Automated Retrieval of Cloud and Aerosol Properties from the ARM Raman Lidar. Part I: Feature Detection

Details

• Journal Title:
  Journal of Atmospheric and Oceanic Technology
• Personal Author:
  Thorsen, Tyler J. ; Fu, Qiang ; Newsom, Rob K. ; Turner, David D. ; Comstock, Jennifer M.
• NOAA Program & Office:
  OAR (Oceanic and Atmospheric Research) ; NSSL (National Severe Storms Laboratory)
• Description:
  A feature detection and extinction retrieval (FEX) algorithm for the Atmospheric Radiation Measurement Program’s (ARM) Raman lidar (RL) has been developed. Presented here is Part I of the FEX algorithm: the detection of features including both clouds and aerosols. The approach of FEX is to use multiple quantities— scattering ratios derived using elastic and nitrogen channel signals from two fields of view, the scattering ratio derived using only the elastic channel, and the total volume depolarization ratio—to identify features using range-dependent detection thresholds. FEX is designed to be context sensitive with thresholds determined for each profile by calculating the expected clear-sky signal and noise. The use of multiple quantities provides complementary depictions of cloud and aerosol locations and allows for consistency checks to improve the accuracy of the feature mask. The depolarization ratio is shown to be particularly effective at detecting optically thin features containing nonspherical particles, such as cirrus clouds. Improvements over the existing ARM RL cloud mask are shown. The performance of FEX is validated against a collocated micropulse lidar and observations from the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite over the ARM Darwin, Australia, site. While the focus is on a specific lidar system, the FEX framework presented here is suitable for other Raman or high spectral resolution lidars.
• Keywords:
  Aerosols Clouds Lidar Observations
• Source:
  Journal of Atmospheric and Oceanic Technology, 32(11), 1977-1998
• DOI:
  https://doi.org/10.1175/JTECH-D-14-00150.1
• Document Type:
  Journal Article
• Rights Information:
  Other
• Compliance:
  Submitted
• Main Document Checksum:
  urn:sha256:b8c9c810830c87c1a042d42fda8ebcb469e87f474cd36e4625544ef1be349a53
• Download URL:
  https://repository.library.noaa.gov/view/noaa/32131/noaa_32131_DS1.pdf
• File Type:
  [PDF - 4.11 MB ]