Difference between revisions of "How to convert data for Geogrid"
(→Get Anaconda3 distribution: update) |
(→Install environment: rm talk) |
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== Install environment == | == Install environment == | ||
− | Create | + | Create the python environment: |
+ | |||
+ | <pre> | ||
conda create -n wrfxpy python=3 gdal netcdf4 pyproj paramiko dill scikit-learn h5py pandas psutil proj4 | conda create -n wrfxpy python=3 gdal netcdf4 pyproj paramiko dill scikit-learn h5py pandas psutil proj4 | ||
conda activate wrfxpy | conda activate wrfxpy | ||
conda install -c conda-forge simplekml pygrib f90nml pyhdf xmltodict basemap | conda install -c conda-forge simplekml pygrib f90nml pyhdf xmltodict basemap | ||
pip install MesoPy python-cmr | pip install MesoPy python-cmr | ||
+ | </pre> | ||
Note that <tt>conda</tt> and <tt>pip</tt> are package managers available in the Anaconda Python distribution. | Note that <tt>conda</tt> and <tt>pip</tt> are package managers available in the Anaconda Python distribution. |
Revision as of 06:19, 19 July 2020
- Back to the WRF-SFIRE user guide.
This wiki page explains how to transform geotiff files to geogrid using convert_geotiff script in wrfxpy.
Get Anaconda3 distribution
Download and install the Python 3 Anaconda Python distribution for your platform. We recommend an installation into the user's home directory.
Install environment
Create the python environment:
conda create -n wrfxpy python=3 gdal netcdf4 pyproj paramiko dill scikit-learn h5py pandas psutil proj4 conda activate wrfxpy conda install -c conda-forge simplekml pygrib f90nml pyhdf xmltodict basemap pip install MesoPy python-cmr
Note that conda and pip are package managers available in the Anaconda Python distribution.
Get wrfxpy repository
Get repository wrfxpy and checkout to convert_geotiff branch. Shortly, it is going to be available in the master branch.
git clone https://github.com/openwfm/wrfxpy git checkout convert_geotiff
Run convert_geotiff.sh
Run the code to generate geogrid from geotiff files. Run the following line for each variable to process.
./convert_geotiff.sh geotiff_file geo_data_path wrf_variable_name [bbox]
where:
- geotiff_file - path to a geotiff file to be converted to geogrid
- geo_data_path - any path where to save all the variables
- wrf_variable - WRF variable created on src/geo/var_wisdom.py
- bbox - optional, bounding box to sample the original geotiff file from, using WGS84 coordinates. Format: min_lon,max_lon,min_lat,max_lat
If you want to know more information and the existing options for wrf_variable, run ./convert_geotiff.sh without inputs
./convert_geotiff.sh
Some examples:
./convert_geotiff.sh elevation.tif geo_data ZSF ./convert_geotiff.sh fuel.tif geo_data NFUEL_CAT ./convert_geotiff.sh fuel.tif geo_data NFUEL_CAT -112.8115,-112.1661,39.4820,39.9750
Results from convert_geotiff.sh
The convert_geotiff.sh script will generate a folder specified by the user by geo_data_path with
- Variable folders: A folder for each variable previously run (ZSF and NFUEL_CAT folders) containing:
- a geogrid file of the variable.
- an index file of the variable.
- geogrid_tbl.json: A JSON file with all the geogrid information for each variable.
- GEOGRID.TBL: A text file with the information to add to GEOGRID.TBL (depends on src/geo/var_wisdom.py, so only copy what you need).
- index.json: A JSON file with index information for each variable.