Denoising Algorithm for the FY-4A GIIRS Based on Principal Component Analysis

被引:10
|
作者
Fan, Sihui [1 ]
Han, Wei [2 ,3 ]
Gao, Zhiqiu [1 ,4 ]
Yin, Ruoying [2 ,4 ]
Zheng, Yu [1 ]
机构
[1] Nanjing Univ Informat Sci & Technol, Sch Atmospher Phys, Climate & Weather Disasters Collaborat Innovat Ct, Key Lab Aerosol Cloud Precipitat China Meteorol A, Nanjing 210044, Jiangsu, Peoples R China
[2] Chinese Meteorol Adm, Numer Weather Predict Ctr, Beijing 100081, Peoples R China
[3] Natl Meteorol Ctr, Beijing 100081, Peoples R China
[4] Chinese Acad Sci, Inst Atmospher Phys, State Key Lab Atmospher Boundary Layer Phys & Atm, Beijing 100029, Peoples R China
基金
中国国家自然科学基金;
关键词
FY-4A; Geostationary Interferometric Infrared Sounder (GIIRS); principal component analysis (PCA); denoising; INFRARED SOUNDERS; SATELLITE DATA; CLOUDY SKIES; ASSIMILATION; SYSTEM; IMPACT; GENERATION; RADIANCES;
D O I
10.3390/rs11222710
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The Geostationary Interferometric Infrared Sounder (GIIRS) is the first high-spectral resolution advanced infrared (IR) sounder onboard the new-generation Chinese geostationary meteorological satellite FengYun-4A (FY-4A). The GIIRS has 1650 channels, and its spectrum ranges from 700 to 2250 cm(-1) with an unapodized spectral resolution of 0.625 cm(-1). It represents a significant breakthrough for measurements with high temporal, spatial and spectral resolutions worldwide. Many GIIRS channels have quite similar spectral signal characteristics that are highly correlated with each other in content and have a high degree of information redundancy. Therefore, this paper applies a principal component analysis (PCA)-based denoising algorithm (PDA) to study simulation data with different noise levels and observation data to reduce noise. The results show that the channel reconstruction using inter-channel spatial dependency and spectral similarity can reduce the noise in the observation brightness temperature (BT). A comparison of the BT observed by the GIIRS (O) with the BT simulated by the radiative transfer model (B) shows that a deviation occurs in the observation channel depending on the observation array. The results show that the array features of the reconstructed observation BT (rrO) depending on the observation array are weakened and the effect of the array position on the observations in the sub-center of the field of regard (FOR) are partially eliminated after the PDA procedure is applied. The high observation and simulation differences (O-B) in the sub-center of the FOR array notably reduced after the PDA procedure is implemented. The improvement of the high O-B is more distinct, and the low O-B becomes smoother. In each scan line, the standard deviation of the reconstructed background departures (rrO-B) is lower than that of the background departures (O-B). The observation error calculated by posterior estimation based on variational assimilation also verifies the efficiency of the PDA. The typhoon experiment also shows that among the 29 selected assimilation channels, the observation error of 65% of the channels was reduced as calculated by the triangle method.
引用
收藏
页数:18
相关论文
共 50 条
  • [31] 基于集成学习的FY-4A/GIIRS红外通道亮温偏差订正研究
    王根
    杜成名
    蒋芸
    范传宇
    潘月
    袁松
    红外, 2024, 45 (04) : 31 - 38
  • [32] Retrieving the Atmospheric Water Vapor Profile Combining FY-4A/GIIRS and Ground-Based GNSS PWV in Hong Kong Region
    Jiang, Peng
    Liu, Ruiyan
    Huo, Yanfeng
    Wu, Yanlan
    Ye, Shirong
    Wang, Sichen
    Mu, Xi
    Zhu, Li
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2025, 63
  • [33] FY-4A GIIRS数据探测大气水汽和臭氧的垂直空间特性评估
    宋慈
    尹球
    红外与毫米波学报, 2021, 40 (04) : 539 - 546
  • [34] The Diel Cycle of NH3 Observed From the FY-4A Geostationary Interferometric Infrared Sounder (GIIRS)
    Clarisse, Lieven
    Van Damme, Martin
    Hurtmans, Daniel
    Franco, Bruno
    Clerbaux, Cathy
    Coheur, Pierre-Francois
    GEOPHYSICAL RESEARCH LETTERS, 2021, 48 (14)
  • [35] An Improved Aerosol Retrieval Algorithm for FY-4A/AGRI Data Based on the GRASP Framework
    Wang, Huaxuan
    Fan, Meng
    Jiao, Sunxin
    Yan, Huanhuan
    Xu, Benben
    Liu, Xu
    Wang, Yang
    Tao, Jinhua
    Chen, Liangfu
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2025, 63
  • [36] Estimation of cloud base height for FY-4A satellite based on random forest algorithm
    Tan Zhong-Hui
    Ma Shuo
    Han Ding
    Gao Ding
    Yan Wei
    JOURNAL OF INFRARED AND MILLIMETER WAVES, 2019, 38 (03) : 381 - 388
  • [37] SPATIAL CORRECTION OF FY-4A SURFACE SOLAR RADIATION BASED ON RANDOM FOREST ALGORITHM
    Xu L.
    Shen Y.
    Hu Y.
    Xing X.
    Taiyangneng Xuebao/Acta Energiae Solaris Sinica, 2024, 45 (01): : 109 - 115
  • [38] WAVELET BASED SPARSE PRINCIPAL COMPONENT ANALYSIS FOR HYPERSPECTRAL DENOISING
    Rasti, Behnood
    Sveinsson, Johannes R.
    Ulfarsson, Magnus O.
    Sigurdsson, Jakob
    2013 5TH WORKSHOP ON HYPERSPECTRAL IMAGE AND SIGNAL PROCESSING: EVOLUTION IN REMOTE SENSING (WHISPERS), 2013,
  • [39] Fringe pattern denoising based on robust principal component analysis
    Zhang, Yiwei
    Xi, Jiangtao
    Tong, Jun
    Yu, Yanguang
    Guo, Qinghua
    DIMENSIONAL OPTICAL METROLOGY AND INSPECTION FOR PRACTICAL APPLICATIONS X, 2021, 11732
  • [40] Scale Analysis of Typhoon In-Fa (2021) Based on FY-4A Geostationary Interferometric Infrared Sounder (GIIRS) Observed and All-Sky-Simulated Brightness Temperature
    Niu, Zeyi
    Wang, Liwen
    Kumar, Prashant
    REMOTE SENSING, 2023, 15 (16)