Journal article

A Tropospheric Emission Spectrometer HDO/H2O retrieval simulator for climate models

Field R, Risi C, Schmidt G, Worden J, Voulgarakis A, Legrande A, Sobel A, Healy R ...see all

Atmospheric Chemistry and Physics, vol. 12, issue 21 (2012) pp. 10485-10504

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Abstract

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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Authors

  • R. D. Field

  • C. Risi

  • G. A. Schmidt

  • J. Worden

  • A. Voulgarakis

  • A. N. Legrande

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