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| Titel |
Ground-based remote sensing of tropospheric water vapour isotopologues within the project MUSICA |
| VerfasserIn |
M. Schneider, S. Barthlott, F. Hase, Y. González, K. Yoshimura, O. E. García, E. Sepúlveda, A. Gomez-Pelaez, M. Gisi, R. Kohlhepp, S. Dohe, T. Blumenstock, A. Wiegele, E. Christner, K. Strong, D. Weaver, M. Palm, N. M. Deutscher, T. Warneke, J. Notholt, B. Lejeune, P. Demoulin, N. Jones, D. W. T. Griffith, D. Smale, J. Robinson |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1867-1381
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Measurement Techniques ; 5, no. 12 ; Nr. 5, no. 12 (2012-12-05), S.3007-3027 |
| Datensatznummer |
250003208
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| Publikation (Nr.) |
 copernicus.org/amt-5-3007-2012.pdf |
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| Zusammenfassung |
| 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 HD16O and H216O. 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 CO2 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 multi-year mean
and seasonal cycles that significantly exceed the estimated errors, thereby
indicating deficits in the modeled atmospheric water cycle. |
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