Abstract
Abstract. 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) the Department of Industry Agency of the British Concession in Tianjin covering 1 September 1890–31 December 1931, (2) the Water Conservancy Commission of North China covering 1 January 1932–31 December 1950 and (3) monthly journal sheets for Tianjin surface meteorological observation records covering 1 January 1951–31 December 2019 – have been collected from the Tianjin Meteorological Archive. The completed daily maximum and minimum temperature series for Tianjin from 1 January 1887 (1 September 1890 for minimum) to 31 December 2019 has been constructed and assessed for quality control with an early extension from 1890 back 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 (BE), Climatic Research Unit Time-Series version 4.03 (CRU TS4.03) and Global Historical Climatology Network (GHCN) v3 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 per decade 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 data, with amplitudes of −1.454, 1.196, −0.140 and 0.975 d per decade 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.org/10.1594/PANGAEA.924561 (Si and Li, 2020).
Highlights
Instrumental observation records at meteorological stations are the most widely used firsthand information about weather and climate change and variability. They have the advantages of better representativeness as well as accuracy compared to other data (Leeper et al, 2015; Dienst et al, 2017; Xu et al, 2018)
Si et al.: Tianjin homogenized daily temperature climate datasets, Xu et al (2018) have developed a new dataset of monthly integrated and homogenized global land surface air temperature (C-LSAT). This has been updated to C-LSAT2.0, with the data extended to the period 1850– 2019 (Li et al, 2020a, 2021)
The Global Historical Climatology Network-Daily (GHCN-D) dataset has been developed, to meet the needs of climate analysis and monitoring research, but about two-thirds of the stations contributing to this dataset report precipitation only
Summary
Instrumental observation records at meteorological stations are the most widely used firsthand information about weather and climate change and variability. Observations from temperature sites at principal stations in Canada were changed to be read at 00:00 to 06:00 universal time (Vincent et al, 2002), making it is very difficult to form a global daily data product at the century-long scale This makes it extremely difficult to study global and/or regional extreme events over the past 100 years, especially before 1950. Considering Tianjin Station as an example, this paper aims to construct a new daily instrumental maximum and minimum temperature series on the century scale in China, through integration, quality control, extension and homogenization of the multiple daily observations.
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