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http://dx.doi.org/10.7465/jkdi.2015.26.2.289

Development of statistical forecast model for PM10 concentration over Seoul  

Sohn, Keon Tae (Department of Statistics, Pusan national University)
Kim, Dahong (Department of Statistics, Pusan national University)
Publication Information
Journal of the Korean Data and Information Science Society / v.26, no.2, 2015 , pp. 289-299 More about this Journal
Abstract
The objective of the present study is to develop statistical quantitative forecast model for PM10 concentration over Seoul. We used three types of data (weather observation data in Korea, the China's weather observation data collected by GTS, and air quality numerical model forecasts). To apply the daily forecast system, hourly data are converted to daily data and then lagging was performed. The potential predictors were selected based on correlation analysis and multicollinearity check. Model validation has been performed for checking model stability. We applied two models (multiple regression model and threshold regression model) separately. The two models were compared based on the scatter plot of forecasts and observations, time series plots, RMSE, skill scores. As a result, a threshold regression model performs better than multiple regression model in high PM10 concentration cases.
Keywords
PM10; quantitative forecast; skill score; threshold regression model;
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