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A Root-Cause Analysis of ATMS Striping Noise

A Root-Cause Analysis of ATMS Striping Noise . Hu Yang 1 and Fuzhong Weng 2 1. UMD/ESSIC, College Park, MD and 2. NOAA/NESDIS/STAR, College Park, MD. (Paul, 2005),. Root Cause Analysis of ATMS Striping Noise. ATMS Striping Reduction Algorithm.

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A Root-Cause Analysis of ATMS Striping Noise

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  1. A Root-Cause Analysis of ATMS Striping Noise Hu Yang1 and Fuzhong Weng2 1. UMD/ESSIC, College Park, MD and 2. NOAA/NESDIS/STAR, College Park, MD (Paul, 2005), • Root Cause Analysis of ATMS Striping Noise • ATMS Striping Reduction Algorithm Abstract: An analysis of the ATMS space view measurements reveals that there exists a striping noise in the along-track direction. ATMS earth view observations also display a striping feature through O-B computed from the numerical weather prediction (NWP) model which can reduce the impacts of the data on the global medium range forecasts if the striping is not mitigated in ATMS data. Variance and spectrum analysis of the ATMS pitch-over maneuver data set shows that the root-cause of striping is due probably to the 1/f noise inherited in the receiver outputs. In this study, we analyze the power density of calibration signals. A low pass filter is used for eliminating the noise in warm/cold calibration counts. Results show that the striping noise was effectively reduced in ATMS brightness temperature. As a result, the channel sensitivity in terms of NEDT was largely improved, especially for those high-level temperature sounding channels. Based on the frequency spectrum analysis of receiver output calibration counts, we developed a low-pass filter to effectively remove the high-frequency component (short-term fluctuation) in the signal while highlighting the low–frequency component (gain variation). The radiometer output signal fluctuates because of the inherent stochastic properties of receiver electronics. When sampling the radiometer output, it is not possible to measure the mean value of voltage output with zero uncertainty. Thus, the radiometer output can be rewritten as the sum of mean and fluctuating components By applying the new filter algorithm to calibration counts, we can effectively eliminate the striping noise from the calibrated antenna temperature. Channel sensitivity (NEDT) is also reduced as shown in the following bar diagrams. Characteristic of ATMS Striping Noise ATMS striping noise exists in calibration targets at both space view and warm counts. Note that for most of channels, there is no apparent striping noise in the raw receiver output of earth viewing count, which indicates that one of the possible causes of ATMS striping noise may be generated from the calibration process as shown in left panels of two channels of the earth view counts. Since the receiver gain and offset are calculated from calibration counts and reference temperature, the uncertainty of calibrated brightness temperature include the measurement uncertainty of reference target and calibration counts. Conclusion In this study, striping noise in ATMS calibrated antenna temperature datasets (TDR) was studied. Using FFT transform technique, we derive signal power density distribution for all scene and calibration counts. The root cause of striping in TDR dataset is associated with the high frequency components inherited in calibration counts and scene counts. It is found that for a total power microwave radiometer like ATMS, an improper processing of calibration counts could result in a striping noise and thus make larger measurement uncertainty. From the signal power density analysis of ATMS calibration counts, a low pass filter was proposed for smoothing ATMS calibration counts. The results show that the striping noise in calibrated TDR datasets was effectively reduced, and the channel sensitivity was significantly improved. For scene (Ce), cold (Cc) and warm (Ch) signals, most of the frequency components with high power density are centered at frequencies higher than 1/10 cycles/line. when they were mixed together to produce a new noise signal Cr,whichis the ratio of Ce-Cc to Ch-Cc and it ranges from 0 to 1.0, the high frequency components in the new noise signals are inherited from the raw signals, making new high frequency components larger than each individual signals. In the time domain, they are manifested as a striping noise in calibrated brightness temperatures. This may be the root cause of the striping ATMS measurements.

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