Variation in daytime troposphereic aerosol via LIDAR and sunphotometer measurements in Penang, Malaysia

Tan, F.; Hee, Wan Shen; Hwee, S. L.; Abdullah, K.; Tiem, L. Y.; MatJafri, M. Z.; Lolli, Simone; Holben, B. N.; Welton, Ellsworth J.

doi:10.1063/1.4866962

Cited by 5 publications

(7 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The underand overpredicted AOD were examined using a Raymetrics LIDAR system if the data were available. Our LIDAR system is co-located with the Cimel sunphotometer at the rooftop Tan et al (2013Tan et al ( , 2014c. The LIDAR signals were pre-analyzed based on the protocol mentioned in Tan et al (2013Tan et al ( , 2014c.…”

Section: Methodology and Statistical Modelmentioning

confidence: 99%

“…Figure 5 indicates that most of the predicted AOD values are lower than the measured counterparts. Tan et al (2014c) analyze the underprediction in these values. They used a LI-DAR system to determine the vertical profile of aerosols in Penang and found that the aerosol concentration decreased with height up to the planetary boundary layer (PBL).…”

Section: Validation Of the Predicted Aodmentioning

confidence: 99%

See 1 more Smart Citation

Monsoonal variations in aerosol optical properties and estimation of aerosol optical depth using ground-based meteorological and air quality data in Peninsular Malaysia

et al. 2015

Self Cite

View full text Add to dashboard Cite

Abstract. Obtaining continuous aerosol-optical-depth (AOD) measurements is a difficult task due to the cloudcover problem. With the main motivation of overcoming this problem, an AOD-predicting model is proposed. In this study, the optical properties of aerosols in Penang, Malaysia were analyzed for four monsoonal seasons (northeast monsoon, pre-monsoon, southwest monsoon, and post-monsoon) based on data from the AErosol RObotic NETwork (AERONET) from February 2012 to November 2013. The aerosol distribution patterns in Penang for each monsoonal period were quantitatively identified according to the scattering plots of the Ångström exponent against the AOD. A new empirical algorithm was proposed to predict the AOD data. Ground-based measurements (i.e., visibility and air pollutant index) were used in the model as predictor data to retrieve the missing AOD data from AERONET due to frequent cloud formation in the equatorial region. The model coefficients were determined through multiple regression analysis using selected data set from in situ data. The calibrated model coefficients have a coefficient of determination, R 2 , of 0.72. The predicted AOD of the model was generated based on these calibrated coefficients and compared against the measured data through standard statistical tests, yielding a R 2 of 0.68 as validation accuracy. The error in weighted mean absolute percentage error (wMAPE) was less than 0.40 % compared with the real data. The results revealed that the proposed model efficiently predicted the AOD data. Performance of our model was compared against selected LIDAR data to yield good correspondence. The predicted AOD can enhance measured shortand long-term AOD and provide supplementary information for climatological studies and monitoring aerosol variation.

show abstract

Section: Methodology and Statistical Modelmentioning

confidence: 99%

Section: Validation Of the Predicted Aodmentioning

confidence: 99%

Monsoonal variations in aerosol optical properties and estimation of aerosol optical depth using ground-based meteorological and air quality data in Peninsular Malaysia

et al. 2015

Self Cite

View full text Add to dashboard Cite

show abstract

“…When LIDAR data were available for examination, only the data that can clearly elucidate the under-and over-predicted AOD were selected. The LIDAR signals were pre-analyzed based on the published works of Tan et al (2013Tan et al ( , 2014c. The backscatter coefficients of the aerosol from LIDAR signals were determined using the method of Fernald (1984).…”

Section: Methodology and Statistical Modelmentioning

confidence: 99%

“…Figure indicates that most of the predicted AOD values were lower than the measured counterparts. Tan et al (2014c) analyzed the underprediction in these values. They used a LIDAR system to determine the vertical profile of aerosols in Penang and found that the aerosol concentration decreased with height up to the planetary boundary layer (PBL).…”

Section: Validation Of the Predicted Aodmentioning

confidence: 99%

Variations in optical properties of aerosols on monsoon seasonal change and estimation of aerosol optical depth using ground-based meteorological and air quality data

Tan¹,

Lim²,

Abdullah³

et al. 2014

Preprint

Self Cite

View full text Add to dashboard Cite

Abstract. In this study, the optical properties of aerosols in Penang, Malaysia were analyzed for four monsoonal seasons (northeast monsoon, pre-monsoon, southwest monsoon, and post-monsoon) based on data from the AErosol RObotic NETwork (AERONET) from February 2012 to November 2013. The aerosol distribution patterns in Penang for each monsoonal period were quantitatively identified according to the scattering plots of the aerosol optical depth (AOD) against the Angstrom exponent. A modified algorithm based on the prototype model of Tan et al. (2014a) was proposed to predict the AOD data. Ground-based measurements (i.e., visibility and air pollutant index) were used in the model as predictor data to retrieve the missing AOD data from AERONET because of frequent cloud formation in the equatorial region. The model coefficients were determined through multiple regression analysis using selected data set from in situ data. The predicted AOD of the model was generated based on the coefficients and compared against the measured data through standard statistical tests. The predicted AOD in the proposed model yielded a coefficient of determination R2 of 0.68. The corresponding percent mean relative error was less than 0.33% compared with the real data. The results revealed that the proposed model efficiently predicted the AOD data. Validation tests were performed on the model against selected LIDAR data and yielded good correspondence. The predicted AOD can beneficially monitor short- and long-term AOD and provide supplementary information in atmospheric corrections.

show abstract

“…In particular, extensive measurement campaigns have taken place to establish aerosol sources and transport [8,18,19]. Nevertheless, in Malaysia, observations are still scarce [20,21] and for a limited amount of time. During monsoonal seasons, November to March and from June to September [22], biomass burning emissions increase [1,2] in SEA neighbor countries around Malaysia, and Pulau Pinang experiences strong hazy atmospheric conditions.…”

Section: Introductionmentioning

confidence: 99%

Monsoon Season Quantitative Assessment of Biomass Burning Clear-Sky Aerosol Radiative Effect at Surface by Ground-Based Lidar Observations in Pulau Pinang, Malaysia in 2014

et al. 2019

View full text Add to dashboard Cite

Direct and indirect aerosol effects are still one of the largest uncertainties related to the Earth energy budget, especially in a wild and remote region like South-East Asia, where ground-based measurements are still difficult and scarce, while endemic cloudy skies make difficult active and passive satellite observations. In this preliminary study, we analyzed and quantitatively assessed the differences between monsoon and inter-monsoon seasons, in terms of radiative effects at surface and columnar heating rate, of clear-sky biomass burning aerosols (no clouds) using ground-based lidar observations obtained with a 355 nm elastic lidar instrument, deployed since 2012 at the Physics Department of Universiti Sains Malaysia (USM). The model-based back-trajectory analysis put in evidence that, during the monsoon seasons (November–March and June–September), the air masses advected towards the observational site transit over active fire hotspot regions, in contrast with the inter-monsoon season. In between the monsoon seasons (April–May, October), the atmosphere over Penang is constituted by local background urban aerosols that originate from road traffic emissions, domestic cooking, and industrial plants emissions. The analysis was carried out using the vertically-resolved profiles of the seasonal averaged aerosol optical properties (monsoon vs. inter-monsoon seasons), e.g., the atmospheric extinction coefficient, to evaluate the seasonal surface aerosol radiative effect and column heating rate differences through the Fu–Liou–Gu (FLG) radiative transfer model. The results put in evidence that the biomass burning advection during the monsoon season (especially during the South West monsoon from June to September) lowers the noon daytime incoming solar shortwave solar radiation reaching the Earth surface with respect to the local background conditions by 91.5 W/m2 (114–69 W/m2). The aerosols also lead to an averaged heating in the first kilometer of the atmosphere of about 4.9 K/day (6.4–3.4 W/m2). The two combined effects, i.e., less absorbed energy by Earth surface and warming of the first kilometer of the boundary layer, increase the low-level stability during monsoon seasons, with a possible reduction in cloud formation and precipitation. The net effect is to exacerbate the haze episodes, as the pollutants rest trapped into the boundary layer. Besides these considerations, the lidar measurements are of great interest in this particular world region and might be used for cal/val of the future space missions, e. g., Earthcare.

show abstract

Variation in daytime troposphereic aerosol via LIDAR and sunphotometer measurements in Penang, Malaysia

Cited by 5 publications

References 10 publications

Monsoonal variations in aerosol optical properties and estimation of aerosol optical depth using ground-based meteorological and air quality data in Peninsular Malaysia

Monsoonal variations in aerosol optical properties and estimation of aerosol optical depth using ground-based meteorological and air quality data in Peninsular Malaysia

Variations in optical properties of aerosols on monsoon seasonal change and estimation of aerosol optical depth using ground-based meteorological and air quality data

Monsoon Season Quantitative Assessment of Biomass Burning Clear-Sky Aerosol Radiative Effect at Surface by Ground-Based Lidar Observations in Pulau Pinang, Malaysia in 2014

Contact Info

Product

Resources

About