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Nowcasting lightning flash rate and peak wind gusts associated with severe thunderstorms using remotely sensed TRMM-LIS data

机译:使用遥感TRMM-LIS数据临近预报雷暴和与强雷暴有关的狂风

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摘要

The momentous weather hazards during the pre-monsoon season (April-May) over Kolkata (22° 32' N, 88° 20' E), India, is mostly due to lightning flashes and surface wind gusts associated with severe thunderstorms. A multi-layer perceptron (MLP) model is developed to forecast the lightning flash rate and peak wind gusts which accompany severe thunderstorms. Meteorological parameters derived from radiosonde weather observations from 1998 to 2009 are taken as input whereas lightning data from the Lightning Imaging Sensor (LIS) and wind gusts from a ground-based observatory are taken as the target output parameters. The skill of the MLP model is compared with the multiple linear regression (MLR) analysis method, and it is observed that the MLP model provides better and more accurate forecasts than the MLR analysis method. The results also reveal that the forecast accuracy is more for surface wind gusts than for the lightning flash rate, both during training and validation of the model. The MLP model forecast is validated with the India Meteorological Department (IMD) weather observations as well as Doppler weather radar and satellite imagery of 2008 and 2009 thunderstorms.
机译:印度加尔各答(22°32'N,88°20'E)季风前季节(4月至5月)的瞬时天气危害主要归因于雷暴和与强雷暴有关的地面阵风。建立了多层感知器(MLP)模型来预测伴随严重雷暴的雷电闪现速率和峰值阵风。从1998年至2009年的探空仪气象观测得出的气象参数被用作输入,而来自闪电成像传感器(LIS)的闪电数据和来自地面天文台的阵风被用作目标输出参数。将MLP模型的技巧与多元线性回归(MLR)分析方法进行了比较,可以观察到MLP模型比MLR分析方法提供了更好,更准确的预测。结果还显示,在模型训练和验证期间,地面阵风的预报准确性要比雷电闪动的预报准确性高。 MLP模型的预测已通过印度气象局(IMD)的气象观测以及2008年和2009年雷暴的多普勒天气雷达和卫星图像的验证。

著录项

  • 来源
    《International journal of remote sensing》 |2013年第6期|1576-1590|共15页
  • 作者单位

    Department of Atmospheric Sciences, University of Calcutta, Kolkata 700019, India;

    Department of Atmospheric Sciences, University of Calcutta, Kolkata 700019, India;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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