Analysis of statistical models on temperature at the Suwon city in Korea

Title & Authors
Analysis of statistical models on temperature at the Suwon city in Korea
Lee, Hoonja;

Abstract
The change of temperature influences on the various aspect, especially human health, plant and animal`s growth, economics, industry, and culture of the country. In this article, the autoregressive error (ARE) model has been considered for analyzing the monthly temperature data at the Suwon monitoring site in Korea. In the ARE model, five meteorological variables, four greenhouse gas variables and five pollution variables are used as the explanatory variables for the temperature data set. The five meteorological variables are wind speed, rainfall, radiation, amount of cloud, and relative humidity. The four greenhouse gas variables are carbon dioxide ($\small{CO_2}$), methane ($\small{CH_4}$), nitrous oxide ($\small{N_2O}$), and chlorofluorocarbon ($\small{CFC_{11}}$). And the five air pollution explanatory variables are particulate matter ($\small{PM_{10}}$), sulfur dioxide ($\small{SO_2}$), nitrogen dioxide ($\small{NO_2}$), ozone ($\small{O_3}$), and carbon monoxide (CO). Among five meteorological variables, radiation, amount of cloud, and wind speed are more influence on the temperature. The radiation influences during spring, summer and fall, whereas wind speed influences for the winter time. Also, among four greenhouse gas variables and five pollution variables, chlorofluorocarbon, methane, and ozone are more influence on the temperature. The monthly ARE model explained about 43-69% for describing the temperature.
Keywords
Autoregressive error model;explanatory variable;greenhouse gas variables;meteorological variables;pollution variable;temperature;
Language
Korean
Cited by
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References
1.
Bae, K., Park, J., Kim, J. and Lee, Y. (2013). Analysis of the abstracts of research articles in food related to climate change using a text-mining algorithm. Journal of the Korean Data & Information Science Society, 24, 1429-1437.

2.
Cho, S. and Lee, J. (1997). Analysis of economic time series analysis using SAS/ETS, Freedom Academy, Seoul.

3.
IPCC (2007). Contribution of working group II to the fourth assessment report of the intergovernmental panel on climate change, Cambridge Press, Cambridge, U.K. 976.

4.
Jeong, M. J. and Cho, Y. (2015). An analysis of a winter-time temperature change and an extream cold waves frequency in Korea. Journal of Climate Change Research, 6, 87-84.

5.
Kim, H. C., Choi, S. K. and Yun, B. R. (2011). A statistical analysis on temperature change and climate variability in Korea. Communications of the Korean Statistical Society, 18, 1-12.

6.
Kim, H., Do, H. Y. and Kim, Y. (2013). A modeling of daily temperature in Seoul using GLM weather generator. The Korean Journal of Applied Statistics, 26, 413-420.

7.
Kim, H. K. and Lee, Y. (2013). A study on the density analysis of climatological stations using the correlation integral method in the fractal dimension. Journal of the Korean Data & Information Science Society, 24, 53-62.

8.
Ko, W. K. (2007). Estimation for change of daily maxima temperature. The Korean Journal of Applied Statistics, 20, 1-9.

9.
Korea Meteorological Administration (2009). Report of global atmosphere watch 2008, Korea Meteorological Administration, Korea, 178.

10.
Lee, H. (2014). Analysis of statistical models on temperature at the Seosan city in Korea. Journal of the Korean Data & Information Science Society, 25, 1293-1300.

11.
Oh, I., Bang, J. and Kim, Y. (2015). Meteorological characteristics in the Ulsan metropolitan region: Focus on air temperature and winds. Journal of Korean Society for Atmospheric Environment, 31, 181-194.

12.
Song, C. K., Lee, S. and Yoon, J. S. (2011). A review of the integrated strategy for climate change and air pollution management. Journal of Korean Society for Atmospheric Environment, 27, 805-818.

13.
Yoo, H. C. and Kang, H. G. (2010). Comparative analysis of temperature change trend and standard meteorological data in Korea over 40 years. Journal of KIAEBS, 4, 97-103.