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
• Docker Compose
• NOTE: if a user uses python and pip in a conda environment, it is recommended that Docker and Docker-Compose are installed outsite such environment as this could cause problems running ecPoint-Calibrate. It is better to install Docker and Docker-Compose using the default installation of Python and pip, for example in /usr/bin.

$ git clone https://github.com/esowc/ecPoint-Calibrate.git
$ cd ecPoint-Calibrate

At this point, the dataset source must be configured on the filesystem, and make it available to the Docker services using volumes. Normally, if the data lives on a removable media, such as an external HDD, you shouldn't need to do anything. To configure a volume, simply add the dataset source to the services core, electron, and logger in the docker_compose.yml file.

$ ./go.sh

$ docker-compose exec core bash