Our algorithms can process the main data formats
traditionally used in meteorology for reporting or forecasting.
In addition to the classical CSV files, it is also possible to analyze more complex binary
formats like the GRIB or the NetCDF files.
In addition to the data provided by our customers, we have access to a large variety of reports from automatic weather stations (for example the METAR network with the aerodrome observations) or to the main online numerical weather forecasts.
This information constitutes the basic inputs that will then be corelated to operational data by machine learning techniques.
The Global Forecast System (GFS) is one the numerical model provided by the US National Centers for Environmental Prediction (NCEP). It is often use due to following advantages:
Alternative modeling approaches are also available: an ensemble model (GEFS) for the stability analysis and a Reforecast model for the long term or climatology analysis.
All these specifications enable to build high quality, low cost and robust models.