应用深度神经网络探测降水和雷暴的可能区域

IF 1.4 4区地球科学 Q4 METEOROLOGY & ATMOSPHERIC SCIENCES

Russian Meteorology and Hydrology Pub Date : 2024-06-27 DOI:10.3103/s1068373924040058

V. V. Chursin, A. A. Kostornaya

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引用次数: 0

摘要

摘要介绍了一种利用人工神经网络（ANN），特别是深度神经网络对降水和雷暴区进行概率识别的方法。从卫星数据中获取的温度和湿度垂直剖面图被用作初始数据。利用西伯利亚地区的地面观测数据对人工神经网络的计算结果进行了验证。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Application of Deep Neural Networks for Detecting Probable Areas of Precipitation and Thunderstorms

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Application of Deep Neural Networks for Detecting Probable Areas of Precipitation and Thunderstorms

Abstract

A method for the probabilistic identification of the precipitation and thunderstorm zones using artificial neural networks (ANNs), in particular, deep neural networks is described. The vertical profiles of temperature and humidity retrieved from satellite data are used as initial data. The ANN calculations have been validated using the ground-based observations in the Siberian region.

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来源期刊

Russian Meteorology and Hydrology METEOROLOGY & ATMOSPHERIC SCIENCES-

CiteScore

1.70

自引率

28.60%

发文量

审稿时长

4-8 weeks

期刊介绍： Russian Meteorology and Hydrology is a peer reviewed journal that covers topical issues of hydrometeorological science and practice: methods of forecasting weather and hydrological phenomena, climate monitoring issues, environmental pollution, space hydrometeorology, agrometeorology.