Chapter 4
Evaluation and Improvement of Radar Rainfall Data
Publication: Radar Rainfall Data Estimation and Use (MOP 139)
Abstract
This chapter summarizes using ground- and radar-based methods to measure rainfall. It focuses on evaluating and improving radar-based rainfall measurement by optimizing functional forms of reflectivity-rainfall relationships because radar rainfall estimates are prone to systematic and random errors. Ground-based measurements are the conventional and direct ways of measuring rainfall that are obtained by a network of rain gauges. The chapter discusses the use of Z-R relationships to estimate rainfall and commonly used Z-R relationships. Incorrectly specified Z-R relationships are less of a problem for non-real-time applications than for real-time data. Analysis of uncertainties in Z-R relationships for different storm events and selection of optimal exponents and coefficients requires selecting several rain gauges within a region. The chapter also presents some issues to consider when optimal or revised Z-R relationships are developed and used to estimate radar-based rainfall.
Get full access to this article
View all available purchase options and get full access to this chapter.
References
Collier, C. G. 1989. Applications of weather radar systems: A guide to uses of radar data in meteorology and hydrology. Hoboken, NJ: Wiley.
Ferreira, A., R. S. V. Teegavarapu, and C. Pathak. 2009. “Evaluation of optimal reflectivity-rainfall (Z-R) relationships for improved precipitation estimates.” EOS Abstract # H31D-0805. Washington, DC: American Geophysical Union.
Fulton, R., J. Breidenbach, D.-J. Seo, D. Miller, and T. O’Bannon. 1998. “The WSR-88D rainfall algorithm.” Weather Forecast. 13(2), 377-395.
Meischner, P. 2005. Weather Radar: Principles and advanced applications. New York: Springer.
Rabinovich, G. S. 2005. Measurement errors and uncertainties: Theory and practice. New York: Springer.
Raghavan, S. 2003. Radar meteorology. Dordrecht, the Netherlands: Springer. Atmospheric and Oceanographic Sciences Library.
Sene, K. 2009. Hydrometeorology: Forecasting and applications. New York: Springer.
Servuk, B., and S. Klemm. 1989. “Types of standard precipitation gages.” WMO/IAHS/ETH Int. Workshop on Precipitation Measurement. Geneva: World Meteorological Organization.
Strangeways, I. 2003. Measuring the natural environment. 2nd Ed. Cambridge, UK: Cambridge Univ. Press.
Strangeways, I. 2007. Precipitation: theory, measurement and distribution. Cambridge, UK: Cambridge Univ. Press.
Teegavarapu, R. S. V. 2012. “Assessment and evaluation of NEXRAD-based rainfall estimates in South Florida Water Management District.” SFWMD Rep., West Palm Beach, FL: SFWMD.
Teegavarapu, R. S. V., and C. Pathak. 2012. “Development of optimal Z-R relationships.” Weather Radar Hydrol. London: International Association of Hydrological Sciences, 75-80.
Vieux, B. E. 2001. Distributed hydrologic modeling using GIS. Dordrecht, the Netherlands: Kluwer Academic Water Science and Technology Library.
Wilson, J., and E. Brandes. 1979. “Radar measurement of rainfall: A summary.” Bull. Amer. Meteor. Soc. 60, 1048-1058.
WMO (World Meteorological Organization). 2009. Guide to hydrological practices: Volume II, Management of water resources and application to hydrological practices. WMO No. 168, Geneva: World Meteorological Organization.
Information & Authors
Information
Published In
Radar Rainfall Data Estimation and Use (MOP 139)
Pages: 53 - 58
Editors: Chandra S. Pathak, Ph.D., P.E., D.WRE, and Ramesh S. V. Teegavarapu, P.E.
ISBN (Print): 978-0-7844-1511-5
ISBN (Online): 978-0-7844-8176-9
Copyright
© 2018 American Society of Civil Engineers.
History
Published in print: Dec 2, 2018
Published online: Dec 4, 2018
ASCE Technical Topics:
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.