Abstract. Within the project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water), long-term tropospheric water vapour isotopologue data records are provided for ten globally distributed ground-based mid-infrared remote sensing stations of the NDACC (Network for the Detection of Atmospheric Composition Change). We present a new method allowing for an extensive and straightforward characterisation of the complex nature of such isotopologue remote sensing datasets. We demonstrate that the MUSICA humidity profiles are representative for most of the troposphere with a vertical resolution ranging from about 2 km (in the lower troposphere) to 8 km (in the upper troposphere) and with an estimated precision of better than 10 %. We find that the sensitivity with respect to the isotopologue composition is limited to the lower and middle troposphere, whereby we estimate a precision of about 30 ‰ for the ratio between the two isotopologues HD 16 O and H 16 2 O. The measurement noise, the applied atmospheric temperature profiles, the uncertainty in the spectral baseline, and the cross-dependence on humidity are the leading error sources. We introduce an a posteriori correction method of the cross-dependence on humidity, and we recommend applying it to isotopologue ratio remote sensing datasets in general. In addition, we present mid-infrared CO 2 retrievals and use them for demonstrating the MUSICA network-wide data consistency.In order to indicate the potential of long-term isotopologue remote sensing data if provided with a well-documented quality, we present a climatology and compare it to simulations of an isotope incorporated AGCM (Atmospheric General Circulation Model). We identify differences in the multiyear mean and seasonal cycles that significantly exceed the estimated errors, thereby indicating deficits in the modeled atmospheric water cycle.

Abstract. NASA's Orbiting Carbon Observatory-2 (OCO-2) has been measuring carbon dioxide column-averaged dryair mole fraction, X CO 2 , in the Earth's atmosphere for over 2 years. In this paper, we describe the comparisons between the first major release of the OCO-2 retrieval algorithm (B7r) and X CO 2 from OCO-2's primary ground-based validation network: the Total Carbon Column Observing Network (TC-CON). The OCO-2 X CO 2 retrievals, after filtering and bias correction, agree well when aggregated around and coincident with TCCON data in nadir, glint, and target observation modes, with absolute median differences less than 0.4 ppm and RMS differences less than 1.5 ppm. After bias correction, residual biases remain. These biases appear to depend on latitude, surface properties, and scattering by aerosols. It is thus crucial to continue measurement comparisons with TCCON to monitor and evaluate the OCO-2 X CO 2 data quality throughout its mission.

Abstract. In the lower/middle troposphere, {H 2 O,δD} pairs are good proxies for moisture pathways; however, their observation, in particular when using remote sensing techniques, is challenging. The project MUSICA (MUltiplatform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) addresses this challenge by integrating the remote sensing with in situ measurement techniques. The aim is to retrieve calibrated tropospheric {H 2 O,δD} pairs from the middle infrared spectra measured from ground by FTIR (Fourier transform infrared) spectrometers of the NDACC (Network for the Detection of Atmospheric Composition Change) and the thermal nadir spectra measured by IASI (Infrared Atmospheric Sounding Interferometer) aboard the MetOp satellites. In this paper, we present the final MUSICA products, and discuss the characteristics and potential of the NDACC/FTIR and MetOp/IASI {H 2 O,δD} data pairs.First, we briefly resume the particularities of an {H 2 O,δD} pair retrieval. Second, we show that the remote sensing data of the final product version are absolutely calibrated with respect to H 2 O and δD in situ profile references measured in the subtropics, between 0 and 7 km. Third, we reveal that the {H 2 O,δD} pair distributions obtained from the different remote sensors are consistent and allow distinct lower/middle tropospheric moisture pathways to be identified in agreement with multi-year in situ references. Fourth, we document the possibilities of the NDACC/FTIR instruments for climatological studies (due to long-term monitoring) and of the MetOp/IASI sensors for observing diurnal signals on a quasi-global scale and with high horizontal resolution. Fifth, we discuss the risk of misinterpreting {H 2 O,δD} pair distributions due to incomplete processing of the remote sensing products.

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.