利用RHtestsV4软件包对天津1951～2012年逐日气温序列的均一性分析

司鹏; 徐文慧

doi:10.3878/j.issn.1006-9585.2015.15014

利用RHtestsV4软件包对天津1951～2012年逐日气温序列的均一性分析

doi: 10.3878/j.issn.1006-9585.2015.15014

司鹏¹,
徐文慧²

1.
天津市气象信息中心, 天津 300074
2.
中国气象局国家气象信息中心, 北京 100081

基金项目: 天津市气象局科研课题项目201302,公益性行业(气象)科研专项经费项目GYHY201206031

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出版历程
- 收稿日期: 2015-02-16
- 修回日期: 2015-05-27

Homogenization of Tianjin Daily Surface Air Temperatures by Software Pack RHtestsV4 during 1951-2012

SI Peng¹,
XU Wenhui²

1.
Tianjin Meteorological Information Center, Tianjin 300074
2.
National Meteorological Information Center, China Meteorological Administration, Beijing 100081

摘要

摘要: 基于国家气象信息中心“基础气象资料建设专项”研制的中国地面历史基础气象资料及台站元数据,利用RHtestV4软件包对天津1951～2012年的历史气温序列进行了均一性分析。结果显示,通过惩罚最大t检验(PMT)方法对12个地面站逐日平均、最高、最低气温序列检验得到,迁站是导致平均气温和最低气温序列突变的主要原因,同类型仪器更换则是导致最高气温序列突变的主要原因,而2005年以后的自动站业务化并没有对天津地区气温序列的均一性造成很大影响。同时,研究中也检验出少部分未知原因的显著间断点,可能是由于观测员的误判或观测仪器翘变等因素造成的历史数据疑误。从订正量来看,逐日平均气温和最高气温序列主要以正偏差订正为主,而最低气温则主要以负偏差订正为主。其中,最高气温序列的分位数匹配(QM)订正量均值最大,90%以上集中在0.1～1.0 ℃,平均气温序列的QM订正量均值相对最小,90%以上的订正量在－0.7～0.7 ℃,而最低气温的订正量90%以上集中在－1.5～1.5 ℃范围中。另外,以Xu et al.(2013)研制的数据集为参照,通过误差分析,发现两类研究得到的年(季节)尺度气温数据具有较高的相符率和一致性,从而可以说明本研究订正后的天津地区1951～2012年逐日气温序列具有一定的可靠性。
- 天津地区 /
- 逐日平均/最高/最低气温序列 /
- RHtestsV4软件包 /
- 均一性检验和订正 /
- 可用性评估
Abstract: Based on historical ground-level meteorological data and their metadata in Tianjin, China, produced by the National Meteorological Information Center, China Meteorological Administration, the homogenization of the daily surface air temperature data for Tianjin during the last 60 years, by the software package RHtestV4, is tested. Results indicate that the main cause of the discontinuities in daily mean and minimum temperatures is station relocation, as tested by the penalized maximal t-test; while for daily maximum temperature, it is instrument change. Furthermore, the operation of automatic stations after 2005 does not have a great impact on the homogeneity of temperature at Tianjin. Moreover, some significant discontinuities for unknown reasons are also detected, which we think may be due to reasons such as observer misjudgment or instrument warping. For the adjustment amount, the positive bias corrections are mainly expressed in daily mean and maximum temperature series. Meanwhile, the negative bias corrections are mainly in daily minimum temperature series, in which the largest average quantile-matching (QM) adjustments are for daily maximum temperature (more than 90% are from 0.1 ℃ to 1.0 ℃), and the smallest are for daily mean temperature (more than 90% are from -0.7 ℃ to 0.7 ℃). For daily minimum temperature, the range is -1.5 ℃ to 1.5 ℃. In addition, error analysis reveals that there is much higher consistency between the two datasets of the present paper and those of a previous study, on annual and seasonal scales, by setting the datasets from the previous study as the reference. This can explain why the daily temperature series for the period 1951-2012 in Tianjin, adjusted in this study, show a certain reliability.
- Tianjin /
- Daily temperature /
- RHtestV4 /
- Homogenization /
- Reliability

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参考文献(38)

[1]	Aguilar E, Auer I, Brunet M, et al. 2003. Guidance on metadata and homogenization [G]. WMO-TD No. 1186, WCDMP No. 53. Geneva, Switzerland: World Meteorological Organization, 55pp.
[2]	Alexandersson H. 1986. A homogeneity test applied to precipitation data[J]. J. Climatol., 6 (6): 661-675, doi: 10.1002/joc.3370060607.
[3]	Alexander L V, Zhang X B, Peterson T C, et al. 2006. Global observed changes in daily climate extremes of temperature and precipitation [J]. J. Geophys. Res.: Atmos. (1984-2012), 111: D05109, doi: 10.1029/ 2005JD006290.
[4]	曹丽娟, 鞠晓慧, 刘小宁. 2010. PMFT方法对我国年平均风速的均一性检验 [J]. 气象, 36 (10): 52-56. Cao Lijuan, Ju Xiaohui, Liu Xiaoning. 2010. Penalized maximal F test for the homogeneity study of the annual mean wind speed over China [J]. Meteorological Monthly (in Chinese), 36 (10): 52-56.
[5]	Caussinus H, Mestre O. 2004. Detection and correction of artificial shifts in climate series [J]. Journal of the Royal Statistical Society: Series C (Applied Statistics), 53 (3): 405-425, doi:10.1111/j.1467-9876.2004. 05155.x.
[6]	Chenoweth M. 1992. A possible discontinuity in the U. S. historical temperature record [J]. J. Climate, 5 (10): 1172-1179, doi: 10.1175/1520-0442(1992)005<1172:APDITU>2.0.CO;2.
[7]	Dai A G, Wang J H, Thorne P W, et al. 2011. A new approach to homogenize daily radiosonde humidity data[J]. J. Climate, 24 (4): 965-991, doi: 10.1175/2010JCLI3816.1.
[8]	Della-Marta P M, Wanner H. 2006. A method of homogenizing the extremes and mean of daily temperature measurements [J]. J. Climate, 19 (17): 4179-4197, doi: 10.1175/JCLI3855.1.
[9]	Easterling D R, Peterson T C. 1995. A new method for detecting undocumented discontinuities in climatological time series[J]. International Journal of Climatology, 15 (4): 369-377, doi:10.1002/joc. 3370150403.
[10]	郭艳君, 丁一汇. 2008. 近50年我国探空温度序列均一化及变化趋势[J]. 应用气象学报, 19 (6): 646-654. Guo Yanjun, Ding Yihui. 2008. Homogeneity and long-term trend analysis on radiosonde temperature time series in China during recent 50 years [J]. Journal of Applied Meteorological Science (in Chinese), 19 (6): 646-654.
[11]	Haimberger L, Tavolato C, Sperka S. 2012. Homogenization of the global radiosonde temperature dataset through combined comparison with reanalysis background series and neighboring stations [J]. J. Climate, 25 (23): 8108-8131, doi: 10.1175/JCLI-D-11-00668.1.
[12]	Hanesiak J M, Wang X L. 2005. Adverse-weather trends in the Canadian Arctic [J]. J. Climate, 18 (16): 3140-3156, doi: 10.1175/JCLI3505.1.
[13]	Jones P D, Lister D H, Li Q X. 2008. Urbanization effects in large-scale temperature records, with an emphasis on China [J]. J. Geophys. Res., 113: D16122, doi: 10.1029/2008JD009916.
[14]	鞠晓慧, 屠其璞, 李庆祥. 2006. 我国太阳总辐射月总量资料的均一性检验及订正 [J]. 南京气象学院学报, 29 (3): 336-341. Ju Xiaohui, Tu Qipu, Li Qingxiang. 2006. Homogeneity test and reduction of monthly total solar radiation over China [J]. Journal of Nanjing Institute of Meteorology (in Chinese), 29 (3): 336-341.
[15]	Kuglitsch F G, Auchmann R, Bleisch R, et al. 2012. Break detection of annual Swiss temperature series [J]. J. Geophys. Res., 117: D13105, doi: 10.1029/2012JD017729.
[16]	Li Q X, Zhang H Z, Liu X N, et al. 2009. A mainland China homogenized historical temperature dataset of 1951-2004 [J]. Bull. Amer. Meteor. Soc., 90 (8): 1062-1065, doi: 10.1175/2009BAMS2736.1.
[17]	李庆祥, 彭嘉栋, 沈艳. 2012. 1900-2009年中国均一化逐月降水数据集研制 [J]. 地理学报, 67 (3): 301-311. Li Qingxiang, Peng Jiadong, Shen Yan. 2012. Development of homogenized monthly precipitation dataset in China during 1900-2009[J]. Acta Geographica Sinica (in Chinese), 67 (3): 301-311, doi: 10.11821/xb201203002.
[18]	刘小宁. 2000. 我国40年年平均风速的均一性检验 [J]. 应用气象学报, 11 (1): 27-34. Liu Xiaoning. 2000. The homogeneity test on mean annual wind speed over China [J]. Quarterly Journal of Applied Meteorology (in Chinese), 11 (1): 27-34.
[19]	Ma L J, Zhang T J, Li Q X, et al. 2008. Evaluation of ERA-40, NCEP-1, and NCEP-2 reanalysis air temperatures with ground-based measurements in China [J]. J. Geophys. Res., 113: D15115, doi: 10.1029/2007JD009549.
[20]	Mielke P W Jr. 1986. Non-metric statistical analyses: Some metric alternatives [J]. Journal of Statistical Planning and Inference, 13: 377-387, doi: 10.1016/0378-3758(86)90147-3.
[21]	Peterson T C. 2003. Assessment of urban versus rural in situ surface temperatures in the contiguous United States: No difference found [J]. J. Climate, 16 (18): 2941-2959, doi: 10.1175/1520-0442(2003)016<2941: AOUVRI>2.0.CO;2.
[22]	Peterson T C, Easterling D R. 1994. Creation of homogeneous composite climatological reference series [J]. International Journal of Climatology, 14 (6): 671-679, doi: 10.1002/joc.3370140606.
[23]	Peterson T C, Easterling D R, Karl T R, et al. 1998. Homogeneity adjustments of in situ atmospheric climate data: A review[J]. International Journal of Climatology, 18 (13): 1493-1517, doi: 10.1002/(SICI)1097-0088(19981115)18: 13<1493: AID-JOC329>3.0.CO;2-T.
[24]	Quayle R G, Easterling D R, Karl T R, et al. 1991. Effects of recent thermometer changes in the cooperative station network [J]. Bull. Amer. Meteor. Soc., 72 (11): 1718-1723, doi: 10.1175/1520-0477(1991)072 <1718: EORTCI>2.0.CO;2.
[25]	任芝花, 余予, 邹凤玲, 等. 2012. 部分地面要素历史基础气象资料质量检测 [J]. 应用气象学报, 23 (6): 739-747. Ren Zhihua, Yu Yu, Zou Fengling, et al. 2012. Quality detection of surface historical basic meteorological data [J]. Journal of Applied Meteorological Science (in Chinese), 23 (6): 739-747.
[26]	司鹏, 解以扬. 2015. 天津太阳总辐射资料的均一性分析 [J]. 气候与环境研究, 20 (3): 269-276. Si Peng, Xie Yiyang. 2015. Analysis of the homogeneity of total solar radiation data in Tianjin [J]. Climatic and Environmental Research (in Chinese), 20 (3): 269-276.
[27]	Wan H, Wang X L, Swail V R. 2010. Homogenization and trend analysis of Canadian near-surface wind speeds [J]. J. Climate, 23 (5): 1209-1225, doi: 10.1175/2009JCLI3200.1.
[28]	Wang X L. 2008a. Penalized maximal F test for detecting undocumented mean shift without trend change [J]. J. Atmos. Oceanic Technol., 25 (3): 368-384, doi: 10.1175/2007JTECHA982.1.
[29]	Wang X L. 2008b. Accounting for autocorrelation in detecting mean shifts in climate data series using the penalized maximal t or F test [J]. Journal of Applied Meteorology and Climatology, 47 (9): 2423-2444, doi: 10.1175/2008JAMC1741.1.
[30]	Wang X L, Wen Q H, Wu Y H. 2007. Penalized maximal t test for detecting undocumented mean change in climate data series [J]. Journal of Applied Meteorology and Climatology, 46 (6): 916-931, doi: 10.1175/JAM2504.1.
[31]	Wang X L, Chen H F, Wu Y H, et al. 2010. New techniques for the detection and adjustment of shifts in daily precipitation data series [J]. Journal of Applied Meteorology and Climatology, 49 (12): 2416-2436, doi: 10.1175/2010JAMC2376.1.
[32]	Wang X L, Feng Y, Vincent L A. 2014. Observed changes in one-in-20 year extremes of Canadian surface air temperatures [J]. Atmosphere Ocean, 52 (3): 222-231, doi: 10.1080/07055900.2013.818526.
[33]	Willmott C J, Matsuura K. 2005. Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance [J]. Climate Research, 30 (1): 79-82.
[34]	Wijngaard J B, Klein Tank A M G, Können G P. 2003. Homogeneity of 20th century European daily temperature and precipitation series[J]. International Journal of Climatology, 23 (6): 679-692, doi: 10.1002/ joc.906.
[35]	Winkler J A, Skaggs R H, Baker D G. 1981. Effect of temperature adjustments on the Minneapolis-St. Paul urban heat island [J]. J. Appl. Meteor., 20 (11): 1295-1300, doi: 10.1175/1520-0450(1981)020<1295: EOTAOT>2.0.CO;2.
[36]	吴必文, 温华洋, 惠军. 2008. 基于分布的气压序列非均一性检验方法初探 [J]. 应用气象学报, 19 (4): 496-501. Wu Biwen, Wen Huayang, Hui Jun. 2008. The inhomogeneity test method of atmospheric pressure sequences based on -distribution [J]. Journal of Applied Meteorological Science (in Chinese), 19 (4): 496-501.
[37]	Xu W H, Li Q X, Wang X L, et al. 2013. Homogenization of Chinese daily surface air temperatures and analysis of trends in the extreme temperature indices [J]. J. Geophys. Res., 118 (17): 9708-9720, doi:10.1002/jgrd. 50791.
[38]	翟盘茂. 1997. 中国历史探空资料中的一些过失误差及偏差问题 [J]. 气象学报, 55 (5): 563-572. Zhai Panmao. 1997. Some gross errors and biases in China's historical radiosonde data [J]. Acta Meteorologica Sinica (in Chinese), 55 (5): 563-572, doi: 10.11676/qxxb1997.055.