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

• Other Authors: Ma, Yuan (authoraut)
• Format: Others
• Language: English; English
• Published: Florida State University
• Subjects: Meteorology
• Online Access: http://purl.flvc.org/fsu/fd/FSU_migr_etd-9642

Advanced Technology Microwave Sounder (ATMS) has been flying on the Suomi National Polar-orbiting Partnership (NPP) satellite since October 28, 2011. A striping phenomenon contained in the global distribution of O (observations) minus B (model simulations) difference was detected in different ATMS channels. In this dissertation, optimal filters are designed for smoothing out the striping noise in warm counts, cold counts, warm load temperatures and scene counts. The optimal filters are developed based on the striping noise free results obtained by a combined method of the principal component analysis (PCA) and the Ensemble Empirical Mode Decomposition (EEMD). Using the two-point algorithm, antenna temperatures are then calculated with warm counts, cold counts, warm load temperatures and scene counts before and after applying the optimal filters. The patterns and magnitudes of the striping noise removed are very close to that from the PCA/EEMD method. It is further demonstrated that the striping noise is present in the scene counts and must be smoothed out in order to eliminate the striping noise in antenna temperatures. It is 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 on brightness temperature is also designed to remove the striping noise in different channels. Impacts of striping noise mitigation on small-scale weather features are investigated by comparing ATMS cloud liquid water path (LWP) retrieved before and after striping noise mitigation. It is shown that the optimal filters do not affect small-scale cloud features while smoothing out striping noise in brightness temperatures. It is also shown that the striping noise is present in the LWP retrievals if the striping noise in brightness temperatures of ATMS channels 1 and 2 is not removed. The amplitude of the striping noise in LWP is found to be linearly related to the magnitude of striping noise in ATMS brightness temperature observations. Striping noise is a general problem for microwave sensors, and is also identified within observations of a recent FY-3C MWTS. Striping noise within MWTS observation is with a magnitude of 1K, which is much larger than in ATMS. A transfer function is employed to explain 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. Instrument noise is simulated by a white noise series with and without adding flicker noise. Power spectral analysis of this instrument noise is then forced by transfer function to produce the power spectral density of output noise. It is shown that flicker signal is the source of striping noise, and transfer function can modify the striping noise in terms of magnitude and peak frequency. === A Dissertation submitted to the Department of Earth, Ocean, and Atmospheric Science in partial fulfillment of the requirements for the degree of Doctor of Philosophy. === Summer Semester 2015. === June 4, 2015. === Includes bibliographical references. === Ming Cai, Professor Directing Dissertation; Xin Yuan, University Representative; Guosheng Liu, Committee Member; Peter Ray, Committee Member; Jeffery Chagnon, Committee Member.