The combined influence of background climate and urbanization on the regional warming in Southeast China

Si, Peng; Ren, Yu; Liang, Dongpo; Lin, Bingwen

doi:10.1007/s11442-012-0924-3

Cited by 13 publications

(7 citation statements)

References 17 publications

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“…On the other hand, the unusually stronger warming in T MIN relative to T MAX over the North China Plain could have partially resulted from the unusually large urban heat effect on T MIN relative to T MAX . The urban heat effect is primarily a nocturnal phenomenon in certain places around the world [ 39 – 40 ]. The North China Plain may be one such place.…”

Section: Discussionmentioning

confidence: 99%

Warming Amplification of Minimum and Maximum Temperatures over High-Elevation Regions across the Globe

Fan

Wang

et al. 2015

PLoS ONE

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An analysis of the annual mean temperature (TMEAN) (1961–2010) has revealed that warming amplification (altitudinal amplification and regional amplification) is a common feature of major high-elevation regions across the globe against the background of global warming since the mid-20th century. In this study, the authors further examine whether this holds for annual mean minimum temperature (TMIN) and annual mean maximum temperature (TMAX) (1961–2010) on a global scale. The extraction method of warming component of altitude, and the paired region comparison method were used in this study. Results show that a significant altitudinal amplification trend in TMIN (TMAX) is detected in all (four) of the six high-elevation regions tested, and the average magnitude of altitudinal amplification trend for TMIN (TMAX) [0.306±0.086 °C km-1(0.154±0.213 °C km-1)] is substantially larger (smaller) than TMEAN (0.230±0.073 °C km-1) during the period 1961–2010. For the five paired high- and low-elevation regions available, regional amplification is detected in the four high-elevation regions for TMIN and TMAX (respectively or as a whole). Qualitatively, highly (largely) consistent results are observed for TMIN (TMAX) compared with those for TMEAN.

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Section: Discussionmentioning

confidence: 99%

Warming Amplification of Minimum and Maximum Temperatures over High-Elevation Regions across the Globe

Fan

Wang

et al. 2015

PLoS ONE

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“…1). We used the classification for urban-rural stations from Si et al (2014) for North China and a regional average method for urban or rural areas from Si et al (2012). Shown in Table 5, the regional trends in annual and seasonal mean wind speed for urban and rural areas all displayed a significant reduction based on the data before and after adjustment at the 95% significant level, consistent with the entire Tianjin region (Fig.…”

Section: Trend Amplitudes Before and After Adjustmentmentioning

confidence: 87%

“…Climate change monitoring and simulation rely on reliable and extensive historical meteorological observations (Hanesiak John and Wang 2005;Jones et al 2008;Li et al 2010;Si et al 2012Si et al , 2014. However, most long-time climate records do not adequately represent climate change characteristics because of changes in instrumentation, observation methods, station relocation, and other non-climate factors; these changes result in a distortion in climate change monitoring (Aguilar et al 2003;Jiang et al 2010).…”

Section: Introductionmentioning

confidence: 99%

Homogenization of Tianjin monthly near-surface wind speed using RHtestsV4 for 1951–2014

Luo

Liang

2017

Theor Appl Climatol

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Historical Chinese surface meteorological records provided by the special fund for basic meteorological data from the National Meteorological Information Center (NMIC) were processed to produce accurate wind speed data. Monthly 2-min near-surface wind speeds from 13 observation stations in Tianjin covering 1951-2014 were homogenized using RHtestV4 combined with their metadata. Results indicate that 10 stations had significant breakpoints-77% of the Tianjin stations-suggesting that inhomogeneity was common in the Tianjin wind speed series. Instrument change accounted for most changes, based on the metadata, including changes in type and height, especially for the instrument type. Average positive quantile matching (QM) adjustments were more than negative adjustments at 10 stations; positive biases with a probability density of 0.2 or more were mainly concentrates in the range 0.2 m s −1 to 1.2 m s −1 , while the corresponding negative biases were mainly in the range −0.1 to −1.2 m s −1 . Here, changes in variances and trends in the monthly mean surface wind speed series at 10 stations before and after adjustment were compared. Climate characteristics of wind speed in Tianjin were more reasonably reflected by the adjusted data; inhomogeneity in wind speed series was largely corrected. Moreover, error analysis reveals that there was a high consistency between the two datasets here and that from the NMIC, with the latter as the reference. The adjusted monthly near-surface wind speed series shows a certain reliability for the period 1951-2014 in Tianjin.

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“…It can effectively avoid a distortion of the smoothed curve by outliers in the process of robust fitting, so that can well describe the subtle changes in the relationship between each variable. This method also has been used in previous researches of Si et al (2012Si et al ( , 2014.…”

Section: Trend and Variability Analysismentioning

confidence: 99%

The observed features and some possible reasons of annual temperature extremes over Beijing‐Tianjin‐Hebei region for a century long‐term based on newly constructed daily observations

Wang²,

et al. 2023

Intl Journal of Climatology

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The observation facts of trend and variability are estimated for a century‐long timescale, as well as some possible attributions affecting temperature extremes over Beijing‐Tianjin‐Hebei region. In this paper, the new constructed daily maximum and minimum temperature series during the last 100 years in situ stations of Beijing, Tianjin and Baoding city are used, and two 30‐year baseline climatology of 1961–1990 and 1980–2010 are both used in calculating extreme temperature events. The results indicate that there are long‐lasting, frequent and serious extreme warming over Beijing‐Tianjin‐Hebei region, especially for extreme low temperature, with larger declining trends (at 5% significance) from 1981 to 2010 baseline than those from 1961 to 1990 baseline. And from a statistical perspective, El Niño decay years and surface sea temperature (SST) anomalies at some typical ocean regions of the Arabian Sea and the Bengal Bay on the northern Indian Ocean, the Western Pacific and the Mid Atlantic, Southern Indian Ocean and around 45°–85°E, 68°–82°N on the southwest Arctic Ocean can be used as the warning signals denoting extreme warming over Beijing‐Tianjin‐Hebei region. Additionally, urbanization has a significant (at 5% significance) effect on extreme warming over Beijing‐Tianjin‐Hebei region since 1979, with 24.3% warming contribution for annual minimum temperature.

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The combined influence of background climate and urbanization on the regional warming in Southeast China

Cited by 13 publications

References 17 publications

Warming Amplification of Minimum and Maximum Temperatures over High-Elevation Regions across the Globe

Warming Amplification of Minimum and Maximum Temperatures over High-Elevation Regions across the Globe

Homogenization of Tianjin monthly near-surface wind speed using RHtestsV4 for 1951–2014

The observed features and some possible reasons of annual temperature extremes over Beijing‐Tianjin‐Hebei region for a century long‐term based on newly constructed daily observations

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