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Development of a neural network based algorithm for rainfall estimation from radar observations

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dc.contributor.authorChandrasekar, V., author
dc.contributor.authorXiao, Rongrui, author
dc.contributor.authorIEEE, publisher
dc.date.accessioned2007-01-03T08:10:57Z
dc.date.available2007-01-03T08:10:57Z
dc.date.issued1997
dc.description.abstractRainfall estimation based on radar measurements has been an important topic in radar meteorology for more than four decades. This research problem has been addressed using two approaches, namely a) parametric estimates using reflectivity-rainfall relation (Z-R relation) or equations using multiparameter radar measurements such as reflectivity, differential reflectivity, and specific propagation phase, and b) relations obtained by matching probability distribution functions of radar based estimates and ground observations of rainfall. In this paper we introduce a neural network based approach to address this problem by taking into account the three-dimensional (3-D) structure of precipitation. A three-layer perceptron neural network is developed for rainfall estimation from radar measurements. The neural network is trained using the radar measurements as the input and the ground raingage measurements as the target output. The neural network based estimates are evaluated using data collected during the Convection and Precipitation Electrification (CaPE) experiment conducted over central Florida in 1991. The results of the evaluation show that the neural network can be successfully applied to obtain rainfall estimates on the ground based on radar observations. The rainfall estimates obtained from neural network are shown to be better than those obtained from several existing techniques. The neural network based rainfall estimate offers an alternate approach to the rainfall estimation problem, and it can be implemented easily in operational weather radar systems.
dc.format.mediumborn digital
dc.format.mediumarticles
dc.identifier.bibliographicCitationXiao, Rongrui and V. Chandrasekar, Development of a Neural Network Based Algorithm for Rainfall Estimation from Radar Observations, IEEE Transactions on Geoscience and Remote Sensing 35, no. 1 (January 1997): 160-171.
dc.identifier.urihttp://hdl.handle.net/10217/68078
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartofFaculty Publications
dc.rights©1997 IEEE.
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.subjectradar rainfall estimation
dc.subjectneural networks
dc.subjectmultiparameter radar
dc.titleDevelopment of a neural network based algorithm for rainfall estimation from radar observations
dc.typeText

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