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

R. D. Field (1, 2) , Camille Risi (3, 4) , G. A. Schmidt (1) , J. Worden (5) , A. Voulgarakis (1, 6, 7) , A. N. Legrande (1, 6) , A. H. Sobel (2, 8, 9) , R. J. Healy (6)

1 GISS - NASA Goddard Institute for Space Studies
2 Columbia Univ, Dept Appl Phys & Appl Math, New York, NY USA
3 LMD - Laboratoire de Météorologie Dynamique (UMR 8539)
4 CIRES - Cooperative Institute for Research in Environmental Sciences
5 JPL - Jet Propulsion Laboratory
6 CCSR - Center for Climate Systems Research [New York]
7 Univ London Imperial Coll Sci Technol & Med, Dept Phys, London, England
8 Department of Earth and Environmental Sciences [New York]
9 LDEO - Lamont-Doherty Earth Observatory

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 opera-tors. 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 delta D fields after applying the retrieval-based and more detailed categorical operators, with increases of up to 30 parts per thousand over the ocean and decreases of up to 40 parts per thousand 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 delta D biases of -8 parts per thousand over ocean and -34 parts per thousand over land compared to TES delta D, which were less than the biases using raw model delta D fields.

Domaines: Océan, Atmosphère; Climatologie

R. D. Field, Camille Risi, G. A. Schmidt, J. Worden, A. Voulgarakis, et al.. A Tropospheric Emission Spectrometer HDO/H2O retrieval simulator for climate models. Atmospheric Chemistry and Physics, 2012, 12 (21), pp.10485-10504. ⟨10.5194/acp-12-10485-2012⟩. ⟨hal-01109269⟩