Remote Sensing of Tropical Cyclone Thermal Structure from Satellite Microwave Sounding Instruments: Impacts of Background Profiles on Retrievals
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摘要
A variational retrieval system often requires background atmospheric profiles and surface parameters in its minimization process. This study investigates the impacts of specific background profiles on retrievals of tropical cyclone(TC) thermal structure. In our Microwave Retrieval Testbed(MRT), the K-means clustering algorithm is utilized to generate a set of mean temperature and water vapor profiles according to stratiform and convective precipitation in hurricane conditions. The Advanced Technology Microwave Sounder(ATMS) observations are then used to select the profiles according to cloud type. It is shown that the cloud-based background profiles result in better hurricane thermal structures retrieved from ATMS observations. Compared to the Global Positioning System(GPS) dropsonde observations, the temperature and specific humidity errors in the TC inner region are less than 3 K and 2.5 g kg~(–1), respectively, which are significantly smaller than the retrievals without using the cloud-based profiles. Further experiments show that all the ATMS observations could retrieve well both temperature and humidity structures, especially within the inner core region. Thus, both temperature and humidity profiles derived from microwave sounding instruments in hurricane conditions can be reliably used for evaluation of the storm intensity with a high fidelity.
A variational retrieval system often requires background atmospheric profiles and surface parameters in its minimization process. This study investigates the impacts of specific background profiles on retrievals of tropical cyclone(TC) thermal structure. In our Microwave Retrieval Testbed(MRT), the K-means clustering algorithm is utilized to generate a set of mean temperature and water vapor profiles according to stratiform and convective precipitation in hurricane conditions. The Advanced Technology Microwave Sounder(ATMS) observations are then used to select the profiles according to cloud type. It is shown that the cloud-based background profiles result in better hurricane thermal structures retrieved from ATMS observations. Compared to the Global Positioning System(GPS) dropsonde observations, the temperature and specific humidity errors in the TC inner region are less than 3 K and 2.5 g kg~(–1), respectively, which are significantly smaller than the retrievals without using the cloud-based profiles. Further experiments show that all the ATMS observations could retrieve well both temperature and humidity structures, especially within the inner core region. Thus, both temperature and humidity profiles derived from microwave sounding instruments in hurricane conditions can be reliably used for evaluation of the storm intensity with a high fidelity.
A variational retrieval system often requires background atmospheric profiles and surface parameters in its minimization process. This study investigates the impacts of specific background profiles on retrievals of tropical cyclone(TC) thermal structure. In our Microwave Retrieval Testbed(MRT), the K-means clustering algorithm is utilized to generate a set of mean temperature and water vapor profiles according to stratiform and convective precipitation in hurricane conditions. The Advanced Technology Microwave Sounder(ATMS) observations are then used to select the profiles according to cloud type. It is shown that the cloud-based background profiles result in better hurricane thermal structures retrieved from ATMS observations. Compared to the Global Positioning System(GPS) dropsonde observations, the temperature and specific humidity errors in the TC inner region are less than 3 K and 2.5 g kg~(–1), respectively, which are significantly smaller than the retrievals without using the cloud-based profiles. Further experiments show that all the ATMS observations could retrieve well both temperature and humidity structures, especially within the inner core region. Thus, both temperature and humidity profiles derived from microwave sounding instruments in hurricane conditions can be reliably used for evaluation of the storm intensity with a high fidelity.
引文
Bennartz,R.,A.Thoss,A.Dybbroe,et al.,2002:Precipitation analysis using the Advanced Microwave Sounding Unit in support of nowcasting applications.Meteor.Appl.,9,177-189,doi:10.1017/S1350482702002037.
Bormann,N.,A.Fouilloux,and W.Bell,2013:Evaluation and assimilation of ATMS data in the ECMWF system.J.Geophys.Res.Atmos.,118,12970-12980,doi:10.1002/2013JD020325.
Boukabara,S.-A.,K.Garrett,W.C.Chen,et al.,2011:MiRS:An all-weather 1DVAR satellite data assimilation and retrieval system.IEEE Trans.Geosci.Remote Sens.,49,3249-3272,doi:10.1109/TGRS.2011.2158438.
Chen,H.,and D.-L.Zhang,2013:On the rapid intensification of Hurricane Wilma(2005).Part II:Convective bursts and the upper-level warm core.J.Atmos.Sci.,70,146-162,doi:10.1175/jas-d-12-062.1.
Chen,H.,D.-L.Zhang,J.Carton,et al.,2011:On the rapid intensification of Hurricane Wilma(2005).Part I:Model prediction and structural changes.Wea.Forecasting,26,885-901,doi:10.1175/waf-d-11-00001.1.
Geer,A.J.,P.Bauer,and P.Lopez,2008:Lessons learnt from the operational 1D+4D-Var assimilation of rain-and cloud-affected SSM/I observations at ECMWF.Quart.J.Roy.Meteor.Soc.,134,1513-1525,doi:10.1002/qj.304.
Grody,N.,J.Zhao,R.Ferraro,et al.,2001:Determination of precipitable water and cloud liquid water over oceans from the NOAA 15 Advanced Microwave Sounding Unit.J.Geophys.Res.Atmos.,106,2943-2953,doi:10.1029/2000JD900616.
Han,Y.,and F.Z.Weng,2018:Remote sensing of tropical cyclone thermal structure from satellite microwave sounding instruments:Impacts of optimal channel selection on retrievals.J.Meteor.Res.,32,804-818,doi:10.1007/s13351-018-8005-x.
Hawkins,H.F.,and D.T.Rubsam,1968:Hurricane Hilda,1964:II.Structure and budgets of the hurricane on October 1,1964.Mon.Wea.Rev.,96,617-636,doi:10.1175/1520-0493(1968)096<0617:hh>2.0.co;2.
Hawkins,H.F.,and S.M.Imbembo,1976:The structure of a small,intense hurricane-Inez 1966.Mon.Wea.Rev.,104,418-442,doi:10.1175/1520-0493(1976)104<0418:tsoasi>2.0.co;2.
Houze,R.A.,Jr.,2014:Cloud Dynamics.2nd ed.Elsevier/Academic Press,Oxford,432 pp.
JPSS ATMS SDR Science Team,2013:Joint Polar Satellite System(JPSS)Advanced Technology Microwave Sounder(ATMS)SDR Calibration Algorithm Theoretical Basis Document(ATBD).E/RA-00001,Center for Satellite Applications and Research,Maryland,41 pp.Available at www.star.nesdis.noaa.gov/jpss/documents/ATBD.Accessed on 28December 2018.
Knaff,J.A.,R.M.Zehr,M.D.Goldberg,et al.,2000:An example of temperature structure differences in two cyclone systems derived from the Advanced Microwave Sounder Unit.Wea.Forecasting,15,476-483,doi:10.1175/1520-0434(2000)015<0476:AEOTSD>2.0.CO;2.
Knaff,J.A.,S.A.Seseske,M.DeMaria,et al.,2004:On the influences of vertical wind shear on symmetric tropical cyclone structure derived from AMSU.Mon.Wea.Rev.,132,2503-2510,doi:10.1175/1520-0493(2004)132<2503:OTIOVW>2.0.CO;2.
LaSeur,N.E.,and H.F.Hawkins,1963:An analysis of Hurricane Cleo(1958)based on data from research reconnaissance aircraft.Mon.Wea.Rev.,91,694-709,doi:10.1175/1520-0493(1963)091<0694:aaohcb>2.3.co;2.
Lin,L.,and F.Z.Weng,2018:Estimation of hurricane maximum wind speed using temperature anomaly derived from Advanced Technology Microwave Sounder.IEEE Geosci.Remote Sens.Lett.,15,639-643,doi:10.1109/LGRS.2018.2807763.
Liu,Q.H.,and F.Z.Weng,2005:One-dimensional variational retrieval algorithm of temperature,water vapor,and cloud water profiles from Advanced Microwave Sounding Unit(AMSU).IEEE Trans.Geosci.Remote Sens.,43,1087-1095,doi:10.1109/TGRS.2004.843211.
Lloyd,S.,1982:Least squares quantization in PCM.IEEE Trans.Inf.Theory,28,129-137,doi:10.1109/TIT.1982.1056489.
Matricardi,M.,F.Chevallier,G.Kelly,et al.,2004:An improved general fast radiative transfer model for the assimilation of radiance observations.Quart.J.Roy.Meteor.Soc.,130,153-173,doi:10.1256/qj.02.181.
Saunders,R.,M.Matricardi,and P.Brunel,1999:An improved fast radiative transfer model for assimilation of satellite radiance observations.Quart.J.Roy.Meteor.Soc.,125,1407-1425,doi:10.1002/qj.1999.49712555615.
Stern,D.P.,and D.S.Nolan,2012:On the height of the warm core in tropical cyclones.J.Atmos.Sci.,69,1657-1680,doi:10.1175/jas-d-11-010.1.
Stern,D.P.,and F.Q.Zhang,2016:The warm-core structure of Hurricane Earl(2010).J.Atmos.Sci.,73,3305-3328,doi:10.1175/jas-d-15-0328.1.
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.Atmos.,121,12630-12646,doi:10.1002/2016JD025042.
Wang,R.,and Y.F.Fu,2017:Structural characteristics of atmospheric temperature and humidity inside clouds of convective and stratiform precipitation in the rainy season over East Asia.J.Meteor.Res.,31,890-905,doi:10.1007/s13351-017-7038-x.
Weng,F.Z.,X.L.Zou,N.H.Sun,et al.,2013:Calibration of Suomi national polar-orbiting partnership advanced technology microwave sounder.J.Geophys.Res.Atmos.,118,11,187-11,200,doi:10.1002/jgrd.50840.
Zhu,T.,and F.Z.Weng,2013:Hurricane Sandy warm-core structure observed from Advanced Technology Microwave Sounder.Geophys.Res.Lett.,40,3325-3330,doi:10.1002/grl.50626.
Zhu,T.,D.-L.Zhang,and F.Z.Weng,2002:Impact of the advanced microwave sounding unit measurements on hurricane prediction.Mon.Wea.Rev.,130,2416-2432,doi:10.1175/1520-0493(2002)130<2416:iotams>2.0.co;2.
Zou,X.,F.Weng,B.Zhang,et al.,2013:Impacts of assimilation of ATMS data in HWRF on track and intensity forecasts of2012 four landfall hurricanes.J.Geophys.Res.Atmos.,118,11,558-11,576,doi:10.1002/2013JD020405.
Bormann,N.,A.Fouilloux,and W.Bell,2013:Evaluation and assimilation of ATMS data in the ECMWF system.J.Geophys.Res.Atmos.,118,12970-12980,doi:10.1002/2013JD020325.
Boukabara,S.-A.,K.Garrett,W.C.Chen,et al.,2011:MiRS:An all-weather 1DVAR satellite data assimilation and retrieval system.IEEE Trans.Geosci.Remote Sens.,49,3249-3272,doi:10.1109/TGRS.2011.2158438.
Chen,H.,and D.-L.Zhang,2013:On the rapid intensification of Hurricane Wilma(2005).Part II:Convective bursts and the upper-level warm core.J.Atmos.Sci.,70,146-162,doi:10.1175/jas-d-12-062.1.
Chen,H.,D.-L.Zhang,J.Carton,et al.,2011:On the rapid intensification of Hurricane Wilma(2005).Part I:Model prediction and structural changes.Wea.Forecasting,26,885-901,doi:10.1175/waf-d-11-00001.1.
Geer,A.J.,P.Bauer,and P.Lopez,2008:Lessons learnt from the operational 1D+4D-Var assimilation of rain-and cloud-affected SSM/I observations at ECMWF.Quart.J.Roy.Meteor.Soc.,134,1513-1525,doi:10.1002/qj.304.
Grody,N.,J.Zhao,R.Ferraro,et al.,2001:Determination of precipitable water and cloud liquid water over oceans from the NOAA 15 Advanced Microwave Sounding Unit.J.Geophys.Res.Atmos.,106,2943-2953,doi:10.1029/2000JD900616.
Han,Y.,and F.Z.Weng,2018:Remote sensing of tropical cyclone thermal structure from satellite microwave sounding instruments:Impacts of optimal channel selection on retrievals.J.Meteor.Res.,32,804-818,doi:10.1007/s13351-018-8005-x.
Hawkins,H.F.,and D.T.Rubsam,1968:Hurricane Hilda,1964:II.Structure and budgets of the hurricane on October 1,1964.Mon.Wea.Rev.,96,617-636,doi:10.1175/1520-0493(1968)096<0617:hh>2.0.co;2.
Hawkins,H.F.,and S.M.Imbembo,1976:The structure of a small,intense hurricane-Inez 1966.Mon.Wea.Rev.,104,418-442,doi:10.1175/1520-0493(1976)104<0418:tsoasi>2.0.co;2.
Houze,R.A.,Jr.,2014:Cloud Dynamics.2nd ed.Elsevier/Academic Press,Oxford,432 pp.
JPSS ATMS SDR Science Team,2013:Joint Polar Satellite System(JPSS)Advanced Technology Microwave Sounder(ATMS)SDR Calibration Algorithm Theoretical Basis Document(ATBD).E/RA-00001,Center for Satellite Applications and Research,Maryland,41 pp.Available at www.star.nesdis.noaa.gov/jpss/documents/ATBD.Accessed on 28December 2018.
Knaff,J.A.,R.M.Zehr,M.D.Goldberg,et al.,2000:An example of temperature structure differences in two cyclone systems derived from the Advanced Microwave Sounder Unit.Wea.Forecasting,15,476-483,doi:10.1175/1520-0434(2000)015<0476:AEOTSD>2.0.CO;2.
Knaff,J.A.,S.A.Seseske,M.DeMaria,et al.,2004:On the influences of vertical wind shear on symmetric tropical cyclone structure derived from AMSU.Mon.Wea.Rev.,132,2503-2510,doi:10.1175/1520-0493(2004)132<2503:OTIOVW>2.0.CO;2.
LaSeur,N.E.,and H.F.Hawkins,1963:An analysis of Hurricane Cleo(1958)based on data from research reconnaissance aircraft.Mon.Wea.Rev.,91,694-709,doi:10.1175/1520-0493(1963)091<0694:aaohcb>2.3.co;2.
Lin,L.,and F.Z.Weng,2018:Estimation of hurricane maximum wind speed using temperature anomaly derived from Advanced Technology Microwave Sounder.IEEE Geosci.Remote Sens.Lett.,15,639-643,doi:10.1109/LGRS.2018.2807763.
Liu,Q.H.,and F.Z.Weng,2005:One-dimensional variational retrieval algorithm of temperature,water vapor,and cloud water profiles from Advanced Microwave Sounding Unit(AMSU).IEEE Trans.Geosci.Remote Sens.,43,1087-1095,doi:10.1109/TGRS.2004.843211.
Lloyd,S.,1982:Least squares quantization in PCM.IEEE Trans.Inf.Theory,28,129-137,doi:10.1109/TIT.1982.1056489.
Matricardi,M.,F.Chevallier,G.Kelly,et al.,2004:An improved general fast radiative transfer model for the assimilation of radiance observations.Quart.J.Roy.Meteor.Soc.,130,153-173,doi:10.1256/qj.02.181.
Saunders,R.,M.Matricardi,and P.Brunel,1999:An improved fast radiative transfer model for assimilation of satellite radiance observations.Quart.J.Roy.Meteor.Soc.,125,1407-1425,doi:10.1002/qj.1999.49712555615.
Stern,D.P.,and D.S.Nolan,2012:On the height of the warm core in tropical cyclones.J.Atmos.Sci.,69,1657-1680,doi:10.1175/jas-d-11-010.1.
Stern,D.P.,and F.Q.Zhang,2016:The warm-core structure of Hurricane Earl(2010).J.Atmos.Sci.,73,3305-3328,doi:10.1175/jas-d-15-0328.1.
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.Atmos.,121,12630-12646,doi:10.1002/2016JD025042.
Wang,R.,and Y.F.Fu,2017:Structural characteristics of atmospheric temperature and humidity inside clouds of convective and stratiform precipitation in the rainy season over East Asia.J.Meteor.Res.,31,890-905,doi:10.1007/s13351-017-7038-x.
Weng,F.Z.,X.L.Zou,N.H.Sun,et al.,2013:Calibration of Suomi national polar-orbiting partnership advanced technology microwave sounder.J.Geophys.Res.Atmos.,118,11,187-11,200,doi:10.1002/jgrd.50840.
Zhu,T.,and F.Z.Weng,2013:Hurricane Sandy warm-core structure observed from Advanced Technology Microwave Sounder.Geophys.Res.Lett.,40,3325-3330,doi:10.1002/grl.50626.
Zhu,T.,D.-L.Zhang,and F.Z.Weng,2002:Impact of the advanced microwave sounding unit measurements on hurricane prediction.Mon.Wea.Rev.,130,2416-2432,doi:10.1175/1520-0493(2002)130<2416:iotams>2.0.co;2.
Zou,X.,F.Weng,B.Zhang,et al.,2013:Impacts of assimilation of ATMS data in HWRF on track and intensity forecasts of2012 four landfall hurricanes.J.Geophys.Res.Atmos.,118,11,558-11,576,doi:10.1002/2013JD020405.
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