运用主成分分析方法诊断和消除风云三号B星微波湿度计观测数据中的噪音

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

风云三号A星和B星上的微波湿度计（MWHS）在183GHz附近有3个水汽探测通道（通道3～5）。搭载在MetOp和NOAA卫星上的微波湿度计（MHS）在相同频率上也有3个水汽探测通道。MWHS和MHS都是跨轨扫描仪器。通过对比MWHS观测亮温和用辐射传输模式模拟得到的亮温，发现在这3个通道的观测中都存在着沿轨道方向、随扫描角变化的直线形噪音。即使对足够长时间里的大量资料进行平均分析，该噪音也没有消除，说明噪音并不是由大气或地表的自然变化引起的。通道3～5噪音的大小分别是0.3，0.2和0.2K。用主成分分析方法（PCA）对MWHS一个月的资料进行研究，发现MWHS的直线形噪音主要存在于第一模态中，MWHS的直线形噪音叠加在该模态所主要描述的观测亮温随扫描角变化特征，即跨轨仪器的主要特性。对于这3个水汽探测通道，第一主成分解释了超过99.91%的总方差。将第一主成分进行5点平滑再对原观测数据重构可以有效地去除MWHS资料中的噪音。重构后的资料随扫描角的变化变得比较平滑，与MHS偏差随扫描角的变化特征一致。

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 first 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 first PC accounts for more than 99.91% total variance in the three MWHS sounding channels.A five-point smoother is then applied to the first PC,which effectively removes such a data noise in the MWHS data.The reconstruction of the MWHS radiance spectra using the noise-filtered first 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.