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A statistical model to predict total column ozone in Peninsular Malaysia

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Abstract

This study aims to predict monthly columnar ozone in Peninsular Malaysia based on concentrations of several atmospheric gases. Data pertaining to five atmospheric gases (CO2, O3, CH4, NO2, and H2O vapor) were retrieved by satellite scanning imaging absorption spectrometry for atmospheric chartography from 2003 to 2008 and used to develop a model to predict columnar ozone in Peninsular Malaysia. Analyses of the northeast monsoon (NEM) and the southwest monsoon (SWM) seasons were conducted separately. Based on the Pearson correlation matrices, columnar ozone was negatively correlated with H2O vapor but positively correlated with CO2 and NO2 during both the NEM and SWM seasons from 2003 to 2008. This result was expected because NO2 is a precursor of ozone. Therefore, an increase in columnar ozone concentration is associated with an increase in NO2 but a decrease in H2O vapor. In the NEM season, columnar ozone was negatively correlated with H2O (–0.847), NO2 (0.754), and CO2 (0.477); columnar ozone was also negatively but weakly correlated with CH4 (–0.035). In the SWM season, columnar ozone was highly positively correlated with NO2 (0.855), CO2 (0.572), and CH4 (0.321) and also highly negatively correlated with H2O (–0.832). Both multiple regression and principal component analyses were used to predict the columnar ozone value in Peninsular Malaysia. We obtained the best-fitting regression equations for the columnar ozone data using four independent variables. Our results show approximately the same R value (≈ 0.83) for both the NEM and SWM seasons.

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Authors and Affiliations

  1. School of Physics, Universiti Sains Malaysia, Penang, 11800, Malaysia

    K. C. Tan, H. S. Lim & M. Z. Mat Jafri

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  1. K. C. Tan
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  2. H. S. Lim
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  3. M. Z. Mat Jafri
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Correspondence to K. C. Tan.

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Tan Kok Chooi is a Senior Lecturer at the School of Physics, Universiti Sains Malaysia. He obtained his Ph.D in image processing from Universiti Sains Malaysia. His research interests cover the field of remote sensing applications and environmental monitoring, such as land use/land cover changes, land surface properties, and image classification. Currently, his research focuses on the environmental remote sensing, atmospheric chemistry and physics.

Lim Hwee San is an Associate Professor of Geophysics and Remote Sensing at the School of Physics, Universiti Sains Malaysia. He obtained his Ph.D from Universiti Sains Malaysia in environmental remote sensing. His research interests lie generally in the field of optical remote sensing-both passive and active-and digital image processing, particularly as it applies to spectral image data. In both cases, the primary applications are water quality monitoring, air quality monitoring, land cover/change detection, land surface properties and digital images classification. He also interested in modelling of the optical properties of atmospheric aerosols. His current effort focus on the applications of ground based LIDAR and satellite based LIDAR (e.g., CALIPSO, AIRS) data for air pollution and green house effects study.

Mohd. Zubir Mat Jafri is a Professor of Optical Sensing and Remote Sensing at the School of Physics, Universiti Sains Malaysia. He obtained his Ph.D from Universiti College of Swansea, Wales, UK, in digital image processing. He has more than twenty years teaching and research experience in the area of physics, optical communication, digital image processing, electronics and microprocessor technology.

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Tan, K.C., Lim, H.S. & Mat Jafri, M.Z. A statistical model to predict total column ozone in Peninsular Malaysia. Front. Earth Sci. 10, 63–73 (2016). https://doi.org/10.1007/s11707-015-0521-8

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  • DOI: https://doi.org/10.1007/s11707-015-0521-8

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