dl: Doppler Lidar

The Doppler lidar (DL) is an active remote-sensing instrument that provides range- and time-resolved measurements of the line-of-sight component of air velocity (i.e., radial velocity) and attenuated aerosol backscatter. The DL operates in the near-infrared and is sensitive to backscatter from atmospheric aerosol, which are assumed to be ideal tracers of atmospheric wind fields.

The DL works by transmitting short pulses of infrared laser light into the atmosphere. Atmospheric aerosols scatter a small fraction of that light energy back to the 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.

Coherent detection is used to measure the Doppler frequency shift of the backscatter signal. This is accomplished by mixing the backscatter signal with a reference laser beam (i.e., local oscillator) of known frequency. The onboard signal processor then determines the Doppler frequency shift from the spectrum of the mixed signal. The Doppler frequency shift and thus the radial air velocity is determined from the peak of the Doppler spectrum. The attenuated backscatter is determined from the energy content of the Doppler spectra.

The DL provides accurate measurements of radial velocity in regions of the atmosphere where aerosol concentrations are high enough to ensure good signal-to-noise ratio. Thus, valid data are usually limited to the atmospheric boundary layer where aerosol is ubiquitous. Valid measurements can also be obtained in elevated aerosol layers or in optically thin clouds above the boundary layer. Most of the ARM DLs have full upper-hemispheric scanning capability, enabling 3D mapping of turbulent flows in the atmospheric boundary layer. With the scanner pointed vertically, the DL provides height- and time-resolved measurements of vertical velocity.

Measurements

Locations

  • Fixed
  • AMF1
  • AMF2
  • AMF3

2020

Weckworth TM, S Spuler, and DD Turner. 2020. Micropulse Differential Absorption Lidar (MPD) Network Demonstration Field Campaign Report. Ed. by Robert Stafford, ARM user facility. DOE/SC-ARM-20-002.

Gustafson W, A Vogelmann, Z Li, X Cheng, K Dumas, S Endo, K Johnson, B Krishna, T Toto, and H Xiao. 2020. "The Large-Eddy Simulation (LES) Atmospheric Radiation Measurement (ARM) Symbiotic Simulation and Observation (LASSO) Activity for Continental Shallow Convection." Bulletin of the American Meteorological Society, , 10.1175/BAMS-D-19-0065.1. ONLINE.

Wainwright C, D Reynolds, and A Reynolds. 2020. "Linking Small-Scale Flight Manoeuvers and Density Profiles to the Vertical Movement of Insects in the Nocturnal Stable Boundary Layer." Scientific Reports, 10(1), 1019, 10.1038/s41598-020-57779-0.

2019

Chipilski H, X Wang, and D Parsons. 2019. "Impact of Assimilating PECAN Profilers on the Prediction of Bore-Driven Nocturnal Convection: A Multi-Scale Forecast Evaluation for the 6 July 2015 Case Study." Monthly Weather Review, , 10.1175/MWR-D-19-0171.1. ONLINE.

Lareau N. 2019. "Subcloud and Cloud-Base Latent Heat Fluxes during Shallow Cumulus Convection." Journal of the Atmospheric Sciences, , 10.1175/JAS-D-19-0122.1. ONLINE.

Zhang C, Y Wang, and M Xue. 2019. " Evaluation of an -ε and three other Boundary Layer Parameterization Schemes in the WRF Model over the Southeast Pacific and the Southern Great Plains ." Monthly Weather Review, , 10.1175/MWR-D-19-0084.1. ONLINE.

Floerchinger C, K McKain, T Bonin, J Peischl, S Biraud, C Miller, T Ryerson, S Wofsy, and C Sweeney. 2019. "Methane emissions from oil and gas production on the North Slope of Alaska." Atmospheric Environment, 218, 10.1016/j.atmosenv.2019.116985.

Zhou X and C Bretherton. 2019. "The Correlation of Mesoscale Humidity Anomalies with Mesoscale Organization of Marine Stratocumulus from Observations over the ARM Eastern North Atlantic Site." Journal of Geophysical Research: Atmospheres, 124(24), 10.1029/2019JD031056.

Kollias P, N Bharadwaj, E Clothiaux, K Lamer, M Oue, J Hardin, B Isom, I Lindenmaier, A Matthews, E Luke, S Giangrande, K Johnson, S Collis, J Comstock, and J Mather. 2019. "The ARM Radar Network: At the Leading-edge of Cloud and Precipitation Observations." Bulletin of the American Meteorological Society, , 10.1175/BAMS-D-18-0288.1. ONLINE.

Riihimaki LD, T Shippert, and DD Turner. 2019. Atmospheric Emitted Radiance Interferometer Optimal Estimation (AERIoe) Value-Added Product Report . Ed. by Robert Stafford, ARM user facility. DOE/SC-ARM-TR-234.


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