Striping Noise Analysis and Mitigation for Microwave Temperature Sounder-2 Observations
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摘要
The Microwave Temperature Sounder(MWTS)-2 has a total of 13 temperature-sounding channels with the capability of observing radiance emissions from near the surface to the stratosphere. Similar to the Advanced Technology Microwave Sounder(ATMS), striping pattern noise, primarily in the cross-track direction, exists in MWTS-2 radiance observations. In this study, an algorithm based on principal component analysis(PCA) combined with ensemble empirical mode decomposition(EEMD) is described and applied to MWTS-2 brightness temperature observations. It is arguably necessary to smooth the first three principal component(PC) coefficients by removing the first four intrinsic mode functions(IMFs) using the EEMD method(denoted as PC3/IMF4). After the PC3/IMF4 noise mitigation, the striping pattern noise is effectively removed from the brightness temperature observations. The noise level in MWTS-2 observations is significantly higher than that detected in ATMS observations. In May 2014, the scanning profile of MWTS-2 was adjusted from varying-speed scanning to constantspeed scanning. The impact on striping noise levels brought on by this scan profile change is also analyzed here. The striping noise in brightness temperature observations worsened after the profile change. Regardless of the scan profile change, the striping noise mitigation method reported in this study can more or less suppress the noise levels in MWTS-2 observations.
The Microwave Temperature Sounder(MWTS)-2 has a total of 13 temperature-sounding channels with the capability of observing radiance emissions from near the surface to the stratosphere. Similar to the Advanced Technology Microwave Sounder(ATMS), striping pattern noise, primarily in the cross-track direction, exists in MWTS-2 radiance observations. In this study, an algorithm based on principal component analysis(PCA) combined with ensemble empirical mode decomposition(EEMD) is described and applied to MWTS-2 brightness temperature observations. It is arguably necessary to smooth the first three principal component(PC) coefficients by removing the first four intrinsic mode functions(IMFs) using the EEMD method(denoted as PC3/IMF4). After the PC3/IMF4 noise mitigation, the striping pattern noise is effectively removed from the brightness temperature observations. The noise level in MWTS-2 observations is significantly higher than that detected in ATMS observations. In May 2014, the scanning profile of MWTS-2 was adjusted from varying-speed scanning to constantspeed scanning. The impact on striping noise levels brought on by this scan profile change is also analyzed here. The striping noise in brightness temperature observations worsened after the profile change. Regardless of the scan profile change, the striping noise mitigation method reported in this study can more or less suppress the noise levels in MWTS-2 observations.
The Microwave Temperature Sounder(MWTS)-2 has a total of 13 temperature-sounding channels with the capability of observing radiance emissions from near the surface to the stratosphere. Similar to the Advanced Technology Microwave Sounder(ATMS), striping pattern noise, primarily in the cross-track direction, exists in MWTS-2 radiance observations. In this study, an algorithm based on principal component analysis(PCA) combined with ensemble empirical mode decomposition(EEMD) is described and applied to MWTS-2 brightness temperature observations. It is arguably necessary to smooth the first three principal component(PC) coefficients by removing the first four intrinsic mode functions(IMFs) using the EEMD method(denoted as PC3/IMF4). After the PC3/IMF4 noise mitigation, the striping pattern noise is effectively removed from the brightness temperature observations. The noise level in MWTS-2 observations is significantly higher than that detected in ATMS observations. In May 2014, the scanning profile of MWTS-2 was adjusted from varying-speed scanning to constantspeed scanning. The impact on striping noise levels brought on by this scan profile change is also analyzed here. The striping noise in brightness temperature observations worsened after the profile change. Regardless of the scan profile change, the striping noise mitigation method reported in this study can more or less suppress the noise levels in MWTS-2 observations.
引文
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Li,J.,and X.L.Zou,2015:Assimilation of FY-3 MWTS radiance data into Chinese NWP systems.World Climate Research Programme,section 1,pp 11-15.
Li,J.,and G.Q.Liu,2016:Assimilation of Chinese Fengyun-3BMicrowave Temperature Sounder radiances into the global GRAPES system with an improved cloud detection threshold.Frontiers of Earth Science,10,145-158,https://doi.org/10.1007/s11707-015-0499-2.
Li,J.,G.Q.Liu,J.Li,and G.Q.Liu,2016:Direct assimilation of Chinese FY-3C Microwave Temperature Sounder-2 radiances in the global GRAPES system.Atmospheric Measurement Techniques,9,3095-3113,https://doi.org/10.5194/amt-9-3095-2016.
Qin,Z.K.,X.L.Zou,and F.Z.Weng,2013:Analysis of ATMSstriping noise from its Earth scene observations.J.Geophys.Res.,118,13 214-13 229,https://doi.org/10.1002/2013JD020399.
Tian,X.X.,and X.L.Zou,2016:ATMS-and AMSU-A-derived hurricane warm core structures using a modified retrieval algorithm.J.Geophys.Res.,121,12 630-12 646,https://doi.org/10.1002/2016JD025042.
Tian,X.X.,and X.L.Zou,2018:Capturing size and intensity changes of hurricanes Irma and Maria(2017)from polarorbiting satellite microwave radiometers.J.Atmos.Sci.,75,2509-2522,https://doi.org/10.1175/JAS-D-17-0315.1.
Tian,X.X.,X.L.Zou,and S.P.Yang,2018:A limb correction method for the Microwave Temperature Sounder 2 and its applications.Adv.Atmos.Sci.,35,1547-1552,https://doi.org/10.1007/s00376-018-8092-8.
Wu,Z.H.,and N.E.Huang,2009:Ensemble empirical mode decomposition:A noise-assisted data analysis method.Advances in Adaptive Data Analysis,1,1-41,https://doi.org/10.1142/S1793536909000047.
Zou,X.,F.Weng,B.Zhang,L.Lin,Z.Qin,and V.Tallapragada,2013:Impacts of assimilation of ATMS data in HWRF on track and intensity forecasts of 2012 four landfall hurricanes.J.Geophys.Res.,118,11 558-11 576,https://doi.org/10.1002/2013JD020405.
Zou,X.,H.Dong,and Z.Qin,2017:Striping noise reduction for ATMS window channels using a modified destriping algorithm.Quart.J.Roy.Meteor.Soc.,143,2567-2577,https://doi.org/10.1002/qj.3107.
Zou,X.L.,and X.X.Tian,2018:Hurricane warm-core retrievals from AMSU-A and remapped ATMS measurements with rain contamination eliminated.J.Geophys.Res.,123,10 815-10829,https://doi.org/10.1029/2018JD028934.
Zou,X.L.,and X.X.Tian,2019:Comparison of ATMS striping noise between NOAA-20 and S-NPP and noise impact on warm core retrieval of typhoon jelawat(2018).IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,1-9,https://doi.org/10.1109/JSTARS.2019.2891683.(in press)
Zou,X.L.,X.X.Tian,and F.Z.Weng,2014:Detection of television frequency interference with satellite microwave imager observations over oceans.J.Atmos.Oceanic Technol.,31,2759-2776,https://doi.org/10.1175/JTECH-D-14-00086.1.
Bormann,N.,A.Fouilloux,and W.Bell,2013:Evaluation and assimilation of ATMS data in the ECMWF system.J.Geophys.Res.,118,12 970-12 980,https://doi.org/10.1002/2013JD020325.
Derber,J.C.,and W.-S.Wu,1998:The use of TOVS cloudcleared radiances in the NCEP SSI analysis system.Mon.Wea.Rev.,126,2287-2299,https://doi.org/10.1175/1520-0493(1998)126<2287:TUOTCC>2.0.CO;2.
Eyre,J.R.,G.A.Kelly,A.P.McNally,E.Andersson,and A.Persson,1993:Assimilation of TOVS radiance information through one-dimensional variational analysis.Quart.J.Roy.Meteor.Soc.,119,1427-1463,https://doi.org/10.1002/qj.49711951411.
Li,J.,and X.L.Zou,2015:Assimilation of FY-3 MWTS radiance data into Chinese NWP systems.World Climate Research Programme,section 1,pp 11-15.
Li,J.,and G.Q.Liu,2016:Assimilation of Chinese Fengyun-3BMicrowave Temperature Sounder radiances into the global GRAPES system with an improved cloud detection threshold.Frontiers of Earth Science,10,145-158,https://doi.org/10.1007/s11707-015-0499-2.
Li,J.,G.Q.Liu,J.Li,and G.Q.Liu,2016:Direct assimilation of Chinese FY-3C Microwave Temperature Sounder-2 radiances in the global GRAPES system.Atmospheric Measurement Techniques,9,3095-3113,https://doi.org/10.5194/amt-9-3095-2016.
Qin,Z.K.,X.L.Zou,and F.Z.Weng,2013:Analysis of ATMSstriping noise from its Earth scene observations.J.Geophys.Res.,118,13 214-13 229,https://doi.org/10.1002/2013JD020399.
Tian,X.X.,and X.L.Zou,2016:ATMS-and AMSU-A-derived hurricane warm core structures using a modified retrieval algorithm.J.Geophys.Res.,121,12 630-12 646,https://doi.org/10.1002/2016JD025042.
Tian,X.X.,and X.L.Zou,2018:Capturing size and intensity changes of hurricanes Irma and Maria(2017)from polarorbiting satellite microwave radiometers.J.Atmos.Sci.,75,2509-2522,https://doi.org/10.1175/JAS-D-17-0315.1.
Tian,X.X.,X.L.Zou,and S.P.Yang,2018:A limb correction method for the Microwave Temperature Sounder 2 and its applications.Adv.Atmos.Sci.,35,1547-1552,https://doi.org/10.1007/s00376-018-8092-8.
Wu,Z.H.,and N.E.Huang,2009:Ensemble empirical mode decomposition:A noise-assisted data analysis method.Advances in Adaptive Data Analysis,1,1-41,https://doi.org/10.1142/S1793536909000047.
Zou,X.,F.Weng,B.Zhang,L.Lin,Z.Qin,and V.Tallapragada,2013:Impacts of assimilation of ATMS data in HWRF on track and intensity forecasts of 2012 four landfall hurricanes.J.Geophys.Res.,118,11 558-11 576,https://doi.org/10.1002/2013JD020405.
Zou,X.,H.Dong,and Z.Qin,2017:Striping noise reduction for ATMS window channels using a modified destriping algorithm.Quart.J.Roy.Meteor.Soc.,143,2567-2577,https://doi.org/10.1002/qj.3107.
Zou,X.L.,and X.X.Tian,2018:Hurricane warm-core retrievals from AMSU-A and remapped ATMS measurements with rain contamination eliminated.J.Geophys.Res.,123,10 815-10829,https://doi.org/10.1029/2018JD028934.
Zou,X.L.,and X.X.Tian,2019:Comparison of ATMS striping noise between NOAA-20 and S-NPP and noise impact on warm core retrieval of typhoon jelawat(2018).IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,1-9,https://doi.org/10.1109/JSTARS.2019.2891683.(in press)
Zou,X.L.,X.X.Tian,and F.Z.Weng,2014:Detection of television frequency interference with satellite microwave imager observations over oceans.J.Atmos.Oceanic Technol.,31,2759-2776,https://doi.org/10.1175/JTECH-D-14-00086.1.