摘要
根据雷达探测的云回波雷达反射率因子和多普勒速度,利用两种独立的双频反演算法,估算了云微物理参数。利用离散偶极子近似(Discrete Dipole Approximation,DDA)计算了云滴后向散射截面和衰减截面,根据模拟数据实验了三种频段组合的反演结果,探讨算法对滴谱参数、粒子形状的敏感性,比较两种方法反演水云和冰云的优劣。结果表明:双频比(Dual-Frequency Ratio,DFR)和多普勒速度差(Doppler Difference of Velocity,DDV)在水云中都可独立推导中值直径(D_(0)),但在高频波段,基于DFR的算法对雨、云水和水汽的衰减非常敏感,而基于DDV的方法受衰减的影响较小。鉴于高频波段衰减完全订正的困难性,水云的DDV反演方法比DFR更直接准确。对于冰云,DFR的技术相较于DDV的方法具有明显的优势,因为两频段处的DFR在冰云中的动态范围更大,而DDV的动态范围相对于系统和测量误差较小。
Two independent dual-frequency retrieval algorithms were used to estimate the cloud microphysical parameters based on the radar reflectivity factor and Doppler velocity measurements of the cloud echo detected by the radar.The backscattering section and attenuation section of the cloud droplets were calculated by Discrete Dipole Approximation(DDA).The retrieval results of the three frequency band combinations experimentally simulated by using simulated data.The sensitivity of the algorithm to the parameters of the droplets and the shape of the particles were discussed.The advantages and disadvantages were compared of water cloud and the ice cloud in two ways.Dual-Frequency Ratio(DFR)and Doppler Difference of Velocity(DDV)techniques can independently derive the median volume diameter of the particle(D_(0))in water clouds,but in the high frequency band,DFR-based algorithms are seriously sensitive to the attenuation of rain,cloud water and water vapor,while DDV-based methods are less affected by attenuation.In view of the difficulty of completely correcting the attenuation of the high frequency band,the DDV retrieval of the water cloud is more direct and accurate than the DFR method.For ice clouds,DFR techniques have significant advantages over DDV methods because the DFR dynamic range is greater in dual-frequency,and DDV is small relative to the system and measurement error.
作者
杨敏
黄兴友
赵泉钦
张正
杨恒祥
周红根
YANG Min;HUANG Xingyou;ZHAO Quanqin;ZHANG Zheng;YANG Hengxiang;ZHOU Honggen(Jiangsu Meteorological Observation Centre,Nanjing 210019,China;Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters,Nanjing University of Information Science&Technology,Nanjing 210044,China)
出处
《气象科学》
北大核心
2022年第1期12-23,共12页
Journal of the Meteorological Sciences
基金
国家重点研发计划项目(2018YFC1506100,2018YFC1506102)
江苏省气象局科研专项(KZ201905)。
