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Diode-Laser-Based Doppler Wind Lidar for Vertical Wind Profiling

Kevin Repasky·Montana State University, MT·2023–2026·ACTIVE
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INSTITUTION

Montana State University, MT

PRINCIPAL INVESTIGATOR

Kevin Repasky

FUNDING

$336K

YEAR

2023

MOONBASE SCORE

59/100

LOADING MOONBASE SCORE

Abstract

Numerical models for weather forecasting rely heavily on observations of the initial conditions of the atmosphere to provide accurate projections. For shorter-term forecasts, it is important to have timely and dense observations of the lower atmosphere. This project intends to fill in a current observational gap by developing an instrument that can provide continuous, unattended measurements of the vertical wind in the layer of the atmosphere closest to the Earth’s surface. In addition to the potential impact on society through enhanced forecasting, this award will provide education and training opportunities for students in optical remote sensing. This project is for the development of a prototype diode-laser-based (DLB) dual-edge direct detection Doppler lidar for vertical wind profiling in the lower troposphere. This development would represent a next step in providing a range of measurements via lidar that began with the successful completion of the MicroPulse Differential absorption lidar (MPD) network for water vapor and the ongoing upgrade to provide remote sensing of temperature. In this project, the research team will develop and demonstrate a DLB Doppler wind lidar instrument’s capability to retrieve vertical wind velocity. The initial phase of the project is to conduct a modeling study that looks at the performance tradeoffs of using etalons and interferometers in the optical receiver. The construction of the lidar will then commence, with the completion of a laser stabilization scheme, the construction of the laser transmitter, design and machining of the temperature-stabilized mounts, and assembling of the lidar receiver. Software development will consist of modifying the current data acquisition program and completing the wind velocity retrieval algorithm. The system would then be tested against other observations of vertical wind. 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.

Data AcquisitionDoppler Wind LidarVertical Wind ProfilingOptical Remote SensingAtmospheric ObservationsWeather ForecastingLaser StabilizationInstrument DevelopmentPerformance TradeoffsLower Troposphere

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