Temperature Change of Shanghai and Its Response to Global Warming and Urbanization

Abstract

Shanghai is the biggest metropolis in China, and its local temperature change is affected not only by global warming but also by urbanization. Integrating the Mann-Kendall test, EMD (Empirical Mode Decomposition), Cross Wavelet Analysis and statistical methods, we studied the response of the local temperature change in Shanghai to global warming and urbanization. The results indicate that the local temperature at Shanghai present a significant warming trend under the background of global warming over the past 135 years. The local temperature at Shanghai displays 2-year, 6-year, 15-year, 23-year and 68-year periodic fluctuation, whereas global temperature shows 4-year, 9-year, 15-year, 23-year and 68-year cyclic variation. Although the two cycles are not exactly the same, they show some comparability. Urbanization facilitated the warming process of Shanghai. In the most recent 50 years, temperature difference between urban and suburban Shanghai has increased nearly 0.4 • C. The related indicators of urban development, such as population, built-up area, Gross Domestic Product (GDP), energy consumption and number of vehicles show significantly positive correlation with the temperature difference between urban and suburban area. In addition, the frequency of extreme high temperature has become higher, whereas the frequency of extreme low temperature has become lower over the most recent 55 years.

Peer Review #1 of "Combined effects of water temperature, grazing snails and terrestrial herbivores on leaf decomposition in urban streams (v0.1)"

“…calm, cloudless nights in winter) (Grimmond 2007). In addition, for big cities such as Shanghai, China, the projected increase of mean temperature is estimated to be 2.5 times of that for global mean temperature (Chu et al 2016). As water temperature in most streams would increase 0.6-0.8 o C for every 1 o C increase in air temperature (Morrill Jean et al 2005), an 8 o C increase in water temperature would be realistic for streams in big cities.…”

Spatiotemporal Change of Plum Rains in the Yangtze River Delta and Its Relation with EASM, ENSO, and PDO During the Period of 1960–2012

“…Ensemble empirical mode decomposition (EEMD) is utilized to analyze the nonlinear and periodic characteristics of the plum rainfall. It is based on empirical mode decomposition (EMD), and improvement of the EMD [41,42]. EMD is an effective method for dealing with the nonlinear and nonstationary time series problem, and it also has some advantages, such as self-adaptability, orthogonality, and completeness, etc.…”

“…In order to solve this problem, Wu and Huang [45] proposed a new method, known as the EEMD, to better solve nonlinear problems. It can adaptively decompose the time-frequency, according to the local time variation features, and is completely free from the constraints of the Fourier transform so that it can obtain a high time-frequency resolution [41]. Therefore, we use the EEMD, which is the best decomposition method to extract the changes of various scales in the plum rainfall signal from the plum rainfall time series.…”

“…Simple statistical analysis, such as linear regression analysis and correlation analysis, can only describe linear time series, and cannot reveal the regularity of nonlinear and non-stationary time series. Studies have shown that EEMD is an improvement of EMD [41] and exhibits a stronger local performance than wavelet analysis [51,52]. Therefore, we used the EEMD to extract the variations of various scales in terms of the plum rainfall, the onset of Plum Rains, the termination of Plum Rains, and the daily intensity of the plum rainfall signal from their original time series to reveal the oscillating mode structure characteristics at different time scales and explore evolution characteristics of these different scale oscillations.…”

The Contribution Rate of Driving Factors and Their Interactions to Temperature in the Yangtze River Delta Region

“…The annual precipitation is about 1000 mm, of which the precipitation in summer accounts for two-thirds of the total precipitation [22]. The average temperature is close to 30 • C in July and August, and the maximum temperature recently exceeded 40 • C in Shanghai [23]. The high terrain is in the north and south and low terrain in the middle, which is dominated by plains and hills.…”