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Polarization lidar: An extended three-signal calibration approach

2019, Jimenez, Cristofer, Ansmann, Albert, Engelmann, Ronny, Haarig, Moritz, Schmidt, Jörg, Wandinger, Ulla

We present a new formalism to calibrate a threesignal polarization lidar and to measure highly accurate height profiles of the volume linear depolarization ratios under realistic experimental conditions. The methodology considers elliptically polarized laser light, angular misalignment of the receiver unit with respect to the main polarization plane of the laser pulses, and cross talk among the receiver channels. A case study of a liquid-water cloud observation demonstrates the potential of the new technique. Long-term observations of the calibration parameters corroborate the robustness of the method and the long-term stability of the three-signal polarization lidar. A comparison with a second polarization lidar shows excellent agreement regarding the derived volume linear polarization ratios in different scenarios: A biomass burning smoke event throughout the troposphere and the lower stratosphere up to 16 km in height, a dust case, and also a cirrus cloud case. © Author(s) 2019.

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Cloud-Aerosol Transport System (CATS) 1064 nm calibration and validation

2019, Pauly, Rebecca M., Yorks, John E., Hlavka, Dennis L., McGill, Matthew J., Amiridis, Vassilis, Palm, Stephen P., Rodier, Sharon D., Vaughan, Mark A., Selmer, Patrick A., Kupchock, Andrew W., Baars, Holger, Gialitaki, Anna

The Cloud-Aerosol Transport System (CATS) lidar on board the International Space Station (ISS) operated from 10 February 2015 to 30 October 2017 providing range-resolved vertical backscatter profiles of Earth's atmosphere at 1064 and 532 nm. The CATS instrument design and ISS orbit lead to a higher 1064 nm signal-to-noise ratio than previous space-based lidars, allowing for direct atmospheric calibration of the 1064 nm signals. Nighttime CATS version 3-00 data were calibrated by scaling the measured data to a model of the expected atmospheric backscatter between 22 and 26 km a.m.s.l. (above mean sea level). The CATS atmospheric model is constructed using molecular backscatter profiles derived from Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis data and aerosol scattering ratios measured by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). The nighttime normalization altitude region was chosen to simultaneously minimize aerosol loading and variability within the CATS data frame, which extends from 28 to −2 km a.m.s.l. Daytime CATS version 3-00 data were calibrated through comparisons with nighttime measurements of the layer-integrated attenuated total backscatter (iATB) from strongly scattering, rapidly attenuating opaque cirrus clouds. The CATS nighttime 1064 nm attenuated total backscatter (ATB) uncertainties for clouds and aerosols are primarily related to the uncertainties in the CATS nighttime calibration technique, which are estimated to be ∼9  %. Median CATS V3-00 1064 nm ATB relative uncertainty at night within cloud and aerosol layers is 7 %, slightly lower than these calibration uncertainty estimates. CATS median daytime 1064 nm ATB relative uncertainty is 21 % in cloud and aerosol layers, similar to the estimated 16 %–18 % uncertainty in the CATS daytime cirrus cloud calibration transfer technique. Coincident daytime comparisons between CATS and the Cloud Physics Lidar (CPL) during the CATS-CALIPSO Airborne Validation Experiment (CCAVE) project show good agreement in mean ATB profiles for clear-air regions. Eight nighttime comparisons between CATS and the PollyXT ground-based lidars also show good agreement in clear-air regions between 3 and 12 km, with CATS having a mean ATB of 19.7 % lower than PollyXT. Agreement between the two instruments (∼7 %) is even better within an aerosol layer. Six-month comparisons of nighttime ATB values between CATS and CALIOP also show that iATB comparisons of opaque cirrus clouds agree to within 19 %. Overall, CATS has demonstrated that direct calibration of the 1064 nm channel is possible from a space-based lidar using the atmospheric normalization technique.