The CALIPSO Version 4 Automated Aerosol Classification and Lidar Ratio Selection Algorithm

Kim, Man‐Hae; Omar, Ali; Tackett, Jason L.; Vaughan, Mark; Winker, David M.; Trepte, Charles R.; Hu, Yongxiang; Liu, Z.; Poole, L. R.; Pitts, Mıchael; Kar, Jayanta; Magill, Brian

doi:10.5194/amt-2018-166

Cited by 74 publications

(134 citation statements)

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“…Obviously particle shape and size widely control the strength of depolarization of backscattered laser radiation at the different wavelengths. However, to obtain clear answers concerning the role of particle size, shape, and composition on light depolarization, we need extended simulation studies with advanced optical particle models (Gasteiger et al, 2011;Lindqvist et al, 2014;Kemppinen et al, 2015a, b;Mishchenko et al, 2016). Unfortunately, modeling of the optical properties of dust and soot particles for our specific lidar application (scattering at exactly 180 • ) is a very crucial task.…”

Section: Discussionmentioning

confidence: 99%

“…Fundamental input parameters in the CALIOP data analysis are the particle extinction-to-backscatter ratio (lidar ratio) at 532 and 1064 nm (Omar et al, 2009;Kim et al, 2018). Observations of the lidar ratio at these two wavelengths for all important aerosol types (e.g., urban haze, marine aerosol, biomass-burning smoke, desert dust) and frequently occurring mixtures of smoke pollution with mineral dust or marine particles with urban haze are a prerequisite to permit accurate aerosol profiling with CALIOP on a global scale.…”

Section: Introductionmentioning

confidence: 99%

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Depolarization and lidar ratios at 355, 532, and 1064 nm and microphysical properties of aged tropospheric and stratospheric Canadian wildfire smoke

et al. 2018

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Abstract. We present spectrally resolved optical and microphysical properties of western Canadian wildfire smoke observed in a tropospheric layer from 5–6.5 km height and in a stratospheric layer from 15–16 km height during a record-breaking smoke event on 22 August 2017. Three polarization/Raman lidars were run at the European Aerosol Research Lidar Network (EARLINET) station of Leipzig, Germany, after sunset on 22 August. For the first time, the linear depolarization ratio and extinction-to-backscatter ratio (lidar ratio) of aged smoke particles were measured at all three important lidar wavelengths of 355, 532, and 1064 nm. Very different particle depolarization ratios were found in the troposphere and in the stratosphere. The obviously compact and spherical tropospheric smoke particles caused almost no depolarization of backscattered laser radiation at all three wavelengths (<3 %), whereas the dry irregularly shaped soot particles in the stratosphere lead to high depolarization ratios of 22 % at 355 nm and 18 % at 532 nm and a comparably low value of 4 % at 1064 nm. The lidar ratios were 40–45 sr (355 nm), 65–80 sr (532 nm), and 80–95 sr (1064 nm) in both the tropospheric and stratospheric smoke layers indicating similar scattering and absorption properties. The strong wavelength dependence of the stratospheric depolarization ratio was probably caused by the absence of a particle coarse mode (particle mode consisting of particles with radius >500 nm). The stratospheric smoke particles formed a pronounced accumulation mode (in terms of particle volume or mass) centered at a particle radius of 350–400 nm. The effective particle radius was 0.32 µm. The tropospheric smoke particles were much smaller (effective radius of 0.17 µm). Mass concentrations were of the order of 5.5 µg m−3 (tropospheric layer) and 40 µg m−3 (stratospheric layer) in the night of 22 August 2017. The single scattering albedo of the stratospheric particles was estimated to be 0.74, 0.8, and 0.83 at 355, 532, and 1064 nm, respectively.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Depolarization and lidar ratios at 355, 532, and 1064 nm and microphysical properties of aged tropospheric and stratospheric Canadian wildfire smoke

et al. 2018

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“…Version 4 level 2 benefits from a number of major improvements relevant to the level 3 aerosol product. Most significantly, updated aerosol lidar ratios and aerosol subtyping corrections (Kim et al, 2018) will have the largest impact on σ and AOD reported by level 3 since these quantities are non-linear functions of lidar ratio (nearly linear at low optical depths). The overall structure of the level 3 aerosol profile product will 5 remain similar in terms of grid size and science data sets, but the quality filtering strategy described in this paper may change to account for modifications in version 4 level 2 processing.…”

Section: Discussionmentioning

confidence: 99%

CALIPSO lidar level 3 aerosol profile product: version 3 algorithm design

Tackett¹,

Winker²,

Getzewich³

et al. 2018

Preprint

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Abstract. The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) level 3 aerosol profile product reports globally-gridded, quality-screened monthly mean aerosol extinction profiles retrieved by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). This paper describes the quality screening and averaging methods used to 10 generate the version 3 product. The fundamental input data are CALIOP level 2 aerosol extinction profiles and layer classification information (aerosol, cloud, and clear-air). Prior to aggregation, the extinction profiles are quality-screened by a series of filters to reduce the impact of layer detection errors, layer classification errors, extinction retrieval errors, and biases due to an intermittent signal anomaly at the surface. The relative influence of these filters are compared in terms of sample rejection frequency, mean extinction, and mean AOD. The "extinction QC flag" filter is the most influential in 15 preventing high-biases in level 3 mean extinction, while the "misclassified cirrus fringe" filter is most aggressive at rejecting cirrus misclassified as aerosol. The impact of quality screening on monthly mean aerosol extinction is investigated globally and regionally. After applying quality filters, monthly mean AOD is reduced by −24 and −31 % for global ocean and global land, respectively, thus indicating the importance of quality screening.

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“…The CALIOP L3 aerosol profile monthly product creation is described by Tackett et al () and is provided at 2° latitudinal by 5° longitudinal resolution. The current standard L3 products use version 3 L2 inputs; version 4 L2 products have been developed (Kim et al, ; Young et al, ), based on improved calibration (Getzewich et al, ; Kar et al, ) and addressing algorithmic issues which (in part) contributed to a low bias in version 3 data. However, version 4 inputs have not yet been incorporated into the standard L3 products.…”

Section: Comparison To Other Over‐water Satellite Data Setsmentioning

confidence: 99%

Validation of SOAR VIIRS Over‐Water Aerosol Retrievals and Context Within the Global Satellite Aerosol Data Record

et al. 2018

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This study validates aerosol properties retrieved using a Satellite Ocean Aerosol Retrieval (SOAR) algorithm applied to Visible Infrared Imaging Radiometer Suite (VIIRS) measurements, from Version 1 of the VIIRS Deep Blue data set. SOAR is the over-water complement to the over-land Deep Blue algorithm and has two processing paths: globally, 95% of pixels are processed with the full retrieval algorithm, while the 5% of pixels in shallow or turbid (mostly coastal) waters are processed with a backup algorithm. Aerosol Robotic Network (AERONET) data are used to validate and compare the midvisible (550 nm) aerosol optical depth (AOD), Ångström exponent (AE), and fine mode fraction of AOD at 550 nm (FMF). AOD uncertainty is shown to be approximately ±(0.03 + 10%) for the full and ±(0.03 + 15%) for the backup algorithms, with a small positive median bias around 0.02. When AOD is below about 0.2, the AE and FMF have small negative offsets from AERONET around −0.15 and −0.04, respectively. For higher AOD, AE is less offset and the magnitudes of differences versus AERONET are about ±0.2 and ±0.14, respectively. Aerosol-type classifications provided by SOAR are found to be reasonable, matching optical-based classifications from AERONET over 80% of the time. Spatial and temporal patterns of AOD and AE are also compared with those of other contemporary over-water satellite aerosol data sets; dependent on region, the satellite data sets show varying levels of consistency, with SOAR broadly in-family, and the largest discrepancies in regions with persistent heavy cloud cover.Plain Language Summary Aerosols are small particles in the atmosphere like desert dust, volcanic ash, smoke, industrial haze, and sea spray. Understanding them is important for applications such as hazard avoidance, air quality and human health, and climate studies. Satellite instruments provide an important tool to study aerosol loading over the world. However, individual satellites do not last forever and newer satellites often have improved capabilities compared to older ones. This paper evaluates an extension of an algorithm, originally designed to monitor aerosols from an older satellite instrument, to a new satellite instrument called Visible Infrared Imaging Radiometer Suite. The evaluation is performed by comparing to ground truth data which are part of the National Aeronautics and Space Administration's global Aerosol Robotic Network, as well as to other satellite-based aerosol data sets from different spaceborne instruments.

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The CALIPSO Version 4 Automated Aerosol Classification and Lidar Ratio Selection Algorithm

Cited by 74 publications

References 71 publications

Depolarization and lidar ratios at 355, 532, and 1064 nm and microphysical properties of aged tropospheric and stratospheric Canadian wildfire smoke

Depolarization and lidar ratios at 355, 532, and 1064 nm and microphysical properties of aged tropospheric and stratospheric Canadian wildfire smoke

CALIPSO lidar level 3 aerosol profile product: version 3 algorithm design

Validation of SOAR VIIRS Over‐Water Aerosol Retrievals and Context Within the Global Satellite Aerosol Data Record

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