Water vapor isotopologue retrievals from high-resolution GOSAT shortwave infrared spectra

Remote sensing of the isotopic composition of water vapor can provide valuable information on the hydrological cycle. Here, we demonstrate the feasibility of retrievals of the relative abundance of HDO (the HDO/H_2O ratio) from the Japanese GOSAT satellite. For this purpose, we use high spectral res...

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Bibliographic Details
Published in:Atmospheric Measurement Techniques
Main Authors: Frankenberg, C., Wunch, D., Toon, G., Risi, C., Scheepmaker, R., Lee, J.-E, Wennberg, P. O., Worden, J.
Format: Article in Journal/Newspaper
Language:unknown
Published: European Geosciences Union 2013
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Online Access:https://doi.org/10.5194/amt-6-263-2013
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Summary:Remote sensing of the isotopic composition of water vapor can provide valuable information on the hydrological cycle. Here, we demonstrate the feasibility of retrievals of the relative abundance of HDO (the HDO/H_2O ratio) from the Japanese GOSAT satellite. For this purpose, we use high spectral resolution nadir radiances around 6400 cm^(−1) (1.56 μm) to retrieve vertical column amounts of H_2O and HDO. Retrievals of H_2O correlate well with ECMWF (European Centre for Medium-Range Weather Forecasts) integrated profiles (r^2 = 0.96). Typical precision errors in the retrieved column-averaged deuterium depletion (δD) are 20–40‰. We compare δD against a TCCON (Total Carbon Column Observing Network) ground-based station in Lamont, Oklahoma. Using retrievals in very dry areas over Antarctica, we detect a small systematic offset in retrieved H_2O and HDO column amounts and take this into account for a bias correction of δD. Monthly averages of δD in the June 2009 to September 2011 time frame are well correlated with TCCON (r^2 = 0.79) and exhibit a slope of 0.98 (1.23 if not bias corrected). We also compare seasonal averages on the global scale with results from the SCIAMACHY instrument in the 2003–2005 time frame. Despite the lack of temporal overlap, seasonal averages in general agree well, with spatial correlations (r^2) ranging from 0.62 in September through November to 0.83 in June through August. However, we observe higher variability in GOSAT δD, indicated by fitted slopes between 1.2 and 1.46. The discrepancies are likely related to differences in vertical sensitivities but warrant further validation of both GOSAT and SCIAMACHY and an extension of the validation dataset. © 2013 Author(s). This work is distributed under the Creative Commons Attribution 3.0 License. Received: 11 July 2012. Published in Atmos. Meas. Tech. Discuss.: 6 September 2012 Revised: 19 December 2012. Accepted: 21 December 2012. Published: 7 February 2013. Part of the research described in this paper was carried out by the ...