ecPoint-Calibrate is a software that uses conditional verification tools to compare numerical weather prediction (NWP) model outputs against point observations and, in this way, anticipate sub-grid variability and identify biases at grid scale. It provides a dynamic and user-friendly environment to post-process NWP model parameters (such as precipitation, wind, temperature, etc.) and produce probabilistic products for geographical locations (everywhere in the world, and up to medium-range forecasts).
The development of this project was sponsored by the project "ECMWF Summer of Weather Code (ESoWC)" @esowc_ecmwf ECMWF.
docker build -f Dockerfile.core -t ecmwf/ecpoint-calibrate-core:dev .
./deploy.sh
yarn dist
The appimage won't work on modern machines without manually adding the --no-sandbox
electron
option and re-packaging.
sudo wget https://github.com/AppImage/AppImageKit/releases/download/continuous/appimagetool-x86_64.AppImage -O /usr/local/bin/appimagetool
sudo chmod +x /usr/local/bin/appimagetool
cd pkg
./ecPoint-Calibrate-0.30.0.AppImage --appimage-extract
This will extract the image into the squashfs-root
directory.
Open squashfs-root/AppRun
and change the exec
lines to have the --no-sandbox
argument.
e.g. exec "$BIN" --no-sandbox
Then repackage:
appimagetool squashfs-root ecPoint-Calibrate-0.30.0.AppImage
We need metview-batch
from conda-forge so unfortunately need to use conda
with poetry
.
conda create --name ecpoint_calibrate_env --file conda-linux-64.lock
conda activate ecpoint_calibrate_env
poetry install
conda activate ecpoint_calibrate_env
Installing a new package with poetry will update the poetry lockfile.
poetry install $DEP
You should very rarely need to add a new conda dep.
conda-lock -k explicit --conda mamba
mamba update --file conda-linux-64.lock
poetry update
First activate the conda env, then run pytest
.
You'll need node v 14.5.0.
yarn
yarn start
npm run test