the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
22 Jan 2021
22 Jan 2021
Construction of homogenized daily surface air temperature for Tianjin city during 1887–2019
- 1Tianjin Meteorological Information Center, Tianjin Meteorological Bureau, Tianjin, China
- 2School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou, China
- 3Climatic Research Unit, School of Environmental Sciences, University of East Anglia, Norwich, UK
- 4Key Laboratory of Tropical Atmosphere-Ocean System (Sun Yat-sen University), Ministry of Education, and Southern Laboratory of Ocean Science and Engineering (Guangdong Zhuhai), Zhuhai, China
- 1Tianjin Meteorological Information Center, Tianjin Meteorological Bureau, Tianjin, China
- 2School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou, China
- 3Climatic Research Unit, School of Environmental Sciences, University of East Anglia, Norwich, UK
- 4Key Laboratory of Tropical Atmosphere-Ocean System (Sun Yat-sen University), Ministry of Education, and Southern Laboratory of Ocean Science and Engineering (Guangdong Zhuhai), Zhuhai, China
Abstract. The century-long continuous daily observations from some stations are important for the study of long-term trends and extreme climate events in the past. In this paper, three daily data sources: (1) Department of Industry Agency of British Concession in Tianjin covering Sep 1 1890–Dec 31 1931 (2) Water Conservancy Commission of North China covering Jan 1 1932–Dec 31 1950 and (3) monthly journal sheets for Tianjin surface meteorological observation records covering Jan 1 1951–Dec 31 2019 have been collected from the Tianjin Meteorological Archive. The completed daily maximum and minimum temperature series for Tianjin from Jan 1 1887 (Sep 1 1890 for minimum) to Dec 31 2019 has been constructed and assessed for quality control and an early extension from 1890 to 1887. Several significant breakpoints are detected by the Penalized Maximal T-test (PMT) for the daily maximum and minimum time series using multiple reference series around Tianjin from monthly Berkeley Earth, CRUTS4.03 and GHCNV3 data. Using neighboring daily series the record has been homogenized with Quantile Matching (QM) adjustments. Based on the homogenized dataset, the warming trend in annual mean temperature in Tianjin averaged from the newly constructed daily maximum and minimum temperature is evaluated as 0.154 ± 0.013 °C decade-1 during the last 130 years. Trends of temperature extremes in Tianjin are all significant at the 5 % level, and have much more coincident change than those from the raw, with amplitudes of −1.454 d decade−1, 1.196 d decade−1, −0.140 d decade−1 and 0.975 d decade−1 for cold nights (TN10p), warm nights (TN90p), cold days (TX10p) and warm days (TX90p) at the annual scale. The adjusted daily maximum, minimum and mean surface air temperature dataset for Tianjin city presented here is publicly available at https://doi.pangaea.de/10.1594/PANGAEA.924561 (Si and Li, 2020).
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Peng Si et al.
Status: open (until 19 Mar 2021)
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RC1: 'Comment on essd-2020-343', Anonymous Referee #1, 31 Jan 2021
reply
The century-long homogenized temperature data is typically lacking and further hampers the robust detection of climate change. Therefore, it is imperative to construct this dataset, laying foundation for better understanding of climate change and variability. To this end, the manuscript by Si et al. confronted this challenge by attempting to construct more than 100-y homogenized temperature dataset at Tianjin, China. This work made significant contribution to the community of climate and climate change. Overall, the homogeneity procedures and test methods are technically robust and scientifically sound. The trends of Tmax, Tmin and Tmean are basically consistent with the well-established trend in midlatitudes, suggesting the findings obtained by the authors are meaningful. Nevertheless, there are still room for improving the quality of this manuscript by adequately addressing following comments:
Major comments:
- Figure 6: I noticed that the significant breakpoint occurred in 1955 for Tmax but in 1992 for Tmin. Why did these points differ greatly? is this due to non-climate factor such as station relocation? If so, the influence is supposed to be the same. Explanation or discussion for this interesting phenomenon will benefit the improved understanding of the newly-constructed homogenized dataset.
- L393-396: it seems a parodox to argue that “annual trend change in mean temperature based on newly constructed series in Tianjin is similar to that for China (Li et al., 2020c)..”. On the contrary, the trends derived from the other two dataset (Berkeley Earth and CRUTS4.03) are more similar the national warminig rate as shown in Table 5. The authors are suggested to clarify this point.
Minor comments:
- L55: “representativeness” -> “better representativeness”
- L286: “surface observation station” -> “surface weather station”
- L291: “quantile matching” has been widely used in recent research associated with precipitation (Lv et al. 2020, doi:1016/j.atmosres.2019.104671), and PM2.5 (Bai et al. 2020, doi:10.5194/essd-12-3067-2020), which is suggested to be mentioned.
- L384: “indicates”-> “shows”
- L392: “internationally authoritative data calculations”? are there any references to support this argument? Further, this sentence is not logically connected with the following sentence “so they are more consistent”. For instance, what does the “they” refer to? Therefore, it is suggested to be rewritten.
- L404: “indiates”-> “shows” or “illustrates”
- L409: grammar errors in ”all passed”
- L410: “trends of TN10p and TX10p in spring are the largest. They are” -> “the negative trends of TN10p and TX10p in spring are the largest, reaching up to be”
- L422: it seems a little strong tone to argue “These same procedures could and should be use”, which can be softened, since there are large room to improve the procedures for data homogeity. More importantly, it remains unknown whether the procedure developed here can be genalized or applied to other regions, which merits further investigation.
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CC1: 'Reply on RC1', Peng Si, 03 Feb 2021
reply
Thank you very much for the valuable time devoted to this paper by the referees and responsible editor of ESSD, as well as for the opportunity to reply to these comments. A point-by-point response to Anonymous Referee #1' comments is as followed.
Major comments:
- Figure 6: I noticed that the significant breakpoint occurred in 1955 for Tmax but in 1992 for Tmin. Why did these points differ greatly? Is this due to non-climate factor such as station relocation? If so, the influence is supposed to be the same. Explanation or discussion for this interesting phenomenon will benefit the improved understanding of the newly-constructed homogenized dataset.
Reply：Thank you for your valuable comments.
It may be related with the physical characteristics of Tmax and Tmin themselves. The Tmin generally occurs near sunrise when calm and stable atmospheric boundary layer conditions are prevalent. Under these conditions, near surface temperature fields are strongly coupled to the local surface characteristics. On the other hand, during daylight hours (like Tmax), the boundary layer is commonly well mixed, and microclimate differences between nearby sites may be less evident. So the difference of the discontinuities between Tmax and Tmin temperature is very normal (Tmin always has more discontinuities in total, see the details in Li and Dong, 2009).
As to the discontinuities, the breakpoints in Jan 1 1955 and Jan 1 1992 are both caused by station relocation, which have an effect on homogeneity of different temperature elements. In Jan 1 1955 Tianjin meteorological station relocated from No. 22 Ziyou Road to Zunyi Road (Table 1), where is 5km north of the original site. However, the relocation of Tianjin meteorological station in 1992 was from Qixiangtai Road, Hexi District to Xidawa, Xiqing District. In addition, there are another two discontinuities in 1897 and in 1907 for Tmin, and both of these two are not for Tmax.
We have added this paragraph on L330—L333 in revised paper * - Feb 2, 2021.pdf.
Ref：
Li, Q. X., and Dong, W. J.: Detection and adjustment of undocumented discontinuities in Chinese temperature series using a composite approach, Adv., Atmos., Sci.，26(1): 143-153, https://doi.org/ 10.1007/s00376-009-0143-8, 2009.
2. L393-396: it seems a parodox to argue that “annual trend change in mean temperature based on newly constructed series in Tianjin is similar to that for China (Li et al., 2020c)”. On the contrary, the trends derived from the other two dataset (Berkeley Earth and CRUTS4.03) are more similar the national warminig rate as shown in Table 5. The authors are suggested to clarify this point.
Reply：Thank you for your valuable comments.
The annual trend in Tmean from newly constructed series in Tianjin is a little larger than that over the whole China. We think this conforms that the result in this manuscript is reasonable. Because the trend in northern region is more prominent than that of other regions in mainland China (Li et al., 2004; Zhai et al., 2004).
Therefore, according to the comments, we have rewritten the sentence into ‘Moreover, annual trend change in mean temperature based on newly constructed series in Tianjin is also a little larger than that over the whole China (Li et al., 2020c), which are 0.130±0.009°C decade-1, 0.114±0.009°C decade-1 and 0.121±0.009°C decade-1 respectively from CRUTEM4, GHCNV3 and C-LSAT (during 1900 - 2017).’ on L398—L401 in revised paper * - Feb 2, 2021.pdf.
And we also added the sentence ‘It conforms that the result is reasonable since the air temperature trends in northern China is more prominent than those in other regions in mainland China (Li et al., 2004; Zhai et al., 2004).’ on L401—L403, and added two references (Li et al., 2004; Zhai et al., 2004) in References section on L527—L529, L618—L619 in revised paper * - Feb 2, 2021.pdf.
Ref：
Li., Q. X., Zhang., H. Z., Liu., X. N., and Huang., J. Y.: Urban heat island effect on annual mean temperature during the last 50 years in China, Theor. Appl. Climatol., 79, 165-174, https://doi.org/10.1007/s00704-004-0065-4, 2004.
Zhai., P. M., Chao., Q. C., and Zou., X. K.: Progress in China’s climate change study in the 20th century, J. Geograph. Sci., 14(1): 3-11, https://doi.org/10.1007/BF02841101, 2004.
Minor comments:
- L55: “representativeness” -> “better representativeness”
Done.
2. L286: “surface observation station” -> “surface weather station”
Done.
- L291: “quantile matching” has been widely used in recent research associated with precipitation (Lv et al. 2020, doi:1016/j.atmosres.2019.104671), and PM2.5 (Bai et al. 2020, doi:10.5194/essd-12-3067-2020), which is suggested to be mentioned.
Done.
4. L384: “indicates”-> “shows”
Done.
5. L392: “internationally authoritative data calculations”? are there any references to support this argument? Further, this sentence is not logically connected with the following sentence “so they are more consistent”. For instance, what does the “they” refer to? Therefore, it is suggested to be rewritten.
According to the Major Comments 2, we have deleted this sentence ‘The average temperature trend changes from the newly constructed series are much closer to internationally authoritative data calculations, so they are more consistent.’ on L396—L398, and rewritten the second half of the paragraph into ‘Moreover, annual trend change in mean temperature based on newly constructed series in Tianjin is also a little larger than that over the whole China (Li et al., 2020c), which are 0.130±0.009°C decade-1, 0.114±0.009°C decade-1 and 0.121±0.009°C decade-1 respectively from CRUTEM4, GHCNV3 and C-LSAT (during 1900 - 2017). It conforms that the result is reasonable since the air temperature trends in northern China is more prominent than those in other regions in mainland China (Li et al., 2004; Zhai et al., 2004).’ on L398—L403 in revised paper * - Feb 2, 2021.pdf.
- L404: “indiates”-> “shows” or “illustrates”
Done.
7. L409: grammar errors in ”all passed”
Done.
8. L410: “trends of TN10p and TX10p in spring are the largest. They are” -> “the negative trends of TN10p and TX10p in spring are the largest, reaching up to be”
Done.
9. L422: it seems a little strong tone to argue “These same procedures could and should be use”, which can be softened, since there are large room to improve the procedures for data homogeity. More importantly, it remains unknown whether the procedure developed here can be genalized or applied to other regions, which merits further investigation.
The word ‘procedure’ refers to the steps of constructing a long and complete climate time series, rather than the techniques and methods. To avoid the confusion, we have modified this sentence into ‘These similar procedures could and should be used for other sufficiently long and complete series across the world.’ on L429 in revised paper * - Feb 2, 2021.pdf.
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RC2: 'Comment on essd-2020-343', Anonymous Referee #2, 07 Mar 2021
reply
The authors present a methodology and analysis for the homogenization of in situ century-long daily observations. The paper addresses an interesting and original problem, since very few studies have carried out the homogenization of daily extreme temperature in China. However, some detailed analyses are needed to further convince audience.
Specific comments:
Firstly, if the authors are keen to use SAT for the detection of the changepoint: 1. Please provide the information about SAT stations (location, surroundings, rural, towns or city, as well as altitude); 2. Provide a correlation analysis and other measure to convince the use these data; 3. Justify why 300km is reasonable. 4. Please explore why use monthly and daily reference series respectively for the extreme temperature series? The extreme temperature series is monthly or daily series?
Minor comments
L248 For Table 2, why there are four data sources shown here, the Table 1 is puzzle?
L284 “Berkeley-daily data” should be “Berkeley Earth-monthly data”
Peng Si et al.
Data sets
Tianjin homogenized daily surface air temperature over century-long scale Peng Si and Qingxiang Li https://doi.pangaea.de/10.1594/PANGAEA.924561
Peng Si et al.
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