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

Zou, Xiaolei; Ma, Yuan

doi:10.1109/tgrs.2012.2202122

Cited by 15 publications

(10 citation statements)

References 11 publications

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“…A new technique has been developed through a combination of PCA and EEMD methods to characterize the scan dependence in brightness temperature observations and to separate the weather signals from the striping noise when present. For the purpose of this study, we will assume that the first PC mode (i.e., the first eigenvector) captures most of the scan‐dependent features of cross‐track radiometer measurements [ Zou et al ., ] and the remaining PC modes describe the atmospheric signals. Also, by assuming the striping noise is constant in the cross‐track direction, the striping noise is contained in the PC coefficients corresponding to the first PC mode.…”

Section: A Striping Analysis Methods For Earth Scene Observationsmentioning

confidence: 99%

“…The PCA method was also used in Zou et al . [] to identify a scan angle‐dependent cohesive noise along the instrument scan line of Microwave Humidity Sounder (MWHS) on board Chinese Fengyun‐3A (FY‐3A) and FY‐3B satellites. A method used to extract random noise in an along‐track varying PC coefficient is the Ensemble Empirical Mode Decomposition (EEMD) [ Huang and Wu , ; Wu and Huang , ; Wu et al ., ].…”

Section: Introductionmentioning

confidence: 99%

“…Tobin et al [2009] also used the PCA approach to remove the subtle distortions in the AIRS instrument line shape introduced by nonuniform scene effects. The PCA method was also used in Zou et al [2012] to identify a scan angle-dependent cohesive noise along the instrument scan line of Microwave Humidity Sounder (MWHS) on board Chinese Fengyun-3A (FY-3A) and FY-3B satellites. A method used to extract random noise in an along-track varying PC coefficient is the Ensemble Empirical Mode Decomposition (EEMD) [Huang and Wu, 2008;.…”

Section: Introductionmentioning

confidence: 99%

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Analysis of ATMS striping noise from its Earth scene observations

2013

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[1] The differences between brightness temperature observations and simulated observations based on numerical weather predictions, i.e., O-B, for Advanced Technology Microwave Sounder (ATMS) temperature sounding channels exhibit a clear striping pattern [Bormann et al., 2013]. We propose to first use the principal component analysis to isolate scan-dependent features such as the cross-track striping from the atmospheric signal and then to use an Ensemble Empirical Mode Decomposition (EEMD) to extract the striping noise in ATMS Earth scene brightness temperature observations for both temperature and water vapor sounding channels. It is shown that the Principal Component (PC) coefficient of the first PC mode, which mainly describes a scan-dependent feature of cross-track radiometer measurements, captures the striping noise. The EEMD is then applied to the PC coefficient to extract the first three high-frequency intrinsic mode functions (IMFs), which are denoted as the PC1/IMF3 noise. When the PC1/IMF3 noise is removed from the data, the striping noise is imperceptible in the global distribution of O-B for ATMS temperature sounding channels 1-16. Using the same method, it is demonstrated that the striping noise is also present in ATMS water vapor sounding channels 17-22. The magnitude of the ATMS striping noise is about ±0.3 K for the temperature sounding channels and ±1.0 K for the moisture sounding channels. The same technique is also applied to Advanced Microwave Sounding Unit-A (AMSU-A), AMSU-B, and Microwave Humidity Sounder (MHS). The striping noise is undetectable for AMSU-A but present in AMSU-B and MHS data.

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Section: A Striping Analysis Methods For Earth Scene Observationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Analysis of ATMS striping noise from its Earth scene observations

2013

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“…The MWHS makes 98 measurements across a scan line from −53.35 • to +53.35 • at about 1.1 • increment with the resolution of 15 km at nadir. Several studies based on the MWRI or the MWHS observations can be found in the literature [25]- [27].…”

Section: Datamentioning

confidence: 99%

Estimating Ice Water Path in Tropical Cyclones With Multispectral Microwave Data From the FY-3B Satellite

Wang

Fang

et al. 2014

IEEE Trans. Geosci. Remote Sensing

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Ice water path (IWP) is an important parameter to characterize tropical cyclones. The FY-3B satellite, with multiple passive microwave sensors onboard, offers a unique opportunity to monitor the variation of cloud IWP during the evolution of tropical cyclones. In this paper, by using the combined simultaneous measurements of the MicroWave atmospheric Humidity Sounder and MicroWave Radiometer Imager on FY-3B satellite, an improved IWP algorithm for tropical clouds is developed. The new algorithm seeks to better estimate ice-free background brightness temperature at 150 GHz using simultaneous observations at low microwave frequencies. This approach improves IWP retrieval accuracy particularly for high IWP clouds that often associated with tropical cyclones. The current algorithm was applied to FY-3B observations of two typhoons with different strengths, and the characteristics of IWP variation at the storms' different evolution stages were investigated. The results showed that IWP tends to vary ahead of the storm intensification or decay, suggesting that IWP can be potentially used to predict the change of storm intensity.Index Terms-FY-3B, ice water path (IWP), MicroWave atmospheric Humidity Sounder (MWHS), MicroWave Radiometer Imager (MWRI), passive microwave, tropical cyclone.

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“…The Earth's atmosphere can be observed more frequently than without Chinese satellites. A preliminary evaluation of instrument performance through a comparison with data from NOAA, MetOp, and the NASA Aqua satellite data revealed that data from MWTS, MWHS, and MWRI were of good quality (Guan et al, 2011;Yang et al, 2011;Zou et al, 2012a;Zou et al, 2012b;Zou et al, 2012c). In this study, we investigated the polarization differences of measurements between two MWHS window channels and investigated the potential value for satellite data assimilation and calibration.…”

Section: Introductionmentioning

confidence: 99%

Polarization signature from the FengYun-3 Microwave Humidity Sounder

Zou

Weng

2014

Front. Earth Sci.

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Microwave Humidity Sounders (MHS) onboard , and EUMETSAT MetOp-A/B satellites provide radiance measurements at a single polarization state at any of five observed frequencies. The Microwave Humidity Sounder (MWHS) onboard the FengYun-3 (FY-3) satellite has a unique instrument design that provides dual polarization measurements at 150 GHz. In this study, the MWHS polarization signal was investigated using observed and modeled data. It is shown that the quasi-polarization brightness temperatures at 150 GHz display a scan angle dependent bias. Under calm ocean conditions, the polarization difference at 150 GHz becomes non-negligible when the scan angle varies from 10°to 45°and reaches a maximum when the scan angle is about 30°. Also, the polarization state is sensitive to surface parameters such as surface wind speed. Under clear-sky conditions, the differences between horizontal and vertical polarization states at 150 GHz increase with decreasing surface wind speed. Therefore, the polarization signals from the cross-track scanning microwave measurements at window channels contain useful information about surface parameters. In addition, the availability of dual polarization measurements allows a one-to-one conversion from antenna brightness temperature to sensor brightness temperature if a cross-polarization spill-over exists.

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

Cited by 15 publications

References 11 publications

Analysis of ATMS striping noise from its Earth scene observations

Analysis of ATMS striping noise from its Earth scene observations

Estimating Ice Water Path in Tropical Cyclones With Multispectral Microwave Data From the FY-3B Satellite

Polarization signature from the FengYun-3 Microwave Humidity Sounder

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