
############################################################################## | ||
# 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 | ||
# with the -c option, i.e. -c parm/use_cases/model_applications/unstructured_grids/StatAnalysis_fcstLFRIC_UGRID_obsASCII_PyEmbed.conf | ||
# | ||
# .. highlight:: bash | ||
# .. literalinclude:: ../../../../parm/use_cases/model_applications/unstructured_grids/StatAnalysis_fcstLFRIC_UGRID_obsASCII_PyEmbed.conf | ||
|
||
############################################################################## | ||
# MET Configuration | ||
# ----------------- | ||
# | ||
# METplus sets environment variables based on user settings in the METplus configuration file. | ||
# See :ref:`How METplus controls MET config file settings<metplus-control-met>` 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<met-config-overrides>` | ||
# | ||
# .. note:: See the :ref:`StatAnalysis MET Configuration<stat-analysis-met-conf>` section of the User's Guide for more information on the environment variables used in the file below: | ||
# | ||
# .. highlight:: bash | ||
# .. literalinclude:: ../../../../parm/met_config/STATAnalysisConfig_wrapped | ||
|
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############################################################################## | ||
# Python Embedding | ||
# ---------------- | ||
# | ||
# This use case uses a Python embedding script to read input data | ||
# | ||
# parm/use_cases/model_applications/unstructured_grids/StatAnalysis_fcstLFRIC_UGRID_obsASCII_PyEmbed/ugrid_lfric_mpr.py | ||
# | ||
# .. highlight:: python | ||
# .. literalinclude:: ../../../../parm/use_cases/model_applications/unstructured_grids/StatAnalysis_fcstLFRIC_UGRID_obsASCII_PyEmbed/ugrid_lfric_mpr.py | ||
# | ||
|
||
############################################################################## | ||
# Running METplus | ||
# --------------- | ||
# | ||
# It is recommended to run this use case by: | ||
# | ||
# Passing in StatAnalysis_fcstLFRIC_UGRID_obsASCII_PyEmbed.conf then a user-specific system configuration file:: | ||
# | ||
# run_metplus.py -c /path/to/StatAnalysis_fcstLFRIC_UGRID_obsASCII_PyEmbed.conf -c /path/to/user_system.conf | ||
# | ||
# The following METplus configuration variables must be set correctly to run this example.: | ||
# | ||
# * **INPUT_BASE** - Path to directory where sample data tarballs are unpacked (See Datasets section to obtain tarballs). | ||
# * **OUTPUT_BASE** - Path where METplus output will be written. This must be in a location where you have write permissions | ||
# * **MET_INSTALL_DIR** - Path to location where MET is installed locally | ||
# | ||
# Example User Configuration File:: | ||
# | ||
# [dir] | ||
# INPUT_BASE = /path/to/sample/input/data | ||
# OUTPUT_BASE = /path/to/output/dir | ||
# MET_INSTALL_DIR = /path/to/met-X.Y | ||
# | ||
# **NOTE:** All of these items must be found under the [dir] section. | ||
# | ||
|
||
|
||
############################################################################## | ||
# 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 StatAnalysis_UGRID (relative to **OUTPUT_BASE**) | ||
# and will contain the following file: | ||
# | ||
# * dump.out | ||
|
||
############################################################################## | ||
# Keywords | ||
# -------- | ||
# | ||
# .. note:: | ||
# | ||
# * StatAnalysisToolUseCase | ||
# * PythonEmbeddingFileUseCase | ||
# * UnstructureGridsUseCase | ||
# | ||
# Navigate to the :ref:`quick-search` page to discover other similar use cases. | ||
# | ||
# | ||
# sphinx_gallery_thumbnail_path = '_static/unstructured_grids-StatAnalysis_fcstLFRIC_UGRID_obsASCII_PyEmbed.png' |
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