The instrumental line shape (ILS) of two commercial high-resolution Fourier transform IR spectrometers has been analysed with gas cell measurements and a new ILS retrieval software LINEFIT. The instruments are used for atmospheric remote sounding, and the compatibility of the ILS deduced from laboratory gas cell measurements with the ILS in the atmospheric measurement itself is examined.

International audienceOzone profile trends over the period 2000 to 2016 from several merged satellite ozone data sets and from ground-based data by four techniques at stations of the Network for the Detection of Atmospheric Composition Change indicate significant ozone increases in the upper stratosphere, between 35 and 48 km altitude (5 and 1 hPa). Near 2 hPa (42 km), ozone has been increasing by about 1.5 % per decade in the tropics (20° S to 20° N), and by 2 to 2.5 % per decade in the 35° to 60° latitude bands of both hemispheres. At levels below 35 km (5 hPa), 2000 to 2016 ozone trends are smaller and not statistically significant. The observed trend profiles are consistent with expectations from chemistry climate model simulations. Using three to four more years of observations and updated data sets, this study confirms positive trends of upper stratospheric ozone already reported, e.g., in the WMO/UNEP Ozone Assessment 2014, or by Harris et al. (2015). The additional years, and the fact that nearly all individual data sets indicate these increases, give enhanced confidence. Nevertheless, a thorough analysis of possible drifts and differences between various data sources is still required, as is a detailed attribution of the observed increases to declining ozone depleting substances and to stratospheric cooling. Ongoing quality observations from multiple independent platforms are key for verifying that recovery of the ozone layer continues as expected

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. At the Izaña Observatory, water vapour amounts have been measured routinely by different techniques for many years. We intercompare the total precipitable water vapour (PWV) amounts measured between 2005 and 2009 by a Fourier Transform Infrared (FTIR) spectrometer, a Multifilter Rotating Shadow-band Radiometer (MFRSR), a Cimel sunphotometer, a Global Positioning System (GPS) receiver, and daily radiosondes (Vaisala RS92). The long-term characteristics of our study allows a reliable and extensive empirical quality assessment of long-term validity, which is an important prerequisite when applying the data to climate research. We estimate a PWV precision of 1% for the FTIR, about 10% for the MFRSR, Cimel, and GPS (when excluding rather dry conditions), and significantly better than 15% for the RS92 (the detection of different airmasses avoids a better constrained estimation). We show that the MFRSR, Cimel and GPS data quality depends on the atmospheric conditions (humid or dry) and that the restriction to clear-sky observations introduces a significant dry bias in the FTIR and Cimel data. In addition, we intercompare the water vapour profiles measured by the FTIR and the Vaisala RS92, which allows the conclusion that both experiments are able to detect lower to upper tropospheric water vapour mixing ratios with a precision of better than 15%.

Abstract.We have examined the utility of retrieved columnaveraged, dry-air mole fractions of CO 2 (XCO 2 ) from the Greenhouse Gases Observing Satellite (GOSAT) for quantifying monthly, regional flux estimates of CO 2 , using the GEOS-Chem four-dimensional variational (4D-Var) data assimilation system. We focused on assessing the potential impact of biases in the GOSAT CO 2 data on the regional flux estimates. Using different screening and bias correction approaches, we selected three different subsets of the GOSAT XCO 2 data for the 4D-Var inversion analyses, and found that the inferred global fluxes were consistent across the three XCO 2 inversions. However, the GOSAT observational coverage was a challenge for the regional flux estimates. In the northern extratropics, the inversions were more sensitive to North American fluxes than to European and Asian fluxes due to the lack of observations over Eurasia in winter and over eastern and southern Asia in summer. The regional flux estimates were also sensitive to the treatment of the residual bias in the GOSAT XCO 2 data. The largest differences obtained were for temperate North America and temperate South America, for which the largest spread between the inversions was 1.02 and 0.96 Pg C, respectively. In the case of temperate North America, one inversion suggested a strong source, whereas the second and third XCO 2 inversions produced a weak and strong sink, respectively. Despite the discrepancies in the regional flux estimates between the three XCO 2 inversions, the a posteriori CO 2 distributions were in good agreement (with a mean difference between the three inversions of typically less than 0.5 ppm) with independent data from the Total Carbon Column Observing Network (TC-CON), the surface flask network, and from the HIAPER Pole-to-Pole Observations (HIPPO) aircraft campaign. The discrepancy in the regional flux estimates from the different inversions, despite the agreement of the global flux estimatesPublished by Copernicus Publications on behalf of the European Geosciences Union. 3704F. Deng et al.: Inferring regional sources and sinks of atmospheric CO 2 from GOSAT XCO 2 data suggests the need for additional work to determine the minimum spatial scales at which we can reliably quantify the fluxes using GOSAT XCO 2 . The fact that the a posteriori CO 2 from the different inversions were in good agreement with the independent data although the regional flux estimates differed significantly, suggests that innovative ways of exploiting existing data sets, and possibly additional observations, are needed to better evaluate the inferred regional flux estimates.