Novel Integrated Characterization of Microphysical Properties of Ice Particles Using In-Situ Field Measurements and Polarimetric Radar Observations
Novel Integrated Characterization of Microphysical Properties of Ice Particles Using In-Situ Field Measurements and Polarimetric Radar Observations
批准号:
2029806
负责人:
Branislav Notaros
金额:
$64.7万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-10-01 至 2024-09-30
中文摘要
东海岸冬季风暴(或东北风暴)从北卡罗来纳州向北发展到美国东海岸,可能是非常具有破坏性的,会产生大量的降雪、冻雨、雨夹雪和随之而来的洪水。福尔斯落在地表的降水类型对环境条件(如温度和相对湿度)的细微垂直变化很敏感。国家气象局最近现代化的雷达网络沿着复杂的数字模型,用于预报危险地区,但这些网络在很大程度上取决于各种降水的物理性质,如大小、形状、浓度、密度、下落速度和成分,这些性质在空间和时间上都有很大的变化。这项研究旨在开发,实施和测试新的方法来测量,表征和分析冬季降水中冰粒的物理和散射特性,结合精密的光学,电子和机械仪器以及最先进的雷达。这些综合实地测量是与弗吉尼亚州沃洛普斯岛的降水研究设施合作进行的,该设施由美国国家航空航天局运营,福尔斯沿着东海岸冬季风暴的气候轨迹之一下降。冬季降水的物理和散射特性的准确测量对于数值天气预报模型的进步和正确解释最近现代化的国家天气雷达网络的数据至关重要。因此,这项研究可以改善冬季降水预报(数量,位置和时间),这对经济,安全和日常生活非常重要,包括公众使用的所有旅行方式,特别是航空旅行和安全。教育影响包括研究生和本科生的研究培训,学生的仪器开发和现场经验。这项研究的首要目标是减少不确定性的雷达信号的解释和提高的准确性的反演的液体等效雪率(SR)使用先进的原位仪器和雷达支持的观测驱动的方法。更具体地,第一个目的是通过优化来自一个平面中的投影视图的数据来改进对冰粒的几何参数、粒度分布(PSD)、下落速度和“有效”密度的表征,所述投影视图由降水仪器包(PIP)获得,两个正交平面来自2D视频粒度仪(2DVD),以及多个平面,由5相机多角度雪花相机(MASC)和7相机雪花测量和分析系统(SMAS)提供。第二个目标是使用PIP,两个2DVD单元和两个3D声波风速计(内部和外部的双栅栏挡风玻璃)的组合,以表征自然降雪中的粒子湍流对下降速度和粒子的“有效”密度的影响。第三个目标是关闭的基础上实现的协议的“最佳”估计SR和前向建模的偏振变量从双极化雷达使用PIP,2DVD,MASC,和SMAS数据与独立的雪计和雷达测量,分别。该项目的一些独特贡献是:学生建造的研究仪器SMAS,该仪器使用6台摄像机提供颗粒的3D形状重建,第7台摄像机同时测量下落速度;使用多种仪器(MASC、SMAS、2DVD和PIP)达到从100微米到20毫米的“完整”PSD;采用实验方法研究颗粒湍流对沉降速度的影响,PIP、2DVD和SMAS分别提供了颗粒的垂直/水平运动、下落速度和尺寸以及习惯(类型)的数据;该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
East Coast Winter Storms (or Nor’easters) that develop off the eastern coast of the US from North Carolina northwards can be very devastating producing large amounts of snowfall, freezing rain, sleet and resultant flooding. The type of precipitation that falls at the surface is sensitive to subtle vertical changes of the environment conditions such as temperature and relative humidity. The National Weather Service’s recently modernized network of radars along with sophisticated numerical models are used to forecast the hazardous areas but they depend crucially on the physical properties of the various classes of precipitation such as size, shape, concentration, density, fall speed and composition which are highly variable in both space and time. This research is aimed at developing, implementing, and testing novel approaches to measurement, characterization, and analysis of the physical and scattering properties of ice particles in winter precipitation combining delicate optical, electronic, and mechanical instrumentation and state-of-the-art radars. These integrated field measurements are performed in collaboration with the Precipitation Research Facility at Wallops Island, Virginia, operated by the National Aeronautic and Space Administration, which falls along one of the climatological tracks of east coast winter storms. Accurate measurements of the physical and scattering properties of winter precipitation are crucial for advancement of numerical weather prediction models and in the correct interpretation of data from the recently modernized national network of weather radars. Hence this research can lead to improved winter precipitation forecasts (amount, location, and timing), which is of great importance to economy, safety, and everyday life, including all travel modes used by the public, and especially air travel and safety. Educational impacts include research training of graduate and undergraduate students, instrumentation development by students, and field experiences. The overarching goal of this research is to reduce uncertainties in the interpretation of radar signatures and improve the accuracy of the retrievals of liquid equivalent snow rate (SR) using an observationally-driven approach supported by advanced in-situ instrumentation and radars. More specifically, the first objective is to improve characterization of geometric parameters, particle size distribution (PSD), fall speeds, and “effective” density of ice particles, by optimizing the data from projected views in one plane, obtained by the Precipitation Instrument Package (PIP), two orthogonal planes, from the 2D-video disdrometer (2DVD), and multiple planes, provided by the 5-camera multi-angle snowflake camera (MASC) and 7-camera Snowflake Measurement and Analysis System (SMAS). The second objective is use of the combination of PIP, two 2DVD units and two 3D sonic anemometers (inside and outside a double-fence windshield) to characterize the effects of particle-turbulence in natural snowfall on the fall speed and “effective” density of particles. The third objective is related to closure based on achieved agreements of the “best” estimate of SR and forward modeled polarimetric variables from dual-polarization radar using PIP, 2DVD, MASC, and SMAS data with independent snow gauge and radar measurements, respectively. Some of the unique contributions of this project are: a student-built research instrument SMAS that offers 3D-shape reconstruction of particles using 6 cameras with the 7th camera simultaneously measuring fall speed; use of multiple instruments (MASC, SMAS, 2DVD, and PIP) to arrive at the “complete” PSD from 100 microns to 20 mm; experimental approach to study particle-turbulence effects on settling speeds, with data on vertical/horizontal movements, fall speeds and sizes, and habits (types) of particles provided by the PIP, 2DVD, and SMAS, respectively; and closure experiments with the agreement between predicted and measured SR and radar observables being evaluated based on the estimated measurement and parameterization errors.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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Measurement and Characterization of Winter Precipitation at Wallops Island Snow Field Site
瓦勒普斯岛雪场冬季降水的测量和表征
DOI:
--
发表时间:
2022
期刊:
Colorado
影响因子:
--
作者:
[Notaros, B. M., Bringi, V.N., Thant, H, Huang, G.-J., Wolff, D. B.]
通讯作者:
Wolff, D. B.
Advanced Deep Learning-Based Supervised Classification of Multi-Angle Snowflake Camera Images
基于高级深度学习的多角度雪花相机图像监督分类
DOI:
10.1175/jtech-d-20-0189.1
发表时间:
2021
期刊:
Journal of Atmospheric and Oceanic Technology
影响因子:
2.2
作者:
[Key, C., Hicks, A., Notaroš, B. M.]
通讯作者:
Notaroš, B. M.
DOI:
10.1109/map.2022.3143442
发表时间:
2022
期刊:
IEEE Antennas and Propagation Magazine
影响因子:
3.5
作者:
[Notaros, Branislav M.]
通讯作者:
Notaros, Branislav M.
“Higher Order Computational Electromagnetics, Uncertainty Quantification, and Meshing Techniques with Applications in Wireless Communication, Medicine, and Meteorology,” Keynote Talk
– 高阶计算电磁学、不确定性量化和网格技术在无线通信、医学和气象学中的应用 – 主题演讲
DOI:
--
发表时间:
2021
期刊:
2021
影响因子:
--
作者:
[Notaros, Branislav M.]
通讯作者:
Notaros, Branislav M.
Machine Learning Based Classification of Snowflake Geometries in Multi-Camera Observation Systems
多摄像机观测系统中基于机器学习的雪花几何形状分类
DOI:
--
发表时间:
2023
期刊:
Proc. 2023 USNC-URSI National Radio Science Meeting
影响因子:
--
作者:
[Thant, H, Zhizhin, M., Notaros B. M.]
通讯作者:
Notaros B. M.
共 10 条
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Novel RF Volume Coils for High and Ultra-High Field Magnetic Resonance Imaging Scanners
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Diakoptic Approach to Modeling and Design of Complex Electromagnetic Systems
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Higher-Order Finite Element-Moment Method Modeling Techniques for Conformal Antenna Applications
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Higher-Order Finite Element-Moment Method Modeling Techniques for Conformal Antenna Applications
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Large-Domain Hybrid Moment Method-Physical Optics Techniques for Efficient and Accurate Electromagnetic Modeling of Cars and Aircraft over a Wide Range of Frequencies
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财政年份:2001
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