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)从北卡罗来纳州向北在美国东海岸向北发展,可能会造成非常严重的破坏,造成大量降雪、冻雨、雨夹雪和随之而来的洪水。落在地表的降水类型对环境条件的细微垂直变化很敏感,例如温度和相对湿度。美国国家气象局最近更新的雷达网络以及复杂的数值模型被用来预测危险区域,但它们关键取决于各种类型降水的物理特性,如大小、形状、浓度、密度、下降速度和成分,这些在空间和时间上都高度可变。这项研究旨在开发、实施和测试新的方法,以测量、表征和分析冬季降水中冰粒的物理和散射特性,并结合精密的光学、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,位于东海岸冬季风暴的气候轨迹之一。准确测量冬季降水的物理和散射特性对于推进数值天气预报模式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,这项研究可以改进冬季降水预报(数量、位置和时间),这对经济、安全和日常生活,包括公众使用的所有出行方式,特别是航空旅行和安全,都具有重要意义。教育影响包括研究生和本科生的研究培训、学生的仪器开发和实地体验。这项研究的总体目标是减少雷达信号解释中的不确定性,并利用先进的现场仪器和雷达支持的观测驱动方法来提高液体当量雪率(SR)的反演精度。更具体地说,第一个目标是改善对冰粒几何参数、粒度分布、下落速度和“有效”密度的表征,方法是优化由降水仪器包(PIP)获得的一个平面、从2D-Video Disdroeter(2DVD)获得的两个正交平面以及由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)提供的多个平面的数据。第二个目标是使用PIP、两个2DVD单元和两个3D声波风速计(在双挡风玻璃内外)的组合来表征自然降雪中的颗粒湍流对颗粒的下落速度和有效密度的影响。第三个目标是在达成一致的基础上,分别使用PIP、2DVD、MASC和SMAS数据以及独立的雪量计和雷达测量数据,从双极化雷达获得SR和正演模型极化变量的“最佳”估计。该项目的一些独特贡献包括:学生建造的研究仪器SMAS,它使用6个相机和第7个相机同时测量坠落速度,提供粒子的3D形状重建;使用多种仪器(MASC、SMAS、2DVD和PIP)得出从100微米到20毫米的“完整”PSD;用PIP、2DVD和SMAS分别提供的垂直/水平运动、坠落速度和大小以及颗粒的习惯(类型)的数据,研究颗粒湍流对沉降速度的影响的实验方法;和闭合实验,根据估计的测量和参数化误差对预测和测量的SR与雷达观测值之间的协议进行评估。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势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.
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批准号:2305106
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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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批准号:1002385
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负责人:Branislav Notaros
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Higher-Order Finite Element-Moment Method Modeling Techniques for Conformal Antenna Applications
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负责人:Branislav Notaros
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负责人:Branislav Notaros
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资助金额:$0.0万
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依托单位:
Higher-Order Finite Element-Moment Method Modeling Techniques for Conformal Antenna Applications
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负责人:Branislav Notaros
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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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资助金额:$18.0万
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财政年份:2001
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