一种浸润冻结机制冰核测量装置(FINDA)的搭建与应用

The development and application of a Freezing Ice Nucleation Detector Array (FINDA) instrument on immersion mode measurement

  • 摘要: 为了定量评估降水(雨、雪、雹等)和大气中冰核浓度,搭建了一种新型的离线式冰核测量装置(FINDA)用于检测浸润冻结机制的冰核。对多通道测温元件进行了改装和校准,并利用红外热成像仪动态校准了冷台水平温差,开发了自动化软件实现对测量过程的控制和数据分析。通过超纯水冻结实验、雪水及大气样品中冰核检验评估了FINDA的测量性能。结果表明,FINDA温度测量偏差随温度降低而线性增大,−25℃时误差为±0.75℃;超纯水初始冻结温度平均为−21.27±1.45℃,中值冻结温度(T50)平均为−25.65±0.64℃;对同一降雪融水样品中冰核浓度温度谱检测,FINDA与其他冻滴设备测量结果基本一致,同冰核浓度下温度偏差小于3℃;大气样品中冰核−20℃时比在线连续流量扩散云室测量值略高,与国际上其他学者的结论一致。FINDA能够有效获得0—−25℃每隔0.25℃的冰核浓度谱,超纯水和试验操作引入的冰核对测量结果影响很小。设备的广泛应用可帮助深入了解大气冰核在混合云降水中的作用,为预报和云模式的本地化改进及对云降水理论研究提供重要的实验数据和理论基础。

     

    Abstract: To quantify the ice nucleating particle (INP) concentrations in precipitation (rain, snow, hail, et al.) and the atmosphere, a new offline Freezing Ice Nucleation Detector Array (FINDA) instrument is developed to detect the immersion mode INPs. The temperature sensor is modified and calibrated. The horizontal temperature bias of cold stage is measured with an infrared camera and calibrated. A software is developed to automatically control the frozen experiment and data analysis. FINDA is validated by performing an ultra-pure water experiment and measuring INPs in snow water and air. The result shows that uncertainty of temperature changes linearly with decreasing temperature and the bias is within ±0.75℃ at −25℃. The starting frozen temperature is −21.27±1.45℃, and the medium frozen temperature is 25.65±0.64℃. The INPs in snow water measured by FINDA compare well with measurements by other instruments with an offset less than 2℃. The result of INPs concentration in the air measured by FINDA is slightly higher than that by Continuous-Flow Diffusion Chamber, and compares well with other studies. With FINDA, the INPs concentration between 0 and −25℃ at 0.25℃ interval is measured effectively. The INPs induced by ultra-pure water and the experiment itself have little impact on the result. The application of FINDA will not only help to further understand the role of INPs in mixed-phase clouds, but also improve the datum and theory support for the development of local weather forecast and cloud models as well as the cloud and precipitation theory.

     

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