Weather forecast retrieval gathers relevant gridded weather forecasts to ingest into physically based models for water supply forecasts
Project description
Weather Forecast Retrieval
Weather forecast retrieval gathers relevant gridded weather forecasts to ingest into physically based models for water supply forecasts
Current atmospheric models implemented:
Install
pip install weather-forecast-retrieval
System dependencies
nccopy
nccopy
is used during the conversion in grib2nc
. To install the netCDF-C
libraries that are specific for your system. See the instructions from Unidata
wgrib2
To use the grib2nc
command/function you will have to have wgrib2
installed on the host computer.
This is easiest done by following NOAA instructions. After completing their instructions, make wgrib2 accessible by cd into the source code and attempt to install it under your ~/bin with:
ln wgrib2/wgrib2 ~/bin/wgrib2
Docker
The retrieval aspect of weather_forecast_retieval
has been built into a Docker image based on the Python 3 Alpine linux image. This allows for a docker deployment to run and retrieve HRRR data and convert to netcdf if needed. To use, first build the image
docker build -t usdaarsnwrc/weather_forecast_retieval .
Grab a coffee as this has to compile pandas
from source (10+ minutes of compile time). Once completed, modify or create a new docker-compose.yml
and modify the volume attachments as necessary. There are 2 volumes to attach, a data
drive mounted to /data
and the config file folders at /code/config
. To setup the download, the config file is passed to docker-compose
:
docker-compose run weather_forecast_retrieval /code/config/hrrr.ini
Command line usage
get_hrrr_archive
usage: get_hrrr_archive [-h] -s START_DATE -e END_DATE -o SAVE_DIR
[-f FORECASTS]
Command line tool for downloading HRRR grib files from the University of Utah
optional arguments:
-h, --help show this help message and exit
-s START_DATE, --start START_DATE
Datetime to start, ie 2018-07-22 12:00
-e END_DATE, --end END_DATE
Datetime to end, ie 2018-07-22 13:00
-o SAVE_DIR, --output SAVE_DIR
Path to save the downloaded files to
-f FORECASTS, --forecasts FORECASTS
Number of forecasts to get
The following command line will download data for a single hour and output into the ~/Downloads
folder to the file ~/Downloads/hrrr.20180722/hrrr.t12z.wrfsfcf01.grib2
:
get_hrrr_archive -s '2018-07-22 12:00' -e '2018-07-22 12:10' -o tests/RME/output/
hrrr_preprocessor
Use hrrr_preprocessor
to make smaller files from a larger HRRR file. This will crop to a bounding box and extract the following variables:
- air temperature 2m (TMP:2 m)
- relative_humidity 2m (RH:2 m)
- wind_u 10m (UGRD:10 m)
- wind_v 10m (VGRD:10 m)
- precip_int surface (APCP: surface)
- short_wave surface (DSWRF: surface)
- elevation (HGT:surface)
- TCDC for entire atmosphere (for WindNinja)
usage: hrrr_preprocessor [-h] -o OUTPUT_DIR -s START_DATE -e END_DATE -f
FORECAST_HR --bbox BBOX [--verbose]
hrrr_dir
Crop HRRR files by a bounding box and extract only the necessary surface variables for running with AWSM.
Example command:
$ hrrr_preprocessor -s '2019-10-01 00:00' -e '2019-10-01 02:00' -f 0 --bbox="-119,-118,37,38" -o /path/to/output --verbose /path/to/hrrr
positional arguments:
hrrr_dir Directory of HRRR files to use as input
optional arguments:
-h, --help show this help message and exit
-o OUTPUT_DIR, --output_dir OUTPUT_DIR
Directory to write cropped HRRR files to
-s START_DATE, --start START_DATE
Start date
-e END_DATE, --end END_DATE
End date
-f FORECAST_HR, --forecast_hr FORECAST_HR
Forecast hour
-n NCPU, --ncpu NCPU Number of CPUs for wgrib2, 0 (default) will use all
available
--bbox BBOX Bounding box as delimited string --bbox='longitude
left, longitude right, latitude bottom, latitude top'
--verbose increase logging verbosity
convert_grib2nc
run_hrrr_retrieval
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