Docker container for the WPS model

This repo contains 4 Docker containers that together allow to run the WPS model.

Content of the repo

• gfs: empty dir that will contains files of gfs model
• ifs: empty dir that will contains files of ifs model
• namelist-prepare: go script to evaluate namelists templates
• WPS_GEOG: empty dir that will contains static GEO data
• wps.compile: Docker container to compile WPS, WRF and theirs relative dependencies
• wps.run: base container to run WPS (inherited by wps.gfs and wps.ifs)
• wps.gfs: container to run WPS based on input from gfs model
• wps.ifs: container to run WPS based on input from ifs model

Build

To build the images, after you clone the repo locally:

Build dependencies image

cd wps.compile
docker build .
docker tag <resulting image id> wps.compile
./run.sh

These commands builds all dependencies of WPS and WRF, and put theme in ../wps.run where they will be add to that image.

Build base wps image

These commands will build the wps.run image, that is the command parent of the two containers that will run: wps.ifs and wps.gfs

cd wps.run
docker build .
docker tag <resulting image id> wps

Build ifs and gfs WPS image

cd wps.gfs
docker build .
docker tag <resulting image id> wps.gfs
cd ../wps.ifs
docker build .
docker tag <resulting image id> wps.ifs

Run ifs container

• make sure that ifs directory contains ifs files for the day/s you want to forecast.
• make sure that WPS_GEOG directory contains static geo data for the run.
• start and end arguments should be in YYYYMMDDHH format, and they must corresponds with time the range of ifs files

cd wps.ifs
./run 2019101000 2019101200         # start and date and time of the time range to forecast.

Run gfs container

• make sure that gfs directory contains gfs files for the day/s you want to forecast.
• make sure that WPS_GEOG directory contains static geo data for the run.
• start and end arguments should be in YYYYMMDDHH format, and they must corresponds with time the range of ifs files

cd wps.gfs
./run 2019101000 2019101200         # start and date and time of the time range to forecast.