Aerosol classification by airborne high spectral resolution lidar observations

Groß, Silke; Esselborn, Michael; Weinzierl, Bernadett; Wirth, Martin; Fix, Andreas; Petzold, A.

doi:10.5194/acpd-12-25983-2012

Cited by 9 publications

(19 citation statements)

References 74 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The main goal of this study was to determine lidar derived optical properties for European pollution aerosols, in particular the particle linear depolarization ratio and the lidar ratio. Both quantities are independent from the aerosol load and, in combination, have the potential to distinguish different aerosol types as was recently shown by Groß et al (2011Groß et al ( , 2012 and Burton et al (2012).…”

Section: Discussionmentioning

confidence: 92%

“…This paper focuses on the analysis of the airborne HSRL measurements of the aerosol lidar ratio and the particle linear depolarisation ratio taken during the first half of EUCAARI-LONGREX (6 May to 14 May). Both quantities only depend on the aerosol type and can be used to classify different types of aerosol (Groß et al, 2011(Groß et al, , 2012Burton et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Airborne high spectral resolution lidar observation of pollution aerosol during EUCAARI-LONGREX

et al. 2013

Self Cite

View full text Add to dashboard Cite

Airborne high spectral resolution lidar observations over Europe during the EUCAARI-LONGREX field experiment in May 2008 are analysed with respect to the optical properties of continental pollution aerosol. Continental pollution aerosol is characterized by its depolarisation and lidar ratio. Over all, the measurements of the lidar ratio and the particle linear depolarization ratio of pollution aerosols provide a narrow range of values. Therefore, this data set allows for a distinct characterization of the aerosol type "pollution aerosol" and thus is valuable both to distinguish continental pollution aerosol from other aerosol types and to determine mixtures with other types of aerosols

show abstract

Section: Discussionmentioning

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Airborne high spectral resolution lidar observation of pollution aerosol during EUCAARI-LONGREX

et al. 2013

Self Cite

View full text Add to dashboard Cite

show abstract

“…Both L2‐1 and L2‐2 were likely influenced by aged smoke from BB due to their relatively low backscatter and low depolarization. The linear depolarization of aged smoke can be lower than fresh smoke [ Burton et al, ; Gro ß et al, ] because the scavenging and deposition processes remove some of the large and nonspherical particles during transport. However, ozone enhancements due to BB alone will rarely reach 30 ppbv [e.g., Real et al, ; Parrington et al ., ] even when ozone production is very efficient at a low NO x concentration [ Hudman et al, ].…”

Section: Resultsmentioning

confidence: 99%

Summertime tropospheric ozone enhancement associated with a cold front passage due to stratosphere‐to‐troposphere transport and biomass burning: Simultaneous ground‐based lidar and airborne measurements

et al. 2017

View full text Add to dashboard Cite

Stratosphere‐to‐troposphere transport (STT) and biomass burning (BB) are two important natural sources for tropospheric ozone that can result in elevated ozone and air‐quality episode events. High‐resolution observations of multiple related species are critical for complex ozone source attribution. In this article, we present an analysis of coinciding ground‐based and airborne observations, including ozone lidar, ozonesonde, high spectral resolution lidar (HSRL), and multiple airborne in situ measurements, made on 28 and 29 June 2013 during the Southeast Nexus field campaign. The ozone lidar and HSRL reveal detailed ozone and aerosol structures as well as the temporal evolution associated with a cold front passage. The observations also captured two enhanced (+30 ppbv) ozone layers in the free troposphere (FT), which were determined from this study to be caused by a mixture of BB and stratospheric sources. The mechanism for this STT is tropopause folding associated with a cutoff upper level low‐pressure system according to the analysis of its potential vorticity structure. The depth of the tropopause fold appears to be shallow for this case compared to events observed in other seasons; however, the impact on lower tropospheric ozone was clearly observed. This event suggests that strong STT may occur in the southeast United States during the summer and can potentially impact lower troposphere during these times. Statistical analysis of the airborne observations of trace gases suggests a coincident influence of BB transport in the FT impacting the vertical structure of ozone during this case study.

show abstract

“…As demonstrated by Baars et al (), aerosol types can be identified by combining their Ångstrom exponent, lidar ratio, and depolarization ratio from multiwavelength HSRL or Raman‐polarization lidar measurements (Burton et al, ; Groß et al, ). Therefore, our study assumes known aerosol types for CCN retrievals for the sake of tackling other more challenging tasks in retrieving CCN profiles.…”

Section: Methodsmentioning

confidence: 99%

“…These can be retrieved from multiwavelength Raman lidar (Ansmann et al, ) or HSRL measurements (Shipley et al, ). Aerosol type, which can be identified from lidar measurements (Baars et al, ; Burton et al, ; Groß et al, ), provides the mean complex refractive index (Table ). Thus, retrieving six parameters ( σ f , N tf , r f , σ c , N tc , and r c ) for a bimodal size distribution from five known quantities ( β 355 , β 532 , β 1064 , α 355 , and α 532 ) is still an ill‐defined problem.…”

Section: Methodsmentioning

confidence: 99%

Retrieval of Cloud Condensation Nuclei Number Concentration Profiles From Lidar Extinction and Backscatter Data

Wang

et al. 2018

JGR Atmospheres

View full text Add to dashboard Cite

The vertical distribution of aerosols and their capability of serving as cloud condensation nuclei (CCN) are important for improving our understanding of aerosol indirect effects. Although ground‐based and airborne CCN measurements have been made, they are generally scarce, especially at cloud base where it is needed most. We have developed an algorithm for profiling CCN number concentrations using backscatter coefficients at 355, 532, and 1,064 nm and extinction coefficients at 355 and 532 nm from multiwavelength lidar systems. The algorithm considers three distinct types of aerosols (urban industrial, biomass burning, and dust) with bimodal size distributions. The algorithm uses look‐up tables, which were developed based on the ranges of aerosol size distributions obtained from the Aerosol Robotic Network, to efficiently find optimal solutions. CCN number concentrations at five supersaturations (0.07–0.80%) are determined from the retrieved particle size distributions. Retrieval simulations were performed with different combinations of systematic and random errors in lidar‐derived extinction and backscatter coefficients: systematic errors range from −20% to 20% and random errors are up to 15%, which fall within the typical error ranges for most current lidar systems. The potential of this algorithm to retrieve CCN concentrations is further evaluated through comparisons with surface‐based CCN measurements with near‐surface lidar retrievals. This retrieval algorithm would be valuable for aerosol‐cloud interaction studies for which virtually none has employed CCN at cloud base because of the lack of such measurements.

show abstract

Aerosol classification by airborne high spectral resolution lidar observations

Cited by 9 publications

References 74 publications

Airborne high spectral resolution lidar observation of pollution aerosol during EUCAARI-LONGREX

Airborne high spectral resolution lidar observation of pollution aerosol during EUCAARI-LONGREX

Summertime tropospheric ozone enhancement associated with a cold front passage due to stratosphere‐to‐troposphere transport and biomass burning: Simultaneous ground‐based lidar and airborne measurements

Retrieval of Cloud Condensation Nuclei Number Concentration Profiles From Lidar Extinction and Backscatter Data

Contact Info

Product

Resources

About