rl: Raman Lidar

The Raman Lidar (RL) is an active, ground-based, laser remote-sensing instrument that provides height- and time-resolved measurements of water-vapor mixing ratio, temperature, aerosol, and cloud optical properties. The RL operates in the UV and is sensitive to both molecular and aerosol backscatter.

The RL works by transmitting short pulses of UV laser light into the atmosphere. As the light propagates, a small fraction of the light energy is scattered back to the lidar transceiver where it is collected and recorded as a time-resolved signal. From the delay between the outgoing pulse and the backscattered signal, the instrument infers the distance to the scattering volume.

As the name implies, the RL makes use of the Raman effect in which light is inelastically scattered by atmospheric N2, O2 and H2O molecules. The ARM RL uses a number of narrow-band detection channels specifically tuned to sense the Raman backscatter from these molecules. Several other detection channels are configured to measure elastically backscattered light from atmospheric aerosol. The raw signals from these detection channels are combined and processed to yield measurements of water vapor mixing ratio, temperature, aerosol backscatter coefficient, extinction, and depolarization ratio.

Measurements

Locations

  • Fixed
  • AMF1
  • AMF2
  • AMF3

Related Publications

2016

Weckwerth TM, K Weber, DD Turner, and SM Spuler. 2016. "Validation of a Water Vapor Micropulse Differential Absorption Lidar (DIAL)." Journal of Atmospheric and Oceanic Technology, 33(11), 10.1175/jtech-d-16-0119.1. ONLINE.

Van Weverberg K, IA Boutle, CJ Morcrette, and RK Newsom. 2016. "Towards retrieving critical relative humidity from ground-based remote-sensing observations." Quarterly Journal of the Royal Meteorological Society, 142(700), 10.1002/qj.2874. ONLINE.

Wulfmeyer V and D Turner. 2016. Land-Atmosphere Feedback Experiment (LAFE) Science Plan. Ed. by Robert Stafford, DOE ARM Climate Research Facility. DOE/SC-ARM-16-038.

Deng M, GG Mace, Z Wang, and E Berry. 2016. "CloudSat 2C-ICE product update with a new Z(e) parameterization in lidar-only region." Journal of Geophysical Research: Atmospheres, 120(23), 10.1002/2015jd023600.

2015

Thorsen TJ and Q Fu. 2015. "CALIPSO-inferred aerosol direct radiative effects: Bias estimates using ground-based Raman lidars." Journal of Geophysical Research: Atmospheres, 120(23), 10.1002/2015jd024095.

Thorsen TJ, Q Fu, RK Newsom, DD Turner, and JM Comstock. 2015. "Automated Retrieval of Cloud and Aerosol Properties from the ARM Raman Lidar. Part I: Feature Detection." Journal of Atmospheric and Oceanic Technology, 32(11), 10.1175/jtech-d-14-00150.1. ONLINE.

Hicks M and R Sakai. 2015. "The Evaluation of a New Method to Detect Mixing Layer Heights Using Lidar Observations." Journal of Atmospheric and Oceanic Technology, 32(11), 10.1175/jtech-d-14-00103.1.

Thorsen TJ and Q Fu. 2015. "Automated Retrieval of Cloud and Aerosol Properties from the ARM Raman Lidar. Part II: Extinction." Journal of Atmospheric and Oceanic Technology, 32(11), 10.1175/jtech-d-14-00178.1. ONLINE.

Lamer K and P Kollias. 2015. "Observations of fair-weather cumuli over land: Dynamical factors controlling cloud size and cover." Geophysical Research Letters, 42(20), 10.1002/2015gl064534.

Klein PM, TA Bonin, JF Newman, DD Turner, PB Chilson, CE Wainwright, WG Blumberg, S Mishra, M Carney, EP Jacobsen, S Wharton, and RK Newsom. 2015. "LABLE: A Multi-Institutional, Student-Led, Atmospheric Boundary Layer Experiment." Bulletin of the American Meteorological Society, 96(10), 10.1175/bams-d-13-00267.1. ONLINE.


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