Spatial distribution and optical properties of Saharan dust observed by
                        airborne high spectral resolution lidar during SAMUM 2006

Esselborn, Michael; Wirth, Martin; Fix, Andreas; Weinzierl, Bernadett; Rasp, Katharina; Tesche, Matthias; Petzold, A.

doi:10.1111/j.1600-0889.2008.00394.x

Cited by 79 publications

(71 citation statements)

References 42 publications

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“…The HSRL receiver channel was already successfully deployed during former field campaigns. A detailed technical description of the HSRL system and a presentation of its measurements can be found by Esselborn et al (2008) and Esselborn et al (2009). Typically, the system allows signal integration times as short as a few seconds with an acceptable statistical error of less than 5 % in the backscatter data.…”

Section: Dlr Falcon Hsrlmentioning

confidence: 99%

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

et al. 2013

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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

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Section: Dlr Falcon Hsrlmentioning

confidence: 99%

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

et al. 2013

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“…Important information about the vertical distributions of aerosols has long been available from ground-based (e.g., Huang et al, 2010;Johnson et al, 2008;Papayannis et al, 2005;Matthias et al, 2004;Reid et al, 2003;Campbell et al, 2002;Welton et al, 2000Welton et al, , 2001 and airborne (e.g., Rogers et al, 2009;Esselborn et al, 2009;Reid et al, 2003;McGill et al, 2002;Browell et al, 1997;Browell et al, 1983) lidar systems, but by their nature these systems have limited spatial and temporal coverage. The launch of the space-based Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite on 28 April 2006 vastly increased the spatial and temporal coverage of aerosol and cloud vertical profiles ).…”

Section: E P Nowottnick Et Al: Global Aerosol Model Evaluation Usimentioning

confidence: 99%

Use of the CALIOP vertical feature mask for evaluating global aerosol models

Nowottnick

Colarco

Welton³

et al. 2015

Atmos. Meas. Tech.

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“…This variability in the dust lidar ratio was also observed by Müller et al (2007), who present lidar ratios of 55 and 59 sr for Saharan dust, but indicate lidar ratios of 38 and 35 sr for Saudi Arabia and the Gobi desert. Esselborn et al (2009) also measured dust lidar ratios in Morocco using a high spectral resolution lidar (HSRL), and found large variability (38-50 sr) that they attributed the dust advection from different source regions.…”

Section: Final Comments About Dustmentioning

confidence: 99%

Comparison of CALIPSO aerosol optical depth retrievals to AERONET measurements, and a climatology for the lidar ratio of dust

et al. 2012

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Abstract. We compared CALIPSO column aerosol optical depths at 0.532 µm to measurements at 147 AERONET sites, synchronized to within 30 min of satellite overpass times during a 3-yr period. We found 677 suitable overpasses, and a CALIPSO bias of −13 % relative to AERONET for the entire data set; the corresponding absolute bias is −0.029, and the standard deviation of the mean (SDOM) is 0.014. Consequently, the null hypothesis is rejected at the 97 % confidence level, indicating a statistically significant difference between the datasets. However, if we omit CALIPSO columns that contain dust from our analysis, the relative and absolute biases are reduced to −3 % and −0.005 with a standard error of 0.016 for 449 overpasses, and the statistical confidence level for the null hypothesis rejection is reduced to 27 %. We also analyzed the results according to the six CALIPSO aerosol subtypes and found relative and absolute biases of −29 % and −0.1 for atmospheric columns that contain the dust subtype exclusively, but with a relatively high correlation coefficient of R = 0.58; this indicates the possibility that the assumed lidar ratio (40 sr) for the CALIPSO dust retrievals is too low. Hence, we used the AERONET size distributions, refractive indices, percent spheres, and forward optics code for spheres and spheroids to compute a lidar ratio climatology for AERONET sites located in the dust belt. The highest lidar ratios of our analysis occur in the non-Sahel regions of Northern Africa, where the median lidar ratio at 0.532 µm is 55.4 sr for 229 retrievals. Lidar ratios are somewhat lower in the African Sahel (49.7 sr for 929 retrievals), the Middle East (42.6 sr for 489 retrievals), and Kanpur, India (43.8 sr for 67 retrievals). We attribute this regional variability in the lidar ratio to the regional variability of the real refractive index of dust, as these two parameters are highly anti-correlated (correlation coefficients range from −0.51 to −0.85 for the various regions). The AERONET refractive index variability is consistent with the variability of illite concentration in dust across the dust belt.

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Spatial distribution and optical properties of Saharan dust observed by airborne high spectral resolution lidar during SAMUM 2006

Cited by 79 publications

References 42 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

Use of the CALIOP vertical feature mask for evaluating global aerosol models

Comparison of CALIPSO aerosol optical depth retrievals to AERONET measurements, and a climatology for the lidar ratio of dust

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