Doppler LiDAR observation of subsidence in synoptic scale and performance of a global numerical weather prediction model in capturing the subsidence
The vertical velocity data from a Doppler LiDAR situated at the centre of Hong Kong were examined to look for signature of subsidence within the atmospheric boundary layer against a synoptic background. Two case studies were performed, namely, stable atmospheric conditions in foggy weather and possi...
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sg-ntu-dr.10356-1738242024-03-04T15:30:49Z Doppler LiDAR observation of subsidence in synoptic scale and performance of a global numerical weather prediction model in capturing the subsidence Chan, Pak Wai Yim, Steve Hung Lam Huang, Tao Asian School of the Environment Lee Kong Chian School of Medicine (LKCMedicine) Earth Observatory of Singapore Earth and Environmental Sciences Doppler LiDAR Vertical velocity The vertical velocity data from a Doppler LiDAR situated at the centre of Hong Kong were examined to look for signature of subsidence within the atmospheric boundary layer against a synoptic background. Two case studies were performed, namely, stable atmospheric conditions in foggy weather and possible “subsidence heating” at the periphery of the outer circulation of an intense tropical cyclone. The LiDAR’s Doppler velocity data were found to provide insights into the vertical motion of the air on the synoptic scale. They appear to confirm subsidence in foggy weather but provide new information about the mechanism for the occurrence of extremely hot weather. The data were also compared with vertical velocity forecasts from a numerical weather prediction model to assess the quality of the forecast. The Doppler LiDAR’s vertical velocity data were found to be useful in the verification of omega forecasts from the global numerical weather prediction model. They were found to provide further insights into the subsidence of the troposphere, particularly the atmospheric boundary layer, in certain synoptic patterns. Published version 2024-02-29T02:38:29Z 2024-02-29T02:38:29Z 2023 Journal Article Chan, P. W., Yim, S. H. L. & Huang, T. (2023). Doppler LiDAR observation of subsidence in synoptic scale and performance of a global numerical weather prediction model in capturing the subsidence. Atmosphere, 14(11), 1686-. https://dx.doi.org/10.3390/atmos14111686 2073-4433 https://hdl.handle.net/10356/173824 10.3390/atmos14111686 2-s2.0-85178085211 11 14 1686 en Atmosphere © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). application/pdf |
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Earth and Environmental Sciences Doppler LiDAR Vertical velocity Chan, Pak Wai Yim, Steve Hung Lam Huang, Tao Doppler LiDAR observation of subsidence in synoptic scale and performance of a global numerical weather prediction model in capturing the subsidence |
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The vertical velocity data from a Doppler LiDAR situated at the centre of Hong Kong were examined to look for signature of subsidence within the atmospheric boundary layer against a synoptic background. Two case studies were performed, namely, stable atmospheric conditions in foggy weather and possible “subsidence heating” at the periphery of the outer circulation of an intense tropical cyclone. The LiDAR’s Doppler velocity data were found to provide insights into the vertical motion of the air on the synoptic scale. They appear to confirm subsidence in foggy weather but provide new information about the mechanism for the occurrence of extremely hot weather. The data were also compared with vertical velocity forecasts from a numerical weather prediction model to assess the quality of the forecast. The Doppler LiDAR’s vertical velocity data were found to be useful in the verification of omega forecasts from the global numerical weather prediction model. They were found to provide further insights into the subsidence of the troposphere, particularly the atmospheric boundary layer, in certain synoptic patterns. |
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Asian School of the Environment |
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Asian School of the Environment Chan, Pak Wai Yim, Steve Hung Lam Huang, Tao |
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Chan, Pak Wai Yim, Steve Hung Lam Huang, Tao |
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Chan, Pak Wai |
title |
Doppler LiDAR observation of subsidence in synoptic scale and performance of a global numerical weather prediction model in capturing the subsidence |
title_short |
Doppler LiDAR observation of subsidence in synoptic scale and performance of a global numerical weather prediction model in capturing the subsidence |
title_full |
Doppler LiDAR observation of subsidence in synoptic scale and performance of a global numerical weather prediction model in capturing the subsidence |
title_fullStr |
Doppler LiDAR observation of subsidence in synoptic scale and performance of a global numerical weather prediction model in capturing the subsidence |
title_full_unstemmed |
Doppler LiDAR observation of subsidence in synoptic scale and performance of a global numerical weather prediction model in capturing the subsidence |
title_sort |
doppler lidar observation of subsidence in synoptic scale and performance of a global numerical weather prediction model in capturing the subsidence |
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2024 |
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https://hdl.handle.net/10356/173824 |
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1794549423833874432 |