Zou Xiaolei, Ma Yuan, Qin Zhengkun. 2013: Fengyun-3B MicroWave Humidity Sounder (MWHS) Data Noise Characterization and Filtering Using Principle Component Analysis. Advances in Meteorological Science and Technology, 3(4): 50-59. DOI: 10.3969/j.issn.2095-1973.2013.04.006
Citation: Zou Xiaolei, Ma Yuan, Qin Zhengkun. 2013: Fengyun-3B MicroWave Humidity Sounder (MWHS) Data Noise Characterization and Filtering Using Principle Component Analysis. Advances in Meteorological Science and Technology, 3(4): 50-59. DOI: 10.3969/j.issn.2095-1973.2013.04.006

Fengyun-3B MicroWave Humidity Sounder (MWHS) Data Noise Characterization and Filtering Using Principle Component Analysis

  • MicroWave Humidity Sounder (MWHS) onboard both Fengyun-3A (FY-3A) and FY-3B satellites have three channels (channels 3–5) near the 183-GHz water-vapor absorption line. These channel frequencies are also used in other instruments such as Advanced Microwave Sounding Unit-B (AMSU-B) and Microwave Humidity Sounder (MHS) onboard MetOp and NOAA satellites. Both MWHS and MHS are cross-track scanners. In this paper, a comparison between the simulated brightness temperatures with MWHS measurements clearly shows that MWHS observations from the three sounding channels contain a scan-angle-dependent cohesive noise along the instrument scanline. This noise does not cancel out when a large amount of data over a sufficiently long period of time is averaged, which eliminates the possibility of such a noise to arise from the natural variability of the atmosphere and the surface. The noises are around 0.3, 0.2, and 0.2 K for channels 3–5, respectively. A principle component analysis is used for the characterization of this cohesive noise using one-month FY-3B MWHS data. It is shown that the MWHS cohesive noise is primarily contained in the fi rst principal component (PC) mode, which mainly describes a scan-angle-dependent brightness temperature variation, i.e., a unique feature of the cross-tracking instrument. The fi rst PC accounts for more than 99.91% total variance in the three MWHS sounding channels. A fi ve-point smoother is then applied to the fi rst PC, which effectively removes such a data noise in the MWHS data. The reconstruction of the MWHS radiance spectra using the noise-filtered fi rst PC component is of good quality. The scan-angle-dependent bias from the reconstructed MWHS data becomes more uniform and is consistent with the NOAA-18 MHS data.
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