G2.27   Random uncertainty in total column O3 retrieved by UV-vis spectroscopy dominated by instrumental imperfections impacting on the spectral fit calculations

Gap detailed description

The uncertainties in the O3 slant columns retrieved with the standard DOAS data analysis fitting procedures are to a large part caused by (1) instrumental imperfections such as detector noise, resolution change, etaloning (a fault that develops in thin charge-coupled devices when they behave as etalons) and other non-linearities of the detector, stray-light, and polarisation effects, as well as (2) by issues introduced within the analysis routine such as uncertainties in the Ring effect, unknown absorbers, and the wavelengths dependency of the AMF (air mass factor). Such uncertainties are mostly random in nature and therefore can be estimated statistically from the least-squares fit procedure.

However, the fitting uncertainties derived from the least-squares analysis typically result in unrealistically small uncertainties and can lead to an underestimate of the measurement uncertainty by up to a factor of two. Results from intercomparison exercises (e.g. Van Roozendael et al., 1998, Vandaele et al., 2005, Roscoe et al., 2010) show that state-of-the-art instruments hardly ever agree to better than a few percent, even when standardised analysis procedures are used. This indicates that the actual accuracy in the O3 slant columns is at least to some degree limited by uncontrolled instrumental and/or analysis factors.

Activities within GAIA-CLIM related to this gap

This gap is addressed within GAIA-CLIM and the planned activities are described below.

Gap remedy(s)

Remedy #1

Specific remedy proposed

The proposed action is to improve our understanding of the discrepancy between the calculated fitting uncertainty and the more realistically estimated total random error. This will be done, firstly, by evaluating all literature studies and other documentation available on this topic and, secondly, by using the upcoming intercomparison campaign at Cabauw, the Netherlands, in September 2016 to provide more state-of-the-art data for further investigation specifically tailored to this issue.

Measurable outcome of success

The success will be measured by how much we can improve our understanding of the difference between a realistic uncertainty estimate versus the uncertainty provided by the data analysis fitting routines.

Achievable outcomes

Technological / organizational viability: medium.

Indicative cost estimate: low (<1 million).


This remedy is specific for measurements using UV-visible spectroscopic measurement techniques and it will address the existing gap by providing a better understanding on what causes the discrepancy between the calculated fitting uncertainty and the more realistically estimated total random uncertainty.


It will take approximately 1 year to develop and apply the suggested remedy on some test data.

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

A distinct difference remains between realistic uncertainty estimates and the uncertainty calculated by the fitting routines, leading to undue confidence in reported data values.


Higher and poorly quantified uncertainty in data products (such as O3) measured with the DOAS technique leading to reduced utility in applications.

Work package: