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

Tackett, Jason L.; Winker, David M.; Getzewich, Brian; Vaughan, Mark; Young, Stuart A.; Kar, Jayanta

doi:10.5194/amt-2018-97

Cited by 20 publications

(32 citation statements)

References 35 publications

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“…Here, we use cloud‐free nighttime CALIOP data to minimize interference from clouds and Sun and select extinction profiles with good retrieval quality, that is, QC flag of 0, 1, 16, or 18, following recommendations by Winker et al (). We then separate aerosol from clouds according to the cloud‐aerosol‐discrimination (CAD) scores, for which the aerosol scores are typically in the range of −100 to −20 (Tackett et al, ; Winker et al, ). However, in this study we choose a more stringent CAD‐score range of −100 to −70 when selecting aerosol data (Yu, Tan, et al, ), which provides greater confidence in excluding possible cloud contamination.…”

Section: Models and Datamentioning

confidence: 99%

“…When the aerosol signal is weak, below CALIOP detection limit, no feature is detected in the level 2 atmospheric sounding, and the sample is classified as “clear‐air.” Aerosol extinction is set to zero (km −1 ) in the level 3 algorithm, whereas several studies have sought to characterize the optical depth of aerosol layers undetected by CALIOP (Tackett et al, , and references therein). For data identified as “clear‐air” in the present comparison, we adopt the approach used in generating the standard level 3 product (Tackett et al, ). However, this could cause a low bias in the averaged data because aerosols at low concentrations are missing, especially over the Pacific Ocean.…”

Section: Models and Datamentioning

confidence: 99%

“…In contrast, a clear and significant contribution of dust to total aerosol extinction ( f DOD > 0.5) appears at most altitudes over all subregions. The strong negative bias near the surface is due to a signal artifact that occurs when the level 1B attenuated backscatter becomes strongly negative, preceding a strongly scattering target such as the surface (Tackett et al, ; Winker et al, , ).…”

Section: Evaluation and Comparisons Of Model Simulations With Observamentioning

confidence: 99%

See 2 more Smart Citations

Asian and Trans‐Pacific Dust: A Multimodel and Multiremote Sensing Observation Analysis

Kim

Chin

et al. 2019

JGR Atmospheres

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Dust is one of the dominant aerosol types over Asia and the North Pacific Ocean, but quantitative estimation of dust distribution and its contribution to the total regional aerosol load from observations is challenging due to the presence of significant anthropogenic and natural aerosols and the frequent influence of clouds over the region. This study presents the dust aerosol distributions over Asia and the North Pacific using simulations from five global models that participated in the AeroCom phase II model experiments, and from multiple satellite remote sensing and ground‐based measurements of total aerosol optical depth and dust optical depth. We examine various aspects of aerosol and dust presence in our study domain: (1) the horizontal distribution, (2) the longitudinal gradient during trans‐Pacific transport, (3) seasonal variations, (4) vertical profiles, and (5) model‐simulated dust life cycles. This study reveals that dust optical depth model diversity is driven mostly by diversity in the dust source strength, followed by residence time and mass extinction efficiency.

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Section: Models and Datamentioning

confidence: 99%

Section: Models and Datamentioning

confidence: 99%

Section: Evaluation and Comparisons Of Model Simulations With Observamentioning

confidence: 99%

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Asian and Trans‐Pacific Dust: A Multimodel and Multiremote Sensing Observation Analysis

Kim

Chin

et al. 2019

JGR Atmospheres

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“…represent unconstrained retrievals which do not change the lidar ratio (0), constrained retrievals which derive an optimized lidar ratio (1), opaque layers for which the lidar ratio was not changed (16), and opaque layers where the lidar ratio was reduced to prevent the retrieval from diverging (18), respectively (Tackett et al, 2018). For 2007 to 2009, the total change in mean nighttime (daytime) CALIOP level 2 column AOD has increased from 0.084 (0.090) in V3 to 0.128 (0.126) in V4 ( Table 5).…”

mentioning

confidence: 99%

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

Kim¹,

Omar²,

Tackett³

et al. 2018

Preprint

Self Cite

131

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Abstract. The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) version 4.10 (V4) level 2 aerosol data products, released in November 2016, include substantial improvements to the aerosol subtyping and lidar ratio selection algorithms. These improvements are described along with resulting changes in aerosol optical depth (AOD). The most fundamental change in V4 level 2 aerosol products is a new algorithm to identify aerosol subtypes in the stratosphere. Four aerosol subtypes are introduced for the stratospheric aerosols: polar stratospheric aerosol (PSA), volcanic ash, sulfate/other, and smoke. The tropospheric aerosol subtyping algorithm was also improved by adding the following enhancements: (1) all aerosol subtypes are now allowed over polar regions, whereas the version 3 (V3) algorithm allowed only clean continental and polluted continental aerosols; (2) a new “dusty marine” aerosol subtype is introduced, representing mixtures of dust and marine aerosols near the ocean surface; and (3) the “polluted continental” and “smoke” subtypes have been renamed “polluted continental/smoke” and “elevated smoke”, respectively. V4 also revises the lidar ratios for clean marine, dust, clean continental, and elevated smoke subtypes. As a consequence of the V4 updates, the mean 532 nm AOD retrieved by CALIOP has increased by 0.044 (0.036) or 52 % (40 %) for nighttime (daytime). Lidar ratio revisions are the most influential factor for AOD changes from V3 to V4, especially for cloud-free skies. Preliminary validation studies show that the AOD discrepancies between CALIOP and AERONET/MODIS (ocean) are reduced in V4 compared to V3.

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“…The extinction coefficient profiles at 532nm are vertically integrated to estimate the Dust Optical Depth (DOD). The quality control procedure follows the CALIPSO L3 version 3 screening procedure [Tackett et al, 2018], and additional filters are applied to ensure the use of cloud-free profiles only [Marinou et al, 2017]. This product has been used to provide the three-dimensional distribution of dust and the dust transport pathways across northern Africa and Europe [Marinou et al, 2017], Asia , as well as in a synergistic approach with dust models for the description of severe events [Solomos et al, 2017] and impacts of dust on radiative transfer [Tsikerdekis et al, 2017].…”

Section: 2mentioning

confidence: 99%

Evaluation of the BSC-DREAM8b regional dust model using the 3D LIVAS-CALIPSO product

Konsta

Binietoglou

Gkikas

et al. 2018

Atmospheric Environment

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The ability of regional atmospheric models to accurately represent long-range transport of dust is crucial for describing dust effects on radiation and clouds and for reducing their uncertainties on these processes. The optimized CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) pure-dust product that provides the three-dimensional patterns of dust and its transport pathways is a unique tool that can address the aforementioned model's issues. In this study we use the CALIPSO dust extinction profiles as a tool for examining the performance of the regional dust model BSC-DREAM8b in space and time, for the period 2009-2013 over Northern Africa, the Mediterranean, Europe, Eastern North Atlantic and the Middle East. Our analysis suggests that the model overestimates the dust extinction coefficient above dust source regions in Sahara Desert especially at altitudes lower than 3km at about 0.04 km-1. We also found a slight underestimation of transported dust over Europe and Atlantic Ocean lower than 0.025km-1 of extinction coefficient values all along the vertical column. Over the Mediterranean dust is overestimated (~0.01km-1) in layers higher than 1 km height. Dust in the Middle East is significantly underestimated by the model (~0.05km-1) all along the vertical column especially during warm seasons. The study also provides an analysis of the CALIPSO limitations and uncertainties on the detection of strong dust activity contributing to the differences between the simulations and observations above the dust sources of Bodelé and Algeria.

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

Cited by 20 publications

References 35 publications

Asian and Trans‐Pacific Dust: A Multimodel and Multiremote Sensing Observation Analysis

Asian and Trans‐Pacific Dust: A Multimodel and Multiremote Sensing Observation Analysis

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

Evaluation of the BSC-DREAM8b regional dust model using the 3D LIVAS-CALIPSO product

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