Articles | Volume 15, issue 17
https://doi.org/10.5194/amt-15-5095-2022
© 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-15-5095-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
07 Sep 2022
Research article |
| 07 Sep 2022
| 07 Sep 2022
Passive ground-based remote sensing of radiation fog
National Centre for Atmospheric Science, Leeds, UK
School of Earth and Environment, University of Leeds, Leeds, UK
David D. Turner
Global Systems Laboratory, National Oceanic and Atmospheric Administration, Boulder, CO, USA
Von P. Walden
Department of Civil and Environmental Engineering, Laboratory for Atmospheric Research, Washington State University, Pullman, WA, USA
Ian M. Brooks
School of Earth and Environment, University of Leeds, Leeds, UK
Ryan R. Neely
National Centre for Atmospheric Science, Leeds, UK
School of Earth and Environment, University of Leeds, Leeds, UK
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James B. Duncan Jr., Laura Bianco, Bianca Adler, Tyler Bell, Irina V. Djalalova, Laura Riihimaki, Joseph Sedlar, Elizabeth N. Smith, David D. Turner, Timothy J. Wagner, and James M. Wilczak
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Piyush Srivastava, Ian M. Brooks, John Prytherch, Dominic J. Salisbury, Andrew D. Elvidge, Ian A. Renfrew, and Margaret J. Yelland
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Irina V. Djalalova, David D. Turner, Laura Bianco, James M. Wilczak, James Duncan, Bianca Adler, and Daniel Gottas
Atmos. Meas. Tech., 15, 521–537, https://doi.org/10.5194/amt-15-521-2022, https://doi.org/10.5194/amt-15-521-2022, 2022
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Heather Guy, Ian M. Brooks, Ken S. Carslaw, Benjamin J. Murray, Von P. Walden, Matthew D. Shupe, Claire Pettersen, David D. Turner, Christopher J. Cox, William D. Neff, Ralf Bennartz, and Ryan R. Neely III
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Raghavendra Krishnamurthy, Rob K. Newsom, Larry K. Berg, Heng Xiao, Po-Lun Ma, and David D. Turner
Atmos. Meas. Tech., 14, 4403–4424, https://doi.org/10.5194/amt-14-4403-2021, https://doi.org/10.5194/amt-14-4403-2021, 2021
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David D. Turner and Ulrich Löhnert
Atmos. Meas. Tech., 14, 3033–3048, https://doi.org/10.5194/amt-14-3033-2021, https://doi.org/10.5194/amt-14-3033-2021, 2021
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Temperature and humidity profiles in the lowest couple of kilometers near the surface are very important for many applications. Passive spectral radiometers are commercially available, and observations from these instruments have been used to get these profiles. However, new active lidar systems are able to measure partial profiles of water vapor. This paper investigates how the derived profiles of water vapor and temperature are improved when the active and passive observations are combined.
Maryna Lukach, David Dufton, Jonathan Crosier, Joshua M. Hampton, Lindsay Bennett, and Ryan R. Neely III
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Jutta Vüllers, Peggy Achtert, Ian M. Brooks, Michael Tjernström, John Prytherch, Annika Burzik, and Ryan Neely III
Atmos. Chem. Phys., 21, 289–314, https://doi.org/10.5194/acp-21-289-2021, https://doi.org/10.5194/acp-21-289-2021, 2021
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This paper provides interesting new results on the thermodynamic structure of the boundary layer, cloud conditions, and fog characteristics in the Arctic during the Arctic Ocean 2018 campaign. It provides information for interpreting further process studies on aerosol–cloud interactions and shows substantial differences in thermodynamic conditions and cloud characteristics based on comparison with previous campaigns. This certainly raises the question of whether it is just an exceptional year.
Peggy Achtert, Ewan J. O'Connor, Ian M. Brooks, Georgia Sotiropoulou, Matthew D. Shupe, Bernhard Pospichal, Barbara J. Brooks, and Michael Tjernström
Atmos. Chem. Phys., 20, 14983–15002, https://doi.org/10.5194/acp-20-14983-2020, https://doi.org/10.5194/acp-20-14983-2020, 2020
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We present observations of precipitating and non-precipitating Arctic liquid and mixed-phase clouds during a research cruise along the Russian shelf in summer and autumn of 2014. Active remote-sensing observations, radiosondes, and auxiliary measurements are combined in the synergistic Cloudnet retrieval. Cloud properties are analysed with respect to cloud-top temperature and boundary layer structure. About 8 % of all liquid clouds show a liquid water path below the infrared black body limit.
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Short summary
Fog formation is highly sensitive to near-surface temperatures and humidity profiles. Passive remote sensing instruments can provide continuous measurements of the vertical temperature and humidity profiles and liquid water content, which can improve fog forecasts. Here we compare the performance of collocated infrared and microwave remote sensing instruments and demonstrate that the infrared instrument is especially sensitive to the onset of thin radiation fog.
Fog formation is highly sensitive to near-surface temperatures and humidity profiles. Passive...
