The main focus of our research is the development and testing of the ability to retrieve 2-component vector wind fields from a eye-safe, scanning elastic backscatter lidars. Funding from our first award (NSF AGS 0924407) enabled us to compare vector components retrieved from the cross-correlation technique to vector components measured by tower-mounted sonic anemometers between 10 and 30 m AGL. Funding from our second award (NSF AGS 1228464) enabled us to retrieve vectors with a new wavelet-based optical flow motion estimation algorithm and compare results with velocity estimates from cross-correlation and winds measured independently by Doppler lidar between 50 m and 150 m AGL. The second award also supported a significant field experiment at the CSU Chico University Farm from June 2013 to January 2014. A supplemental award on AGS 1228464 allowed us to test the ability of the technique to retrieve the wind field over the ocean in March 2015. Our most recent award (NSF AGS 2054969) will utilize this unique observational capability to test new theories on the structure of surface layer turbulence.
A full list of the CSU Chico Atmospheric Lidar Research Group publications can be found on our Publications page. However, the following list contains the papers most relevant to the longer history of this general technique:
Mayor, S. D., P. Dérian, C. F. Mauzey, S. M. Spuler, P. Ponsardin, J. Pruitt, D. Ramsey, and N. S. Higdon, 2016: Comparison of an analog direct detection and a micropulse aerosol lidar at 1.5-microns wavelength for wind field observations---with first results over the ocean. J. Appl. Remote Sens. 10, 016031, doi: 10.1117/1.JRS.10.016031.
Hamada, M., P. Dérian, C. F. Mauzey, and S. D. Mayor, 2016: Optimization of the cross-correlation algorithm for two-component wind field estimation from single aerosol lidar data and comparison with Doppler lidar, J. Atmos. Ocean. Technol. 33, 81-101.
Dérian, P., C. F. Mauzey, and S. D. Mayor, 2015: Wavelet-based optical flow for two-component wind field estimation from single aerosol lidar data, J. Atmos. Ocean. Technol., 32, 1759-1778.
Mayor, S. D., J. P. Lowe, and C. F. Mauzey, 2012: Two-component horizontal aerosol motion vectors in the atmospheric surface layer from a cross-correlation algorithm applied to elastic backscatter lidar data, J. Atmos. Ocean. Technol., 29, 1585-1602.
Mayor, S. D. and E. W. Eloranta, 2001 Two-dimensional vector wind fields from volume imaging lidar data. J. Appl. Meteor., 40, 1331¿1346.
Piironen, A. and E. W. Eloranta, 1995: An accuracy analysis of the wind profiles calculated from Volume Imaging Lidar data. J. Geophys. Res., 100, D12, 25559-25567.
Schols, J. L. and E. W. Eloranta, 1992: The calculation of area-averaged vertical profiles of the horizontal wind velocity from volume-imaging lidar data. J. Geophys. Res., 97, 18 395-18 407.
Kolev, I., O. Parvanov, and B. Kaprielov, 1988: Lidar determination of winds by aerosol inhomogeneities: motion velocity in the planetary boundary layer, Appl. Opt., 27, 2524-2531.
Hooper, W. P. and E. W. Eloranta, 1986: Lidar measurements of wind in the planetary boundary layer: the method, accuracy and results from joint measurements with radiosonde and kytoon. J. Clim. Appl. Meteor., 25, 990-1001.
Sasano, Y., H. Hirohara, T. Yamasaki, H. Shimizu, N. Takeuchi, and T. Kawamura, 1982: Horizontal wind vector determination from the displacement of aerosol distribution patterns observed by a scanning lidar. J. Appl. Meteor., 21, 1516-1523.
Kunkel, K. E., E. W. Eloranta, and J. A. Weinman, 1980: Remote determination of winds, turbulence spectra and energy dissipation rates in the boundary layer from lidar measurements. J. Atmos. Sci., 37, 978-985.
Sroga, J. T., E. W. Eloranta, and T. Barber, 1980: Lidar measurements of wind velocity profiles in the boundary layer. J. Appl. Meteor., 19, 598-605.
Eloranta, E. W., J. M. King, and J. A. Weinman, 1975: The determination of wind speeds in the boundary layer by monostatic lidar. J. Appl. Meteor., 14, 1485-1489.