Abstract
Estimating the rainfall from Radar observation plays an important role in the hydrological research. The Radar Rainfall plays a fundamental role in weather modeling and forecasting applications. Doppler Weather Radar (DWR) is used estimating the rainfall within 120 km from the Radar station. Rainfall intensity data obtained from the Surface Rainfall Intensity (SRI) product of DWR has been validated with the rain gauges located at Automatic Weather Station (AWS) data. Image processing methods such as edge detection and color identification are used to extract the rainfall from the SRI product. Time series rainfall over a particular location is compared with the AWS data using statistical parameters like correlation coefficient and Squared Pearson coefficient. The experimental results convey that the proposed method yields the high amount of accuracy. Graphical User Interface is developed to extract the point rainfall and time series rainfall over different locations within the range of Radar.
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Acknowledgements
We are thankful to Mr. Kannan from IMD Chennai, Mr. Yesubabu from NARL Gadanki, and Mr. M. S. Arunachalam from IIT Chennai, who helped us in understanding the DWR images and deriving the algorithm.
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Anil Kumar, P., Anuradha, B. (2019). Estimation of Precipitation from the Doppler Weather Radar Images. In: Pandian, D., Fernando, X., Baig, Z., Shi, F. (eds) Proceedings of the International Conference on ISMAC in Computational Vision and Bio-Engineering 2018 (ISMAC-CVB). ISMAC 2018. Lecture Notes in Computational Vision and Biomechanics, vol 30. Springer, Cham. https://doi.org/10.1007/978-3-030-00665-5_21
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DOI: https://doi.org/10.1007/978-3-030-00665-5_21
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