Access the full text.
Sign up today, get DeepDyve free for 14 days.
Hongping Liu, V. Chandrasekar (2000)
Classification of Hydrometeors Based on Polarimetric Radar Measurements: Development of Fuzzy Logic and Neuro-Fuzzy Systems, and In Situ VerificationJournal of Atmospheric and Oceanic Technology, 17
E. Gorgucci, G. Scarchilli, V. Chandrasekar, P. Meischner, M. Hagen (1998)
Intercomparison of Techniques to Correct for Attenuation of C-Band Weather Radar SignalsJournal of Applied Meteorology, 37
Karen Andsager, K. Beard, Neil Laird (1999)
Laboratory Measurements of Axis Ratios for Large RaindropsJournal of the Atmospheric Sciences, 56
Timothy Smyth, A. Illingworth (1998)
Correction for attenuation of radar reflectivity using polarization dataQuarterly Journal of the Royal Meteorological Society, 124
V. Bringi, V. Chandrasekar, N. Balakrishnan, D. Zrnic (1990)
An Examination of Propagation Effects in Rainfall on Radar Measurements at Microwave FrequenciesJournal of Atmospheric and Oceanic Technology, 7
John Hubbert, V. Bringi, D. Brunkow (2003)
Studies of the Polarimetric Covariance Matrix. Part I: Calibration MethodologyJournal of Atmospheric and Oceanic Technology, 20
H. Al-Khatib (1979)
Differential reflectivity and its use in the radar measurement of rainfall
D. Zrnic, V. Melnikov, J. Carter (2005)
Calibrating Differential Reflectivity on the WSR-88DJournal of Atmospheric and Oceanic Technology, 23
D. Atlas (2002)
RADAR CALIBRATION: SOME SIMPLE APPROACHESBulletin of the American Meteorological Society, 83
A. Ryzhkov, S. Giangrande, V. Melnikov, T. Schuur (2005)
Calibration Issues of Dual-Polarization Radar MeasurementsJournal of Atmospheric and Oceanic Technology, 22
G. Scarchilli, E. Gorgucci, V. Chandrasekar, A. Dobaie (1996)
Self-consistency of polarization diversity measurement of rainfallIEEE Trans. Geosci. Remote. Sens., 34
K. Beard, C. Chuang (1987)
A New Model for the Equilibrium Shape of RaindropsJournal of the Atmospheric Sciences, 44
T. Seliga, V. Bringi, H. Al-khatib (1979)
Differential Reflectivity Measurements in Rain: First ExperimentsIEEE Transactions on Geoscience Electronics, 17
Professor Bringi, V. Chandrasekar (2001)
Polarimetric Doppler Weather Radar: Principles and Applications
K. Khac, F. Zanghi, P. Tabary (2004)
Radar-disdrometer comparison
K. Aydin, Yang Zhao, T. Seliga (1989)
Rain-induced attenuation effects on C-band dual-polarization meteorological radarsIEEE Transactions on Geoscience and Remote Sensing, 27
E. Gorgucci, G. Scarchilli, V. Chandrasekar (1999)
A procedure to calibrate multiparameter weather radar using properties of the rain mediumIEEE Trans. Geosci. Remote. Sens., 37
E. Gorgucci, G. Scarchilli, V. Chandrasekar (1992)
Calibration of radars using polarimetric techniquesIEEE Trans. Geosci. Remote. Sens., 30
C. Ulbrich, D. Atlas (1998)
Rainfall Microphysics and Radar Properties: Analysis Methods for Drop Size SpectraJournal of Applied Meteorology, 37
B. Efron, R. Tibshirani (1994)
An Introduction to the Bootstrap
The conventional technique for calibrating Z dr using natural scatterers is based on vertical-looking observations. In some operational weather radar, this method is not applicable because of mechanical constraints that prohibit vertical measurement or choices in the scanning strategies. A technique for calibrating Z dr based on properties of rain returns is proposed and analyzed. The technique is based on an examination of properties of differential reflectivity measurements collected at increasing elevations. Differential reflectivity observed in rain decreases with increasing elevation due to the increasing view angle. Using the hypothesis of uniform microphysical profiles below the bright band, deviations of the profile of differential reflectivity with elevation with respect to the theoretical profile can be used to detect and quantify the presence of a bias on differential reflectivity. To apply this concept in the presence of a nonuniform microphysical profile, the contribution of vertical changes in microphysics to Z dr variation in height is also accounted for. An error parameter associated with the estimated Z dr bias can be used as a quality indicator of the bias estimation; it allows definition of a criterion based on a threshold of root-mean-square error that permits acceptance or rejection of a Z dr bias estimation obtained with the proposed method. The technique is demonstrated using data collected by an operational weather radar at Arpa Piemonte (Italy) and evaluated using independent disdrometer measurement. Results show that under certain conditions discussed in the paper, this method can provide Z dr calibration within an accuracy of 0.1 dB.
Journal of Atmospheric and Oceanic Technology – American Meteorological Society
Published: Jun 13, 2007
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.