## 3 Establishment of Standard Daily Meteorological Model
### Extreme Daily Meteorological Model  
An extreme meteorological climate caused by global warming is becoming more and more frequent. However, the definition of extreme meteorological climate is still unclear in the area of civil engineering. [PERSON] defines extreme meteorology as a large scale of meteorology abnormality (temperature, rainfall, etc.), or a meteorological event (hurricane, flood, etc.) [21; 22; 23; 24]. Moreover, [PERSON] also considers that the effect of a meteorological event on society can be used to judge extreme meteorology. Generally, however, an extreme meteorological event is different from disastrous weather events. The damage of extreme events can not only can be affected by the intensity of an anomaly of the meteorological climate, but also affected by the area where the disaster occurred and the victims [25; 26; 27; 28]. [PERSON] [29] generalizes three characteristics of extreme meteorological climate: (1) low frequency, (2) high intensity, and (3) huge society loss. The report of the IPCC (Intergovernmental Panel on Climate Change) shows that the possibility of extreme meteorological climate is usually lower than 5% [1; 2]. Building structures exposed to natural environments for a long time will be affected by various factors of meteorological environments. But the effect is not as sensitive and direct as the effect of extreme meteorological climate on agriculture and animal husbandry. Moreover, for industrial and civil building construction, the density of population is large and the social economic value is high. Therefore, extreme climate can cause serious social and economic losses. According to the research and the suggestions of the IPCC and [PERSON], for civil engineering, extreme meteorological climate is a rare meteorological event whose possibility of occurring is lower than 1% in a geographic area for a certain time.  
According to the definition of extreme meteorological, the temperature value with the occurrence probability of 1% (within a 100-year return-period) is the representative daily temperature of extreme weather, and the results of computation are obtained as shown in  
Figure 4: Temperature meteorological model of standard day in January in Beijing.  
Figure 3: Temperature meteorological model of standard day in July in Beijing.  
where \(C_{1}\), \(C_{2}\) can be valued according to the Table E.3.2 in the Load code for the design of building structures GB50009-2012 [13].  
Assume \(F(x)=1-1/R\), the daily temperature difference \(x_{R}\), of which the recurrence interval is \(R\), during the selected month can be calculated by Equation (9):  
\[x_{R}=u-\frac{1}{\alpha}\ln[\ln(\frac{R}{R-1})] \tag{15}\]  
3.2 The Analysis of Daily Temperature Differences in Different Recurrence Intervals in Different Months  
The daily temperature differences of each month in Beijing were gathered, and the mean value \(\overline{x}\), standard deviation \(\sigma_{1}\) of the daily temperature difference were calculated afterwards. The results are shown in Table 2. Assuming \(R\) equals 10 years, 20 years, 50 years and 100 years, the daily temperature differences were calculated with different recurrence intervals in each month by using Equations (14) and (9). The computations are shown in Table 2.  
According to Table 2, the months with larger daily temperature differences are March, April, May, June, September and October, with an extreme temperature difference of approximately 27.0 \({}^{\circ}\)C. Moreover, the months with smaller daily temperature difference are July and August, with an extreme temperature difference of approximately 17.0 \({}^{\circ}\)C. The extreme temperature differences of the other months are approximately 22.0 \({}^{\circ}\)C.