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Extending Micro-Pulse DIAL (MPD) Water Vapor Estimation Capability for Increased and Enhanced Weather Applications by Leveraging Advanced Signal Processing Techniques

利用先进的信号处理技术扩展微脉冲 DIAL (MPD) 水蒸气估算能力，以增加和增强天气应用

基本信息

批准号：
1930907
负责人：
Willem Marais
金额：
$ 19.83万
依托单位：
University of Wisconsin-Madison
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2019
资助国家：
美国
起止时间：
2019-11-01 至 2024-10-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1930907&HistoricalAwards=false
关键词：
Extending Micro Pulse DIAL MPD

项目摘要

The accurate measurement of water vapor in the lower atmosphere is one of the keys to unlocking improved forecasts of cloud, precipitation, and severe weather. Through NSF funding, researchers have developed a network of lidars that can run unattended and provide research-quality water vapor measurements. This project will enhance the capability of those lidars to provide measurements in space and time by using advanced signal processing techniques that are already in use in the medical imaging community. Beyond the potential to improve forecasting, the project could allow for a change in how future instruments are constructed, lowering the cost and allowing for more coverage. This also represents the first NSF award for an early-career scientist.The research plan is to apply a new signal processing technique to the micro-pulse differential absorption lidar (MPD) network to increase the capability of the instrument to retrieve water vapor measurements. The Poisson Total Variation (PTV) technique is used as a signal processor framework for lidar applications and can be conceptualized as an approach where the spatial and temporal resolutions of the observations are systematically and optimally adjusted based on the signal-to-noise ratio. The PTV is based on well-established signal processing techniques that have been used in medical imaging. The short-term objective of the project is to further validate the preliminary PTV techniques and improve it where necessary by processing several MPD datasets that have coincident radiosonde water vapor retrievals. The long-term objective is to refine the technique to be more computationally efficient and integrate it to the MPD testbed data processing system.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.

准确测量低层大气中的水蒸气是解锁云、降水和恶劣天气预报的关键之一。通过NSF的资助，研究人员开发了一个激光雷达网络，可以无人值守运行，并提供研究质量的水蒸气测量。该项目将利用医学成像界已在使用的先进信号处理技术，提高这些激光雷达提供空间和时间测量的能力。除了改善预测的潜力外，该项目还可以改变未来工具的构建方式，降低成本并扩大覆盖面。这也是美国国家科学基金会颁发给早期职业科学家的第一个奖项。该研究计划将新的信号处理技术应用于微脉冲差分吸收激光雷达（MPD）网络，以提高仪器检索水蒸气测量值的能力。泊松全变差（PTV）技术被用作激光雷达应用的信号处理器框架，并且可以被概念化为一种方法，其中观测的空间和时间分辨率基于信噪比进行系统和最佳调整。 PTV基于已在医学成像中使用的成熟的信号处理技术。该项目的短期目标是进一步验证初步的PTV技术，并在必要时通过处理几个MPD数据集，具有重合的无线电探空仪水汽反演来改进它。长期目标是改进该技术，使其计算效率更高，并将其集成到MPD试验台数据处理系统中。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。