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Impact of doppler radar wind in simulating the intensity and propagation of rainbands associated with mesoscale convective complexes using MM5-3DVAR system

机译:多普勒雷达风对使用MM5-3DVAR系统模拟中尺度对流复合体相关雨带强度和传播的影响

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Pre-monsoon rainfall around Kolkata (northeastern part of India) is mostly of convective origin as 80% of the seasonal rainfall is produced by Mesoscale Convective Systems (MCS). Accurate prediction of the intensity and structure of these convective cloud clusters becomes challenging, mostly because the convective clouds within these clusters are short lived and the inaccuracy in the models initial state to represent the mesoscale details of the true atmospheric state. Besides the role in observing the internal structure of the precipitating systems, Doppler Weather Radar (DWR) provides an important data source for mesoscale and microscale weather analysis and forecasting. An attempt has been made to initialize the storm-scale numerical model using retrieved wind fields from single Doppler radar. In the present study, Doppler wind velocities from the Kolkata Doppler weather radar are assimilated into a mesoscale model, MM5 model using the three-dimensional variational data assimilation (3DVAR) system for the prediction of intense convective events that occurred during 0600 UTC on 5 May and 0000 UTC on 7 May, 2005. In order to evaluate the impact of the DWR wind data in simulating these severe storms, three experiments were carried out. The results show that assimilation of Doppler radar wind data has a positive impact on the prediction of intensity, organization and propagation of rain bands associated with these mesoscale convective systems. The assimilation system has to be modified further to incorporate the radar reflectivity data so that simulation of the microphysical and thermodynamic structure of these convective storms can be improved.
机译:加尔各答(印度东北部)附近的季风前降雨主要来自对流,因为80%的季节性降雨是由中尺度对流系统(MCS)产生的。这些对流云团的强度和结构的准确预测变得具有挑战性,这主要是因为这些对流云团中的对流云寿命短,并且模型初始状态中的误差不代表真实大气状态的中尺度细节。多普勒天气雷达(DWR)除了在观测降水系统的内部结构中发挥作用外,还为中尺度和微尺度天气分析和预报提供了重要的数据源。已经尝试使用从单个多普勒雷达获取的风场来初始化风暴尺度数值模型。在本研究中,将来自加尔各答多普勒天气雷达的多普勒风速同化为中尺度模型MM5模型,该模型使用三维变分数据同化(3DVAR)系统预测5月5日0600 UTC期间发生的强对流事件和0000 UTC(2005年5月7日)。为了评估DWR风数据对模拟这些强风暴的影响,进行了三个实验。结果表明,多普勒雷达风数据的同化对与这些中尺度对流系统有关的雨带强度,组织和传播的预测具有积极影响。必须进一步修改同化系统,以纳入雷达反射率数据,以便可以改善对流风暴的微物理和热力学结构的仿真。

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