G2.29   Uncertainty in the vertical averaging kernels used for DOAS total column ozone retrievals

Gap detailed description

Within the NDACC UV-vis working group, look-up tables of total column O3 averaging kernels have been developed based on the Eskes and Boersma (2003) approach, i.e. the averaging kernel of a layer i can be approximated by the ratio of the box airmass factor of this layer i and the total airmass factor calculated from an O3 profile climatology. The availability of averaging kernel information as part of the total column retrieval product is important for the interpretation of the observations, and for applications like chemical data assimilation and detailed satellite validation studies. However, vertical averaging kernels (when provided based on a climatology) are only approximations of the real 3D averaging kernel of a retrieval and cannot fully account for the representativeness of the data.

Activities within GAIA-CLIM related to this gap

This gap is not addressed within GAIA-CLIM.

Gap remedy(s)

Remedy #1

Specific remedy proposed

An evaluation of 3D averaging kernels for zenith-sky UV-visible twilight measurements based on the look-up tables described above is needed and a comparison with averaging kernels derived using a direct coupling of the retrieval with the output of a chemistry-transport model, in which the a priori profile used in the air-mass factor calculation is replaced by a more realistic model-derived time and space dependent profile.

Measurable outcome of success

Including 3D averaging kernels for zenith-sky UV-visible O3 measurements in satellite and model validation studies should improve the agreement between the different data sets, especially for UV-visible stations located in winter/spring at the edge of the polar vortex where the spatial and temporal gradients of the O3 field can be very large.

Achievable outcomes

Technological / organizational viability: medium.

Indicative cost estimate: medium (>1million) - low (<1 million).


Many research groups are not setup to run their retrieval code coupled with a chemistry-transport model and so it is essential to have a less computationally demanding approach which can then be used much more widely. However, hence it is vital to understand how the uncertainties increase using the method based on the look-up tables and how representative the vertical averaging kernel climatology is of real measurement conditions.



2-3 years.

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

Vertical averaging kernel climatology not representative of real measurement conditions


The smoothing of model and/or satellite data using vertical averaging kernel climatology can introduce bias in the validation studies.


Work package: