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Final version of tools for quantification of co-location mismatch and smoothing uncertainties and associated documentation for integration in the virtual observatory

Final version of tools for quantification of co-location mismatch and smoothing uncertainties and associated documentation for integration in the virtual observatory that reflects any subsequent updates arising as a result of a. feedback from WP5 and b. any subsequent finessing in tasks T3.1 and 3.2

An introduction to the GRUAN Processor

Poster by Fabien Carmiati at the Environment and Climate Change Canada 5th WGNE workshop Montreal -  June 19-23, 2017

Smoothing and co-location uncertainty libraries

GAIA-CLIM is supporting the European Commission’s Copernicus Programme by assessing and improving the fitness-for-purpose of sub-orbital (ground- and balloon-based) reference measurements for the validation of observational data sets from satellites. Amongst others, the project aims at improved traceability and uncertainty characterization of the individual sub-orbital measurement systems, and of the comparison with satellite data.  The latter implies the need for a rigorous treatment of so-called co-location mismatch uncertainties. These are the result of (differences in) smoothing and sampling properties of the various ground-based and satellite observing systems. These differences matter because the atmosphere is inhomogeneous and variable on the scale of individual measurements and on the scale of a typical co-location. Consequently, sampling and smoothing differences yield real physical and chemical differences, which have nothing to do with the measurement performance per se. Two perfect measurements measuring a slightly different volume and time integral are a priori expected to differ.   

Within GAIA-CLIM, several methods have been developed for - and applied to - the quantification of smoothing and sampling issues in a range of atmospheric ground-based measurement techniques, and to estimate the uncertainties that need to be taken into account when comparing non-perfectly co-located ground-based and satellite measurements with different spatio-temporal smoothing and sampling properties. The motivation for these developments and the principles of the different methods has been described in deliverable D3.2 (“Generic metrology aspects of an atmospheric composition measurement and of data comparisons”), and a wide variety of applications were performed and reported on in D3.4 (“Measurement mismatch studies and their impact on data comparisons”).

To translate these developments and results into a practical, usable resource for Copernicuas Climate Change Services users, two avenues were foreseen within GAIA-CLIM: (1) an integration of (derived) tools into the Virtual Observatory (VO), where they serve to estimate smoothing, sampling, and co-location uncertainties for the data ingested into the VO and for the satellite-ground co-locations performed by that system, and (2) publication of libraries (i.e. guiding material and data files) of such uncertainties for key ground-based measurement systems and for key comparisons. The former avenue constitutes the material for deliverables D3.5 ("Tools for quantification and smoothing uncertainties for integration in development of VO") and D3.7 ("Final version of tools for quantification of collocation mismatch and smoothing uncertainties and associated documentation for integration in the virtual observatory"), while the latter is the topic of the deliverable D3.6 ("Library of (1) smoothing/sampling error estimates for key atmospheric composition measurement systems, and (2) smoothing/sampling error estimates for key data comparisons").

The actual data files, are available for download (by anonymous/guest ftp) at:

Library of (1) smoothing/sampling error estimates for key atmospheric composition measurement systems, and (2) smoothing sampling error estimates for key data comparisons

A final Version 1.1 of the libraries and corresponding document, including the description of NetCDF files for T and q temporal mismatch uncertainties, was produced in October 2017 (after formal submission of the deliverable). These netCDF files complement the MS Excel workbooks already included in the 1st version.




The Recommendations document attempts to distill the findings from the gap analysis performed within GAIA-CLIM as described in the Gaps Assessment and Impacts Document (GAID) and associated online Catalogue of Gaps into a set of high-level actionable priority recommended activities. It is intended to be a high-level accessible document supported by the rich information on gaps collected throughout the project.

Comments and feedback are welcome via Feedback

Table: High-level recommendation titles and thematic clustering.

Education and training

Maintain and further develop a trained workforce competent in EO data characterisation and downstream applications to support Copernicus activities

Non-satellite data quality and availability

Improve the metrological characterisation of a suite of non-satellite measurement techniques: Striving for traceable, reference quality, fiducial measurement series

Augment and consolidate existing geographical coverage of fiducial reference quality observational networks to be more globally representative, including a range of surface types and climate zones

Improve time scheduling coherency of satellite and non-satellite measurements to minimise the need to account for co-location uncertainty effects

Instigate and sustain time-bounded access to a comprehensive set of harmonised fiducial reference data and metadata holdings under a common data model and open data policy that enables interoperability for applications

Observational network governance

Take steps to reassess, rationalise, and improve coordination of high quality observing networks

Conversion of non-satellite measures to Top Of Atmosphere radiance-equivalents and their use

Improve knowledge of fundamental spectroscopy and undertake associated innovations in radiative-transfer modelling

Improve quantification of the effects of surface properties to reduce uncertainties in satellite data assimilation and satellite to non-satellite data comparisons

Develop and provide tools that convert non-satellite fiducial reference quality measurements to Top-Of-Atmosphere radiance equivalents with associated rigorously quantified uncertainties

Understanding and quantifying irreducible co-location mismatch effects

Improve the basis for assigning co-locations and quantifying rigorously the associated uncertainties, including steps towards operational provision of co-location uncertainties

Provision of user tools that enable exploitation

Operationalise co-location match-ups, extraction and visualisation tools, such as the GAIA-CLIM Virtual Observatory, to facilitate user access to satellite to non-satellite match-ups


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