Investigating the long-term evolution of subtropical ozone profiles applying ground-based FTIR spectrometry

Abstract

Abstract. This study investigates the long-term evolution of subtropical ozone profile time series (1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010) obtained from ground-based FTIR (Fourier Transform InfraRed) spectrometry at the Izaña Observatory ozone super-site. Different ozone retrieval strategies are examined, analysing the influence of an additional temperature retrieval and different constraints. The theoretical assessment reveals that the FTIR system is able to resolve four independent ozone layers with a precision of better than 6 % in the troposphere and of better than 3 % in the lower, middle and upper stratosphere. This total error includes the smoothing error, which dominates the random error budget. Furthermore, we estimate that the measurement noise as well as uncertainties in the applied atmospheric temperature profiles and instrumental line shape are leading error sources. We show that a simultaneous temperature retrieval can significantly reduce the total random errors and that a regular determination of the instrumental line shape is important for producing a consistent long-term dataset. These theoretical precision estimates are empirically confirmed by daily intercomparisons with Electro Chemical Cell (ECC) sonde profiles. In order to empirically document the long-term stability of the FTIR ozone profile data we compare the linear trends and seasonal cycles as obtained from the FTIR and ECC time series. Concerning seasonality, in winter both techniques observe stratospheric ozone profiles that are typical middle latitude profiles (low tropopause, low ozone maximum concentrations) and in summer/autumn profiles that are typical tropical profiles (high tropopause, high maximum concentrations). The linear trends estimated from the FTIR and the ECC datasets agree within their error bars. For the FTIR time series, we observe a significant negative trend in the upper troposphere/lower stratosphere of about −0.2 % yr −1 and a significant positive trend in the middle and upper stratosphere of about +0.3 % yr −1 and +0.4 % yr −1 , respectively. Identifying such small trends is a difficult task for any measurement technique. In this context, super-sites applying different techniques are very important for the detection of reliable ozone trends.

The MUSICA MetOp/IASI H<sub>2</sub>O and δD products: characterisation and long-term comparison to NDACC/FTIR data

“…As a consequence, the absorption spectra contain some information on the vertical distribution of the absorbing trace gases. For example, in the case of O 3 four independent layers between the surface and about 35 km altitude García et al, 2012) and in the case of H 2 O three layers between the surface and the upper troposphere can be resolved.…”

Consistency and quality assessment of the Metop-A/IASI and Metop-B/IASI operational trace gas products (O<sub>3</sub>, CO, N<sub>2</sub>O, CH<sub>4</sub>, and CO<sub>2</sub>) in the subtropical North Atlantic

“…3, the errors in the spectroscopic line parameters could explain between 2 and 4 % of the FTS bias, according to our error estimation (see Appendix B). Indeed, experimental intercomparisons between FTS and Brewer observations carried out at IZO in the last years found that FTS systematically overestimates the Brewer O 3 TC amounts by ∼ 4 % Viatte et al, 2011;García et al, 2012b), which may be due to inconsistencies in the ultraviolet and infrared spectroscopic parameters. This implies that the IASI O 3 observations should have less bias with respect to the actual O 3 concentrations (less than 2 %).…”

“…The good quality of these long-term ground-based FTS data sets has been extensively documented by theoretical and empirical validation studies (e.g. Schneider et al, 2006Sepúlveda et al, 2012;García et al, 2012b;Sepúlveda et al, 2014;.…”

Ground-based remote sensing of tropospheric water vapour isotopologues within the project MUSICA

“…An uncertainty of the instrumental line shape (ILS), which is a leading error source for the ground-based remote sensing of stratospheric trace gas profiles (e.g. García et al, 2012), is of lower importance for tropospheric water vapour retrievals. The reason is that most water vapour is situated at low altitudes.…”