| 摘要: |
| 全球及区域气候模式中云滴有效半径的参数化对于理解云的辐射效应特别是气溶胶间接效应是非常重要的。本文利用延安地区（位于中国西北地区）一次降水层状云的飞机观测资料，首先给出该次过程的云微物理特性包括云滴数浓度（Nc），云水含量（Qc），云滴的半径（Rm），体积半径（Rv），以及有效半径（Re），云滴谱离散度（ε）以及Re/Rv比值因子β；并指出云滴谱离散度ε与云滴数浓度Nc有着很好的递减关系式，所对应的关系式可以表述为ε = 0.579 − 7.42×10-4Nc+ 4.2×10 -7Nc2。进一步，发现云滴尺度谱采用Lognormal分布函数，Gamma分布函数以及Weibull分布函数所参数化的云滴有效半径与观测结果较为一致。值得指出的是，基于Lognormal分布函数的参数化能够更好地描述云滴有效半径。该云滴有效半径的参数化结果将会加强对于气溶胶在中国西北地区间接辐射强迫的认识。 |
| 关键词: 云滴尺度谱分布 云滴谱离散度 云滴有效半径 |
| DOI：10.7515/JEE201601002 |
| CSTR：32259.14.JEE201601002 |
| 分类号: |
| 基金项目:国家自然科学基金项目（41105071）；中国科学院战略性先导科技专项（XDA05110101）；国家重点基础研究发展计划项目（2011CB403406） |
| 英文基金项目:National Natural Science Foundation of China (41105071); Strategic Priority Research Program of Chinese Academy of Sciences (XDA05110101); National Basic Research and Development Program of China?(2011CB403406) |
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| Cloud microphysical properties and parameterization of cloud droplet effective radius from aircraft measurements: aircraft observational results from a stratiform precipitation cloud |
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XIE Xiaoning, WANG Zhaosheng, WANG Hongli, YUE Zhiguo1,2,3
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1. State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment,
Chinese Academy of Sciences, Xi’an 710061, China;2. Shaanxi Radio & TV University, Xi’an 710119, China;3. Weather Modification Office of Shaanxi Province, Xi’an 710015, China
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| Abstract: |
| Background, aim, and scope Cloud is one of the most important components of the Earth-atmosphere system, which covers approximately half of our planet surface and affect its radiative energy balance, as well as the global and regional spatial-temporal distribution of surface precipitation. The treatment of radiative properties of clouds is very important in numerical models that can simulate the expected climate change produced by increasing concentrations of anthropogenic greenhouse gases and aerosols. The radiative properties of clouds (including optical thickness, the single scattering albedo, and the asymmetry factor) are mainly dependent on the cloud droplet effective radius, which is defined as the ratio of the third to second moment of the cloud droplet size distribution. Hence, the parameterization of cloud droplet effective radius in the various climate and weather models is fundamental to understanding the radiative effects of clouds, and its accurate paremeterization is also especially of importance to evaluate the aerosol indirect effect and can reduce the uncertity of the aerosol indirect effect. Materials and methods Here, we use an observed data about the cloud droplet size distribution, which is derived from aircraft measurements for a stratiform cloud in Yan’an area in September 17, 2003 (Northwest China). This cloud dropet data can dispaly the cloud microphysical properties including the droplet number concentration, the cloud water content, the cloud droplet radius, volume radius, effective radius, the cloud droplet relative dispersion, and the prefactor about the ratio of the effective radius and the volume radius. Additionally, using the analytical methods based on the defination of effective radius, we can analytically derive the theoretical parameterization of the cloud droplet effective radius interms of three size distribution funcions described as the Lognormal, the Gamma, and the Weibull expressions, which are usually employed in the numerical models based on the various scales. Results (1) We summarize the Maximum, Mean, Median, and STDEV (Standard Deviation) values about the cloud microphysical properties including the cloud droplet number concentration (Nc), the cloud water content (Qc), the cloud droplet radius (Rm), the volume radius (Rv), the effective radius (Re), the cloud droplet relative dispersion (ε), and the Re/Rv prefactor β for this stratiform cloud in Yan’an area (Northwest China). (2) Based on the observed data about the cloud droplet number concentration Nc and the cloud droplet relative dispersion ε, we can derive a ε—Nc negative relationship as ε = 0.579 − 7.42×10-4Nc+ 4.2×10-7Nc2, which represents the cloud droplet relative dispersion decreases with the increase in cloud droplet number concentration. This ε—Nc relationship can be directly coupled to the numerical models to evaluated the cloud dropet dispersion effect. (3) We find that theoretical parameterization of the cloud droplet effective radius based on the Lognormal, the Gamma, and the Weibull expressions all fit better with the observed results, where the parameterization of the Lognormal expression is best for this stratiform cloud in Yan’an area. Discussion It is worthy noting that all the observed results is derived from only one case interms of the stratiform cloud in Yan’an area. However, as we know, the macrophysical and microphysical cloud processes are very complex, which is closely related to atmospheric environment (including atmospheric humidity and stability), as well as the aerosol physical and chemical properties. Additionally, various types of clouds have different environment factors, they also have change the cloud droplet effective radius. Hence, we need much more data derived from aircraft measurements including different cloud types, different atmospheric environment, and different aerosol backgrouds to study the paremeterization of the cloud droplet effective radius. Conclusions Compared with these aircraft measurements of cloud droplet size distributions, it is found that the parameterization of the cloud droplet effective radius based on Lognormal, Gamma, and Weibull expressions all fit better with the observed results from aircraft measurements, and the parameterization based on Lognormal expression is best for this stratiform cloud in Yan’an area. Recomendations and perspectives We recommend that Lognormal expression is the best parameterization of the cloud droplet effective radius for this stratiform cloud in Yan’an area. These results could shed light on understanding the aerosol indirect radiative forcing in Northwest China. Additionally, the ε—Nc relationship has been presented based on this case, which can be coupled to the model to evaluate the cloud droplet dispersion effect. |
| Key words: cloud droplet size distribution spectral dispersion cloud droplet effective radius |
