Guo Yanjun, Ding Yinhui. Homogeneity and long-term trend analysis on radiosonde temperature time series in China during recent 50 years. J Appl Meteor Sci, 2008, 19(6): 646-654.
Citation: Guo Yanjun, Ding Yinhui. Homogeneity and long-term trend analysis on radiosonde temperature time series in China during recent 50 years. J Appl Meteor Sci, 2008, 19(6): 646-654.

Homogeneity and Long-term Trend Analysis on Radiosonde Temperature Time Series in China During Recent 50 Years

  • Received Date: 2008-02-18
  • Rev Recd Date: 2008-06-19
  • Publish Date: 2008-12-31
  • In order to study long-term trend of upper air temperature in China, radiosonde temperature time series during 1958-2005 at 116 Chinese stations are examined.Firstly, uncertainties in the time series caused by artificial errors and breakpoints are detected by quality control and homogenization procedure. Original radionsonde temperature time series at 7 levels are adjusted by employing hydrostatic and two-phase-regression (TPR) method.The identification results show significant discontinuities in the studied time series, especially in earlier period (1960s-1970s). Parts of the break points are documented by station' s metadata, which contributes to the changes of instrument model or method.Significant impact on long-term trends of original time series is caused by the adjustments which vary with different periods. The cooling trends in mid-upper troposphere during 1958-1978 are weakened by homogenization; also, cooling trends in lower stratosphere are enhanced and warming trends at 400 hPa and 500 hPa during 1979-2005 are weakened.Missing rate, as an important factor influencing the utilization of radiosonde temperature time series in China, is a reasonable index for sampling stations to assess regional average trend. Sampling by low missing rate (high data requirement) results in reduced number of potential stations. By analysis on averaged trend profile with different minimum data requirements (MDR), it is found that warming trends in low troposphere are enhanced and cooling trends in upper troposphere and low stratosphere are weakened by the decreasing number of stations in accordance with low missing rate or high M DR of stations. Critical maximum missing rate is suggested as 30% (MDR as 70%) for examining reliability of the time series. Averaged temperature time series in China are deduced by 92 radiosonde stations, which are selected by meeting maximum missing rate (or minimum data requirement by MDR).Homogenous radiosonde temperature time series show that trends of upper air temperature in China are generally consistent with that at global scale but with some discrepancies. During 1958-2005, atmospheric temperatures in China tend to decrease in the low stratosphere and upper troposphere, and increase in the middle and low troposphere. The trends of upper air vary with different periods. For 1958-1978, cooling trends in the entire atmosphere are similar to those at global scale. During 1979-2005, obvious warming occurs in the low and mid-troposphere; the amplitude of warming trend weakens with the increase of altitude and shifts to cooling trend above 400 hPa. Analysis on decadal averaged temperatures anomalies shows that cooling in low stratosphere has occurred since 1980s and enhances in 1990s and warming in midlow troposphere below 500 hPa has occurred since 1970s and significantly warming in the layer between 700 hPa and 300 hPa has occurred since 1980s.
  • Fig. 1  Comparison of mean vertical trend profiles with different minimum percentage of data requirements for periods of 1958-2005(a) and 1979-2005(b)

    Fig. 2  Seasonal temperature anomalies of Shanghai station (58362) at 850-100 hPa

    (filled circles denote detected break points; thin lines denote in strument mode change; dot-dased lines denote correction method change)

    Fig. 3  Comparisons of mean trends between original and adjusted radiosonde temperature time series for different periods

    Fig. 4  Spatial distribution of in situ temperature trends for 1958-2005 at different levels (unit:K/10a)

    (circles denote warming trends; squares denote cooling trends; filled circles and squares denote level over 95%)

    Table  1  The number of percentage stations meeting to various MDR in China

    Table  2  Radiosonde temperature trends averaged in China during different periods

  • [1]
    翟盘茂, 郭艳君.高空大气温度变化研究.气候变化研究进展, 2006, 2(5):228-232 http://www.cnki.com.cn/Article/CJFDTOTAL-QHBH200605006.htm
    [2]
    郭艳君.高空大气温度变化趋势不确定性的研究进展.地球科学进展, 2008, 23(1):24-30 http://www.cnki.com.cn/Article/CJFDTOTAL-DXJZ200801007.htm
    [3]
    Guo Yanjun, Thorne P W, McCarthy M P, et al. Radiosonde temperature trends and their uncertainties over eastern China. Int J Climatol, 2008, 28 :1269-1281 doi:  10.1002/joc.v28:10
    [4]
    Gaffen D J. Temporal inhomogeneities in radiosonde temper aturerecords. JGeophysRes, 1994, 99: 3667-3676 doi:  10.1029/93JD03179/abstract
    [5]
    Zhai P M, Eskridge R E. Analysis of inhomogeneities in Radiosonde temperature and humidity time series. J Climate, 1996, 9:884-894 doi:  10.1175/1520-0442(1996)009<0884:AOIIRT>2.0.CO;2
    [6]
    翟盘茂.中国历史探空资料中的一些过失误差及偏差问题.气象学报, 1997, 55(5):564-572 http://www.cnki.com.cn/Article/CJFDTOTAL-QXXB705.004.htm
    [7]
    Collins W G, Gandin L S. Comprehensive hydrostatic quality control at the National Meteorological Center. Mon Wea Rev, 1990, 118: 2752-2767 doi:  10.1175/1520-0493(1990)118<2752:CHQCAT>2.0.CO;2
    [8]
    Solow A R. Testing for climate change: An application of the two-phase regression model. J Climate Appl Meteor, 1987, 26:1401-1405 doi:  10.1175/1520-0450(1987)026<1401:TFCCAA>2.0.CO;2
    [9]
    Easterling D R, Peterson T C. A new method for detecting undocumented discontinuities in climatological time series. Int J Climatolog, 1995, 15: 369-377 doi:  10.1002/(ISSN)1097-0088
    [10]
    Haimberger L. Homogenization of radiosonde temperature time series using innovation statistics. J Climate, 2007, 20: 1377-1403 doi:  10.1175/JCLI4050.1
    [11]
    Kalnay E, Kanamitsu M, Kistler R, et al. The NCEP/NCAR 40 year reanalysis project. Bull Amer Meteor Soc, 1996, 77:437-471 doi:  10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2
    [12]
    McCarthy M P, Titchner H A, Thorne P W, et al. Assessing bias and uncertainty in the HadAT adjusted radiosonde climate record. J Climate, 2008, 21:817-832 doi:  10.1175/2007JCLI1733.1
    [13]
    Gaffen D J, Sargent M A, Habermann R E, et al. Sensitivity of tropospheric and stratospheric temperature trends to radio sonde data quality. J Climate, 2000, 13 :1776-1796 doi:  10.1175/1520-0442(2000)013<1776:SOTAST>2.0.CO;2
    [14]
    Free M, Seidel D J. Causes of differing temperature trends in radiosonde upper air data sets. J Geophys Res, 2005, 110: D07101, doi:  10.1029/2004JD005481
    [15]
    Frederick J E, DougIass A R. Atmospheric temperatures near the tropical tropopause: Temporal variations, zonal asymmetry and implications for stratospheric water vapor. Mort Wea Rev, 1983, 111:1397-1403 doi:  10.1175/1520-0493(1983)111<1397:ATNTTT>2.0.CO;2
    [16]
    唐国利, 任国玉.近百年中国地表气温变化趋势的再分析.气候与环境研究, 2005, 10(4):791-798. http://www.cnki.com.cn/Article/CJFDTOTAL-QHYH200504010.htm
  • 加载中
  • -->

Catalog

    Figures(4)  / Tables(2)

    Article views (3144) PDF downloads(1570) Cited by()
    • Received : 2008-02-18
    • Accepted : 2008-06-19
    • Published : 2008-12-31

    /

    DownLoad:  Full-Size Img  PowerPoint