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

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.

[1]  Vertical Profiling of Aerosol Types Observed across Monsoon Seasons with a Raman Lidar in Penang Island, Malaysia , 2016 .

[2]  R. Draxler.  An Overview of the HYSPLIT_4 Modelling System for Trajectories, Dispersion, and Deposition , 1998 .

[3]  Ellsworth J. Welton,et al.  Measurements of aerosol vertical profiles and optical properties during INDOEX 1999 using micropulse lidars , 2002 .

[4]  Yu Gu,et al.  Parameterization of Cloud–Radiation Processes in the UCLA General Circulation Model , 2003 .

[5]  A. Ansmann,et al.  Independent measurement of extinction and backscatter profiles in cirrus clouds by using a combined Raman elastic-backscatter lidar. , 1992, Applied optics.

[6]  David N. Whiteman,et al.  Use of rotational Raman measurements in multiwavelength aerosol lidar for evaluation of particle backscattering and extinction , 2015 .

[7]  J. Klett.  Stable analytical inversion solution for processing lidar returns. , 1981, Applied optics.

[8]  T. J. Boyd,et al.  Aerosol meteorology of Maritime Continent for the 2012 7SEAS southwest monsoon intensive study - Part 2: Philippine receptor observations of fine-scale aerosol behavior , 2016 .

[9]  F. G. Fernald.  Analysis of atmospheric lidar observations: some comments. , 1984, Applied optics.

[10]  M. Ciofini,et al.  Diffractive optical components for high power laser beam sampling , 2003 .

[11]  Soo Chin Liew,et al.  Degradation and development of peatlands in Peninsular Malaysia and in the islands of Sumatra and Borneo since 1990 , 2010 .

[12]  D. Winker,et al.  CALIPSO Lidar Description and Performance Assessment , 2009 .

[13]  L. Brasseur,et al.  Raman lidar measurements of the aerosol extinction‐to‐backscatter ratio over the Southern Great Plains , 2001 .

[14]  S. Page,et al.  The amount of carbon released from peat and forest fires in Indonesia during 1997 , 2002, Nature.

[15]  A. Smirnov,et al.  AERONET-a federated instrument network and data archive for aerosol Characterization , 1998 .

[16]  F. Siegert,et al.  Increased damage from fires in logged forests during droughts caused by El Niño , 2001, Nature.

[17]  J. Muller,et al.  MODIS BRDF / Albedo Product : Algorithm Theoretical Basis Document Version 5 . 0 , 1999 .

[18]  EARTHCARE SATELLITE,et al.  The EarthCARE satellite: the next step forward in global measurements of clouds, aerosols, precipitation, and radiation next step forward in global , 2018 .

[19]  Ellsworth J. Welton,et al.  Global monitoring of clouds and aerosols using a network of micropulse lidar systems , 2001, SPIE Asia-Pacific Remote Sensing.

[20]  Piers M. Forster,et al.  The semi‐direct aerosol effect: Impact of absorbing aerosols on marine stratocumulus , 2004 .

[21]  Q. Fu,et al.  On the correlated k-distribution method for radiative transfer in nonhomogeneous atmospheres , 1992 .

[22]  P. Koepke,et al.  Optical Properties of Aerosols and Clouds: The Software Package OPAC , 1998 .

[23]  B. Holben,et al.  Origin, transport, and vertical distribution of atmospheric pollutants over the northern South China Sea during the 7-SEAS/Dongsha Experiment , 2013 .

[24]  Soo Chin Liew,et al.  Daytime Top-of-the-Atmosphere Cirrus Cloud Radiative Forcing Properties at Singapore , 2017 .

[25]  E. Maloney,et al.  Multi-scale meteorological conceptual analysis of observed active fire hotspot activity and smoke optical depth in the Maritime Continent , 2011 .

[26]  Pierre H. Flamant,et al.  0.355-micrometer direct detection wind lidar under testing during a field campaign in consideration of ESA's ADM-Aeolus mission , 2013 .

[27]  Albert Ansmann,et al.  Saharan dust over a central European EARLINET‐AERONET site: Combined observations with Raman lidar and Sun photometer , 2003 .

[28]  L. Sauvage,et al.  Evaluation of Mixing-Height Retrievals from Automatic Profiling Lidars and Ceilometers in View of Future Integrated Networks in Europe , 2012, Boundary-Layer Meteorology.

[29]  E. Vermote,et al.  The MODIS Aerosol Algorithm, Products, and Validation , 2005 .

[30]  Q. Fu,et al.  Multiple Scattering Parameterization in Thermal Infrared Radiative Transfer , 1997 .

[31]  Bin Wang,et al.  The Global Monsoon System Research and Forecast 2nd Edition , 2011 .

[32]  U. Dayan,et al.  Atmospheric pollution over the eastern Mediterranean during summer – a review , 2016 .

[33]  Muhammad Bilal,et al.  A Simplified and Robust Surface Reflectance Estimation Method (SREM) for Use over Diverse Land Surfaces Using Multi-Sensor Data , 2019, Remote. Sens..

[34]  G. Pappalardo,et al.  Aerosol observations by lidar in the nocturnal boundary layer. , 1999, Applied optics.

[35]  Soo Chin Liew,et al.  Observing and understanding the Southeast Asian aerosol system by remote sensing: An initial review and analysis for the Seven Southeast Asian Studies (7SEAS) program , 2013 .

[36]  Lidar measurements of aerosol column content in an urban nocturnal boundary layer , 1997 .

[37]  Johannes Quaas,et al.  Estimates of aerosol radiative forcing from the MACC re-analysis , 2012 .

[38]  N. Spinelli,et al.  Optimization of the lidar optical design for measurement of the aerosol extinction vertical profile , 2019, EPJ Web of Conferences.

[39]  Simone Lolli,et al.  Assessment of aerosol optical property and radiative effect for the layer decoupling cases over the northern South China Sea during the 7‐SEAS/Dongsha Experiment , 2016 .

[40]  Philippe Ciais,et al.  An Assessment of Pseudo-Operational Ground-Based Light Detection and Ranging Sensors to Determine the Boundary-Layer Structure in the Coastal Atmosphere , 2012 .

[41]  Yu Gu,et al.  Impact of varying lidar measurement and data processing techniques in evaluating cirrus cloud and aerosol direct radiative effects , 2018 .

[42]  W. Thomas,et al.  What is the benefit of ceilometers for aerosol remote sensing? An answer from EARLINET , 2014 .

[43]  Q. Fu,et al.  Parameterization of the Radiative Properties of Cirrus Clouds , 1993 .

[44]  J. Ackermann.  The Extinction-to-Backscatter Ratio of Tropospheric Aerosol: A Numerical Study , 1998 .

[45]  V. Ramanathan,et al.  Aerosols, Climate, and the Hydrological Cycle , 2001, Science.

[46]  Mohd Talib Latif,et al.  Composition and source apportionment of surfactants in atmospheric aerosols of urban and semi-urban areas in Malaysia. , 2013, Chemosphere.

[47]  Boon N. Chew,et al.  Aerosol transport model evaluation of an extreme smoke episode in Southeast Asia , 2010 .

[48]  Soo Chin Liew,et al.  Applying Advanced Ground-Based Remote Sensing in the Southeast Asian Maritime Continent to Characterize Regional Proficiencies in Smoke Transport Modeling , 2016 .

[49]  Samuel S. P. Shen,et al.  Human amplification of drought-induced biomass burning in Indonesia since 1960 , 2009 .

[50]  Yu Gu,et al.  Cirrus cloud simulations using WRF with improved radiation parameterization and increased vertical resolution , 2011 .

[51]  Simone Lolli,et al.  Principal Component Analysis Approach to Evaluate Instrument Performances in Developing a Cost-Effective Reliable Instrument Network for Atmospheric Measurements , 2015 .

[52]  Jaakko Kukkonen,et al.  Comparison of CALIOP level 2 aerosol subtypes to aerosol types derived from AERONET inversion data , 2009 .

[53]  P. Di Girolamo,et al.  Rain Evaporation Rate Estimates from Dual-Wavelength Lidar Measurements and Intercomparison against a Model Analytical Solution , 2017 .