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Comparison of two homogenized datasets of daily maximum/mean/minimum temperature in China during 1960–2013

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Abstract

Two homogenized datasets of daily maximum temperature (Tmax), mean temperature (Tm), and minimum temperature (Tmin) series in China have recently been developed. One is CHTM3.0, based on the Multiple Analysis of Series for Homogenization (MASH) method, and includes 753 stations for the period 1960–2013. The other is CHHTD1.0, based on the Relative Homogenization test (RHtest), and includes 2419 stations over the period 1951–2011. The daily Tmax/Tm/Tmin series at 751 stations, which are in both datasets, are chosen and compared against the raw dataset, with regard to the number of breakpoints, long-term climate trends, and their geographical patterns. The results indicate that some robust break points associated with relocations can be detected, the inhomogeneities are removed by both the MASH and RHtest method, and the data quality is improved in both homogenized datasets. However, the differences between CHTM3.0 and CHHTD1.0 are notable. By and large, in CHHTD1.0, the break points detected are fewer, but the adjustments for inhomogeneities and the resultant changes of linear trend estimates are larger. In contrast, CHTM3.0 provides more reasonable geographical patterns of long-term climate trends over the region. The reasons for the differences between the datasets include: (1) different algorithms for creating reference series for adjusting the candidate series—more neighboring stations used in MASH and hence larger-scale regional signals retained; (2) different algorithms for calculating the adjustments—larger adjustments in RHtest in general, partly due to the individual local reference information used; and (3) different rules for judging inhomogeneity—all detected break points are adjusted in CHTM3.0, based on MASH, while a number of break points detected via RHtest but without supporting metadata are overlooked in CHHTD1.0. The present results suggest that CHTM3.0 is more suitable for analyses of large-scale climate change in China, while CHHTD1.0 contains more original information regarding station temperature records.

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References

  • Begert, M., T. Schlegel, and W. Kirchhofer, 2005: Homogeneous temperature and precipitation series of Switzerland from 1864 to 2000. Int. J. Climatol., 1, 65–80.

    Article  Google Scholar 

  • Brandsma, T., and G. P. Können, 2006: Application of nearest-neighbor resampling for homogenizing temperature records on a daily to sub-daily level. Int. J. Climatol., 1, 75–89.

    Article  Google Scholar 

  • Brohan, P., J. J. Kennedy, I. Harris, et al., 2006: Uncertainty estimates in regional and global observed temperature changes: A new data set from 1850. J. Geophys. Res., 1, D12106, doi: 10.1029/2005JD006548.

    Article  Google Scholar 

  • Cao, L. J., P. Zhao, Z. W. Yan, et al., 2013: Instrumental temperature series in eastern and central China back to the nineteenth century. J. Geophys. Res., 1, 8197–8207.

    Google Scholar 

  • Caussinus, H., and O. Mestre, 2004: Detection and correction of artificial shifts in climate series. J. Roy. Statist. Sci., 1, 405–425.

    Google Scholar 

  • Coll, J. R., 2010: Homogenization of Daily Temperature and Precipitation Data Using ProClimDB Software–A Comparison of Methods. Reports of the 2010, STSM in Brno. [Available online at http://wwwhomogenisationorg/admin/docs/repport- STSMpdf].

    Google Scholar 

  • Craddock, J. M., 1979: Methods of comparing annual rainfall records for climatic purposes. Weather, 1, 332–346.

    Article  Google Scholar 

  • Della-Marta, P. M., and H. Wanner, 2006: A method of homogenizing the extremes and mean of daily temperature measurements. J. Climate, 1, 4179–4197.

    Article  Google Scholar 

  • Domonkos, P., 2011: Efficiency evaluation for detecting inhomogeneities by objective homogenisation methods. Theor. Appl. Climatol., 1, 455–467.

    Article  Google Scholar 

  • Domonkos, P., 2013: Measuring performances of homogenization methods. Quart. J. Hungarian Meteor. Serv., 1, 91–112.

    Google Scholar 

  • Freitas, L., M. Gonzalez Pereira, L. Caramelo, et al., 2013: Homogeneity of monthly air temperature in Portugal with HOMER and MASH. Quart. J. Hungarian Meteor. Serv., 1, 69–90.

    Google Scholar 

  • Guo Yanjun and Ding Yihui, 2011: Impacts of reference time series on the homogenization of radiosonde temperature. Adv. Atmos. Sci., 1, 1011–1022.

    Article  Google Scholar 

  • Li Qingxiang and Dong Wenjie, 2009: Detection and adjustment of undocumented discontinuities in Chinese temperature series using a composite approach. Adv. Atmos. Sci., 1, 143–153.

    Article  Google Scholar 

  • Li, Q. X., H. Z. Zhang, X. N. Liu, et al., 2009: A mainland China homogenized historical temperature dataset of 1951–2004. Bull. Amer. Meteor. Soc., 1, 1062–1065.

    Article  Google Scholar 

  • Li Qingxiang and Huang Jiayou, 2013: Effects of urbanization on extreme warmest night temperatures during summer near Bohai. Acta Meteor. Sinica, 1, 808–818.

    Article  Google Scholar 

  • Li Zhen and Yan Zhongwei, 2009: Homogenized daily mean/maximum/minimum temperature series for China from 1960–2008. Atmos. Oceanic Sci. Lett., 1, 237–243.

    Google Scholar 

  • Li Zhen and Yan Zhongwei, 2010: Application of multiple analysis of series for homogenization to Beijing daily temperature series (1960–2006). Adv. Atmos. Sci., 1, 777–787.

    Article  Google Scholar 

  • Li Zhen, Yan Zhongwei, Tu Kai, et al., 2011: Changes in wind speed and extremes in Beijing during 1960–2008 based on homogenized observations. Adv. Atmos. Sci., 1, 408–420.

    Article  Google Scholar 

  • Li, Z., Z. W. Yan, L. J. Cao, et al., 2014: Adjusting inhomogeneous daily temperature variability using wavelet analysis. Int. J. Climatol., 1, 1196–1207.

    Article  Google Scholar 

  • Li Zhen, Yan Zhongwei, and Wu Hongyi, 2015: Updated homogenized Chinese temperature series with physical consistency. Atmos. Oceanic Sci. Lett., 1, 17–22.

    Google Scholar 

  • Liu Jia, Ma Zhenfeng, Fan Guangzhou, et al., 2012: Research on the comparison of different homogeneity test methods. Meteor. Mon., 1, 1121–1128. (in Chinese)

    Google Scholar 

  • Liu Xiaoning and Li Qingxiang, 2003: Research of the inhomogeneity test of climatological data series in China. Acta Meteor. Sinica, 1, 492–502.

    Google Scholar 

  • Lund, R., and J. Reeves, 2002: Detection of undocumented changepoints: A revision of the two-phase regression model. J. Climate, 1, 2547–2554.

    Article  Google Scholar 

  • Mamara, A., A. A. Argiriou, and M. Anadranistakis, 2013: Homogenization of mean monthly temperature time series of Greece. Int. J. Climatol., 1, 2649–2666.

    Google Scholar 

  • Mamara, A., A. A. Argiriou, and M. Anadranistakis, 2014: Detection and correction of inhomogeneities in Greek climate temperature series. Int. J. Climatol., 1, 3024–3043.

    Article  Google Scholar 

  • Manton, M. J., P. M. Della-Marta, M. R. Haylock, et al., 2001: Trends in extreme daily rainfall and temperature in Southeast Asia and the South Pacific: 1961–1998. Int. J. Climatol., 1, 269–284.

    Article  Google Scholar 

  • McCarthy, M. P., H. A. Titchner, P. W. Thorne, et al., 2008: Assessing bias and uncertainty in the HadATadjusted radiosonde climate record. J. Climate, 1, 817–832.

    Article  Google Scholar 

  • Menne, M. J., and C. N. Williams Jr., 2009: Homogenization of temperature series via pairwise comparisons. J. Climate, 1, 1700–1717.

    Article  Google Scholar 

  • Menne, M. J., C. N. Williams Jr., and M. A. Palecki, 2010: On the reliability of the U.S. surface temperature record. J. Geophys. Res., 1, D11108, doi: 10.1029/2009JD013094.

    Article  Google Scholar 

  • Mestre, O., C. Gruber, C. Prieur, et al., 2011: SPLIDHOM: A method for homogenization of daily temperature observations. J. Appl. Meteor. Climatol., 1, 2343–2358.

    Article  Google Scholar 

  • Mestre, O., P. Domonkos, F. Picard, et al., 2013: HOMER: A homogenization software–methods and applications. Quart. J. Hungarian Meteor. Serv., 1, 47–67.

    Google Scholar 

  • Pandžić, K., and T. Likso, 2010: Homogeneity of average annual air temperature time series for Croatia. Int. J. Climatol., 1, 1215–1225.

    Google Scholar 

  • Peterson, T. C., D. R. Easterling, T. R. Karl, et al., 1998: Homogeneity adjustments of in-situ atmospheric climate data: A review. Int. J. Climatol., 1, 1493–1517.

    Article  Google Scholar 

  • ˘Stˇepánek, P., P. Zahradnícek, and P. Skalák, 2009: Data quality control and homogenization of air temperature and precipitation series in the area of the Czech Republic in the period 1961–2007. Adv. Sci. Res., 1, 23–26.

    Google Scholar 

  • Szentimrey, T., 1999: Multiple Analysis of Series for Homogenization (MASH). Proceeding Second Seminar for Homogenization of Surface Climatological Data, Budapest, Hungary, WMO, WCDMP-No. 1, 27–46.

    Google Scholar 

  • Trewin, B., 2013: A daily homogenized temperature data set for Australia. Int. J. Climatol., 1, 1510–1529.

    Article  Google Scholar 

  • Trewin, B. C., and A. C. F. Trevitt, 1996: The development of composite temperature records. Int. J. Climatol., 1, 1227–1242.

    Article  Google Scholar 

  • Venema, V. K. C., O. Mestre, E. Aguilar, et al., 2012: Benchmarking homogenization algorithms for monthly data. Climate Past, 1, 89–115.

    Article  Google Scholar 

  • Vincent, L. A., and D. W. Gullett, 1999: Canadian historical and homogeneous temperature datasets for climate change analyses. Int. J. Climatol., 1, 1357–1388.

    Google Scholar 

  • Vincent, L. A., C. B. Zhang, B. R. Bonsal, et al., 2002: Homogenization of daily temperatures over Canada. J. Climate, 1, 1322–1334.

    Article  Google Scholar 

  • Vincent, L. A., X. L. Wang, E. J. Milewska, et al., 2012: A second generation of homogenized Canadian monthly surface air temperature for climate trend analysis. J. Geophys. Res., 1, D18110, doi: 10.1029/2012JD017859.

    Google Scholar 

  • Wang Shaowu, Ye Jinlin, Gong Daoyi, et al., 1998: Construction of mean annual temperature series for the last one hundred years in China. J. Appl. Meteor. Sci., 1, 392–401. (in Chinese)

    Google Scholar 

  • 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., 1, 916–931.

    Article  Google Scholar 

  • Wang, X. L., 2008a: Accounting for autocorrelation in detecting mean shifts in climate data series using the penalized maximal t or F test. J. Appl. Meteor. Climatol., 1, 2423–2444.

    Article  Google Scholar 

  • Wang, X. L., 2008b: Penalized maximal F test for detecting undocumented mean shift without trend change. J. Atmos. Oceanic Technol., 1, 368–384.

    Article  Google Scholar 

  • Wang, X. L., H. F. Chen, Y. H. Wu, et al., 2010: New techniques for the detection and adjustment of shifts in daily precipitation data series. J. Appl. Meteor. Climatol., 1, 2416–2436.

    Article  Google Scholar 

  • Wang Zunya, Ding Yihui, Zhang Qiang, et al., 2012: Changing trends of daily temperature extremes with different intensities in China. Acta Meteor. Sinica, 1, 399–409.

    Article  Google Scholar 

  • 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., 1, 9708–9720.

    Google Scholar 

  • Yan, Z. W, Z. Li, Q. X. Li, et al., 2010: Effects of site change and urbanisation in the Beijing temperature series 1977–2006. Int. J. Climatol., 1, 1226–1234.

    Google Scholar 

  • Yan Zhongwei, Li Zhen, and Xia Jiangjiang, 2014: Homogenization of climate series: The basis for assessing climate changes. Sci. China (Ser. D), 1, 2891–2900.

    Article  Google Scholar 

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Authors and Affiliations

  1. Key Laboratory of Regional Climate-Environment in Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China

    Zhen Li  (李 珍) & Zhongwei Yan  (严中伟)

  2. National Meteorological Information Center, China Meteorological Administration, Beijing, 100081, China

    Lijuan Cao  (曹丽娟) & Yani Zhu  (朱亚妮)

Authors
  1. Zhen Li  (李 珍)
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  2. Lijuan Cao  (曹丽娟)
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  3. Yani Zhu  (朱亚妮)
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  4. Zhongwei Yan  (严中伟)
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Corresponding author

Correspondence to Zhongwei Yan  (严中伟).

Additional information

Supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA05090100), National Science and Technology Support Program of China (2012BAC22B04), China Meteorological Administration Special PublicWelfare Research Fund (GYHY201206013), and National Natural Science Foundation of China (41505071).

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Li, Z., Cao, L., Zhu, Y. et al. Comparison of two homogenized datasets of daily maximum/mean/minimum temperature in China during 1960–2013. J Meteorol Res 30, 53–66 (2016). https://doi.org/10.1007/s13351-016-5054-x

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  • DOI: https://doi.org/10.1007/s13351-016-5054-x

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