Remedy 2: Use of statistical analysis techniques based upon available and targeted additional observations

Primary gap remedy type: 
Secondary gap remedy type: 
Proposed remedy description: 

This remedy concerns the statistical analysis of existing and future satellite and non-satellite high-resolution data sets, which allows us to separate the contribution of atmospheric variability from the total uncertainty budget of a data comparison, e.g. using so-called structure functions or heteroskedastic functional regression. Within the geographical and temporal coverage of the data set, these methods produce an estimate of the variability (or auto-correlation) of the field.  Note that, as for Remedy G3.01(1), the scientific interest for higher resolution in the data sets is much broader than only the validation needs, e.g. for the identification of emission sources in an urban environment.

The technological and organizational effort required to make step changes in the spatiotemporal resolution of the observational data sets is in general very large, and comes with a large financial cost (more than 5M euro), in particular if global coverage is aimed for.  Hence, such developments need a much larger user base and the use proposed here should be considered secondary to the scientific objectives of such new missions. Nevertheless, smaller dedicated campaigns with for instance aircraft or Unmanned Aerial Vehicles (UAVs) can offer great insight at particularly interesting sites (e.g. at ground stations with a multitude of instruments observing a particular ECV), and this at medium cost (between 1M and 5M euro). 


This remedy directly addresses the gap, as already illustrated for instance with aircraft data for ozone by Sparling et al. (2006). 

Measurable outcome of success: 

The primary outcome would be publications describing for the different ECVs and various atmospheric regimes, locations and altitude ranges the atmospheric variability at scales ranging from those of in-situ measurements (e.g. 10s of meters for balloon sonde measurements) to that of a satellite pixel (several 10s to 100s of kilometres). These can be based either on existing data sets, or represent an exploitation of newly designed campaigns and missions. 

Expected viability for the outcome of success: 
  • High
Scale of work: 
  • Single institution
Time bound to remedy: 
  • Less than 5 years
Indicative cost estimate (investment): 
  • Low cost (< 1 million)
Indicative cost estimate (exploitation): 
  • No
Potential actors: 
  • EU H2020 funding
  • Copernicus funding
  • National funding agencies
  • National Meteorological Services