A Tropospheric Emission Spectrometer HDO/H 2 O retrieval simulator for climate models
A Tropospheric Emission Spectrometer HDO/H 2 O retrieval simulator for climate models
复制标题
用于气候模型的对流层发射光谱仪 HDO/H 2 O 反演模拟器
DOI:
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发表时间:
2012
期刊:
影响因子:
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通讯作者:
R. Healy
中科院分区:
文献类型:
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作者:
R. Field;C. Risi;G. Schmidt;J. Worden;A. Voulgarakis;A. Legrande;A. Sobel;R. Healy
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 op- erator 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 ap- proach is not reliable when the model meteorological con- ditions 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 empiri- cally from model conditions, rather than obtained from collo- cated satellite observations. This approach can be used for ar- bitrary model configurations, and requires no agreement be- tween satellite-retrieved and model meteorology at short time scales. To test this approach, nudged simulations were con- ducted using both the retrieval-based and categorical opera- tors. Cloud cover, surface temperature and free-tropospheric moisture content were the most important predictors of re- trieval quality and averaging kernel structure. There was good agreement between the D 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 cat- egorical 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 D bi- ases of 8 ‰ over ocean and 34 ‰ over land compared to TES D, which were less than the biases using raw model D fields.