A posteriori calculation of δ18O and δD in atmospheric water vapour from ground-based near-infrared FTIR retrievals of H216O, H218O, and HD16O / Rokotyan N.V., Zakharov V.I., Gribanov K.G., Schneider M., Bréon F.-M., Jouzel J., Imasu R., Werner M., Butzin M., Petri C., Warneke T., Notholt J. // Atmospheric Measurement Techniques. - 2014. - V. 7, l. 8. - P. 2567-2580.

ISSN:
18671381
Type:
Article
Abstract:
This paper investigates the scientific value of retrieving H 218O and HDO columns in addition to H2 16O columns from high-resolution ground-based near-infrared spectra. We present a set of refined H216O, H2 18O, and HDO spectral windows. The retrieved H2 16O, H218O, and HDO columns are used for an a posteriori calculation of columnar δD and δ18O. We estimate the uncertainties for the so-calculated columnar δD and δ18O values. These estimations include uncertainties due to the measurement noise, errors in the a priori data, and uncertainties in spectroscopic parameters. Time series of δ18O obtained from ground-based FTIR (Fourier transform infrared) spectra are presented for the first time. For our study we use a full physics isotopic general circulation model (ECHAM5-wiso). We show that the full physics simulation of HDO and H 218O can already be reasonably predicted from the H 216O columns by a simple linear regression model (scatter values between full physics and linear regression simulations are 35 and 4‰ for HDO and H218O, respectively). We document that the columnar δD and δ18O values as calculated a posteriori from the retrievals of H216O, H 218O, and HDO show a better agreement with the ECHAM5-wiso simulation than the δD and δ18O values as calculated from the H216O retrievals and the simple linear regression model. This suggests that the H218O and HDO column retrievals add complementary information to the H216O retrievals. However, these data have to be used carefully, because of the different vertical sensitivity of the H216O, H 218O, and HDO columnar retrievals. Furthermore, we have to note that the retrievals use reanalysis humidity profiles as a priori input and the results are thus not independent of the reanalysis data. © Author(s) 2014.
Author keywords:
Index keywords:
chemical composition; error analysis; estimation method; FTIR spectroscopy; general circulation model; humidity; linear programing; parameterization; regression analysis; uncertainty analysis; water v
DOI:
10.5194/amt-7-2567-2014
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Affiliations Laboratory of Climate and Environmental Physics, Ural Federal University, Yekaterinburg, Russian Federation; Institute for Meteorology and Climate Research (IMK-ASF), Karlsruhe Institute of Technology, Karlsruhe, Germany; Institut Pierre Simon Laplace, Laboratoire des Sciences du Climat et de l'Environnement, Gif-sur-Yvette, France; Atmosphere and Ocean Research Institute, University of Tokyo, Tokyo, Japan; Alfred Wegener Institute for Polar and Marine Research, Bremen, Germany; Institute of Environmental Physics, Bremen University, Bremerhaven, Germany
Funding Details EC, European Research Council; 12-01-00801-a, RFBR, European Research Council; 256961, ERC, European Research Council
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Correspondence Address Rokotyan, N.V.; Laboratory of Climate and Environmental Physics, Ural Federal University, Yekaterinburg, Russian Federation; email: nikita.rokotyan@urfu.ru
Language of Original Document English
Abbreviated Source Title Atmos. Meas. Tech.
Source Scopus