Estimation of aerosol optical depth at different wavelengths by multiple regression method

Area of Science:

• Atmospheric Science
• Environmental Monitoring
• Remote Sensing

Background:

• Aerosol optical depth (AOD) is crucial for understanding atmospheric conditions and climate.
• Continuous monitoring of AOD is challenging, especially during periods without satellite retrieval data.
• Ground-based measurements offer potential for AOD estimation.

Purpose of the Study:

• To develop and validate a predictive model for estimating AOD.
• To utilize routine ground-based measurements for AOD monitoring.
• To assess aerosol characteristics during non-retrieval times.

Main Methods:

• Statistical analysis to establish relationships between ground measurements (API, visibility, humidity, temperature, pressure) and CIMEL sun photometer AOD.
• Development of a calibrated AOD prediction model with wavelength-specific coefficients.
• Validation of the model using statistical tests and comparison of aerosol size estimations.

Main Results:

• The proposed model accurately predicted AOD across a wide range of wavelengths (340 nm to 1020 nm).
• The model demonstrated consistency with measured AOD data in characterizing aerosol size distribution.
• Penang was found to be dominated by fine mode aerosols in 2012-2013 based on both measured and predicted AOD.

Conclusions:

• The developed AOD prediction model is a viable tool for regular aerosol variation monitoring.
• Routine ground measurements can effectively supplement satellite data for AOD estimation.
• The model aids in understanding aerosol properties and their temporal variations.