A practical information-centered technique to remove a priori information from lidar optimal-estimation-method retrievals
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Published:2019-07-18
Issue:7
Volume:12
Page:3943-3961
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ISSN:1867-8548
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Container-title:Atmospheric Measurement Techniques
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language:en
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Short-container-title:Atmos. Meas. Tech.
Author:
Jalali Ali, Hicks-Jalali ShannonORCID, Sica Robert J.ORCID, Haefele Alexander, von Clarmann Thomas
Abstract
Abstract. Lidar retrievals of atmospheric temperature and water vapor mixing ratio profiles using the optimal estimation method (OEM) typically use a retrieval grid with a number of points larger than the number of pieces of independent information obtainable from the measurements. Consequently, retrieved geophysical quantities contain some information from their respective a priori values or profiles, which can affect the results in the higher altitudes of the temperature and water vapor profiles due to decreasing signal-to-noise ratios. The extent of this influence can be estimated using the retrieval's averaging kernels. The removal of formal a priori information from the retrieved profiles in the regions of prevailing a priori effects is desirable, particularly when these greatest heights are of interest for scientific studies. We demonstrate here that removal of a priori information from OEM retrievals is possible by repeating the retrieval on a coarser grid where the retrieval is stable even without the use of formal prior information. The averaging kernels of the
fine-grid OEM retrieval are used to optimize the coarse retrieval grid. We demonstrate the adequacy of this method for the case of a large power-aperture Rayleigh scatter lidar nighttime temperature retrieval and for a Raman scatter lidar water vapor mixing ratio retrieval during both day and night.
Publisher
Copernicus GmbH
Subject
Atmospheric Science
Reference20 articles.
1. Boersma, K. F., Eskes, H. J., and Brinksma, E. J.: Error analysis for
tropospheric NO2 retrieval from space, J. Geophys. Res., 109, D04311,
https://doi.org/10.1029/2003JD003962, 2004. a 2. Brocard, E., Philipona, R., Haefele, A., Romanens, G., Mueller, A., Ruffieux, D., Simeonov, V., and Calpini, B.: Raman Lidar for Meteorological Observations, RALMO – Part 2: Validation of water vapor measurements, Atmos. Meas. Tech., 6, 1347–1358, https://doi.org/10.5194/amt-6-1347-2013, 2013. a 3. Ceccherini, S., Raspollini, P., and Carli, B.: Optimal use of the information
provided by indirect measurements of atmospheric vertical profiles, Opt.
Express, 17, 4944–4958, https://doi.org/10.1364/OE.17.004944, 2009. a 4. Committee on Extension to the Standard Atmosphere: U.S. standard
atmosphere, US Government Printing Office, 1–227, NASA-TM-X-74335, NOAA-S/T-76-1562, 1976. a 5. Cunnold, D. M., Chu, W., Barnes, R. A., McCormick, M. P., and Veiga, R. E.:
Validation of SAGE II ozone measurements, J. Geophys. Res., 94, 8447–8460,
https://doi.org/10.1029/JD094iD06p08447, 1989. a
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