G3.02    Limited quantification of the impact of different co-location criteria on comparison results

Gap detailed description

Co-location criteria should represent an optimal compromise between the obtained number of co-located measurements (as large as possible to have robust statistical results) and the impact of natural variability on the comparisons (as low as possible to allow a confrontation between measured differences and reported measurement uncertainties). Hitherto, only a limited set of ground-based satellite validation studies explored the impact of the adopted co-location criteria on the comparison results (e.g. Wunch et al., 2011, and Dils et al., 2014, for CO2, Verhoelst et al., 2015, for O3, Pappalardo et al., 2010, for aerosols, and Van Malderen et al. 2014, for integrated water vapour). Still, atmospheric variability is often assumed –or even known- to impact the comparisons (e.g. De Maziere et al. 2008), but without detailed testing of several co-location criteria (or by extensive model-based simulations), this impact is hard to quantify. Besides the need for dedicated studies, from which clear recommendations could be formulated (cfr. gap G3.03), this gap also concerns the “community practices” regarding validation approaches, which often rely on a set of default (historical) co-location criteria, which are not necessarily fit-for-purpose for the accuracy and spatiotemporal sampling properties of current measurement systems.   

Activities within GAIA-CLIM related to this gap

Two activities within GAIA-CLIM target this gap to some extent:

·         Within task T3.2 in WP3, data intercomparison studies focussing on a closure of the comparison uncertainty budget include an exploration of different co-location criteria, see for instance the results on total ozone columns already published by Verhoelst et al. (2015, their Fig. 11).

·         The Virtual Observatory developed in WP5 will offer the user the possibility to adjust co-location criteria and to visualize the resulting impact on the comparison results. 

Gap remedy(s)

Remedy #1

Specific remedy proposed

Dedicated studies exploring in detail the advantages and disadvantages of several co-location methods and criteria.  Dedicated working groups or activities could/should be set up within the framework of the ground-based observing networks, as already initiated for meteorological variables at a GRUAN-GSICS-GNSSRO WIGOS workshop on Upper-Air Observing System Integration and Application, hosted by WMO in  Geneva  in May 2014.

Measurable outcome of success

A peer-reviewed publication or a widely distributed technical note on the subject.

Achievable outcomes

The technical and organizational requirements for such studies are low, and so is the estimated cost, which is mostly to cover the salaries of the researchers involved.


In view of the increasingly operational nature of satellite data validation using non-satellite data for the ECVs targeted within GAIA-CLIM (e.g. within the Copernicus context), such studies would be of high relevance, as they could support the definition of current and future validation protocols (cfr. also gap G3.03). 


This remedy should not require more than a year’s FTE per ECV.  Note that some additional effort will be required to re-address this gap when both the satellite and ground-based observing systems undergo step changes in their performance, e.g. for the upcoming geo-stationary platforms with much higher temporal sampling.

Gap risks to non-resolution

Identified future risk / impact

Probability of occurrence if gap not remedied

Downstream impacts on ability to deliver high quality services to science / industry / society

Poor feedback on data quality (in particular on the reported uncertainties) from validation studies due to unknown/unquantified influence of atmospheric variability.

Very high

Interpretation of satellite data validation results severely hampered. This impacts negatively the reliability of the data sets, the reported uncertainties, and the products and services derived from these.


Work package: