EAGER: Robust, Low-power Strategies for Unattended Micrometeorological Buoy Deployments in Extreme Cold and Freezing Spray

该项目旨在测试/开发低功率方法，以减轻冰和液态水对海气动量和热流传感器的性能和数据质量的影响。它利用冷室和风洞设施来开发和测试已成功用于飞机应用的主动除冰策略。该技术将适应和优化的低功率的情况下，越冬浮标在安大略湖。如果成功，这种方法可以在冬季直接测量从湖泊进入大气的动量，热量和水分。需要这些测量来更好地模拟和预测湖效应雪，湖效应雪经常影响北美五大湖的顺风社区，造成生命损失，财产和基础设施破坏，以及商业和社会混乱。除此研究应用外，用于减轻传感器和结构上冰积累的鲁棒、低功耗策略也将具有更广泛的应用。该项目将部分资助纽约州立大学奥尔巴尼和宾夕法尼亚州立大学的研究生，他们将在测试中发挥不可或缺的作用，从而获得宝贵的培训和经验，这是他们的研究生教育的一部分。在冬季使用涡度相关（EC）技术直接测量通量将是最有用的开发/改进表面通量参数化，测试研究假设，并检查极端强迫下的模式性能。到目前为止，由于在冬季恶劣条件下测量功率有限的平台的湍流和通量存在困难，因此无法收集此类数据。作为在这些条件下发展EC通量测量能力的一步，该项目将采用航空工业的技术，并探索使用短，强烈的机械振动和/或热脉冲从仪器表面去除冰或水的可行性。这些方法将在模拟冷冻喷雾条件下进行测试。这种除冰方法预计比简单地加热传感器以保持它们不结冰更节能。如果成功，该方法将用于具有额外浮力和高扶正力矩的浮标上，以抵抗上层建筑其他部分上的冰堆积。浮标将提供五大湖无冰部分的冬季时间测量。这些技术的成功演示将发表在同行评审的文献中，使其他研究人员能够在极端环境下专注于微气象学的应用，以及更广泛地说，冰缓解是关键和可用功率有限的应用。该奖项反映了NSF的法定使命，并被认为值得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来支持。

This project is for the testing/development of low-power methods to mitigate the effects of ice and liquid water on the performance and data quality of air-sea momentum and heat flux sensors. It utilizes cold chambers and wind tunnel facilities to develop and test active deicing strategies that have been successfully used in aircraft applications. The techniques will be adapted and optimized for the low-power scenario of an overwinter buoy on Lake Ontario. If successful, this approach could enable direct measurements of momentum, heat and moisture from the lake into the atmosphere during the winter. Such measurements are needed for better modeling and prediction of lake effect snow, which frequently impact communities downwind of the North American Great Lakes, causing loss of life, destruction of property and infrastructure, and commercial and social disruption. Robust, low-power strategies to mitigate ice accumulation on sensors and structures would also have broader applications beyond this research application. This project will partially fund graduate students at SUNY Albany and Penn State who will play an integral role in the testing, and thereby receive valuable training and experience that is part of their graduate education.The overarching scientific goal motivating this project is to improve parameterizations of lake-atmosphere momentum, heat, and moisture fluxes that will lead to better lake effect snow forecasts. Direct measurements of fluxes using the eddy covariance (EC) technique during the winter would be most useful to develop/improve surface flux parameterizations, test research hypotheses, and examine model performance under extreme forcing. To date, difficulties associated with measuring turbulence and fluxes from power-limited platforms during hard winter conditions have precluded collection of such data. As a step toward developing the capability for EC flux measurements in these conditions, this project will adopt a technique from the aviation industry and explore the feasibility of using short, intense pulses of mechanical vibrations and/or heat to dislodge ice or water from the instrument surfaces. These methods will be tested under simulated freezing spray conditions. This de-icing method is expected to be much more power efficient than simply heating the sensors to keep them ice free. If successful, the method is intended to be deployed on buoys with extra buoyancy and high righting moment to resist ice buildup on other parts of the superstructure. The buoys would provide winter time measurements from the ice-free parts of the Great Lakes. Successful demonstration of these techniques will be published in the peer reviewed literature, enabling application by other researchers focused on micrometeorology in extreme environments, and, more broadly, applications where ice mitigation is critical and available power is limited.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.