scholarly journals Construction of homogenized daily surface air temperature for Tianjin city during 1887–2019

2021 ◽  
Author(s):  
Peng Si ◽  
Qingxiang Li ◽  
Phil Jones
Keyword(s):  
Air Temperature ◽  
Minimum Temperature ◽  
Surface Air Temperature ◽  
Warming Trend ◽  
Daily Maximum ◽  
Daily Data ◽  
Long Term Trends ◽  
Tianjin City ◽  
Monthly Journal ◽  
Annual Scale

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).

scholarly journals Construction of homogenized daily surface air temperature for the city of Tianjin during 1887–2019

2021 ◽  
Vol 13 (5) ◽  
pp. 2211-2226
Author(s):  
Peng Si ◽  
Qingxiang Li ◽  
Phil Jones
Keyword(s):  
Time Series ◽  
Air Temperature ◽  
Minimum Temperature ◽  
Surface Air Temperature ◽  
Warming Trend ◽  
Research Unit ◽  
Climatic Research Unit ◽  
Daily Maximum ◽  
Tianjin City ◽  
Monthly Journal

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).

scholarly journals Construction of a surface air temperature series for Qingdao in China for the period 1899 to 2014

2018 ◽  
Vol 10 (1) ◽  
pp. 643-652
Author(s):  
Yan Li ◽  
Birger Tinz ◽  
Hans von Storch ◽  
Qingyuan Wang ◽  
Qingliang Zhou ◽  
...  
Keyword(s):  
Time Series ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Warming Trend ◽  
Observation Data ◽  
China Meteorological Administration ◽  
Ascii Format ◽  
Long Term Trends ◽  
The City

Abstract. We present a homogenized surface air temperature (SAT) time series at 2 m height for the city of Qingdao in China from 1899 to 2014. This series is derived from three data sources: newly digitized and homogenized observations of the German National Meteorological Service from 1899 to 1913, homogenized observation data of the China Meteorological Administration (CMA) from 1961 to 2014 and a gridded dataset of Willmott and Matsuura (2012) in Delaware to fill the gap from 1914 to 1960. Based on this new series, long-term trends are described. The SAT in Qingdao has a significant warming trend of 0.11 ± 0.03 ∘C decade−1 during 1899–2014. The coldest period occurred during 1909–1918 and the warmest period occurred during 1999–2008. For the seasonal mean SAT, the most significant warming can be found in spring, followed by winter. The homogenized time series of Qingdao is provided and archived by the Deutscher Wetterdienst (DWD) web page under overseas stations of the Deutsche Seewarte (http://www.dwd.de/EN/ourservices/overseas_stations/ueberseedoku/doi_qingdao.html) in ASCII format. Users can also freely obtain a short description of the data at https://doi.org/https://dx.doi.org/10.5676/DWD/Qing_v1. And the data can be downloaded at http://dwd.de/EN/ourservices/overseas_stations/ueberseedoku/data_qingdao.txt.

Diurnal Cycle of Surface Air Temperature within China in Current Reanalyses: Evaluation and Diagnostics

2018 ◽  
Vol 31 (11) ◽  
pp. 4585-4603 ◽  
Author(s):  
Jizeng Du ◽  
Kaicun Wang ◽  
Jiankai Wang ◽  
Shaojing Jiang ◽  
Chunlüe Zhou
Keyword(s):  
Air Temperature ◽  
Diurnal Cycle ◽  
Surface Air Temperature ◽  
Warming Trend ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Positive Trend ◽  
Southeastern China

Abstract Diurnal cycle of surface air temperature T is an important metric indicating the feedback of land–atmospheric interaction to global warming, whereas the ability of current reanalyses to reproduce its variation had not been assessed adequately. Here, we evaluate the daily maximum temperature Tmax, daily minimum temperature Tmin, and diurnal temperature range (DTR) in five reanalyses based on observations collected at 2253 weather stations over China. Our results show that the reanalyses reproduce Tmin very well; however, except for Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2), they substantially underestimate Tmax and DTR by 1.21°–6.84°C over China during the period of 1980–2014. MERRA-2 overestimates Tmax and DTR by 0.35° and 0.81°C, which are closest with observation. The reanalyses are skillful in reproducing the interannual variability of Tmax and Tmin but relatively poor for DTR. All reanalyses underestimate the warming trend of Tmin by 0.13°–0.17°C (10 yr)−1 throughout China during 1980–2014, and underestimate the warming trend of Tmax by 0.24°–0.40°C (10 yr)−1 in northwestern China while overestimating this quantity by 0.18°–0.33°C (10 yr)−1 in southeastern China. These trend biases in Tmax and Tmin introduce a positive trend bias in DTR of 0.01°–0.26°C (10 yr)−1 within China, especially in the north China plain and southeastern China. In the five reanalyses, owing to the sensitivity discrepancies and trend biases, the surface solar radiation Rs and precipitation frequency (PF) are notable deviation sources of the diurnal cycle of air temperature, which explain 31.0%–38.7% (31.9%–37.8%) and 9.8%–22.2% (7.4%–15.3%) of the trend bias in Tmax (DTR) over China, respectively.

scholarly journals Construction of surface air temperature series of Qingdao in China for the period 1899 to 2014

2017 ◽  
Author(s):  
Yan Li ◽  
Birger Tinz ◽  
Hans von Storch ◽  
Qingyuan Wang ◽  
Qingliang Zhou
Keyword(s):  
Air Temperature ◽  
Surface Air Temperature ◽  
Warming Trend ◽  
Observation Data ◽  
Web Page ◽  
China Meteorological Administration ◽  
Data Set ◽  
Long Term Trends ◽  
The City

Abstract. We present a homogenized time series surface air temperature at 2 meters (SAT) for the city of Qingdao in China from 1899 to 2014. This series is derived from three data sources: newly digitized and homogenized observations of German National Meteorological Service from 1899 to 1913; National observation data of China Meteorological Administration (CMA) from 1961–2014 and a gridded data set of Willmott and Matsuura in Delaware to fill the gap from 1914 to 1959. Based on this new series, long-term trends are described. The SAT in Qingdao has a significant warming trend of 0.11 °C (10 yr)-1 during 1899–2014. The coldest period occurred in 1909–1918 and the warmest period occurred in 1999–2008. For the seasonal mean SAT, the most significant warming can be found in spring, followed by winter. Access to the data is provided in excel and archived by Deutscher Wetterdienst (DWD) web page under overseas stations of the Deutsche Seewarte (http://www.dwd.de/EN/ourservices/overseas_stations/ueberseedoku/doi_qingdao.html) or be freely available at https://doi.org/10.5676/DWD/Qing_v1.

scholarly journals An analysis of present and future seasonal Northern Hemisphere land snow cover simulated by CMIP5 coupled climate models

2012 ◽  
Vol 6 (4) ◽  
pp. 3317-3348 ◽  
Author(s):  
C. Brutel-Vuilmet ◽  
M. Ménégoz ◽  
G. Krinner
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Air Temperature ◽  
Linear Correlation ◽  
Large Scale ◽  
Climate Models ◽  
Surface Air Temperature ◽  
Warming Trend ◽  
Snow Cover Extent ◽  
Global Mean

Abstract. The 20th century seasonal Northern Hemisphere land snow cover as simulated by available CMIP5 model output is compared to observations. On average, the models reproduce the observed snow cover extent very well, but the significant trend towards a~reduced spring snow cover extent over the 1979–2005 is underestimated. We show that this is linked to the simulated Northern Hemisphere extratropical land warming trend over the same period, which is underestimated, although the models, on average, correctly capture the observed global warming trend. There is a good linear correlation between hemispheric seasonal spring snow cover extent and boreal large-scale annual mean surface air temperature in the models, supported by available observations. This relationship also persists in the future and is independent of the particular anthropogenic climate forcing scenario. Similarly, the simulated linear correlation between the hemispheric seasonal spring snow cover extent and global mean annual mean surface air temperature is stable in time. However, the sensitivity of the Northern Hemisphere spring snow cover to global mean surface air temperature changes is underestimated at present because of the underestimate of the boreal land temperature change amplification.

Trend of Surface Air Temperature in Eastern China and Associated Large-Scale Climate Variability over the Last 100 Years

2014 ◽  
Vol 27 (12) ◽  
pp. 4693-4703 ◽  
Author(s):  
Ping Zhao ◽  
Phil Jones ◽  
Lijuan Cao ◽  
Zhongwei Yan ◽  
Shuyao Zha ◽  
...  
Keyword(s):  
Air Temperature ◽  
Large Scale ◽  
Eastern China ◽  
Surface Air Temperature ◽  
Tropical Indian Ocean ◽  
Population Data ◽  
Warming Trend ◽  
Climate Indices ◽  
The Past ◽  
Linear Trends

Abstract Using the reconstructed continuous and homogenized surface air temperature (SAT) series for 16 cities across eastern China (where the greatest industrial developments in China have taken place) back to the nineteenth century, the authors examine linear trends of SAT. The regional-mean SAT over eastern China shows a warming trend of 1.52°C (100 yr)−1 during 1909–2010. It mainly occurred in the past 4 decades and this agrees well with the variability in another SAT series developed from a much denser station network (over 400 sites) across this part of China since 1951. This study collects population data for 245 sites (from these 400+ locations) and split these into five equally sized groups based on population size. Comparison of these five groups across different durations from 30 to 60 yr in length indicates that differences in population only account for between 9% and 24% of the warming since 1951. To show that a larger urbanization impact is very unlikely, the study additionally determines how much can be explained by some large-scale climate indices. Anomalies of large-scale climate indices such as the tropical Indian Ocean SST and the Siberian atmospheric circulation systems account for at least 80% of the total warming trends.

Long-term trends of surface air temperature in india

1985 ◽  
Vol 5 (5) ◽  
pp. 521-528 ◽  
Author(s):  
L. S. Hingane ◽  
K. Rupa Kumar ◽  
Bh. V. Ramana Murty
Keyword(s):  
Air Temperature ◽  
Surface Air Temperature ◽  
Long Term Trends

scholarly journals Global air temperature variability independent of sea-surface temperature influences

2012 ◽  
Vol 37 (1) ◽  
pp. 29-35
Author(s):  
Andrew C. Comrie ◽  
Gregory J. McCabe
Keyword(s):  
Time Series ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Air Temperature ◽  
Recent Literature ◽  
Surface Air Temperature ◽  
Warming Trend ◽  
Sea Surface ◽  
Sst Variability ◽  
Global Surface

Mean global surface air temperature (SAT) and sea surface temperature (SST) display substantial variability on timescales ranging from annual to multi-decadal. We review the key recent literature on connections between global SAT and SST variability. Although individual ocean influences on SAT have been recognized, the combined contributions of worldwide SST variability on the global SAT signal have not been clearly identified in observed data. We analyze these relations using principal components of detrended SST, and find that removing the underlying combined annual, decadal, and multi-decadal SST variability from the SAT time series reveals a nearly monotonic global warming trend in SAT since about 1900.

scholarly journals Role of radiatively forced temperature changes in enhanced semi-arid warming over East Asia

2015 ◽  
Vol 15 (16) ◽  
pp. 22975-23004 ◽  
Author(s):  
X. Guan ◽  
J. Huang ◽  
R. Guo ◽  
P. Lin ◽  
Y. Zhang
Keyword(s):  
East Asia ◽  
Human Activities ◽  
Radiative Forcing ◽  
Decadal Variability ◽  
Regional Scale ◽  
Surface Air Temperature ◽  
Warming Trend ◽  
Daily Maximum ◽  
Surface Temperature Change ◽  
Semi Arid

Abstract. As the climate change occurred over East Asia since 1950s, intense interest and debate have arisen concerning the contribution of human activities to the warming observed in previous decades. In this study, we investigate surface temperature change using a recently developed methodology that can successfully identify and separate the dynamically induced temperature (DIT) and radiatively forced temperature (RFT) changes in raw surface air temperature (SAT) data. For regional averages, DIT and RFT make 43.7 and 56.3 % contributions to the SAT over East Asia, respectively. The DIT changes dominate the SAT decadal variability and are mainly determined by internal climate variability, such as the North Atlantic Oscillation (NAO), Pacific Decadal Oscillation (PDO), and Atlantic Multi-decadal Oscillation (AMO). The radiatively forced SAT changes made major contribution to the global-scale warming trend and the regional-scale enhanced semi-arid warming (ESAW). Such enhanced warming is also found in radiatively forced daily maximum and minimum SAT. The long-term global-mean SAT warming trend is mainly related to radiative forcing produced by global well-mixed greenhouse gases. The regional anthropogenic radiative forcing, however, caused the enhanced warming in the semi-arid region, which may be closely associated with local human activities. Finally, the relationship between global warming hiatus and regional enhanced warming is discussed.

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