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  • Presentation | A21O: Observations and Modeling of Marine Fog Processes Poster
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  • A21O-2201: AI-Enabled, Cost-Effective Measurement of Fog Liquid Water Content and Wind Speed
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Author(s):
Dhiraj Singh, University of Utah (First Author)
Carson Ledesma, University of Utah
Ismail Gultepe, University of Notre Dame
Alexei Perelet, University of Utah
Sebastian Hoch, NCAR, Boulder
Eric Pardyjak, University of Utah (Presenting Author)


Understanding how much water is in the air as fog and how wind moves that moisture around is important for weather forecasting, aviation safety, and climate research. Fog contains tiny droplets of water that can be hard to measure accurately, especially close to the ground where wind and turbulence affect the results. Most instruments used today are large, expensive, and require support from other sensors to give full measurements.


We developed two lightweight and low-cost sensors that use thin heated wires to measure fog water and wind speed. One sensor operates at high temperature and is very sensitive to changes in wind. The other sensor runs at a much lower temperature, which helps it isolate the energy loss caused by fog droplets alone. Together, they can provide better measurements of fog and wind in real time.


In field and laboratory tests, our sensors performed well, even in dense fog. The low-power sensor can run on solar panels or batteries, making it useful for remote areas. This system could help improve how scientists study fog and clouds, and it may support better weather models and environmental monitoring across different regions.




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