Advances in microphysical properties and detection approaches of high-altitude ice-crystal clouds
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摘要:
冰晶进入航空发动机导致发动机结冰是危害飞行安全的重要因素。针对冰晶结冰研究过程中，影响结冰过程的关键高空云雾微物理特性参数及冰晶探测方法的系统性总结还比较少见。为了掌握国内外高空冰晶云雾微物理特性的研究情况，作者通过文献调研，总结了当前国内外对高空大气云层中的冰晶形状分类、冰晶尺寸、总水含量（TWC）及其探测方法的研究现状；并分类总结了冰晶形状和尺寸随云层类型、海拔高度、环境温度的分布特性与变化规律，以及TWC随云层海拔高度、环境温度、暴露长度等因素的变化规律。研究结果表明：冰晶形状会受到云层类型影响，冰晶的粒径（最大尺度）和冰晶的形状密切相关，云层中的TWC会随着云暴露长度、海拔高度和环境温度变化。在此基础上，结合高空冰晶探测技术的特点，归纳了高空冰晶云雾微物理特性研究和探测技术发展面临的挑战，主要表现在冰晶粒子实时观测和分类困难，环境因素影响及地理适用性限制，试验所需冰晶粒子的获取困难，探测技术手段的限制等方面。
Abstract:Engine icing arising from the entry of ice crystals into aircraft engines is a significant factor endangering flight safety. There is a scarcity of systematic summaries on the key microphysical properties of high-altitude cloud ice crystals and the methods for detecting them, which are crucial for understanding the ice formation process. To grasp the current state of research on the microphysical characteristics of ice crystals in high-altitude clouds, both domestic and international, a literature review was conducted for summarizing the current status of research on the classification of ice crystal shapes, ice crystal size, total water content (TWC), and their detection methods in high-altitude atmospheric clouds. The study also categorized and summarized the distribution characteristics and variation patterns of ice crystal shape and size with cloud type, altitude, and environmental temperature, as well as the variation patterns of TWC with cloud altitude, environmental temperature, and exposure length. Results showed that the shape of ice crystals was influenced by the type of cloud; the size (largest dimension) of ice crystals was closely related to their shape; and the TWC in clouds varied with cloud exposure length, altitude, and environmental temperature. Based on this, and in conjunction with the characteristics of high-altitude ice crystal detection technology, the challenges faced in the research and development of detection technology for the microphysical properties of high-altitude ice crystals and clouds were summarized. The primary challenges were encapsulated in the difficulties associated with real-time observation and classification of ice crystal particles, the impact of environmental factors and limitations in geographical applicability, the challenges in acquiring ice crystal particles necessary for experiments, and the constraints imposed by the detection technology itself. These issues underscored the complexity of advancing our understanding and capabilities in this field.
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表 1 大陆和海洋地区的砧状云中聚合冰晶的占比及存在的大气环境温度[37]
Table 1. Percentage of aggregated ice crystals in anvil clouds in continental and oceanic regions and the ambient atmospheric temperature at which they are present[37]
砧状云类型 观测位置 聚合冰晶占比/% 大气温度/℃ 大陆型 Colorado 28 −47 海洋型 Kwajalein 0.5 −60～−40 
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几何形状 轴比关系 体积 
$\left\{ \begin{gathered} a = 0.35L\quad\quad （L < 100\;{\text{μm}}） \\ a = 3.48{L^{0.5}}\quad （L > 100\;{\text{μm}}） \\ \end{gathered} \right.$ $V = \dfrac{{3\sqrt 3 }}{2}{a^2}L$ 
$\left\{ \begin{gathered} L = 2a\quad\quad\quad\quad\quad\quad\quad\quad\quad\quad\quad\quad\quad \quad\quad（a \leqslant 2\;{\text{μm}}） \\ L = 2 +[ （0.248\;83{a^{0.474}} - 2） /4] （a - 1） \quad \;（2\;{\text{μm}} \leqslant a \leqslant 5\;{\text{μm}}） \\ L = 0.248\;83{a^{0.474}}\quad\quad\quad\quad\quad\quad\quad\quad\quad\quad\;（a \geqslant 5\;{\text{μm}}） \\ \end{gathered} \right.$ $V = \dfrac{{3\sqrt 3 }}{2}{a^2}L$ 
$\left\{ \begin{gathered} a = 0.35L\quad \quad\;\;\;（L < 100\;{\text{μm}}） \\ a = 0.348{L^{0.5}}\quad \; （L \geqslant 100\;{\text{μm}}） \\ h = 0.25L \\ \end{gathered} \right.$ $V = \dfrac{{3\sqrt 3 }}{2}{a^2}L - \sqrt 3 {a^2}h$ 
$ \left\{ \begin{gathered} a = 1.552{L^{0.63}} \\ t = \dfrac{{\sqrt 3 a}}{{2{\text{tan}}\;\alpha }}\quad \alpha = 28{\text{°}} \\ \end{gathered} \right. $ $V = 3\sqrt 3 {a^2} \cdot （3L + t） $ 
$\begin{gathered} {a_1} = 0.291{L_1}\quad {a_2} = 0.323{L_2} \\ {a_3} = 0.359{L_3}\quad {a_4} = 0.381{L_4} \\ {a_5} = 0.368{L_5}\quad {a_6} = 0.352{L_6} \\ {a_7} = 0.333{L_7}\quad {a_8} = 0.312{L_8} \\ D = 7.297{L_{{\text{min}}}} \\ \end{gathered} $ $V = \displaystyle\sum\limits_{i = 1}^8 {\dfrac{{3\sqrt 3 }}{2}a_i^2{L_i}} $ 
$\begin{gathered} D = 2R \\ {a_1} = R{\text{sin}}\;{\theta _1}\quad {a_2} = R{\text{sin}}\;{\theta _2} \\ {L_1} = R{\text{cos}}\;{\theta _1}\quad {L_2} = R{\text{cos}}\;{\theta _2} \\ {\theta _1} = 32.35{\text{deg }}\quad {\theta _2} = 71.8{\text{deg}} \\ \end{gathered} $ $\begin{gathered} V = \sqrt 3 [ （{L_1} + 2{L_2} + h） \cdot a_2^2 - ha_1^2] \\ h = \dfrac{{{a_1} （{L_1} - {L_2}） }}{{{a_2} - {a_1}}} \\ \end{gathered} $
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数据集 大气温度/℃ −50 −40 −30 −10 F20数据集 316 401 476 747 DC8数据集 329 381 493 Convair-580数据集 630
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表 4 Bowden给出TWC参考值与文献[52]附录D中TWC参考值的比较[51,55]
Table 4. Comparisons of Bowden’s result of TWC and Ref.[52] appendix D TWC guidelines[51,55]
环境温度范围/℃ 海拔范围/ft 云层水平
延伸范围/nmiBowden给出的
TWC/（g/m3）Mazzawy给出的
TWC范围/（g/m3）Mazzawy给出的TWC的
中位数/（g/m3）−20 ～ 0 10000 ～30000 0.44 8 2.6 5 4.6 4.4 2.0～5.7 4.8 17.4 1.8～5.1 4.3 44 2 1.6～4.7 4.0 161 1 1.4～4.1 3.4 −40 ～ −20 15000 ～40000 2.6 5 4.6 2.0～5.5 4.5 8.7 2 1.9～5.2 4.3 17.4 1.8～4.9 4.0 44 1 1.7～4.5 3.7 161 0.5 1.4～3.9 3.2 −60 ～ −40 20000 ～45000 2.6 5 4.6 2.4～4.7 3.7 8.7 2 2.2～4.4 3.5 17.4 2.1～4.2 3.3 44 1 1.9～3.9 3.0 161 0.5 1.7～3.4 2.6 −80 ～ −60 60000 ～80000 2.6 1 4.6 8.7 0.5 161 0.1
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表 5 不同冰晶测量传感器优缺点比较
Table 5. Comparison of advantages and disadvantages of different ice crystal measurement sensors
仪器 优点 缺点 CVI 按粒径分离粒子；便于增加粒子的粒子数浓度 小冰晶测量误差 FSSP 实时提供测量粒子数浓度；高分辨率 时间响应限制；高速时无法确定小于300 μm
粒子的形状和相态HVPS 可测量大量降水粒子；可提供粒子的详细图像 采样空间相对较小；数据量大，需要有效的数据处理和
存储解决方案OAP 能提供粒子数浓度、大小和形状数据；测量误差较小 小冰晶测量误差；数据重访需求
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