ecPoint is a post-processing system that uses conditional verification concepts to compare NWP model outputs against point observations, and thereby anticipate weather-dependant sub-grid variability and biases at grid scale.
The main ecPoint outputs are provided in grib files and consist of:

1. bias corrected rainfall forecasts at point scale (probabilistic forecast, provided in the form of percentiles).
2. bias corrected rainfall forecasts at grid scale (quatitative, in mm, with the same number of members as the raw ensemble).
3. diagnosed "weather type" indicators (provided for each ensemble member, for each grid box).

1. ecPoint code (written in an ECMWF proprietary language called "Metview")
2. Calibration "mapping function" files (computed using ecPoint-Calibrate)

Metview
Information about Metview and how to install it can be found here and in the Metview-Python GitHub repository. Versions from Metview 5 are required.

Test Data
Before running ecPoint, the user might want to download the test data from Zenodo:

1. ecPoint Vers1.0.0 and Vers2.0.0:

$ vi InParam.mv # Modify the input parameters as needed
$ metview -b ecPoint.mv # execute code in batch mode

N.B: depending on the chosen settings, ecPoint might take a long time to run in series. In such a case, the user might consider parallel running.

ecPoint uses the SemVer standard for versioning. The available ecPoint versions are provided here.