Title of article :
Combining multiple regression and principal component analysis for accurate predictions for column ozone in Peninsular Malaysia
Author/Authors :
Rajab، نويسنده , , Jasim M. and MatJafri، نويسنده , , M.Z. and Lim، نويسنده , , H.S.، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2013
Pages :
8
From page :
36
To page :
43
Abstract :
This study encompasses columnar ozone modelling in the peninsular Malaysia. Data of eight atmospheric parameters [air surface temperature (AST), carbon monoxide (CO), methane (CH4), water vapour (H2Ovapour), skin surface temperature (SSKT), atmosphere temperature (AT), relative humidity (RH), and mean surface pressure (MSP)] data set, retrieved from NASAʹs Atmospheric Infrared Sounder (AIRS), for the entire period (2003–2008) was employed to develop models to predict the value of columnar ozone (O3) in study area. The combined method, which is based on using both multiple regressions combined with principal component analysis (PCA) modelling, was used to predict columnar ozone. This combined approach was utilized to improve the prediction accuracy of columnar ozone. Separate analysis was carried out for north east monsoon (NEM) and south west monsoon (SWM) seasons. The O3 was negatively correlated with CH4, H2Ovapour, RH, and MSP, whereas it was positively correlated with CO, AST, SSKT, and AT during both the NEM and SWM season periods. Multiple regression analysis was used to fit the columnar ozone data using the atmospheric parameterʹs variables as predictors. A variable selection method based on high loading of varimax rotated principal components was used to acquire subsets of the predictor variables to be comprised in the linear regression model of the atmospheric parameterʹs variables. It was found that the increase in columnar O3 value is associated with an increase in the values of AST, SSKT, AT, and CO and with a drop in the levels of CH4, H2Ovapour, RH, and MSP. The result of fitting the best models for the columnar O3 value using eight of the independent variables gave about the same values of the R (≈0.93) and R2 (≈0.86) for both the NEM and SWM seasons. The common variables that appeared in both regression equations were SSKT, CH4 and RH, and the principal precursor of the columnar O3 value in both the NEM and SWM seasons was SSKT.
Keywords :
Ozone (O3) , Regression analysis , Principal component analysis , Atmosphere infrared sounder (AIRS)
Journal title :
Atmospheric Environment
Serial Year :
2013
Journal title :
Atmospheric Environment
Record number :
2240861
Link To Document :
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