Abstract. The purpose of this study is to demonstrate that S-5P/TROPOMI aerosol layer height (ALH) observations can be used to improve the single scattering albedo (SSA) retrieval from ultraviolet satellite observations. We take the Thomas Fire in southern California on 12 December 2017 as a case study. In the first part of this paper, we apply conventional radiative transfer simulations to retrieve the SSA. With forward simulations constrained by TROPOMI ALH, we can determine the uncertainty in SSA due to the assumed spectral dependence of refractive indices between two wavelengths of the near-ultraviolet absorbing aerosol index (UVAI). A significant gap in the retrieved SSA (0.24) between radiative transfer simulations with grey and colored aerosols implies that inappropriate spectral dependences may cause severe misinterpretations of aerosol absorption. In the second part of this paper, we propose a data-driven method to quantify aerosol absorption from long-term measurements of UVAI, the aerosol optical depth (AOD) and ALH using support vector regression (SVR). We present the potential of TROPOMI ALH in this new method. The SVR predicted SSA (0.96 ± 0.01) outperforms that predicted by radiative transfer simulations (0.90 ± 0.05), considering the AERONET SSA measurement is 0.96 and assuming that the aerosol absorption should be homogeneous within the plume (i.e. small SSA standard deviation). We thus believe that the upcoming TROPOMI ALH product can make it feasible to quantify aerosol absorption via data-driven methods, which would play an important role in constructing a long-term global SSA data set.
Abstract. The absorbing aerosol index (AAI) based on the near Ultra-Violet (near-UV) remote sensing techniques is a qualitative parameter that allows to retrieve aerosol optical properties with confidence. In the first part of this study, a series of AAI sensitivity analysis is presented exclusively on biomass burning aerosols. Later on, this study applies a radiative 10 transfer model (DISAMAR) to simulate the AAI measured by the Ozone Monitoring Instrument (OMI) and to derive the aerosol single scattering albedo (ω 0 ). The inputs for the radiative transfer calculations are satellite measurement geometry and surface conditions from OMI, aerosol optical thickness (τ) from the MODerate-resolution Imaging Spectroradiometer (MODIS), and aerosol micro-physical parameters from the AErosol RObotic NETwork (AERONET), respectively. This approach is applied to the Chile wildfires for the period from 26 to 30 January 2017, when the OMI observed AAI of this 15 event reached its peak. The Cloud and Aerosol Lidar with Orthogonal Polarization (CALIOP) failed to capture the evolution of the smoke plume, therefore the aerosol profile is parameterized. The simulated plume ascends to an altitude of 4.5-4.9 km, which is in good agreement with measurements. Due to the relatively small data size of this case, an outlier detection criterion has to be applied. The results show that the AAI simulated by DISAMAR is consistent with observations. The correlation coefficients are over 0.85. The retrieved mean ω 0 at 550 nm is approximately 0.84, slightly smaller than the value 20 of 0.90 measured independently by the AERONET instrument. The relative distance between the AERONET site and the plume, the assumption of homogeneous and static plume properties, the lack of the aerosol profile information, and the uncertainties in observations are primarily responsible for this discrepancy. Except for the observational errors, the impact of remaining error sources on ω 0 retrieval is difficult to quantify.
The absorbing aerosol index (AAI) is a qualitative parameter directly calculated from satellite-measured reflectance. Its sensitivity to absorbing aerosols in combination with a long-term data record since 1978 makes it an important parameter for climate research. In this study, we attempt to quantify aerosol absorption by retrieving the singlescattering albedo (ω 0) at 550 nm from the satellite-measured AAI. In the first part of this study, AAI sensitivity studies are presented exclusively for biomass-burning aerosols. Later on, we employ a radiative transfer model (DISAMAR) to simulate the AAI measured by the Ozone Monitoring Instrument (OMI) in order to derive ω 0 at 550 nm. Inputs for the radiative transfer calculations include satellite measurement geometry and surface conditions from OMI, aerosol optical thickness (τ) from the Moderate Resolution Imaging Spectroradiometer (MODIS) and aerosol microphysical parameters from the AErosol RObotic NETwork (AERONET), respectively. This approach is applied to the Chile wildfires for the period from 26 to 30 January 2017, when the OMIobserved AAI of this event reached its peak. The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) overpasses missed the evolution of the smoke plume over the research region; therefore the aerosol profile is parameterized. The simulated plume is at an altitude of 4.5-4.9 km, which is in good agreement with available CALIOP backscatter coefficient measurements. The data may contain pixels outside the plume, so an outlier detection criterion is applied. The results show that the AAI simulated by DISAMAR is consistent with satellite observations. The correlation coefficients fall into the range between 0.85 and 0.95. The retrieved mean ω 0 at 550 nm for the entire plume over the research period from 26 to 30 January 2017 varies from 0.81 to 0.87, whereas the nearest AERONET station reported ω 0 between 0.89 and 0.92. The difference in geolocation between the AERONET site and the plume, the assumption of homogeneous plume properties, the lack of the aerosol profile information and the uncertainties in the inputs for radiative transfer calculation are primarily responsible for this discrepancy in ω 0 .
The absorbing aerosol index (AAI) is a qualitative parameter directly calculated from satellite-measured reflectance. Its sensitivity to absorbing aerosols in combination with a long-term data record since 1978 makes it an important parameter for climate research. In this study, we attempt to quantify aerosol absorption by retrieving the singlescattering albedo (ω 0) at 550 nm from the satellite-measured AAI. In the first part of this study, AAI sensitivity studies are presented exclusively for biomass-burning aerosols. Later on, we employ a radiative transfer model (DISAMAR) to simulate the AAI measured by the Ozone Monitoring Instrument (OMI) in order to derive ω 0 at 550 nm. Inputs for the radiative transfer calculations include satellite measurement geometry and surface conditions from OMI, aerosol optical thickness (τ) from the Moderate Resolution Imaging Spectroradiometer (MODIS) and aerosol microphysical parameters from the AErosol RObotic NETwork (AERONET), respectively. This approach is applied to the Chile wildfires for the period from 26 to 30 January 2017, when the OMIobserved AAI of this event reached its peak. The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) overpasses missed the evolution of the smoke plume over the research region; therefore the aerosol profile is parameterized. The simulated plume is at an altitude of 4.5-4.9 km, which is in good agreement with available CALIOP backscatter coefficient measurements. The data may contain pixels outside the plume, so an outlier detection criterion is applied. The results show that the AAI simulated by DISAMAR is consistent with satellite observations. The correlation coefficients fall into the range between 0.85 and 0.95. The retrieved mean ω 0 at 550 nm for the entire plume over the research period from 26 to 30 January 2017 varies from 0.81 to 0.87, whereas the nearest AERONET station reported ω 0 between 0.89 and 0.92. The difference in geolocation between the AERONET site and the plume, the assumption of homogeneous plume properties, the lack of the aerosol profile information and the uncertainties in the inputs for radiative transfer calculation are primarily responsible for this discrepancy in ω 0 .
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