Intercomparison of aerosol measurements performed with multi-wavelength Raman lidars, automatic lidars and ceilometers in the framework of INTERACT-II campaign

Abstract. Following the previous efforts of INTERACT (INTERcomparison of Aerosol and Cloud Tracking), the INTERACT-II campaign used multi-wavelength Raman lidar measurements to assess the performance of an automatic compact micro-pulse lidar (MiniMPL) and two ceilometers (CL51 and CS135) in providing reliable information about optical and geometric atmospheric aerosol properties. The campaign took place at the CNR-IMAA Atmospheric Observatory (760  m a . s . l . ; 40.60 ∘  N, 15.72 ∘  E) in the framework of ACTRIS-2 (Aerosol Clouds Trace gases Research InfraStructure) H2020 project. Co-located simultaneous measurements involving a MiniMPL, two ceilometers and two EARLINET multi-wavelength Raman lidars were performed from July to December 2016. The intercomparison highlighted that the MiniMPL range-corrected signals (RCSs) show, on average, a fractional difference with respect to those of CNR-IMAA Atmospheric Observatory (CIAO) lidars ranging from 5 to 15 % below 2.0  km  a.s.l. (above sea level), largely due to the use of an inaccurate overlap correction, and smaller than 5 % in the free troposphere. For the CL51, the attenuated backscatter values have an average fractional difference with respect to CIAO lidars   20–30 % below 3  km and larger above. The variability of the CL51 calibration constant is within ± 46 %. For the CS135, the performance is similar to the CL51 below 2.0  km a . s . l . , while in the region above 3  km a . s . l . the differences are about ± 40 %. The variability of the CS135 normalization constant is within ± 47 %. Finally, additional tests performed during the campaign using the CHM15k ceilometer operated at CIAO showed the clear need to investigate the CHM15k historical dataset (2010–2016) to evaluate potential effects of ceilometer laser fluctuations on calibration stability. The number of laser pulses shows an average variability of 10 % with respect to the nominal power which conforms to the ceilometer specifications. Nevertheless, laser pulses variability follows seasonal behavior with an increase in the number of laser pulses in summer and a decrease in winter. This contributes to explain the dependency of the ceilometer calibration constant on the environmental temperature hypothesized during INTERACT.

[1]  Josef Gasteiger,et al.  Correction of water vapor absorption for aerosol remote sensing with ceilometers , 2015 .

[2]  David D. Turner,et al.  Full-Time, Eye-Safe Cloud and Aerosol Lidar Observation at Atmospheric Radiation Measurement Program Sites: Instruments and Data Analysis , 2013 .

[3]  V. Freudenthaler,et al.  Depolarization ratio profiling at several wavelengths in pure Saharan dust during SAMUM 2006 , 2009 .

[4]  W. Thomas,et al.  What is the benefit of ceilometers for aerosol remote sensing? An answer from EARLINET , 2014 .

[5]  K. Liou Influence of Cirrus Clouds on Weather and Climate Processes: A Global Perspective , 1986 .

[6]  V. Freudenthaler,et al.  EARLINET Single Calculus Chain – technical – Part 1: Pre-processing of raw lidar data , 2015 .

[7]  Jeremy Coupland,et al.  Determination of overlap in lidar systems. , 2011, Applied optics.

[8]  Ina Mattis,et al.  EARLINET Single Calculus Chain – technical – Part 2: Calculation of optical products , 2016 .

[9]  Yu Gu,et al.  Cirrus cloud simulations using WRF with improved radiation parameterization and increased vertical resolution , 2011 .

[10]  R. Engelmann,et al.  An overview of the first decade of Polly NET : an emerging network of automated Raman-polarization lidars for continuous aerosol profiling , 2016 .

[11]  Vincenzo Cuomo,et al.  CIAO: the CNR-IMAA advanced observatory for atmospheric research , 2010 .

[12]  V. Freudenthaler,et al.  EARLINET: towards an advanced sustainable European aerosol lidar network , 2014 .

[13]  Yu Gu,et al.  Technical note: Fu–Liou–Gu and Corti–Peter model performance evaluation for radiative retrievals from cirrus clouds , 2016 .

[14]  K. Sassen,et al.  On the radiative properties of contrail cirrus , 1998 .

[15]  V. Freudenthaler,et al.  EARLINET instrument intercomparison campaigns: overview on strategy and results , 2015 .

[16]  E. O'connor,et al.  A Technique for Autocalibration of Cloud Lidar , 2004 .

[17]  Martial Haeffelin,et al.  Recommendations for processing atmospheric attenuated backscatter profiles from Vaisala CL31 ceilometers , 2016 .

[18]  R. Draxler,et al.  NOAA’s HYSPLIT Atmospheric Transport and Dispersion Modeling System , 2015 .

[19]  G. Pappalardo,et al.  Ceilometer aerosol profiling versus Raman lidar in the frame of the INTERACT campaign of ACTRIS , 2014 .

[20]  Yu Gu,et al.  Impact of varying lidar measurement and data processing techniques in evaluating cirrus cloud and aerosol direct radiative effects , 2018 .

[21]  Albert Mendoza,et al.  Novel polarization-sensitive micropulse lidar measurement technique. , 2007, Optics express.

[22]  L. Mona,et al.  Stratospheric AOD after the 2011 eruption of Nabro volcano measured by lidars over the Northern Hemisphere , 2012 .

[23]  Volker Freudenthaler,et al.  The telecover test: A quality assurance tool for the optical part of a lidar system , 2008 .