Dr. Ivan G. Dors Profile

Dr. Ivan G. Dors

at Univ of New Hampshire

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Author

Publications (2)

Proceedings Article | 21 March 2003 Paper

Performance and comparison of 532-nm and 355-nm groundwinds lidars

Michael Dehring, Carl Nardell, Jane Pavlich, Paul Hays, Ivan Dors

Proceedings Volume 4893, (2003) https://doi.org/10.1117/12.466675

KEYWORDS: Fabry–Perot interferometers, Aerosols, Neodymium, Telescopes, LIDAR, Doppler effect, Signal detection, Wind measurement, Charge-coupled devices, Optical filters

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Proceedings Article | 7 February 2003 Paper

Supporting the missions of the Mauna Kea Observatories with GroundWinds incoherent UV lidar measurements

Steven Businger, Tiziana Cherubini, I. Dors, J. McHugh, Robert McLaren, J. Moore, James Ryan, Carl Nardell

Proceedings Volume 4839, (2003) https://doi.org/10.1117/12.479588

KEYWORDS: Turbulence, LIDAR, Interferometers, Observatories, Telescopes, Aerosols, Fabry–Perot interferometers, Charge-coupled devices, Sensors, Wind measurement

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The recently commissioned GroundWinds LIDAR Observatory, based at ~3300 m on the slope of Mauna Loa, can measure altitude resolved line-of-sight wind velocities, turbulence power spectra, aerosol content and faint cirrus clouds among other things of interest to astronomers. The overarching goal of the GroundWinds program is to develop and demonstrate incoherent ultra-violet LIDAR technology for a future space-based system to measure the vertical structure of global winds from molecular backscatter. The LIDAR observatory employs spectral line profiling of incoherent backscattered 355 nm laser light. Rapid measurement of the Doppler shift (400 ns resolution) is accomplished by feeding the returned laser light into a combination of two Fabry-Perot etalons and collapsing the interference fringes into a 1-dimensional interference pattern using a conical optic. This allows the system to obtain the maximum signal-to-noise ratio and best vertical resolution given the performance of the CCD. Each measurement takes 10 s. The molecular return is strong up to 15-km altitude. The YAG laser is pulsed at 10 Hz, and each pulse is stretched to 50 ns; the average power dissipated is 5 W. The outgoing beam is expanded to match the field of view of the telescope. The Doppler shift as a function of altitude, measured along two lines of sight orthogonal to one another, is then used to determine the horizontal wind velocity as a function of altitude. A recent intercomparison campaign demonstrated the accuracy of the GroundWinds instrument. In addition to average wind measurements intended for global winds, the LIDAR can be operated with a short integration time and used to directly measure turbulence spectra over a range of elevations. The turbulence spectra are used to approximate the velocity turbulence parameter, C_v², and turbulent dissipation. A recent comparison with an independent measurement of C_T² has shown good agreement. Data from the incoherent LIDAR are used in a custom forecasting project (Mauna Kea Weather Center: http://hokukea.soest.hawaii.edu) that provides operational support for the world-class group of astronomical observatories located on the summit of Mauna Kea. The LIDAR data are used to help prepare wind and turbulence nowcasts/forecasts for the summit of Mauna Kea (~4000 m) and as input for an operational mesoscale numerical weather prediction model (MM5). Clear-air turbulence in both the free atmosphere and in the summit boundary layer causes phase distortions to incoming electromagnetic wave fronts, resulting in motion, intensity fluctuations (scintillation), and blurring of images obtained by ground-based telescopes. Astronomical parameters that quantify these effects are generically referred to as seeing. Seeing improves or degrades with changes in the vertical location and strength of turbulence as quantified by profiles of the refractive index structure function C_n². C_n² fluctuations usually occur at scales that are too small for routine direct measurement, but they can be parameterized from vertical gradients in wind, temperature, and moisture in our MM5 runs. Seeing at a particular wavelength is then calculated by vertically integrating the C_n² profile. LIDAR wind profiles represent an important data resource for nowcasting seeing, input for MM5 initial conditions and algorithm refinement, and for forecast verification.

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