WeChat Mini Program
Old Version Features

    • Potential Method for Warning the First Lightning Flash of Isolated Thunderstorm Cells over South China

    Chuanhong Zhao,Yijun Zhang,Dong Zheng,Wen Yao,Sai Du

    WEATHER AND FORECASTING（2025）

    Chengdu Univ Informat Technol

    Cited 0|Views5
    Abstract
    This study improved the fi rst lightning fl ash (FLF) warning method of isolated thunderstorm cells in the warm season over South China. The S-band polarimetric radar and three independent lightning location systems provided 57 thunderstorm and 39 nonthunderstorm cells. The results indicated the median value of horizontal reflectivity below the melting layer when the cloud detected by the radar fi rst was a good indicator for forecasting the FLF with the longest lead time (threshold value <= 15 dBZ in this study). The algorithm produced 0.96-1 probability of detection (POD), 0.32-0.38 false alarm ratio (FAR), 0.63-0.66 critical skill index (CSI), and 12-21-min average lead time. Methods of minimum echo (20 dBZ) top height extending to-10 degrees C and the 35 dBZ at-10 degrees C were more accurately for warning the FLF but with a shorter lead time; the former algorithm resulted in 1 POD, 0.08-0.29 FAR, 0.71-0.92 CSI, and 5-9-min average lead time. The latter algorithm resulted in 1 POD, 0-0.06 FAR, 0.94-1 CSI, and 3-5.5-min average lead time. The fl uctuation of lead time depended on the FLF occurrence time. The differential reflectivity Z DR column and the height of graupel were not as effective as the reflectivity information on warning the FLF in this study. The results are expected to improve the FLF forecasting in considering accuracy and lead time within warm-season thunderstorm cells over South China based on the radar. SIGNIFICANCE STATEMENT: It is difficult to forecast the fi rst lightning fl ash (FLF) occurrence. While many methods are provided based on weather radars, the threshold values for hitting the start of lightning activity are dominated by mixed-phase ice microphysics, especially associated with graupel particles; therefore, to improve the lead time of the FLF nowcasting, usage of knowledge of warm-phase microphysics is possible. Fortunately, the latest discovery indicates the difference is recognizable in warm-phase microphysics during the fi rst radar echo between thunderstorms and nonthunderstorms based on the weather radar. This study utilized the fi nding to construct a method for the FLF warning. The early lead time and accuracy are considered comprehensively in this method. It is important for the FLF warning.
    More
    Translated text
    Key words
    Lightning,Thunderstorms,Radars/Radar observations,Nowcasting
    求助PDF
    上传PDF
    View via Publisher
    Bibtex
    AI Read Science
    AI Summary
    AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
    Example
    Background
    Key content
    Introduction
    Methods
    Results
    Related work
    Fund
    Key content
    • Pretraining has recently greatly promoted the development of natural language processing (NLP)
    • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
    • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
    • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
    • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
    Upload PDF to Generate Summary
    Must-Reading Tree
    Example
    Generate MRT to find the research sequence of this paper
    Data Disclaimer
    The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
    Chat Paper
    Summary is being generated by the instructions you defined