A Study on Typhoon Rainfall Echo Velocity Estimation Using the Advection-Based Lagrangian Eulerian Regression Algorithm
Date Issued
2014
Date
2014
Author(s)
Liu, Chen-Hsin
Abstract
In this research, we conduct a method to estimate the moving velocity field using the parameters of the regression function by comparing the radar echo image pairs in adjacent time. The regression function is built from advection equation in polar coordinate, with an assumption that the system velocity of typhoon can be represented by Fourier series. The purpose is to forecast precipitation with the estimated moving velocity fields.
The radar echo data in Central Weather Bureau is separated by ten minutes in time and resolution fixed in space. Typhoon behavior is often unable to meet the CFL condition under such data density. This limits the ability of the regression model to estimate the correct velocity field.
The estimation method shifts the typhoon features, and is conducted by two parts. The first part is similar to method of Tracking Radar Echo by Correlation (TREC), utilizing Lagrangian scheme, test the displacement by try-and-error method, to track the rough overall shift.
The second part is performed after the system is satisfying CFL condition, an Eulerian scheme utilizing advection equation to perform regression, estimate the coefficients of the detailed Fourier velocity function. The system velocity is the summation of the rough overall shifting velocity and the detailed velocity obtained from regression. This method is named Advection Based Lagrangian-Eulerian Regression (ABLER).
In this research, the algorithm of our method is verified with observing system experiments (OSE), the data of composed 2-D Gaussian image and simulation results of the WRF model in 2013 Soulik typhoon event are used in the verification.
Subjects
洪水預報
颱風降雨
降雨預報
即時預報
雷達回波
雨胞追蹤
Type
thesis
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