Articles | Volume 18, issue 21
https://doi.org/10.5194/amt-18-6069-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-18-6069-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Mixed layer height retrievals using MicroPulse Differential Absorption Lidar
Luke Colberg
Montana State University, Department of Electrical and Computer Engineering, Bozeman, MT, USA
Kevin S. Repasky
CORRESPONDING AUTHOR
Montana State University, Department of Electrical and Computer Engineering, Bozeman, MT, USA
Matthew Hayman
NSF National Center for Atmospheric Research, Earth Observing Laboratory, Boulder, CO, USA
Robert A. Stillwell
NSF National Center for Atmospheric Research, Earth Observing Laboratory, Boulder, CO, USA
Scott M. Spuler
NSF National Center for Atmospheric Research, Earth Observing Laboratory, Boulder, CO, USA
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Robert A. Stillwell, Adam Karboski, Matthew Hayman, and Scott M. Spuler
Atmos. Meas. Tech., 18, 4119–4130, https://doi.org/10.5194/amt-18-4119-2025, https://doi.org/10.5194/amt-18-4119-2025, 2025
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A method is introduced to expand the observational capability of a diode-laser-based lidar system. This method allows the lidar transmitter to change the laser pulse characteristics from one shot to the next. We use this capability to lower the minimum altitude of observation and to observe clouds with higher range resolution.
Matthew Hayman, Robert A. Stillwell, Adam Karboski, and Scott M. Spuler
EGUsphere, https://doi.org/10.5194/egusphere-2025-3523, https://doi.org/10.5194/egusphere-2025-3523, 2025
Short summary
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A new processing method for lidar data obtained from rapidly changing laser pulse lengths enables measurement of atmospheric water vapor from the ground up to 6 km. The technique blends all captured data to reveal hidden water vapor structures, especially near the surface. This solution offers continuous, high-resolution insights, key for improving weather forecasts. It showcases how flexible laser technology can enhance atmospheric observation.
John S. Schreck, Gabrielle Gantos, Matthew Hayman, Aaron Bansemer, and David John Gagne
Atmos. Meas. Tech., 15, 5793–5819, https://doi.org/10.5194/amt-15-5793-2022, https://doi.org/10.5194/amt-15-5793-2022, 2022
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We show promising results for a new machine-learning based paradigm for processing field-acquired cloud droplet holograms. The approach is fast, scalable, and leverages GPUs and other heterogeneous computing platforms. It combines applications of transfer and active learning by using synthetic data for training and a small set of hand-labeled data for refinement and validation. Artificial noise applied during synthetic training enables optimized models for real-world situations.
Willem J. Marais and Matthew Hayman
Atmos. Meas. Tech., 15, 5159–5180, https://doi.org/10.5194/amt-15-5159-2022, https://doi.org/10.5194/amt-15-5159-2022, 2022
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For atmospheric science and weather prediction, it is important to make water vapor measurements in real time. A low-cost lidar instrument has been developed by Montana State University and the National Center for Atmospheric Research. We developed an advanced signal-processing method to extend the scientific capability of the lidar instrument. With the new method we show that the maximum altitude at which the MPD can make water vapor measurements can be extended up to 8 km.
Scott M. Spuler, Matthew Hayman, Robert A. Stillwell, Joshua Carnes, Todd Bernatsky, and Kevin S. Repasky
Atmos. Meas. Tech., 14, 4593–4616, https://doi.org/10.5194/amt-14-4593-2021, https://doi.org/10.5194/amt-14-4593-2021, 2021
Short summary
Short summary
Continuous water vapor and temperature profiles are critically needed for improved understanding of the lower atmosphere and potential advances in weather forecasting skill. To address this observation need, an active remote sensing technology based on a diode-laser-based lidar architecture is being developed. We discuss the details of the lidar architecture and analyze how it addresses a national-scale profiling network's need to provide continuous thermodynamic observations.
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Short summary
Two methods were developed to measure the mixed layer height, an important variable for weather forecasting and air quality studies. An aerosol-based method and a thermodynamic method were tested using a lidar system that can measure vertical profiles of aerosols, humidity, and temperature. Each method performed best under different conditions. Together, they provide a path toward more reliable mixed layer height monitoring with a single instrument.
Two methods were developed to measure the mixed layer height, an important variable for weather...