Abstract Based on the relationship between lightning and thunderstorm microphysics, this paper aims to determine the averaged vertical profiles of polarimetric variables for different classes of lightning density according to the GLM grid and then evaluate the potential use of these profiles for data assimilation in models with high spatial and temporal resolutions. Polarimetric variables from an X-band radar located in Campinas-SP and data from the Brazilian Network were used to detect the microphysics properties and atmospheric discharges of clouds (GLM proxy). The main differences between the lightning density class-averaged profiles for the four variables of ZH, ZDR, KDP and ρHV were observed in the region above the melting layer. For the most intense lightning classes, the signatures associated with high concentrations of ice particles at high altitudes, the presence of supercooled drops above the freezing level and the occurrence of large and more oblate raindrops were observed. To analyze the possible use of reflectivity profiles as a way to indirectly assimilate GLM information into forecast models, two case studies were conducted using the Weather Research and Forecasting model. The analyses and forecasts obtained with the assimilation of radar data (reflectivity factor and Doppler winds) and with the indirect assimilation of GLM lightning density rates through mean reflectivity profiles were evaluated against a control run assimilating no data. Overall, the two assimilation experiments offered substantial improvements over the control run in terms of short-term forecasts of reflectivity patterns and storm motion. These encouraging results supports the ability of the GLM data to positively contribute to nowcasting and forecasting of convective-scale systems, especially over the vast regions of the South American continent currently suffering from limited and, even, an utter lack of observations.

中文翻译：

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GLM 在临近预报和数据同化中的潜在用途

摘要 基于闪电和雷暴微物理之间的关系，本文旨在根据 GLM 网格确定不同类别闪电密度的极化变量的平均垂直剖面，然后评估这些剖面在高密度模型中数据同化的潜在用途。空间和时间分辨率。来自 Campinas-SP 的 X 波段雷达的极化变量和来自巴西网络的数据用于检测云的微物理特性和大气放电（GLM 代理）。ZH、ZDR、KDP 和 ρHV 四个变量的闪电密度等级平均分布之间的主要差异在熔化层以上区域观察到。对于最强烈的闪电课程，观察到与高海拔冰粒浓度高、出现冰点以上过冷滴以及出现大而扁的雨滴相关的特征。为了分析可能使用反射率剖面作为将 GLM 信息间接同化到预测模型中的方法，使用天气研究和预测模型进行了两个案例研究。通过同化雷达数据（反射系数和多普勒风）和通过平均反射率剖面间接同化 GLM 闪电密度率获得的分析和预测，针对没有同化数据的控制运行进行了评估。全面的，在反射率模式和风暴运动的短期预测方面，这两个同化实验比控制运行提供了实质性的改进。这些令人鼓舞的结果支持 GLM 数据对对流尺度系统的临近预报和预测做出积极贡献的能力，特别是在目前遭受有限甚至完全缺乏观测的南美洲大陆的广大地区。