CALIOP near-real-time backscatter products compared to EARLINET data

Abstract

Abstract. The expedited near-real-time Level 1.5 Cloud–Aerosol Lidar (Light Detection and Ranging) with Orthogonal Polarization (CALIOP) products were evaluated against data from the ground-based European Aerosol Research Lidar Network (EARLINET). Over a period of three years, lidar data from 48 CALIOP overpasses with ground tracks within a 100 km distance from an operating EARLINET station were deemed suitable for analysis and they included a valid aerosol classification type (e.g. dust, polluted dust, clean marine, clean continental, polluted continental, mixed and/or smoke/biomass burning). For the complete dataset comprising both PBL and FT data, the correlation coefficient was 0.86, and when separated into separate layers, the PBL and FT correlation coefficients were 0.6 and 0.85 respectively. The presence of FT layers with high attenuated backscatter led to poor agreement in PBL backscatter profiles between the CALIOP and EARLINET measurements and prompted a further analysis filtering out such cases. However, the correlation coefficient value for the complete dataset decreased marginally from 0.86 to 0.84 while the PBL coefficient increased from 0.6 up to 0.65 and the FT coefficient also decreased from 0.85 to 0.79. For specific aerosol types, the correlation coefficient between CALIOP backscatter profiles and ground-based lidar data ranged from 0.37 for polluted continental aerosol in the planetary boundary layer (PBL) to 0.57 for dust in the free troposphere (FT). The results suggest different levels of agreement based on the location of the dominant aerosol layer and the aerosol type.

Comparisons of aerosol backscatter using satellite and ground lidars: implications for calibrating and validating spaceborne lidar

“…Our comparisons in Fig. S2 do not show appreciably better agreement than in the previous statistical study 8 or in Level 1 data comparisons at EARLINET ground lidar stations. This finding suggested to us that there are some underlying problems in ground lidar Cal/Val methods, and prompted us to look into statistical limitations due to the CALIOP random noise.…”

“…In our experimantal study, we used 100-km averages of CALIOP profiles, as did Grigas et al . 8 . The protocol employed by previous Cal/Val studies with Level 1 data used 5-km averaged profiles, which would require the acquisition of such profiles on nearly 300 nighttime overpasses in order to achieve 2% uncertainty.…”

“…That assessment used a statistical appraisal of the agreement between CALIOP data and archived EARLINET (European Aerosol Research Lidar Network 7 ) profiles using three measures of comparison: the mean bias, the factor of exceedance, and the correlation coefficient, along with scatterplots. The scatterplots showed ground and satellite aerosol profile differences as large as ±50% 8 .…”

Multi‐Year CALIPSO Observations of Ubiquitous Elevated Aerosol Layer in the Free Troposphere Over South Asia: Sources and Formation Mechanism

“…The seasonal differences between MPL‐ and CALIOP‐ derived β ext are also in line with the previous studies (e.g., Misra et al., 2012). A large discrepancy between CALIOP and MPL and BLL measurements could be due to (a) spatial heterogeneity of aerosol properties and horizontal distance of sampled volumes (distinct air masses) between CALIOP and MPL/BLL (see above) and (b) CALIOP being download‐looking Lidar undergoes the signal loss in the PBL due to aerosol layer above, which limits CALIOP's capability to detect aerosols within PBL (Grigas et al., 2015; Mona et al., 2009) and (c) invalid aerosol subtypes classification (Grigas et al., 2015). However, the issues associated with large sensor‐to‐target distances, low SNR (Vaughan & Young, 2004), multiple scattering effects, an inaccurate value of the LRs (Ansmann, 2006), calibration and cloud‐screening algorithm (Kacenelenbogen et al., 2011) could be additional sources of error in the CALIOP β ext profiles.…”

Development of China’s first space-borne aerosol-cloud high-spectral-resolution lidar: retrieval algorithm and airborne demonstration

“…The regularization parameter could be smaller for space-borne lidar to constrain the impact of S p to a reasonable range during the iteration. Ground-based lidar networks or airborne lidar campaigns are often used for spaceborne lidar validation [45,46]. The original data of ACHSRL would be processed by the satellite research team, which is not available yet.…”