太赫兹频段雷达探测的冰云微物理参数反演算法模拟研究

丁霞; 黄兴友; 王海涛

doi:10.16032/j.issn.1004-4965.2019.006

太赫兹频段雷达探测的冰云微物理参数反演算法模拟研究

doi: 10.16032/j.issn.1004-4965.2019.006

丁霞^{1, 2, ,},
黄兴友³,
王海涛^{1, 2}

1.
上海无线电设备研究所，上海 200090
2.
上海目标识别与环境感知工程技术研究中心，上海 200090
3.
南京信息工程大学，江苏南京 210044

基金项目:

国家自然科学基金 41475034

上海市自然科学基金 16ZR1434900

上海市自然科学基金 17ZR1428700

上海市科学技术委员会工程技术研究中心建设立项 15DZ2250800

详细信息

通讯作者:
丁霞，女，湖北省人，工程师，博士，主要从事雷达数据处理和反演研究。E-mail: miragedx@sina.com

中图分类号: P412.25
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- 被引次数: 0
出版历程
- 收稿日期: 2017-12-12
- 修回日期: 2018-08-18
- 刊出日期: 2019-02-01

SIMULATION RESEARCH OF ICE CLOUD MICROPHYSICAL PARAMETERS RETRIEVAL WITH THZ-BAND RADAR MEASUREMENT

Xia DING^{1, 2
, ,},
Xing-you HUANG³,
Hai-tao WANG^{1, 2}

1.
Shanghai Radio Equipment Research Institute, Shanghai 200090, China
2.
Shanghai Engineering Research Center of Target Identification and Environment Perception, Shanghai 200090, China
3.
Nanjing University of Information Science & Technology, Nanjing 210044, China

摘要

摘要: 在假设冰云粒子呈球形以及粒子谱服从对数正态分布的条件下，利用离散偶极子近似法(DDA)，计算出太赫兹频段(220 GHz)冰云粒子的雷达反射率因子，及其与瑞利假设下雷达反射率因子的比值。忽略衰减和多次散射的影响，根据太赫兹波段冰云的雷达反射率因子，基于最优估计理论反演冰云的微物理参数，并验证该算法的可靠性。反演结果表明，当冰云粒子大小在设定的尺度范围内时，有效粒子半径(r_e)的反演误差小于4%，粒子谱宽(σ)的误差小于2.5%、粒子数密度(N_T)的误差小于1%，冰水含量(IWC)的误差小于5%。还分析了当N_T和σ为定值时，反演结果随粒子尺寸的变化情况，当冰云粒子尺寸在模拟计算设定的范围内时，r_e的反演误差小于0.04%，σ的反演误差小于0.02%，N_T的反演误差小于0.50%，IWC的反演误差小于0.08%，如果冰云粒子大小超出模拟计算设置的范围，反演误差随着r_e增加而增大。该结果证明了基于最优估计理论反演得到的冰云微物理参数与模拟设定值有良好的一致性，说明该方法可应用于太赫兹频段云雷达的冰云观测及云微物理参数的反演和研究。
- 太赫兹 /
- 冰云 /
- 最优估计 /
- 云微物理参数 /
- 反演
Abstract: With the assumption that ice cloud droplets are spherical and size spectra follows lognormal distribution, the factor of radar reflectivity of the ice cloud droplets and their ratio to that with the Rayleigh assumption are determined for the frequency of THz (220 GHz) by adopting the DDA (Discrete Dipole Approximation) algorithm. Without considering the attenuation and multiple scattering effects, the characteristic parameters for ice cloud particles are retrieved using the simulated radar reflectivity factor of ice clouds. Based on the optimal estimation theory the retrieval algorithm is verified to be reliable in the THz band according to the simulated radar reflectivity factor of ice clouds. The retrieval result of a case study shows that retrieval error of effective radius(r_e), width parameter(σ), number concentration(N_T) and ice water content(IWC) are less than 4%, 2.5%, 1% and 5%, respectively, when the ice cloud particle size distribution is in the range of simulation setting. Then the retrieval variation with ice cloud particle size is analyzed with N_T and σ set as constants; when the ice cloud particle size distribution is in the range of simulation setting, retrieval error of retrieved r_e, σ, N_T and IWC is less than 0.04%, 0.02%, 0.50% and 0.08%, respectively, otherwise the retrieval error increases with re. These results have proved that retrieved ice cloud microphysical parameters are well consistent with simulated real values, so this retrieval algorithm based on optimal estimation theory can be useful for observation and retrieval research of ice cloud microphysical parameters with THz cloud profiling radars.
- THz /
- ice cloud /
- optimal estimation theory /
- cloud microphysical parameters /
- retrieval algorithm

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图 1 雷达反射率因子(a)、实际雷达反射率因子和瑞利假设下雷达反射率因子的比值(b)

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图 2 云粒子分布

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图 3 基于最优估计理论的冰云微物理参数反演流程

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图 4 粒子有效半径r_e反演结果

实线为反演值，虚线为真值。

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图 5 粒子谱分布宽度σ反演结果

实线为反演值，虚线为真值。

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图 6 粒子数密度N_T反演结果

实线为反演值，虚线为真值。

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图 7 冰水含量IWC反演结果

实线为反演值，虚线为真值。

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图 8 单个冰云粒子的雷达反射率因子

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表 1 太赫兹云雷达反射率因子及其粒子谱参数信息个例

个例	Z_dB/dBz	r_e/μm	IWC/(g/m³)	D_g/μm	σ	N_T/m^-3
Case1	-16.23	37.29	0.025	50	0.4	200 000
Case2	15.63	149.18	1.578	200	0.4	200 000
Case3	-26.23	37.29	0.002	50	0.4	20 000
Case4	5.63	149.18	0.158	200	0.4	20 000
Case5	-2.35	123.83	0.021	50	0.8	20 000
Case6	20.81	495.30	1.230	200	0.8	20 000

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表 2 云粒子反演结果及误差

个例	r_e/μm	误差/%	IWC/%C/(g/m³)	误差/%	σ	误差/%	N_T/m^-3	误差/%
Case1	37.42	0.35	0.025	0	0.40	0	198 325.68	0.84
Case2	148.89	0.19	1.545	4.55	0.41	2.50	200 045.21	0.02
Case3	37.42	0.35	0.002	0	0.40	0	19 832.56	0.84
Case4	148.89	0.19	0.155	1.12	0.41	2.50	20 004.52	0.02
Case5	118.89	3.98	0.019	2.34	0.79	1.25	19 821.60	0.89
Case6	451.68	8.81	1.127	42.2	0.78	2.50	19 931.80	0.34

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