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

2013 ◽  
Vol 13 (5) ◽  
pp. 2435-2444 ◽  
Author(s):  
S. Groß ◽  
M. Esselborn ◽  
F. Abicht ◽  
M. Wirth ◽  
A. Fix ◽  
...  

Abstract. 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.

2013 ◽  
Vol 6 (1) ◽  
pp. 1815-1858 ◽  
Author(s):  
S. P. Burton ◽  
R. A. Ferrare ◽  
M. A. Vaughan ◽  
A. H. Omar ◽  
R. R. Rogers ◽  
...  

Abstract. Aerosol classification products from the NASA Langley Research Center (LaRC) airborne High Spectral Resolution Lidar (HSRL-1) on the NASA B200 aircraft are compared with coincident V3.01 aerosol classification products from the CALIOP instrument on the CALIPSO satellite. For CALIOP, aerosol classification is a key input to the aerosol retrieval, and must be inferred using aerosol loading-dependent observations and location information. In contrast, HSRL-1 makes direct measurements of aerosol intensive properties, including the lidar ratio, that provide information on aerosol type. In this study, comparisons are made for 109 underflights of the CALIOP orbit track. We find that 62% of the CALIOP marine layers and 54% of the polluted continental layers agree with HSRL-1 classification results. In addition, 80% of the CALIOP desert dust layers are classified as either dust or dusty mix by HSRL-1. However, agreement is less for CALIOP smoke (13%) and polluted dust (35%) layers. Specific case studies are examined, giving insight into the performance of the CALIOP aerosol type algorithm. In particular, we find that the CALIOP polluted dust type is overused due to an attenuation-related depolarization bias. Furthermore, the polluted dust type frequently includes mixtures of dust plus marine aerosol. Finally, we find that CALIOP's identification of internal boundaries between different aerosol types in contact with each other frequently do not reflect the actual transitions between aerosol types accurately. Based on these findings, we give recommendations which may help to improve the CALIOP aerosol type algorithms.


2012 ◽  
Vol 5 (1) ◽  
pp. 73-98 ◽  
Author(s):  
S. P. Burton ◽  
R. A. Ferrare ◽  
C. A. Hostetler ◽  
J. W. Hair ◽  
R. R. Rogers ◽  
...  

Abstract. The NASA Langley Research Center (LaRC) airborne High Spectral Resolution Lidar (HSRL) on the NASA B200 aircraft has acquired extensive datasets of aerosol extinction (532 nm), aerosol optical depth (AOD) (532 nm), backscatter (532 and 1064 nm), and depolarization (532 and 1064 nm) profiles during 18 field missions that have been conducted over North America since 2006. The lidar measurements of aerosol intensive parameters (lidar ratio, depolarization, backscatter color ratio, and spectral depolarization ratio) are shown to vary with location and aerosol type. A methodology based on observations of known aerosol types is used to qualitatively classify the extensive set of HSRL aerosol measurements into eight separate types. Several examples are presented showing how the aerosol intensive parameters vary with aerosol type and how these aerosols are classified according to this new methodology. The HSRL-based classification reveals vertical variability of aerosol types during the NASA ARCTAS field experiment conducted over Alaska and northwest Canada during 2008. In two examples derived from flights conducted during ARCTAS, the HSRL classification of biomass burning smoke is shown to be consistent with aerosol types derived from coincident airborne in situ measurements of particle size and composition. The HSRL retrievals of AOD and inferences of aerosol types are used to apportion AOD to aerosol type; results of this analysis are shown for several experiments.


2013 ◽  
Vol 13 (5) ◽  
pp. 2487-2505 ◽  
Author(s):  
S. Groß ◽  
M. Esselborn ◽  
B. Weinzierl ◽  
M. Wirth ◽  
A. Fix ◽  
...  

Abstract. During four aircraft field experiments with the DLR research aircraft Falcon in 1998 (LACE), 2006 (SAMUM-1) and 2008 (SAMUM-2 and EUCAARI), airborne High Spectral Resolution Lidar (HSRL) and in situ measurements of aerosol microphysical and optical properties were performed. Altogether, the properties of six different aerosol types and aerosol mixtures – Saharan mineral dust, Saharan dust mixtures, Canadian biomass burning aerosol, African biomass burning mixture, anthropogenic pollution aerosol, and marine aerosol have been studied. On the basis of this extensive HSRL data set, we present an aerosol classification scheme which is also capable to identify mixtures of different aerosol types. We calculated mixing lines that allowed us to determine the contributing aerosol types. The aerosol classification scheme was supported by backward trajectory analysis and validated with in-situ measurements. Our results demonstrate that the developed aerosol mask is capable to identify complex stratifications with different aerosol types throughout the atmosphere.


2014 ◽  
Vol 7 (12) ◽  
pp. 4317-4340 ◽  
Author(s):  
R. R. Rogers ◽  
M. A. Vaughan ◽  
C. A. Hostetler ◽  
S. P. Burton ◽  
R. A. Ferrare ◽  
...  

Abstract. The Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument onboard the Cloud–Aerosol Lidar and Pathfinder Satellite Observations (CALIPSO) spacecraft has provided over 8 yr of nearly continuous vertical profiling of Earth's atmosphere. In this paper we investigate the V3.01 and V3.02 CALIOP 532 nm aerosol layer optical depth (AOD) product (i.e the AOD of individual layers) and the column AOD product (i.e., the sum AOD of the complete column) using an extensive database of coincident measurements. The CALIOP AOD measurements and AOD uncertainty estimates are compared with collocated AOD measurements collected with the NASA High Spectral Resolution Lidar (HSRL) in the North American and Caribbean regions. In addition, the CALIOP aerosol lidar ratios are investigated using the HSRL measurements. In general, compared with the HSRL values, the CALIOP layer AOD are biased high by less than 50% for AOD < 0.3 with higher errors for higher AOD. Less than 60% of the HSRL AOD measurements are encompassed within the CALIOP layer 1 SD uncertainty range (around the CALIOP layer AOD), so an error estimate is created to encompass 68% of the HSRL data. Using this new metric, the CALIOP layer AOD error is estimated using the HSRL layer AOD as ±0.035 ± 0.05 · (HSRL layer AOD) at night and ±0.05 ± 0.05 · (HSRL layer AOD) during the daytime. Furthermore, the CALIOP layer AOD error is found to correlate with aerosol loading as well as aerosol subtype, with the AODs in marine and dust layers agreeing most closely with the HSRL values. The lidar ratios used by CALIOP for polluted dust, polluted continental, and biomass burning layers are larger than the values measured by the HSRL in the CALIOP layers, and therefore the AODs for these types retrieved by CALIOP were generally too large. We estimated the CALIOP column AOD error can be expressed as ±0.05 ± 0.07 · (HSRL column AOD) at night and ±0.08 ± 0.1 · (HSRL column AOD) during the daytime. Multiple sources of error contribute to both positive and negative errors in the CALIOP column AOD, including multiple layers in the column of different aerosol types, lidar ratio errors, cloud misclassification, and undetected aerosol layers. The undetected layers were further investigated and we found that the layer detection algorithm works well at night, although undetected aerosols in the free troposphere introduce a mean underestimate of 0.02 in the column AOD in the data set examined. The decreased signal-to-noise ratio (SNR) during the daytime led to poorer performance of the layer detection. This caused the daytime CALIOP column AOD to be less accurate than during the nighttime, because CALIOP frequently does not detect optically thin aerosol layers with AOD < 0.1. Given that the median vertical extent of aerosol detected within any column was 1.6 km during the nighttime and 1.5 km during the daytime, we can estimate the minimum extinction detection threshold to be 0.012 km−1 at night and 0.067 km−1 during the daytime in a layer median sense. This extensive validation of level 2 CALIOP AOD products extends previous validation studies to nighttime lighting conditions and provides independent measurements of the lidar ratio; thus, allowing the assessment of the effect on the CALIOP AOD of using inappropriate lidar ratio values in the extinction retrieval.


2012 ◽  
Vol 12 (10) ◽  
pp. 26843-26869
Author(s):  
S. Groß ◽  
M. Esselborn ◽  
F. Abicht ◽  
M. Wirth ◽  
A. Fix ◽  
...  

Abstract. Airborne high spectral resolution lidar observations over Europe during the EUCAARI field experiment in May 2008 are analysed with respect to spatial distribution and optical properties of continental pollution aerosol. Continental aerosol is characterized by its depolarisation and lidar ratio. Mean values of 6%±1% for the particle linear depolarisation ratio, and 56 sr±6 sr for the lidar ratio were found for pollution aerosol. Both, lidar ratio and depolarisation ratio at 532 nm show virtually no variations for all analysed days during the measurement campaign.


2013 ◽  
Vol 6 (5) ◽  
pp. 1397-1412 ◽  
Author(s):  
S. P. Burton ◽  
R. A. Ferrare ◽  
M. A. Vaughan ◽  
A. H. Omar ◽  
R. R. Rogers ◽  
...  

Abstract. Aerosol classification products from the NASA Langley Research Center (LaRC) airborne High Spectral Resolution Lidar (HSRL-1) on the NASA B200 aircraft are compared with coincident V3.01 aerosol classification products from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument on the CALIPSO satellite. For CALIOP, aerosol classification is a key input to the aerosol retrieval, and must be inferred using aerosol loading-dependent observations and location information. In contrast, HSRL-1 makes direct measurements of aerosol intensive properties, including the lidar ratio, that provide information on aerosol type. In this study, comparisons are made for 109 underflights of the CALIOP orbit track. We find that 62% of the CALIOP marine layers and 54% of the polluted continental layers agree with HSRL-1 classification results. In addition, 80% of the CALIOP desert dust layers are classified as either dust or dusty mix byHSRL-1. However, agreement is less for CALIOP smoke (13%) and polluted dust (35%) layers. Specific case studies are examined, giving insight into the performance of the CALIOP aerosol type algorithm. In particular, we find that the CALIOP polluted dust type is overused due to an attenuation-related depolarization bias. Furthermore, the polluted dust type frequently includes mixtures of dust plus marine aerosol. Finally, we find that CALIOP's identification of internal boundaries between different aerosol types in contact with each other frequently do not reflect the actual transitions between aerosol types accurately. Based on these findings, we give recommendations which may help to improve the CALIOP aerosol type algorithms.


2011 ◽  
Vol 4 (5) ◽  
pp. 5631-5688 ◽  
Author(s):  
S. P. Burton ◽  
R. A. Ferrare ◽  
C. A. Hostetler ◽  
J. W. Hair ◽  
R. R. Rogers ◽  
...  

Abstract. The NASA Langley Research Center (LaRC) airborne High Spectral Resolution Lidar (HSRL) on the NASA B200 aircraft has acquired extensive datasets of aerosol extinction (532 nm), aerosol optical thickness (AOT) (532 nm), backscatter (532 and 1064 nm), and depolarization (532 and 1064 nm) profiles during 18 field missions that have been conducted over North America since 2006. The lidar measurements of aerosol intensive parameters (lidar ratio, depolarization, backscatter color ratio, and spectral depolarization ratio) are shown to vary with location and aerosol type. A methodology based on observations of known aerosol types is used to qualitatively classify the extensive set of HSRL aerosol measurements into eight separate types. Several examples are presented showing how the aerosol intensive parameters vary with aerosol type and how these aerosols are classified according to this new methodology. The HSRL-based classification reveals vertical variability of aerosol types during the NASA ARCTAS field experiment conducted over Alaska and northwest Canada during 2008. In two examples derived from flights conducted during ARCTAS, the HSRL classification of biomass burning smoke is shown to be consistent with aerosol types derived from coincident airborne in situ measurements of particle size and composition. The HSRL retrievals of AOT and inferences of aerosol types are used to apportion AOT to aerosol type; results of this analysis are shown for several experiments.


2018 ◽  
Vol 10 (12) ◽  
pp. 2003 ◽  
Author(s):  
James Churnside ◽  
Johnathan Hair ◽  
Chris Hostetler ◽  
Amy Scarino

Ocean lidar attenuation and scattering parameters were derived from a high-spectral-resolution lidar (HSRL) using two different retrieval techniques. The first used the standard HSRL retrieval, and the second used only the total backscatter channel and a perturbation retrieval (PR). The motivation is to evaluate differences between the two techniques that would affect the decision of whether to use a simple backscatter lidar or a more complex HSRL in future applications. For the data set investigated, the attenuation coefficient from the PR was an average of 11% lower than that from the HSRL. The PR estimate of the scattering parameter decreased with depth relative to the HSRL estimate, although the overall bias was zero as a result of the calibration procedure. Near the surface, the coefficient of variability in both estimates of attenuation and in HSRL estimates of scattering were around 5%, but that in the PR estimate of scattering was over 10%. At greater depths, the variability increases for all of the profile parameters. The correlation between the two estimates of attenuation coefficient was 0.7. The correlation between scattering parameters was > 0.8 near the surface, but decreased to 0.4 at a depth of around 20 m. Overall, the PR performed better relative to the HSRL in offshore waters than in nearshore waters.


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