An Analysis of the Discontinuity in Chinese Radiosonde Temperature Data Using Satellite Observation as a Reference
|
摘要
Reconciling upper-air temperature trends derived from radiosonde and satellite observations is a necessary step to confidently determine the global warming rate. This study examines the raw and homogenized radiosonde observations over China and compares them with layer-mean atmospheric temperatures derived from satellite microwave observations for the lower-troposphere(TLT), mid-troposphere(TMT), upper-troposphere(TUT), and lower-stratosphere(TLS) by three research groups. Comparisons are for averages over China, excluding the Tibetan Plateau, and at individual stations where metadata contain information on radiosonde instrument changes. It is found that major differences between the satellite and radiosonde observations are related to artificial systematic changes. The radiosonde system updates in the early 2000 s over China caused significant discontinuities and led the radiosonde temperature trends to exhibit less warming in the middle and upper troposphere and more cooling in the lower stratosphere than satellite temperatures. Homogenized radiosonde data have been further adjusted by using the shift-point adjustment approaches to match with satellite products for China averages. The obtained trends during 1979–2015 from the re-adjusted radiosonde observation are respectively 0.203 ± 0.066, 0.128 ± 0.044, 0.034 ± 0.039, and –0.329 ± 0.135 K decade~(–1) for TLT, TMT, TUT, and TLS equivalents. Compared to satellite trends, the re-adjusted radiosonde trends are within 0.01 K decade~(–1) for TMT and TUT, 0.054 K decade~(–1) warmer for TLT, and 0.051 K decade~(–1) cooler for TLS. The results suggest that the use of satellite data as a reference is helpful in identifying and removing inhomogeneities of radiosonde temperatures over China and reconciling their trends to satellite microwave observations. Future efforts are to homogenize radiosonde temperatures at individual stations over China by using similar approaches.
Reconciling upper-air temperature trends derived from radiosonde and satellite observations is a necessary step to confidently determine the global warming rate. This study examines the raw and homogenized radiosonde observations over China and compares them with layer-mean atmospheric temperatures derived from satellite microwave observations for the lower-troposphere(TLT), mid-troposphere(TMT), upper-troposphere(TUT), and lower-stratosphere(TLS) by three research groups. Comparisons are for averages over China, excluding the Tibetan Plateau, and at individual stations where metadata contain information on radiosonde instrument changes. It is found that major differences between the satellite and radiosonde observations are related to artificial systematic changes. The radiosonde system updates in the early 2000 s over China caused significant discontinuities and led the radiosonde temperature trends to exhibit less warming in the middle and upper troposphere and more cooling in the lower stratosphere than satellite temperatures. Homogenized radiosonde data have been further adjusted by using the shift-point adjustment approaches to match with satellite products for China averages. The obtained trends during 1979–2015 from the re-adjusted radiosonde observation are respectively 0.203 ± 0.066, 0.128 ± 0.044, 0.034 ± 0.039, and –0.329 ± 0.135 K decade~(–1) for TLT, TMT, TUT, and TLS equivalents. Compared to satellite trends, the re-adjusted radiosonde trends are within 0.01 K decade~(–1) for TMT and TUT, 0.054 K decade~(–1) warmer for TLT, and 0.051 K decade~(–1) cooler for TLS. The results suggest that the use of satellite data as a reference is helpful in identifying and removing inhomogeneities of radiosonde temperatures over China and reconciling their trends to satellite microwave observations. Future efforts are to homogenize radiosonde temperatures at individual stations over China by using similar approaches.
Reconciling upper-air temperature trends derived from radiosonde and satellite observations is a necessary step to confidently determine the global warming rate. This study examines the raw and homogenized radiosonde observations over China and compares them with layer-mean atmospheric temperatures derived from satellite microwave observations for the lower-troposphere(TLT), mid-troposphere(TMT), upper-troposphere(TUT), and lower-stratosphere(TLS) by three research groups. Comparisons are for averages over China, excluding the Tibetan Plateau, and at individual stations where metadata contain information on radiosonde instrument changes. It is found that major differences between the satellite and radiosonde observations are related to artificial systematic changes. The radiosonde system updates in the early 2000 s over China caused significant discontinuities and led the radiosonde temperature trends to exhibit less warming in the middle and upper troposphere and more cooling in the lower stratosphere than satellite temperatures. Homogenized radiosonde data have been further adjusted by using the shift-point adjustment approaches to match with satellite products for China averages. The obtained trends during 1979–2015 from the re-adjusted radiosonde observation are respectively 0.203 ± 0.066, 0.128 ± 0.044, 0.034 ± 0.039, and –0.329 ± 0.135 K decade~(–1) for TLT, TMT, TUT, and TLS equivalents. Compared to satellite trends, the re-adjusted radiosonde trends are within 0.01 K decade~(–1) for TMT and TUT, 0.054 K decade~(–1) warmer for TLT, and 0.051 K decade~(–1) cooler for TLS. The results suggest that the use of satellite data as a reference is helpful in identifying and removing inhomogeneities of radiosonde temperatures over China and reconciling their trends to satellite microwave observations. Future efforts are to homogenize radiosonde temperatures at individual stations over China by using similar approaches.
引文
Cao,L.J.,Y.N.Zhu,G.L.Tang,et al.,2016:Climatic warming in China according to a homogenized data set from 2419 stations.Int.J.Climatol.,36,4384-4392,doi:10.1002/joc.4639.
Chen,Z.,and S.Yang,2014:Homogenization and analysis of China radiosonde temperature data from 1979 to 2012.Acta Meteor.Sinica,72,794-804,doi:10.11676/qxxb2014.046.(in Chinese)
Christy,J.R.,and W.B.Norris,2006:Satellite and VIZ-radiosonde intercomparisons for diagnosis of nonclimatic influences.J.Atmos.Oceanic Technol.,23,1181-1194,doi:10.1175/JTECH1937.1.
Christy,J.R.,and W.B.Norris,2009:Discontinuity issues with radiosonde and satellite temperatures in the Australian region1979-2006.J.Atmos.Oceanic Technol.,26,508-522,doi:10.1175/2008JTECHA1126.1.
Christy,J.R.,R.W.Spencer,W.B.Norris,et al.,2003:Error estimates of version 5.0 of MSU-AMSU bulk atmospheric temperatures.J.Atmos.Oceanic Technol.,20,613-629,doi:10.1175/1520-0426(2003)20<613:EEOVOM>2.0.CO;2.
Christy,J.R.,W.B.Norris,R.W.Spencer,et al.,2007:Tropospheric temperature change since 1979 from tropical radiosonde and satellite measurements.J.Geophys.Res.Atmos.,112,D06102,doi:10.1029/2005JD006881.
Christy,J.R.,R.W.Spencer,W.D.Braswell,et al.,2018:Examination of space-based bulk atmospheric temperatures used in climate research.Int.J.Remote Sens.,39,3580-3607,doi:10.1080/01431161.2018.1444293.
Durre,I.,R.S.Vose,and D.B.Wuertz,2006:Overview of the integrated global radiosonde archive.J.Climate,19,53-68,doi:10.1175/JCLI3594.1.
Free,M.,D.J.Seidel,J.K.Angell,et al.,2005:Radiosonde atmospheric temperature products for assessing climate(RAT-PAC):A new data set of large-area anomaly time series.J.Geophys.Res.Atmos.,110,D22101,doi:10.1029/2005JD006169.
Guo,Y.J.,and Y.H.Ding,2009:Long-term free-atmosphere temperature trends in China derived from homogenized in situ radiosonde temperature series.J.Climate,22,1037-1051,doi:10.1175/2008JCLI2480.1.
Guo,Y.J.,and Y.H.Ding,2011:Impacts of reference time series on the homogenization of radiosonde temperature.Adv.Atmos.Sci.,28,1011-1022,doi:10.1007/s00376-010-9211-3.
Guo,Y.J.,P.W.Thorne,M.P.McCarthy,et al.,2008:Radiosonde temperature trends and their uncertainties over eastern China.Int.J.Climatol.,28,1269-1281,doi:10.1002/joc.1633.
Guo,Y.J.,S.Q.Zhang,J.H.Yan,et al.,2016:A comparison of atmospheric temperature over China between radiosonde observations and multiple reanalysis datasets.J.Meteor.Res.,30,242-257,doi:10.1007/s13351-016-5169-0.
Haimberger,L.,2007:Homogenization of radiosonde temperature time series using innovation statistics.J.Climate,20,1377-1403,doi:10.1175/JCLI4050.1.
Haimberger,L.,C.Tavolato,and S.Sperka,2008:Toward elimination of the warm bias in historic radiosonde temperature records-Some new results from a comprehensive intercomparison of upper-air data.J.Climate,21,4587-4606,doi:10.1175/2008JCLI1929.1.
Haimberger,L.,C.Tavolato,and S.Sperka,2012:Homogenization of the global radiosonde temperature dataset through combined comparison with reanalysis background series and neighboring stations.J.Climate,25,8108-8131,doi:10.1175/JCLI-D-11-00668.1.
Hurrell,J.W.,S.J.Brown,K.E.Trenberth,et al.,2000:Comparison of tropospheric temperatures from radiosondes and satellites:1979-98.Bull.Amer.Meteor.Soc.,81,2165-2178,doi:10.1175/1520-0477(2000)081<2165:COTTFR>2.3.CO;2.
IPCC,2013:Climate Change 2013:The Physical Science Basis.Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change,T.F.Stocker,D.Qin,G.-K.Plattner,et al.,Eds.,Cambridge University Press,Cambridge,United Kingdom and New York,NY,USA,1535 pp.
Mears,C.A.,and F.J.Wentz,2009a:Construction of the remote sensing systems V3.2 atmospheric temperature records from the MSU and AMSU Microwave Sounders.J.Atmos.Oceanic Technol.,26,1040-1056,doi:10.1175/2008JTECHA1176.1.
Mears,C.A.,and F.J.Wentz,2009b:Construction of the RSSV3.2 lower-tropospheric temperature dataset from the MSUand AMSU Microwave Sounders.J.Atmos.Oceanic Technol.,26,1493-1509,doi:10.1175/2009JTECHA1237.1.
Mears,C.A.,and F.J.Wentz,2016:Sensitivity of satellite-derived tropospheric temperature trends to the diurnal cycle adjustment.J.Climate,29,3629-3646,doi:10.1175/JCLI-D-15-0744.1.
Mears,C.A.,and F.J.Wentz,2017:A satellite-derived lower-tropospheric atmospheric temperature dataset using an optimized adjustment for diurnal effects.J.Climate,30,7695-7718,doi:10.1175/JCLI-D-16-0768.1.
Mears,C.A.,M.C.Schabel,and F.J.Wentz,2003:A reanalysis of the MSU channel 2 tropospheric temperature record.J.Climate,16,3650-3664,doi:10.1175/1520-0442(2003)016<3650:AROTMC>2.0.CO;2.
Mears,C.A.,F.J.Wentz,and P.W.Thorne,2012:Assessing the value of microwave sounding unit-radiosonde comparisons in ascertaining errors in climate data records of tropospheric temperatures.J.Geophys.Res.Atmos.,117,D19103,doi:10.1029/2012JD017710.
Parker,D.E.,M.Gordon,D.P.N.Cullum,et al.,1997:A new global gridded radiosonde temperature data base and recent temperature trends.Geophys.Res.Lett.,24,1499-1502,doi:10.1029/97GL01186.
Po-Chedley,S.,and Q.Fu,2012:A bias in the midtropospheric channel warm target factor on the NOAA-9 microwave sounding unit.J.Atmos.Oceanic Technol.,29,646-652,doi:10.1175/JTECH-D-11-00147.1.
Po-Chedley,S.,T.J.Thorsen,and Q.Fu,2015:Removing diurnal cycle contamination in satellite-derived tropospheric temperatures:Understanding tropical tropospheric trend discrepancies.J.Climate,28,2274-2290,doi:10.1175/JCLI-D-13-00767.1.
Randall,R.M.,and B.M.Herman,2008:Using limited time period trends as a means to determine attribution of discrepancies in microwave sounding unit-derived tropospheric temperature time series.J.Geophys.Res.Atmos.,113,D05105,doi:10.1029/2007JD008864.
Randel,W.J.,and F.Wu,2006:Biases in stratospheric and tropospheric temperature trends derived from historical radiosonde data.J.Climate,19,2094-2104,doi:10.1175/JCLI3717.1.
Ren,Z.H.,Y.Yu,F.L.Zou,et al.,2012:Quality detection of surface historical basic meteorological data.J.Appl.Meteor.Sci.,23,739-747,doi:10.3969/j.issn.1001-7313.2012.06.011.(in Chinese)
Ruan,X.,A.Y.Xiong,K.X.Hu,et al.,2015:Correcting geopotential height errors of some mandatory levels of Chinese historic radiosonde observations.J.Appl.Meteor.Sci.,26,257-267,doi:10.11898/1001-7313.20150301.(in Chinese)
Santer,B.D.,T.M.L.Wigley,J.S.Boyle,et al.,2000:Statistical significance of trends and trend differences in layer-average atmospheric temperature time series.J.Geophys.Res.Atmos.,105,7337-7356,doi:10.1029/1999JD901105.
Santer,B.D.,S.Solomon,G.Pallotta,et al.,2017a:Comparing tropospheric warming in climate models and satellite data.J.Climate,30,373-392,doi:10.1175/JCLI-D-16-0333.1.
Santer,B.D.,J.C.Fyfe,G.Pallotta,et al.,2017b:Causes of differences in model and satellite tropospheric warming rates.Nat.Geosci.,10,478-485,doi:10.1038/ngeo2973.
Seidel,D.J.,J.K.Angell,J.Christy,et al.,2004:Uncertainty in signals of large-scale climate variations in radiosonde and satellite upper-air temperature datasets.J.Climate,17,2225-2240,doi:10.1175/1520-0442(2004)017<2225:UISOLC>2.0.CO;2.
Seidel,D.J.,F.H.Berger,H.J.Diamond,et al.,2009:Reference upper-air observations for climate:Rationale,progress,and plans.Bull.Amer.Meteor.Soc.,90,361-369,doi:10.1175/2008BAMS2540.1.
Seidel,D.J.,N.P.Gillett,J.R.Lanzante,et al.,2011:Stratospheric temperature trends:Our evolving understanding.Wiley Interdiscip.Rev.:Climate Change,2,592-616,doi:10.1002/wcc.125.
Sherwood,S.C.,and N.Nishant,2015:Atmospheric changes through 2012 as shown by iteratively homogenized radiosonde temperature and wind data(IUKv2).Environ.Res.Lett.,10,054007,doi:10.1088/1748-9326/10/5/054007.
Shi,Y.,P.M.Zhai,and Z.H.Jiang,2016:Multi-sliding time windows based changing trend of mean temperature and its association with the global-warming hiatus.J.Meteor.Res.,30,232-241,doi:10.1007/s13351-016-5093-3.
Spencer,R.W.,and J.R.Christy,1990:Precise monitoring of global temperature trends from satellites.Science,247,1558-1562,doi:10.1126/science.247.4950.1558.
Spencer,R.W.,and J.R.Christy,1992:Precision and radiosonde validation of satellite gridpoint temperature anomalies.Part I:MSU channel 2.J.Climate,5,847-857,doi:10.1175/1520-0442(1992)005<0847:PARVOS>2.0.CO;2.
Spencer,R.W.,J.R Christy,and W.D.Braswell,2017:UAHversion 6 global satellite temperature products:Methodology and results.Asia-Pac.J.Atmos.Sci.,53,121-130,doi:10.1007/s13143-017-0010-y.
Thorne,P.W.,D.E.Parker,J.R.Christy,et al.,2005a:Uncertainties in climate trends:Lessons from upper-air temperature records.Bull.Amer.Meteor.Soc.,86,1437-1442,doi:10.1175/BAMS-86-10-1437.
Thorne,P.W.,D.E.Parker,S.F.B.Tett,et al.,2005b:Revisiting radiosonde upper air temperatures from 1958 to 2002.J.Geophys.Res.Atmos.,110,D18105,doi:10.1029/2004jd005753.
Thorne,P.W.,J.R.Lanzante,T.C.Peterson,et al.,2011:Tropospheric temperature trends:History of an ongoing controversy.Wiley Interdiscip.Rev.:Climate Change,2,66-88,doi:10.1002/wcc.80.
Wang,X.L.,Q.H.Wen,and Y.H.Wu,2007:Penalized maximal t test for detecting undocumented mean change in climate data series.J.Appl.Meteor.Climatol.,46,916-931,doi:10.1175/JAM2504.1.
Xu,W.H.,Q.X.Li,X.L.Wang,et al.,2013:Homogenization of Chinese daily surface air temperatures and analysis of trends in the extreme temperature indices.J.Geophys.Res.Atmos.,118,9708-9720,doi:10.1002/jgrd.50791.
Zhai,P.M.,1997:Some gross errors and biases in China’s historical radiosonde data.Acta Meteor.Sinica,55,563-572,doi:10.11676/qxxb1997.055.(in Chinese)
Zhai,P.M.,and R.E.Eskridge,1996:Analyses of inhomogeneities in radiosonde temperature and humidity time series.J.Climate,9,884-894,doi:10.1175/1520-0442(1996)009<0884:AOIIRT>2.0.CO;2.
Zou,C.Z.,and W.Wang,2011:Intersatellite calibration of AMSU-A observations for weather and climate applications.J.Geophys.Res.Atmos.,116,D23113,doi:10.1029/2011JD016205.
Zou,C.Z,and H.F.Qian,2016:Stratospheric temperature climate data record from merged SSU and AMSU-A observations.J.Atmos.Oceanic Technol.,33,1967-1984,doi:10.1175/JTECH-D-16-0018.1.
Zou,C.Z.,M.D.Goldberg,Z.H.Cheng,et al.,2006:Recalibration of microwave sounding unit for climate studies using simultaneous nadir overpasses.J.Geophys.Res.Atmos.,111,D19114,doi:10.1029/2005JD006798.
Zou,C.-Z.,M.D.Goldberg,and X.J.Hao,2018:New generation of U.S.satellite microwave sounder achieves high radiometric stability performance for reliable climate change detection.Sci.Adv.,4,eaau0049,doi:10.1126/sciadv.aau0049.
Chen,Z.,and S.Yang,2014:Homogenization and analysis of China radiosonde temperature data from 1979 to 2012.Acta Meteor.Sinica,72,794-804,doi:10.11676/qxxb2014.046.(in Chinese)
Christy,J.R.,and W.B.Norris,2006:Satellite and VIZ-radiosonde intercomparisons for diagnosis of nonclimatic influences.J.Atmos.Oceanic Technol.,23,1181-1194,doi:10.1175/JTECH1937.1.
Christy,J.R.,and W.B.Norris,2009:Discontinuity issues with radiosonde and satellite temperatures in the Australian region1979-2006.J.Atmos.Oceanic Technol.,26,508-522,doi:10.1175/2008JTECHA1126.1.
Christy,J.R.,R.W.Spencer,W.B.Norris,et al.,2003:Error estimates of version 5.0 of MSU-AMSU bulk atmospheric temperatures.J.Atmos.Oceanic Technol.,20,613-629,doi:10.1175/1520-0426(2003)20<613:EEOVOM>2.0.CO;2.
Christy,J.R.,W.B.Norris,R.W.Spencer,et al.,2007:Tropospheric temperature change since 1979 from tropical radiosonde and satellite measurements.J.Geophys.Res.Atmos.,112,D06102,doi:10.1029/2005JD006881.
Christy,J.R.,R.W.Spencer,W.D.Braswell,et al.,2018:Examination of space-based bulk atmospheric temperatures used in climate research.Int.J.Remote Sens.,39,3580-3607,doi:10.1080/01431161.2018.1444293.
Durre,I.,R.S.Vose,and D.B.Wuertz,2006:Overview of the integrated global radiosonde archive.J.Climate,19,53-68,doi:10.1175/JCLI3594.1.
Free,M.,D.J.Seidel,J.K.Angell,et al.,2005:Radiosonde atmospheric temperature products for assessing climate(RAT-PAC):A new data set of large-area anomaly time series.J.Geophys.Res.Atmos.,110,D22101,doi:10.1029/2005JD006169.
Guo,Y.J.,and Y.H.Ding,2009:Long-term free-atmosphere temperature trends in China derived from homogenized in situ radiosonde temperature series.J.Climate,22,1037-1051,doi:10.1175/2008JCLI2480.1.
Guo,Y.J.,and Y.H.Ding,2011:Impacts of reference time series on the homogenization of radiosonde temperature.Adv.Atmos.Sci.,28,1011-1022,doi:10.1007/s00376-010-9211-3.
Guo,Y.J.,P.W.Thorne,M.P.McCarthy,et al.,2008:Radiosonde temperature trends and their uncertainties over eastern China.Int.J.Climatol.,28,1269-1281,doi:10.1002/joc.1633.
Guo,Y.J.,S.Q.Zhang,J.H.Yan,et al.,2016:A comparison of atmospheric temperature over China between radiosonde observations and multiple reanalysis datasets.J.Meteor.Res.,30,242-257,doi:10.1007/s13351-016-5169-0.
Haimberger,L.,2007:Homogenization of radiosonde temperature time series using innovation statistics.J.Climate,20,1377-1403,doi:10.1175/JCLI4050.1.
Haimberger,L.,C.Tavolato,and S.Sperka,2008:Toward elimination of the warm bias in historic radiosonde temperature records-Some new results from a comprehensive intercomparison of upper-air data.J.Climate,21,4587-4606,doi:10.1175/2008JCLI1929.1.
Haimberger,L.,C.Tavolato,and S.Sperka,2012:Homogenization of the global radiosonde temperature dataset through combined comparison with reanalysis background series and neighboring stations.J.Climate,25,8108-8131,doi:10.1175/JCLI-D-11-00668.1.
Hurrell,J.W.,S.J.Brown,K.E.Trenberth,et al.,2000:Comparison of tropospheric temperatures from radiosondes and satellites:1979-98.Bull.Amer.Meteor.Soc.,81,2165-2178,doi:10.1175/1520-0477(2000)081<2165:COTTFR>2.3.CO;2.
IPCC,2013:Climate Change 2013:The Physical Science Basis.Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change,T.F.Stocker,D.Qin,G.-K.Plattner,et al.,Eds.,Cambridge University Press,Cambridge,United Kingdom and New York,NY,USA,1535 pp.
Mears,C.A.,and F.J.Wentz,2009a:Construction of the remote sensing systems V3.2 atmospheric temperature records from the MSU and AMSU Microwave Sounders.J.Atmos.Oceanic Technol.,26,1040-1056,doi:10.1175/2008JTECHA1176.1.
Mears,C.A.,and F.J.Wentz,2009b:Construction of the RSSV3.2 lower-tropospheric temperature dataset from the MSUand AMSU Microwave Sounders.J.Atmos.Oceanic Technol.,26,1493-1509,doi:10.1175/2009JTECHA1237.1.
Mears,C.A.,and F.J.Wentz,2016:Sensitivity of satellite-derived tropospheric temperature trends to the diurnal cycle adjustment.J.Climate,29,3629-3646,doi:10.1175/JCLI-D-15-0744.1.
Mears,C.A.,and F.J.Wentz,2017:A satellite-derived lower-tropospheric atmospheric temperature dataset using an optimized adjustment for diurnal effects.J.Climate,30,7695-7718,doi:10.1175/JCLI-D-16-0768.1.
Mears,C.A.,M.C.Schabel,and F.J.Wentz,2003:A reanalysis of the MSU channel 2 tropospheric temperature record.J.Climate,16,3650-3664,doi:10.1175/1520-0442(2003)016<3650:AROTMC>2.0.CO;2.
Mears,C.A.,F.J.Wentz,and P.W.Thorne,2012:Assessing the value of microwave sounding unit-radiosonde comparisons in ascertaining errors in climate data records of tropospheric temperatures.J.Geophys.Res.Atmos.,117,D19103,doi:10.1029/2012JD017710.
Parker,D.E.,M.Gordon,D.P.N.Cullum,et al.,1997:A new global gridded radiosonde temperature data base and recent temperature trends.Geophys.Res.Lett.,24,1499-1502,doi:10.1029/97GL01186.
Po-Chedley,S.,and Q.Fu,2012:A bias in the midtropospheric channel warm target factor on the NOAA-9 microwave sounding unit.J.Atmos.Oceanic Technol.,29,646-652,doi:10.1175/JTECH-D-11-00147.1.
Po-Chedley,S.,T.J.Thorsen,and Q.Fu,2015:Removing diurnal cycle contamination in satellite-derived tropospheric temperatures:Understanding tropical tropospheric trend discrepancies.J.Climate,28,2274-2290,doi:10.1175/JCLI-D-13-00767.1.
Randall,R.M.,and B.M.Herman,2008:Using limited time period trends as a means to determine attribution of discrepancies in microwave sounding unit-derived tropospheric temperature time series.J.Geophys.Res.Atmos.,113,D05105,doi:10.1029/2007JD008864.
Randel,W.J.,and F.Wu,2006:Biases in stratospheric and tropospheric temperature trends derived from historical radiosonde data.J.Climate,19,2094-2104,doi:10.1175/JCLI3717.1.
Ren,Z.H.,Y.Yu,F.L.Zou,et al.,2012:Quality detection of surface historical basic meteorological data.J.Appl.Meteor.Sci.,23,739-747,doi:10.3969/j.issn.1001-7313.2012.06.011.(in Chinese)
Ruan,X.,A.Y.Xiong,K.X.Hu,et al.,2015:Correcting geopotential height errors of some mandatory levels of Chinese historic radiosonde observations.J.Appl.Meteor.Sci.,26,257-267,doi:10.11898/1001-7313.20150301.(in Chinese)
Santer,B.D.,T.M.L.Wigley,J.S.Boyle,et al.,2000:Statistical significance of trends and trend differences in layer-average atmospheric temperature time series.J.Geophys.Res.Atmos.,105,7337-7356,doi:10.1029/1999JD901105.
Santer,B.D.,S.Solomon,G.Pallotta,et al.,2017a:Comparing tropospheric warming in climate models and satellite data.J.Climate,30,373-392,doi:10.1175/JCLI-D-16-0333.1.
Santer,B.D.,J.C.Fyfe,G.Pallotta,et al.,2017b:Causes of differences in model and satellite tropospheric warming rates.Nat.Geosci.,10,478-485,doi:10.1038/ngeo2973.
Seidel,D.J.,J.K.Angell,J.Christy,et al.,2004:Uncertainty in signals of large-scale climate variations in radiosonde and satellite upper-air temperature datasets.J.Climate,17,2225-2240,doi:10.1175/1520-0442(2004)017<2225:UISOLC>2.0.CO;2.
Seidel,D.J.,F.H.Berger,H.J.Diamond,et al.,2009:Reference upper-air observations for climate:Rationale,progress,and plans.Bull.Amer.Meteor.Soc.,90,361-369,doi:10.1175/2008BAMS2540.1.
Seidel,D.J.,N.P.Gillett,J.R.Lanzante,et al.,2011:Stratospheric temperature trends:Our evolving understanding.Wiley Interdiscip.Rev.:Climate Change,2,592-616,doi:10.1002/wcc.125.
Sherwood,S.C.,and N.Nishant,2015:Atmospheric changes through 2012 as shown by iteratively homogenized radiosonde temperature and wind data(IUKv2).Environ.Res.Lett.,10,054007,doi:10.1088/1748-9326/10/5/054007.
Shi,Y.,P.M.Zhai,and Z.H.Jiang,2016:Multi-sliding time windows based changing trend of mean temperature and its association with the global-warming hiatus.J.Meteor.Res.,30,232-241,doi:10.1007/s13351-016-5093-3.
Spencer,R.W.,and J.R.Christy,1990:Precise monitoring of global temperature trends from satellites.Science,247,1558-1562,doi:10.1126/science.247.4950.1558.
Spencer,R.W.,and J.R.Christy,1992:Precision and radiosonde validation of satellite gridpoint temperature anomalies.Part I:MSU channel 2.J.Climate,5,847-857,doi:10.1175/1520-0442(1992)005<0847:PARVOS>2.0.CO;2.
Spencer,R.W.,J.R Christy,and W.D.Braswell,2017:UAHversion 6 global satellite temperature products:Methodology and results.Asia-Pac.J.Atmos.Sci.,53,121-130,doi:10.1007/s13143-017-0010-y.
Thorne,P.W.,D.E.Parker,J.R.Christy,et al.,2005a:Uncertainties in climate trends:Lessons from upper-air temperature records.Bull.Amer.Meteor.Soc.,86,1437-1442,doi:10.1175/BAMS-86-10-1437.
Thorne,P.W.,D.E.Parker,S.F.B.Tett,et al.,2005b:Revisiting radiosonde upper air temperatures from 1958 to 2002.J.Geophys.Res.Atmos.,110,D18105,doi:10.1029/2004jd005753.
Thorne,P.W.,J.R.Lanzante,T.C.Peterson,et al.,2011:Tropospheric temperature trends:History of an ongoing controversy.Wiley Interdiscip.Rev.:Climate Change,2,66-88,doi:10.1002/wcc.80.
Wang,X.L.,Q.H.Wen,and Y.H.Wu,2007:Penalized maximal t test for detecting undocumented mean change in climate data series.J.Appl.Meteor.Climatol.,46,916-931,doi:10.1175/JAM2504.1.
Xu,W.H.,Q.X.Li,X.L.Wang,et al.,2013:Homogenization of Chinese daily surface air temperatures and analysis of trends in the extreme temperature indices.J.Geophys.Res.Atmos.,118,9708-9720,doi:10.1002/jgrd.50791.
Zhai,P.M.,1997:Some gross errors and biases in China’s historical radiosonde data.Acta Meteor.Sinica,55,563-572,doi:10.11676/qxxb1997.055.(in Chinese)
Zhai,P.M.,and R.E.Eskridge,1996:Analyses of inhomogeneities in radiosonde temperature and humidity time series.J.Climate,9,884-894,doi:10.1175/1520-0442(1996)009<0884:AOIIRT>2.0.CO;2.
Zou,C.Z.,and W.Wang,2011:Intersatellite calibration of AMSU-A observations for weather and climate applications.J.Geophys.Res.Atmos.,116,D23113,doi:10.1029/2011JD016205.
Zou,C.Z,and H.F.Qian,2016:Stratospheric temperature climate data record from merged SSU and AMSU-A observations.J.Atmos.Oceanic Technol.,33,1967-1984,doi:10.1175/JTECH-D-16-0018.1.
Zou,C.Z.,M.D.Goldberg,Z.H.Cheng,et al.,2006:Recalibration of microwave sounding unit for climate studies using simultaneous nadir overpasses.J.Geophys.Res.Atmos.,111,D19114,doi:10.1029/2005JD006798.
Zou,C.-Z.,M.D.Goldberg,and X.J.Hao,2018:New generation of U.S.satellite microwave sounder achieves high radiometric stability performance for reliable climate change detection.Sci.Adv.,4,eaau0049,doi:10.1126/sciadv.aau0049.