Report on the harmonization and qualification of meteorological data


A series of procedures and advanced mathematical tools have been developed to harmonize meteorological data sets to support validation activities as well as the integration of data into product generation and services. More precisely, MINES ParisTech has:

  • explored the different techniques for over-sampling, and showed that none of them respect the consistency property. They have also proposed a corrected version of the linear and cubic spline interpolations and demonstrate that it improves the results.
  • They have quantified the impact of missing subdaily values on daily average time series. They expressed this impact as a function of the percentage in missing data. As well, they propose a limit of acceptable percentage of missing data according to the foreseen exploitation of the daily data.
  • They have proposed a series of automatic quality check procedures to assess the sometimes unknown quality of the meteorological ground station data.
  • Finally, relying on previous improvements, a auality assessment protocol of satellite-derived variables compared to a reference have been established.

This work corresponds to the deliverable D3.2.