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Doppler radar echo characteristics of “train effect” for the widespread rainstorm on 19 June 2010 in Hunan

Tang Yao

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Abstract

Using conventional meteorological observational data,mesoscale automatic weather station data and Doppler radar data,the rainstorm event occurred in a large area in Hunan Province from June 18 to 20,2010 is analyzed,and the emphasis is on the analysis of Doppler radar echo characteristics oftrain effect.The results are as follows.(1) The deep moist layer is the vapor source of high efficiency precipitation and the vertical wind shear in mid-lower level makes a contribution to the better organizing convection system,so that the strong precipitation lasts for a longer time leading to a heavy rainstorm.(2) The large area precipitation echo(greater than or equal to 40 dBz) with low center of mass and high efficiency is passing from the north of Hunan continuously making thetrain effectto lead to the rainstorm and even heavy rainfall in a large area north to the central Hunan.(3) The radial velocity characteristics with cold and warm advection superposed on convergence,meso-cyclone and low level jet make for the long maintenance oftrain effect.(4) The timely identification of both strong precipitation echo and thetrain effectand the estimation of persistent time of thetrain effectare beneficial to warn and forecast rainstorm accurately and in time.

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What this paper is about

Using conventional meteorological observational data,mesoscale automatic weather station data and Doppler radar data,the rainstorm event occurred in a large area in Hunan Province from June 18 to 20,2010 is analyzed,and the emphasis is on the analysis of Doppler radar echo characteristics oftrain effect.The results are as follows.(1) The deep moist layer is the vapor source of high efficiency precipitation and the vertical wind shear in mid-lower level makes a contribution to the better organizing convection system,so that the strong precipitation lasts for a longer time leading to a heavy rainstorm.(2) The large area precipitation echo(greater than or equal to 40 dBz) with low center of mass and high efficiency is passing from the north of Hunan continuously making thetrain effectto lead to the rainstorm and even heavy rainfall in a large area north to the central Hunan.(3) The radial velocity characteristics with cold and warm advection superposed on convergence,meso-cyclone and low level jet make for the long maintenance oftrain effect.(4) The timely identification of both strong precipitation echo and thetrain effectand the estimation of persistent time of thetrain effectare beneficial to warn and forecast rainstorm accurately and in time.

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Available abstract

Using conventional meteorological observational data,mesoscale automatic weather station data and Doppler radar data,the rainstorm event occurred in a large area in Hunan Province from June 18 to 20,2010 is analyzed,and the emphasis is on the analysis of Doppler radar echo characteristics oftrain effect.The results are as follows.(1) The deep moist layer is the vapor source of high efficiency precipitation and the vertical wind shear in mid-lower level makes a contribution to the better organizing convection system,so that the strong precipitation lasts for a longer time leading to a heavy rainstorm.(2) The large area precipitation echo(greater than or equal to 40 dBz) with low center of mass and high efficiency is passing from the north of Hunan continuously making thetrain effectto lead to the rainstorm and even heavy rainfall in a large area north to the central Hunan.(3) The radial velocity characteristics with cold and warm advection superposed on convergence,meso-cyclone and low level jet make for the long maintenance oftrain effect.(4) The timely identification of both strong precipitation echo and thetrain effectand the estimation of persistent time of thetrain effectare beneficial to warn and forecast rainstorm accurately and in time.

Key concepts: Mesoscale meteorology, Precipitation, Doppler radar, Meteorology, Radar, Advection, Wind shear, Environmental science

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