Automatic Identification of Clear-Air Echoes Based on Millimeter-wave Cloud Radar Measurements

Abstract

Millimeter-wave cloud radar (MMCR) provides the capability of detecting the features of micro particles inside clouds and describing the internal microphysical structure of the clouds. Therefore, MMCR has been widely applied in cloud observations. However, due to the influence of non-meteorological factors such as insects, the cloud observations are often contaminated by non-meteorological echoes in the clear air, known as clear-air echoes. It is of great significance to automatically identify the clear-air echoes in order to extract effective meteorological information from the complex weather background. The characteristics of clear-air echoes are studied here by combining data from four devices: an MMCR, a laser-ceilometer, an L-band radiosonde, and an all-sky camera. In addition, a new algorithm, which includes feature extraction, feature selection, and classification, is proposed to achieve the automatic identification of clear-air echoes. The results show that the recognition algorithm is fairly satisfied in both simple and complex weather conditions. The recognition accuracy can reach up to 95.86% for the simple cases when cloud echoes and clear-air echoes are separate, and 88.38% for the complicated cases when low cloud echoes and clear-air echoes are mixed.

摘要

毫米波云雷达 (MMCR) 不仅能够探测到云中微小粒子的特征信息, 还可以获取云内的微物理结构, 所以在云的观测领域得到了广泛应用. 但是, 由于诸如昆虫之类的非气象因素的影响, 云观测通常会被晴空中的非气象回波污染, 这被称为晴空回波. 如何在这种复杂天气背景下消除晴空回波的干扰, 并从雷达回波中提取有用气象信息, 具有重要研究意义和实用价值. 通过结合以下四个设备的数据来研究晴空回波的特性: MMCR, 激光云高仪, L 波段探空仪和全天空成像仪. 此外, 提出了一种新的算法, 该算法包括特征提取, 特征选择和特征筛选, 以实现晴空回波的自动识别. 结果表明, 在简单和复杂的天气条件下, 该识别算法都令人满意. 在云回波和晴空回波分开的简单情况下, 识别精度可以达到 95.86%, 在低云回波和晴空回波混合在一起的复杂情况下, 识别精度可以达到 88.38%.