The Climate Change in Qingdao during 1899-2015 and Its Response to Global Warming

In this work, the average mean (TAvg), maximum (TMax), and minimum temperature (TMin) and precipitation records of Qingdao from 1899 to 2015 are analyzed. The TAvg, TMax and TMin all go through several warm and cold periods, and exhibit statistically significant linear warming trend especially in spring and winter, as a response to global warming. Besides, the TAvg reflects more the TMin evolution for the most part, either as a trend or an abrupt change, and the contribution of TMin to Tavg is far greater than that of TMax. The abrupt change year of climate is also around 1979 in Qingdao, and it is 2 or 3-years later than the TAvg for the TMin, while there is no abrupt change of TMax. In terms of the precipitation in Qingdao, it varies periodically and dramatically with a slow increasing trend. As for the seasonal precipitation, the precipitation varies widely year by year for the four seasons but with no obvious variation trend except for spring.


Introduction
The global climate has changed dramatically since the industrial revolution.
More and more people start to concern the climate change as the technology advances and the dramatic development of communicating technology.The climate refers to a change in the state of the climate that can be identified (e.g., using statistical tests) by changes in the mean and/or the variability of its properties, and that persists for an extended period, typically decades or longer [1].
Though the internal processes and/or external forcing can induce the climate change, the increase of anthropogenic greenhouse gases such as CO 2 is considered primarily to cause the climate change especially for temperature in recent decades [1].The IPCC Fourth Assessment Report (IPCC) [1] published in 2007 presented new estimates of global warming trends for the past 100 years since 1906, the global mean temperature increased by about 0.74˚C per 100-yr.The temperature series and new assessment results have not only confirmed the ascending trend of global mean temperature, but also enhanced the reliability of estimates on warming.
Until recently, studies on the climatic change were focused for the most part on the analysis of temperature data especially for the annual mean temperature.
Examples of this are the works of Balling et al. [2], Tang et al. [3], and so on.Besides, some climatologist [4] had analyzed the minimum and maximum temperatures in some parts of the world, finding asymmetric trend.Under the global warming, the change of extreme low temperature varies more dramatically [5] [6], and is more sensitive to the global climate change than the extreme high temperature.Trenberth et al. [7] pointed out that the global warming induces the increase of the surface evaporation rate and the water-holding capacity of the atmosphere, and causes more intense rainfall or snowfall events.Thus, the climate change impacts a lot in fields such as atmospheric circulation, temperature, precipitation, agriculture, water resources, and so on [8] [9] [10] [11] [12].Climate change has impacts on abnormal first and last frost date [13].The results from Zhang et al. [14] showed that the comprehensive agricultural loss rate increased by an average of 0.5% per decade in the past 50 years, and the risk increased significantly under the climate change.
In the last decades, an increasing number of Chinese studies on climate and associated climate change were accomplished [15], but most of them dealt with effects occurring in the past 50 years [16].There are few studies on temperature or precipitation change in the past 100 years due to limited data availability [12].
In order to obtain meaningful results, it requires a longer period of the observations to study the characteristics and laws for climate change.However, only few stations have the temperature and precipitation records longer than 100 years in China.
Qingdao station occupies significant position in the Chinese meteorological history, which is one of the first three cities (Hongkong, Shanghai, and Qingdao) to set up the weather station.Though the Qingdao Observatory has went through several vicissitudes since it was built in 1898 [17], the observation has been suspended only twice from June 1914 to March 1915, and from September 1937 to January 1938.We have constructed the time series of temperature and precipitation from 1898 to 2015 so far.In order to obtain the continuous time series of average temperature and precipitation, we replenished the missed data using their climate mean (30 years), which will not change their climate trend.
Based on the long-term data, we investigated the possible trends and abrupt changes of the maximum, minimum, and mean temperatures and precipitation, F. Y. Guo

Data and Method
The Qingdao meteorological observatory is one of the National Basic Weather Station, which located at Guanxiang hill from 1899-1960 and then moved to Fulong hill in 1961.The two stations are only 700 m apart and their height difference is less than 1m, so the observation environment is basically the same.Almost all the regular meteorological elements (for example, temperature including daily maximum and minimum temperature, precipitation, and wind) have being observed since January 1899.In this paper, the seasonal mean and annual mean temperature (TAvg) or precipitation is the arithmetic mean of the temperature for the four seasons or the whole year.The annual maximum/minimum temperature (TMax/TMin) is the maximum/minimum temperature in every year.Based on the annually/monthly mean temperature, maximum/minimum temperature and precipitation, the characters of short-term and long-term climate trend and oscillation, and their responses to global warming were analyzed using the power spectrum, linear trend analysis, Mann-Kendall (MK) method, five-point sliding average method, and so on.Mann-Kendall (MK) method is a trend detecting method proposed by Mann Goossens [18], this method gained ability to detect the abrupt change.In the MK method, if the value of UF or UB is greater than 0, the series has an increasing trend; if the value is smaller than 0, the series has a decreasing trend.When these parameters exceed critical values, a significant increase or decrease is indicated, and the amount by which they exceed the critical value indicates the time over which the abrupt change occurred.
If the UF and UB curves intersect and the point of intersection is within the critical line, the time at which they intersect is the time when an abrupt change began [19].More information about the MK method can be gained from the reasearch by Chen [20].
The meteorological data from January 1899 to December 2015 was adopted in this study.It should be noted that the time series of maximum and minimum temperature broke from 1914 to 1915, and from 1937 to 1938.Nevertheless, these discontinuous do not affect the analysis for the features of the climate change in this paper.rate in this study is a little bit higher than the result of 0.90˚C per 100a from Chen et al. [21] and 0.94 per 100a from Pang et al. [22]; this could be because of the longer data coverage in our study.In order to discuss various short-term climate changes, the high frequency signals were removed by five-point sliding average method.The TAvg had a decreasing trend from the early twentieth century, dropped its bottom in 1910s, and then rose in volatility (red line in Figure 1(a)).From the results of TAvg MK (Figure 2(a)), the UF was negative from 1899, but turned to be positive around 1937, which indicated the coming of warm period.However, this warm stage only lasts for less than 10 years, and then turns to cold stage in 1944.These results are consistent with the result from Chen et al. [21].The temperature in Qingdao had an evident interdecadal variation with two warm and cold stages during the year 1944 to 1979 (Figure 1(a)).

The Features of Climate Trends in
The MK shows a jump point in 1979 (Figure 2   3-years later than the TAvg, and that the warming rate for the TMin is 4 times more than the TMax during the past 117 years.In addition, the correlation coefficient between the TAvg and TMin is up to 0.67, while it is only 0.33 between TAvg and TMin.It seems that the TAvg reflect more the TMin evolution for the most part, either as a trend or an abrupt change.We can thus speculate that the contribution of TMin to Tavg is far greater than that of TMax. From the trend analysis for the TAvg, TMax, and TMin, it is found that they all go through several warm and cold periods, but they all increase with different warming rates as a response to global warming.Based on the above results, we perform trend analyses in different periods (shown in Figure 3).

Precipitation
For the past 117 years from 1899 to 2015, the annual precipitation in Qingdao

The Trends of Temperature and Precipitation for Different Seasons in Qingdao
Figure 7 shows the yearly seasonal mean temperatures and their linear trends in spring, summer, autumn, and winter from 1899 to 2015.The seasonal temperatures for the four seasons are all on the rise with different increasing rates of 1.44˚C per 100a, 0.67˚C per 100a, 0.88˚C per 100a, and 1.32˚C per 100a.Compared with the increasing rate of 1.11˚C per 100a for the TAvg, the warming rates in summer and autumn especially the former are far below that of the TAvg, the steeper rise of temperature in spring and winter was the mainly distributor to the significant warming of TAvg.That is to say that the significant warming temperature in spring and winter in Qingdao responses the most to global warming.As for the seasonal precipitation (Figure 8), the precipitation varies widely year by year for the four seasons but with no obvious variation trend except for spring.The precipitation increases 28.1 mm, 12.2 mm, and 14.4 mm respectively in spring, summer, and autumn, but decreases about 4.6 mm in winter, and their variation rates are 24.1 mm/100a, 10.4 mm/100a, 12.3 mm/100a, and −3.9 mm/100a.

Conclusions
The meteorological data in Qingdao from January 1899 to December 2015 were adopted, and their climate change and their response to global warming were investigated in this study.Journal of Geoscience and Environment Protection

Figure 1 .
Figure 1.Time series of TAvg (a), the TMax (b) and TMin (c) (green line) and their climate mean (black line), linear trend (blue line) and 5-year running mean (red line) during 1899-2015.
(a)), which indicates that Qingdao entered into an evident warming period since 1979 under the global warming.Reide [23] confirmed that the 1980s regime shift represented a major change F. Y. Guo et al.DOI: 10.4236/gep.2018.6900562 Journal of Geoscience and Environment Protection

Figure 1 (
Figure 1(b) and Figure 2(b) show the time series and their MK abrupt change test for the TMax.The TMax has a broader fluctuation range than the TAvg, but its warming rate is much less than the TAvg (Figure 1(a) and Figure 1(b)).The average TMax is 32.23˚C from 1899 to 2013.After the observation restarted in 1915, the average TMax is 33.12˚C with an increase rate (0.80 per 100a) from 1915 to 2015.The UFs fluctuate above zero for most years (Figure 2(b)), which suggest a slower warming.The TMax in the year 1949 and 1996 (30.1˚C) is the lowest for the past 117 years, which is 3.02˚C lower than the climate mean (33.12˚C), and the highest TMax (38.9˚C) occurred in 2002 is 5.78˚C higher than the climate mean.From 1899 to 1947 (49 years), the interannual amplitude is large, and the difference between the crest and bottom of the time series is up to 4.5˚C (36˚C at the peak and 31.5˚C at the bottom).But the TMax comes to a stabilization period in a fluctuant range of 3˚C from 1948.The decreasing UF means that the TMax slowly declines during this period.The TMax rises and falls acutely during the year 1965-1972.After then, Qingdao has 23 years of climate peace of TMax, the oscillating amplitude of the TMax is 2.5˚C -
varies periodically and dramatically (green line in Figure4(a)) with a slow increasing trend (blue line in Figure 4(a)), and the mean precipitation is about 681.78 mm•yr −1 .In 1981 Qingdao has the least precipitation, which is only 308.3 mm, while it is up to 1353.2 mm in 2007.From the trend analysis of Figure 5, F. Y. Guo et al.

Figure 4 .
Figure 4. Same as Figure 1(a) but for annual accumulative precipitation.

Figure 5 .Figure 4 )
Figure 5. Same as Figure 3(a) but for the annual accumulative precipitation.

Figure 6 .
Figure 6.Same as Figure 2(a) but for the annual accumulative precipitation.

Figure 7 .
Figure 7. Time series of seasonal mean temperature (black line) and their linear trend (red trend) in spring (a); summer (b); fall (c); and winter (d) during 1899-2015.

Figure 8 .
Figure 8. Same as Figure 7 but for seasonal accumulative precipitation.
et al.