摘要
云微物理参数是研究云物理过程和云辐射效应的基础。采用35 GHz的Ka波段毫米波云雷达的IQ数据,处理得到功率谱数据,进行了云微物理参数的反演,并且与云雷达和微波辐射计的联合反演方法进行了对比。个例研究表明:(1)层状云的云滴数浓度(N 0)典型值在80~100个/cm 3;有效半径R e(Effective Radius)在15~25μm之间;液态水含量LWC(Liquid Water Content)在0.01~1 g·m-3之间;(2)利用功率谱进行反演,可以消除空气运动的干扰,提高了反演结果的可靠性;(3)反演结果的对比分析表明,功率谱反演方法和联合反演方法有较好的一致性,两种方案都适用于水云微物理参数的反演。
As an essential element to the climate system,clouds cover generally a fraction of 60%and more of the sky,Therefore,cloud microphysical variables is of great importance to study cloud-physics process and radiation effect.This paper focuses on the retrieval of cloud microphysical parameters by using the Doppler spectrum data of a 35 GHz cloud measurement radar.Moreover,comparison is made between the aforesaid parameters and those retrieved from the combination data of cloud radar and ground-based microwave radiometer.Result shows that:(1)The typical value of stratus cloud particle number concentration is 80—100 cm-3,the effective radius(Re)spans from 15μm to 25μm,and the Liquid Water Content(LWC)is from 0.01 g·m-3 to 1 g·m-3.(2)Retrievals from the Doppler spectrum is improved partly due to that the algorithm has advantage of eliminating the velocity perturbation from environmental air.(3)Comparison shows that there is a good agreement between the Doppler-spectrum-retrieval and the combination-retrieval,which verifies that both retrieval schemes are practical.
作者
黄兴友
张帅
李盈盈
黄佳欢
王平
HUANG Xingyou;ZHANG Shuai;LI Yingying;HUANG Jiahuan;WANG Ping(Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters,Nanjing University of Information Science&Technology,Nanjing 210044,China;Cixi Meteorological Bureau,Zhejing Ningbo 315300,China;The Environmental Science Research Institute of Wuxi,Jiangsu Wuxi 214121,China;Shanghai Radio Equipment Research Institute,Shanghai 200090,China)
出处
《气象科学》
北大核心
2019年第5期608-616,共9页
Journal of the Meteorological Sciences
基金
国家自然科学基金资助项目(41475034
41475035)
国家重点基础研究发展计划(973计划)项目(2013CB430101)
关键词
毫米波测云雷达
功率谱
云微物理参数
反演
对比
millimeter-wavelength cloud radar
doppler spectrum
cloud microphysical parameters
retrieval
comparison