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| Titel |
A Tropospheric Emission Spectrometer HDO/H2O retrieval simulator for climate models |
| VerfasserIn |
R. D. Field, C. Risi, G. A. Schmidt, J. Worden, A. Voulgarakis, A. N. LeGrande, A. H. Sobel, R. J. Healy |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 12, no. 21 ; Nr. 12, no. 21 (2012-11-12), S.10485-10504 |
| Datensatznummer |
250011578
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| Publikation (Nr.) |
 copernicus.org/acp-12-10485-2012.pdf |
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| Zusammenfassung |
| Retrievals of the isotopic composition of water vapor from the Aura
Tropospheric Emission Spectrometer (TES) have unique value in constraining
moist processes in climate models. Accurate comparison between simulated and
retrieved values requires that model profiles that would be poorly retrieved
are excluded, and that an instrument operator be applied to the remaining
profiles. Typically, this is done by sampling model output at satellite
measurement points and using the quality flags and averaging kernels from
individual retrievals at specific places and times. This approach is not
reliable when the model meteorological conditions influencing retrieval
sensitivity are different from those observed by the instrument at short
time scales, which will be the case for free-running climate simulations. In
this study, we describe an alternative, "categorical" approach to applying
the instrument operator, implemented within the NASA GISS ModelE general
circulation model. Retrieval quality and averaging kernel structure are
predicted empirically from model conditions, rather than obtained from
collocated satellite observations. This approach can be used for arbitrary
model configurations, and requires no agreement between satellite-retrieved
and model meteorology at short time scales. To test this approach, nudged
simulations were conducted using both the retrieval-based and categorical
operators. Cloud cover, surface temperature and free-tropospheric moisture
content were the most important predictors of retrieval quality and
averaging kernel structure. There was good agreement between the δD
fields after applying the retrieval-based and more detailed categorical
operators, with increases of up to 30‰ over the ocean
and decreases of up to 40‰ over land relative to the
raw model fields. The categorical operator performed better over the ocean
than over land, and requires further refinement for use outside of the
tropics. After applying the TES operator, ModelE had δD biases of −8‰ over ocean and −34‰ over land
compared to TES δD, which were less than the biases using raw
model δD fields. |
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