Publication Date:
2019-07-13
Description:
Retrievals were run using the AIRS Science Team Version-6 AIRS Only retrieval algorithm, which generates a Neural-Net first guess (T(sub s))(sup 0), (T(p))(sup 0), and (q(p))(sup 0) as a function of observed AIRS radiances. AIRS Science Team Neural-Net coefficients performed very well beneath 300 mb using the simulated radiances. This means the simulated radiances are very realistic. First guess and retrieved values of T(p) above 300 mb were biased cold, but both represented the model spatial structure very well. QC'd T(p) and q(p) retrievals for all experiments had similar accuracies compared to their own truth fields, and were roughly consistent with results obtained using real data. Spatial coverage of retrievals, as well as the representativeness of the spatial structure of the storm, improved dramatically with decreasing size of the instrument's FOV. We sent QC'd values of T(p) and q(p) to Bob Atlas at AOML for use as input to OSSE Data Assimilation experiments.
Keywords:
Computer Programming and Software; Earth Resources and Remote Sensing; Meteorology and Climatology
Type:
SPIE Paper No. 9611-9
,
GSFC-E-DAA-TN25992
,
SPIE Optics and Photonics 2015; Aug 09, 2015 - Aug 13, 2015; San Diego, CA; United States
Format:
application/pdf
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