doi:  10.3878/j.issn.1006-9895.1701.16170
Ka波段固态发射机体制云雷达和激光云高仪探测青藏高原夏季云底能力和效果对比分析

The Comparison of Cloud Base Observations with Ka-Band Solid-State Transmitter-Based Millimeter Wave Cloud Radar and Ceilometer in Summer over Tibetan Plateau
摘要点击 608  全文点击 499  投稿时间:2016-05-03  
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基金:  国家自然科学基金项目91337103、41375038,财政部/科技部公益性行业(气象)科研专项GYHY201406001
中文关键词:  云底探测  云雷达  激光云高仪  观测模式优化  青藏高原
英文关键词:  Cloud base observation  Cloud radar  Ceilometer  Operational mode improved  Tibetan Plateau
        
作者中文名作者英文名单位
吴翀WU Chong南京信息工程大学气象灾害预报预警与评估协同创新中心, 南京 210044
刘黎平LIU Liping中国气象科学研究院灾害天气国家重点实验室, 北京 100081;南京信息工程大学气象灾害预报预警与评估协同创新中心, 南京 210044
翟晓春ZHAI Xiaochun中国海洋大学, 青岛 266100
引用:吴翀,刘黎平,翟晓春.2017.Ka波段固态发射机体制云雷达和激光云高仪探测青藏高原夏季云底能力和效果对比分析[J].大气科学,41(4):659-672,doi:10.3878/j.issn.1006-9895.1701.16170.
Citation:WU Chong,LIU Liping,ZHAI Xiaochun.2017.The Comparison of Cloud Base Observations with Ka-Band Solid-State Transmitter-Based Millimeter Wave Cloud Radar and Ceilometer in Summer over Tibetan Plateau[J].Chinese Journal of Atmospheric Sciences (in Chinese),41(4):659-672,doi:10.3878/j.issn.1006-9895.1701.16170.
中文摘要:
      激光云高仪和云雷达是探测云底的两种设备,但其探测能力和探测结果有一定的差异,对比分析两种设备的测云效果有助于正确认识它们的探测优势,推进我国云雷达在云探测中的应用。本文提出了基于云雷达数据的云底和云顶高度分析方法,利用2014年夏季第三次青藏高原大气科学试验云雷达、激光雷达和激光云高仪数据,统计了三种设备探测青藏高原低云、中云和高云的云底高度偏差、探测率,分析了激光云高仪探测云底偏高的原因,根据探测结果提出了固态发射机体制雷达探测青藏高原低云的优化观测模式,模拟分析了探测效果。结果表明:(1)云雷达对高云的探测能力要明显优于激光云高仪,但其对低云的探测能力有待改进,激光云高仪探测云底下部的边界层内的云雷达回波信号可能是非云降水回波;低层云的遮挡作用明显降低了激光云高仪对多层云的观测能力;与激光云高仪相比,云雷达仍然会漏掉一些高云和中云。(2)激光云高仪探测的中云和高云的云底很多在云雷达回波内部,云雷达和激光云高仪观测的云底的时空对应关系比较差。(3)增大激光发射功率和优化固态发射机体制云雷达观测模式可提高云的观测能力,微波和激光雷达数据融合可全面了解不同类型云的宏观特征。这一工作为云雷达和激光雷达数据的应用,评估激光云高仪和云雷达探测青藏高原云的能力,讨论设计优化的云观测方案,为推进我国云观测技术的发展提供了重要参考依据。
Abstract:
      Understanding the observation abilities and advantages of ceilometer and cloud radar will be helpful for their operational applications in cloud observation. During the summer of 2014, the third Tibetan Plateau Atmospheric Science Experiment was carried out and clouds were observed using Ka-band solid-state transmitter-based millimeter wave cloud radar, Lidar and ceilometer. Based on the cloud measurements in this experiment, the algorithm to determine cloud base using cloud radar observations was developed. The biases of cloud base and data acquisition ratios by ceilometer and cloud radar for low clouds, medium clouds and altocumulus were analyzed. Reasons for the overestimation of cloud base by ceilometer were explained. The improved observation mode was introduced and the observation skill was simulated. The results indicate that (1) the cloud radar observation ability for altocumulus are better than that of ceilometer, the cloud radar echoes below the ceilometer-derived cloud bases are possibly clutter, and its observation for low clouds should be improved. Blockages of low clouds affect the observations of medium cloud and altocumulus by ceilometer. Compared with ceilometer, the cloud radar missed some shallow altocumulus. (2) Most of cloud bases observed by ceilometer are located within the cloud echoes observed by cloud radar. The temporal and spatial correspondences of cloud base observed by cloud radar and ceilometer are poor. (3) Increasing the transmitter power of ceilometer and improving the operational mode of cloud radar can improve the cloud observation abilities. The cloud radar and ceilometer data merging would enhance cloud observation abilities. The research results provide references for usages of cloud radar and ceilometer data and evaluation of observation abilities of cloud radar and ceilometer. They are also helpful in designing operational modes for cloud radar, and promoting the development and application of advanced cloud observation technology.
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