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New measurements of snowflake scattering and microstructure using a novel Multi-Wavelength, Multi-Angle Scatterometer (MuWMAS)

New measurements of snowflake scattering and microstructure using a novel Multi-Wavelength, Multi-Angle Scatterometer (MuWMAS)
使用新型多波长、多角度散射仪 (MuWMAS) 对雪花散射和微观结构进行新测量
批准号:
NE/W000946/1
负责人:
Chris Westbrook
金额:
$103.56万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2022
资助国家:
英国
项目状态:
未结题
起止时间:
2022 至 --

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中文摘要
翻译
在高纬度地区,降落在地球表面的降水大部分是雪。降雪的定量测量和预报很重要,因为大雪会破坏交通和电力基础设施,降雪条件对自然生态系统、农业和旅游业的健康很重要,而且降雪是水文循环的重要组成部分。然而,并非所有的雪都落在地面上。在中纬度地区(如英国),我们的大部分降水都是以降雨的形式出现的:大部分降雨实际上是由大气中较高的雪花形成的,这些雪花在降落到地面时融化了。云层中的雪花也很重要,因为它们强烈地影响着地球的气候。我们需要能够定量测量雪花的微物理特性,在计算机模型中真实地模拟冰相过程,并“吸收”受雪花影响的遥感卫星数据,以更好地初始化数值天气预报模型,进而改进预报。这些应用的关键是雪花的复杂和高度可变的几何形状,或“微观结构”。这种微观结构控制着雪花散射电磁波的方式;对解释和利用遥感测量进行研究和初步预测至关重要的信息。雪花的形状和微观结构模型的范围不断扩大,有许多由各种数值算法或模型生成的雪花散射特性数据库,每个数据库都基于关于颗粒性质或产生它们的物理过程的不同假设。我们希望回答的问题是:(1)如果有的话,这些模型中哪一个是正确的?(2)在什么条件下给定的模型是现实的表现,在什么条件下它失败?我们的项目是一个独特的实验,它将使我们能够回答这些问题。本课题的目的是通过研制多波长多角度散射仪(MuWMAS)来约束这些散射特性和微观结构信息,MuWMAS是一种新型的地面仪器,可以用毫米和亚毫米电磁波原位照射自然飘落的雪花。雪花以不同的角度将这些波分散到5个探测器阵列上。我们将使用这些数据直接测试雪花散射特性的当前最先进的模型,理论告诉我们,这也为这些颗粒的微观结构提供了直接的约束。此外,通过在水平和垂直极化取样,我们将能够测试雪花方向的理论,并推断这对雪的遥感的影响。MuWMAS将是一个可靠的自动化仪器,提供校准的准确数据。我们将把它部署到高纬度(62 N)的现场,那里经常下雪,并且配备了额外的仪器(光学成像探测器、雷达、激光雷达等),可以帮助我们更深入地解释我们的结果。MuWMAS将在两个冬季的不同降雪季节对该站点的雪花进行连续采样,从而研究不同的微物理过程和生长条件对雪花散射和微观结构特性的影响。最后,我们将利用散射模型和数据库的准确性(或其他方面)来改进雪花散射的表现,以供气象部门(如英国气象局)使用。这将增强用于初始化气象模式的卫星测量的同化,并最终导致更好的天气预报。对雪花散射的更好理解也将导致从2024年发射的冰云成像仪(ice Cloud Imager)等卫星上更准确地“检索”冰的特性。
英文摘要
At high latitudes the majority of precipitation falling at the earth's surface is snow. Quantitative measurements and forecasting of snow precipitation is important because heavy snow can disrupt transport and electricity infrastructure, snow conditions are important for the health of natural ecosystems, agriculture and tourism, and snow is an essential part of the hydrological cycle. However, not all snow falls at the ground. In the mid-latitudes (like the UK), most of our precipitation falls as rain: the majority of that rain actually originates as snowflakes higher up in the atmosphere that melt as they fall to earth. Snowflakes in clouds are also important as they strongly affect the earth's climate. We need to be able to quantitatively measure the microphysical properties of snowflakes, realistically simulate ice-phase processes in computer models, and "assimilate" remote sensing satellite data affected by snowflakes to betterinitialise numerical weather prediction models and, in turn, improve forecasts. Essential to these applications is the famously complex and highly variable geometry, or "microstructure", of the snowflakes. This microstructure controls the way that snowflakes scatter electromagnetic waves; information that is vital to interpreting and exploiting remote sensing measurements for research and for initialising forecasts. There is an ever-expanding range of models for the shape and microstructure of snowflakes, with numerous databases of scattering properties for snowflakes generated by various numerical algorithms or models, each based on different assumptions about the nature of the particles or the physical processes that generated them. The questions we wish to answer are: (1) which, if any, of these models is right?, and (2) under what conditions is a given model a realistic representation and under what conditions does it fail? Our project is a unique experiment which will allow us to answer these questions. The aim of this proposal is to constrain those scattering properties and microstructure information by developing and exploiting a Multi-Wavelength, Multi-Angle Scatterometer (MuWMAS), a novel ground-based instrument which illuminates natural falling snowflakes in-situ with millimetre and sub-millimetre electromagnetic waves. The snowflakes scatter some of these waves to an array of 5 detectors at different angles. We will use the data to directly test current state-of-the-art models for the scattering properties of snowflakes, and theory shows us that this also provides a direct constraint on the microstructure of those particles. Furthermore, by sampling at both horizontal and vertical polarisations we will be able to test theories of snowflake orientation and deduce the impact of this on the remote sensing of snow. MuWMAS will be a reliable, automated instrument, providing calibrated accurate data. We will deploy it to a high-latitude (62 N) field site where there is frequent snowfall and which is well equipped with additional instrumentation (optical imaging probes, radars, lidars etc.) that can help us interpret our results in greater depth. MuWMAS will sample snowflakes at this site continuously over two winter seasons in a variety of snowfalls, allowing us to investigate the influence of different microphysical processes and growth conditions on the scattering and microstructure properties of the snowflakes. Finally, we will use our results on the accuracy (or otherwise) of scattering models and databases to improve the representation of snowflake scattering to be used by meteorological services, such as the Met Office. This will enhance the assimilation of satellite measurements used to initialise meteorological models and ultimately lead to better weather forecasts. The improved understanding of snowflake scattering will also lead to more accurate operational "retrievals" of ice properties from satellites like the Ice Cloud Imager due to be launched in 2024.
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