Access the full text.
Sign up today, get DeepDyve free for 14 days.
Peter Ay, R. Strauch (1998)
NOTES AND CORRESPONDENCE Reducing the Effect of Ground Clutter on Wind Profiler Velocity Measurements
H. Urkowitz, J. Nespor (1992)
Obtaining Spectral Moments By Discrete Fourier Transform With Noise removal In Radar Meteorology[Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium, 1
R. Chadwick (1986)
Wind profiler demonstration system
(1997)
Application of the prototype control , acquisition and signal processing engine for radars ( CASPER ) to wind profilers and RASS
P. Hildebrand, R. Sekhon (1974)
Objective Determination of the Noise Level in Doppler SpectraJournal of Applied Meteorology, 13
W. Angevine, S. Avery, W. Ecklund, D. Carter (1993)
Fluxes of Heat and Momentum Measured with a Boundary-Layer Wind Profiler Radar-Radio Acoustic Sounding System.Journal of Applied Meteorology, 32
(1995)
Radar remote sensing of scalar and velocity microturbulence in the convective boundary layer
Available from OFCM, 8455 Colesville Road, Suite 1500, Silver Spring
(1986)
Wind profiler demonstration network. Handbook for MAP
P. May, R. Strauch, K. Moran, W. Ecklund (1990)
Temperature sounding by RASS with wind profiler radars: a preliminary studyIEEE Transactions on Geoscience and Remote Sensing, 28
F. Harris (1978)
On the use of windows for harmonic analysis with the discrete Fourier transformProceedings of the IEEE, 66
J. Röttger, M. Larsen (1990)
UHF/VHF radar techniques for atmospheric research and wind profiler applications
M. Barth, R. Chadwick, D. Kamp (1994)
Data processing algorithms used by NOAA’s wind profiler demonstration networkAnnales Geophysicae, 12
J. Wilczak, R. Strauch, F. Ralph, B. Weber, D. Merritt, J. Jordan, D. Wolfe, L. Lewis, D. Wuertz, J. Gaynor, S. McLaughlin, R. Rogers, A. Riddle, T. Dye (1995)
Contamination of Wind Profiler Data by Migrating Birds: Characteristics of Corrupted Data and Potential SolutionsJournal of Atmospheric and Oceanic Technology, 12
M. Fischler, R. Bolles (1981)
Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartographyCommun. ACM, 24
Toru Sato, R. Woodman (1982)
Spectral parameter estimation of CAT radar echoes in the presence of fading clutterRadio Science, 17
(1998)
wind profilers: A review. Office of the Federal Coordinator for Meteorological Services and Supporting Research (OFCM) Rep. FCM-R14-1998
(1986)
Wind profiler demonstration network
W. Hocking (1997)
Recent advances in radar instrumentation and techniques for studies of the mesosphere, stratosphere, and troposphereRadio Science, 32
R. Doviak, D. Zrnic (1984)
Doppler Radar and Weather Observations
D. Merritt (1995)
Statistical averaging method for wind profiler doppler spectraJournal of Atmospheric and Oceanic Technology, 12
P. May, R. Strauch (1989)
An Examination of Wind Profiler Signal Processing AlgorithmsJournal of Atmospheric and Oceanic Technology, 6
E. Gossard, D. Wolfe, K. Moran, R. Paulus, K. Anderson, L. Rogers (1998)
Measurement of Clear-Air Gradients and Turbulence Properties with Radar Wind ProfilersJournal of Atmospheric and Oceanic Technology, 15
W. Hocking (1997)
System design, signal‐processing procedures, and preliminary results for the Canadian (London, Ontario) VHF atmospheric radarRadio Science, 32
M. Petitdidier, A. Sy, A. Garrouste, J. Delcourt (1997)
Statistical characteristics of the noise power spectral density in UHF and VHF wind profilersRadio Science, 32
Radar wind profilers (RWPs) sense the mean and turbulent motion of the clear air through Doppler shifts induced along several (3––5) upward-looking beams. RWP signals, like all radars signals, are often contaminated. The contamination is clearly evident in the associated Doppler spectra, and automatic routines designed to extract meteorological quantities from these spectra often yield inaccurate results. Much of the observed contamination is due to an aliasing of higher frequency signals into the clear-air portion of the spectrum and a broadening of the spectral contaminants caused by the relatively short time series used to generate Doppler spectra. In the past, this source of contamination could not be avoided because of limitations on the size and speed of RWP processing computers. Today’’s computers, however, are able to process larger amounts of data at greatly increased speeds. Here it is shown how standard and well-known spectral processing methods can be applied to significantly longer time series to reduce contamination in the radar spectra and thereby improve the accuracy and the reliability of meteorological products derived from RWP systems. In particular, spectral processing methods to identify and remove contamination that is often aliased into the clear-air portion of the spectrum are considered. Optimal techniques for combining multiple spectra to produce averaged spectra are also discussed.
Journal of Atmospheric and Oceanic Technology – American Meteorological Society
Published: Dec 26, 1997
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.