[Eoas-seminar] MET Dissertation Defense - Yuan Ma - 6/4/15 - 3:30 - LOV 353

eoas-seminar at lists.fsu.edu eoas-seminar at lists.fsu.edu
Fri May 22 10:06:16 EDT 2015

Meteorology Seminar

Yuan Ma

PhD Meteorology Candidate
Major Professors:
Dr. Ming Cai

Development of the "Optimal Filters" for Mitigation of Striping Noise in Satellite Microwave Temperature and Humidity Sounding Data

Thursday June 4th
3:30 PM

Werner A. Baum Seminar Room (353 Love Building)
(Please join us for refreshments served outside room 353 Love @ 3:00 PM)

Advanced Technology Microwave Sounder (ATMS) has been flying on the Suomi National Polar-orbiting Partnership (NPP) satellite since October 28, 2011. A striping noise phenomenon was noticed in the global distribution of O (observations) minus B (model simulations) differences for different ATMS sounding channels. A set of “optimal filters” is developed for smoothing out the striping noise in warm counts, cold counts, warm load temperatures and scene counts. Using the two-point calibration equation, antenna temperatures were calculated with and without applying the optimal filters on warm counts, cold counts, warm load temperatures and scene counts. The patterns and magnitudes of the striping noise removed are very close to that from an early method that combines the principal component analysis (PCA) with the Ensemble Empirical Mode Decomposition (EEMD) method. It was also shown that the optimal filters are superior to the conventional boxcar filters in terms of being able to effectively remove the striping noise in the high frequency range but not to alter the lower frequency weather signals. A set of 22 “optimal filters” that can be applied directly on brightness temperature was also developed to remove the striping noise in all ATMS channels. Impacts of striping noise mitigation on small-scale weather features were investigated by comparing ATMS cloud liquid water path (LWP) retrieved before and after striping noise mitigation. It was shown that the optimal filters do not affect small-scale cloud features while smoothing out striping noise in brightness temperatures. Striping noise is a general problem for microwave sensors, and is also identified within observations of a recent Fengyun-3C (FY-3C) microwave temperature sounder (MWTS). It was found that the magnitude of the striping noise in MWTS is around 1 K, which is much larger than in ATMS (~0.3 K). A transfer function was employed to seek the root cause of the striping noise. This transfer function is controlled by instrument parameters such as scan cycle, calibration integration time and scene integration time. It was shown that flicker noise is the source of striping noise, whose magnitude and peak frequency can be modified by different setting of input parameters of transfer function.

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