Articles | Volume 15, issue 19
https://doi.org/10.5194/amt-15-5681-2022
© Author(s) 2022. 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-15-5681-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Adaptive thermal image velocimetry of spatial wind movement on landscapes using near-target infrared cameras
Benjamin Schumacher
CORRESPONDING AUTHOR
School of Earth and Environment, University of Canterbury, Christchurch, New Zealand
Earth Observation Data Centre for Water Resources Monitoring GmbH, Vienna, Austria
Marwan Katurji
School of Earth and Environment, University of Canterbury, Christchurch, New Zealand
Jiawei Zhang
School of Earth and Environment, University of Canterbury, Christchurch, New Zealand
New Zealand Forest Research Institute (Scion), Christchurch, New Zealand
Peyman Zawar-Reza
School of Earth and Environment, University of Canterbury, Christchurch, New Zealand
Benjamin Adams
Department of Computer Science and Software Engineering, University of Canterbury, Christchurch, New Zealand
Matthias Zeeman
Chair of Environmental Meteorology, Faculty of Environment and Natural Resources, University of Freiburg, Freiburg, Germany
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William Morrison, Dana Looschelders, Jonnathan Céspedes, Bernie Claxton, Marc-Antoine Drouin, Jean-Charles Dupont, Aurélien Faucheux, Martial Haeffelin, Christopher C. Holst, Simone Kotthaus, Valéry Masson, James McGregor, Jeremy Price, Matthias Zeeman, Sue Grimmond, and Andreas Christen
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-167, https://doi.org/10.5194/essd-2025-167, 2025
Revised manuscript accepted for ESSD
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We conducted research using sophisticated wind sensors to better understand wind patterns in Paris. By installing these sensors across the city, we gathered detailed data on wind speeds and directions from 2022 to 2024. This information helps improve weather and climate models, making them more accurate for city environments. Our findings offer valuable insights for scientists studying urban air and weather, improving predictions and understanding of city-scale atmospheric processes.
Matthias Zeeman, Andreas Christen, Sue Grimmond, Daniel Fenner, William Morrison, Gregor Feigel, Markus Sulzer, and Nektarios Chrysoulakis
Geosci. Instrum. Method. Data Syst., 13, 393–424, https://doi.org/10.5194/gi-13-393-2024, https://doi.org/10.5194/gi-13-393-2024, 2024
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This study presents an overview of a data system for documenting, processing, managing, and publishing data streams from research networks of atmospheric and environmental sensors of varying complexity in urban environments. Our solutions aim to deliver resilient, near-time data using freely available software.
Tamara Pletzer, Jonathan P. Conway, Nicolas J. Cullen, Trude Eidhammer, and Marwan Katurji
Hydrol. Earth Syst. Sci., 28, 459–478, https://doi.org/10.5194/hess-28-459-2024, https://doi.org/10.5194/hess-28-459-2024, 2024
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We applied a glacier and hydrology model in the McMurdo Dry Valleys (MDV) to model the start and duration of melt over a summer in this extreme polar desert. To do so, we found it necessary to prevent the drainage of melt into ice and optimize the albedo scheme. We show that simulating albedo (for the first time in the MDV) is critical to modelling the feedbacks of albedo, snowfall and melt in the region. This paper is a first step towards more complex spatial modelling of melt and streamflow.
Dongqi Lin, Jiawei Zhang, Basit Khan, Marwan Katurji, and Laura E. Revell
Geosci. Model Dev., 17, 815–845, https://doi.org/10.5194/gmd-17-815-2024, https://doi.org/10.5194/gmd-17-815-2024, 2024
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GEO4PALM is an open-source tool to generate static input for the Parallelized Large-Eddy Simulation (PALM) model system. Geospatial static input is essential for realistic PALM simulations. However, existing tools fail to generate PALM's geospatial static input for most regions. GEO4PALM is compatible with diverse geospatial data sources and provides access to free data sets. In addition, this paper presents two application examples, which show successful PALM simulations using GEO4PALM.
Dongqi Lin, Marwan Katurji, Laura E. Revell, Basit Khan, and Andrew Sturman
Atmos. Chem. Phys., 23, 14451–14479, https://doi.org/10.5194/acp-23-14451-2023, https://doi.org/10.5194/acp-23-14451-2023, 2023
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Accurate fog forecasting is difficult in a complex environment. Spatial variations in soil moisture could impact fog. Here, we carried out fog simulations with spatially different soil moisture in complex topography. The soil moisture was calculated using satellite observations. The results show that the spatial variations in soil moisture do not have a significant impact on where fog occurs but do impact how long fog lasts. This finding could improve fog forecasts in the future.
Marte G. Hofsteenge, Nicolas J. Cullen, Carleen H. Reijmer, Michiel van den Broeke, Marwan Katurji, and John F. Orwin
The Cryosphere, 16, 5041–5059, https://doi.org/10.5194/tc-16-5041-2022, https://doi.org/10.5194/tc-16-5041-2022, 2022
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In the McMurdo Dry Valleys (MDV), foehn winds can impact glacial meltwater production and the fragile ecosystem that depends on it. We study these dry and warm winds at Joyce Glacier and show they are caused by a different mechanism than that found for nearby valleys, demonstrating the complex interaction of large-scale winds with the mountains in the MDV. We find that foehn winds increase sublimation of ice, increase heating from the atmosphere, and increase the occurrence and rates of melt.
Matthias Zeeman
Atmos. Meas. Tech., 14, 7475–7493, https://doi.org/10.5194/amt-14-7475-2021, https://doi.org/10.5194/amt-14-7475-2021, 2021
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Understanding turbulence near the surface is important for many applications. In this work, methods for observing and analysing temperature structures in a near-surface volume were explored. Experiments were conducted to identify modes of organised motion. These help explain interactions between the vegetation and the atmosphere that are not currently well understood. Techniques used include fibre-optic sensing, thermal infrared imaging, signal decomposition, and machine learning.
Dongqi Lin, Basit Khan, Marwan Katurji, Leroy Bird, Ricardo Faria, and Laura E. Revell
Geosci. Model Dev., 14, 2503–2524, https://doi.org/10.5194/gmd-14-2503-2021, https://doi.org/10.5194/gmd-14-2503-2021, 2021
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We present an open-source toolbox WRF4PALM, which enables weather dynamics simulation within urban landscapes. WRF4PALM passes meteorological information from the popular Weather Research and Forecasting (WRF) model to the turbulence-resolving PALM model system 6.0. WRF4PALM can potentially extend the use of WRF and PALM with realistic boundary conditions to any part of the world. WRF4PALM will help study air pollution dispersion, wind energy prospecting, and high-impact wind forecasting.
Martina Botter, Matthias Zeeman, Paolo Burlando, and Simone Fatichi
Biogeosciences, 18, 1917–1939, https://doi.org/10.5194/bg-18-1917-2021, https://doi.org/10.5194/bg-18-1917-2021, 2021
John J. Cassano, Melissa A. Nigro, Mark W. Seefeldt, Marwan Katurji, Kelly Guinn, Guy Williams, and Alice DuVivier
Earth Syst. Sci. Data, 13, 969–982, https://doi.org/10.5194/essd-13-969-2021, https://doi.org/10.5194/essd-13-969-2021, 2021
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Between January 2012 and June 2017, a small unmanned aerial system (sUAS), or drone, known as the Small Unmanned Meteorological Observer (SUMO), was used to observe the lowest 1000 m of the Antarctic atmosphere. During six Antarctic field campaigns, 116 SUMO flights were completed. These flights took place during all seasons over both permanent ice and ice-free locations on the Antarctic continent and over sea ice in the western Ross Sea providing unique observations of the Antarctic atmosphere.
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Short summary
This investigation presents adaptive thermal image velocimetry (A-TIV), a newly developed algorithm to spatially measure near-surface atmospheric velocities using an infrared camera mounted on uncrewed aerial vehicles. A validation and accuracy assessment of the retrieved velocity fields shows the successful application of the algorithm over short-cut grass and turf surfaces in dry conditions. This provides new opportunities for atmospheric scientists to study surface–atmosphere interactions.
This investigation presents adaptive thermal image velocimetry (A-TIV), a newly developed...