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Published October 14, 2011 | Published
Journal Article Open

Comparison of an isotopic atmospheric general circulation model with new quasi-global satellite measurements of water vapor isotopologues

Abstract

We performed an intensive comparison of an isotope-incorporated atmospheric general circulation model with vapor isotopologue ratio observation data by two quasi-global satellite sensors in preparation for data assimilation of water isotope ratios. A global Isotope-incorporated Global Spectral Model simulation nudged toward the reanalysis wind field, atmospheric total column data from Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) on Envisat, and midtropospheric (800 to 500 hPa) data from Tropospheric Emission Spectrometer (TES) on Aura were used. For the mean climatological δD of both the total atmospheric column and the midtroposphere layer, the model reproduced their geographical variabilities quite well. There is, however, some degree of underestimation of the latitudinal gradient (higher δD in the tropics and lower δD in midlatitudes) compared to the SCIAMACHY data, whereas there is generally less disagreement except lower δD over the Maritime Continent compared to the TES data. It was also found that the two satellite products have different relationships between water vapor amount and isotopic composition. Particularly, atmospheric column mean δD, which is dominated by lower-tropospheric vapor, closely follows the fractionation pattern of a typical Rayleigh-type "rain out" process, whereas in the midtroposphere the relationship between isotopic composition and vapor amount is affected by a "mixing" process. This feature is not reproduced by the model, where the relationships between δD and the vapor are similar to each other for the atmospheric column and midtroposphere. Comparing on a shorter time scale, it becomes clear that the data situation for future data assimilation for total column δD is most favorable for tropical and subtropical desert areas (i.e., Sahel, southern Africa, mideastern Asia, Gobi, Australia, and the southwest United States), whereas the available midtropospheric δD observations cover wider regions, particularly over tropical to subtropical oceans.

Additional Information

© 2011 by the American Geophysical Union. Received 29 March 2011; revised 19 July 2011; accepted 20 July 2011; published 14 October 2011. A part of this research was funded by the Japan Society for the Promotion of Science (JSPS) grant 23686071. The numerical simulations were performed with computing resources at the Center for Observations and Prediction at Scripps (COMPAS) and at TeraGrid. Part of this work was also funded by the California Energy Commission Public Interest Energy Research (PIER) program, which supports the California Climate Change Center (award MGC‐04‐04) and NOAA (NA17RJ1231). The views expressed herein are those of the authors and do not necessarily reflect the views of NOAA. We would like to thank J. Roads for his encouragement in the beginning of this study. The assistance of Ms. D. Boomer in refining the writing is appreciated. The authors thank all the comments from two reviewers including Matthias Schneider.

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August 22, 2023
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October 23, 2023