Improved cloud phase retrievals based on remote-sensing observations have the potential to decrease the Southern Ocean shortwave cloud radiation bias
Accurately identifying liquid water layers in mixed-phase clouds is crucial for estimating cloud radiative effects. Lidar-based retrievals are limited in optically thick or multilayer clouds, leading to positive biases in simulated shortwave radiative fluxes. At the same time, general circulation mo...
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2023
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Online Access: | http://dx.doi.org/10.22541/essoar.168182347.76241143/v1 |
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crwinnower:10.22541/essoar.168182347.76241143/v1 2024-06-02T08:14:45+00:00 Improved cloud phase retrievals based on remote-sensing observations have the potential to decrease the Southern Ocean shortwave cloud radiation bias Schimmel, Willi Velasco, Carola Barrientos Witthuhn, Jonas Radenz, Martin González, Boris Barja Kalesse-Los, Heike 2023 http://dx.doi.org/10.22541/essoar.168182347.76241143/v1 unknown Authorea, Inc. posted-content 2023 crwinnower https://doi.org/10.22541/essoar.168182347.76241143/v1 2024-05-07T14:19:23Z Accurately identifying liquid water layers in mixed-phase clouds is crucial for estimating cloud radiative effects. Lidar-based retrievals are limited in optically thick or multilayer clouds, leading to positive biases in simulated shortwave radiative fluxes. At the same time, general circulation models also tend to overestimate the downwelling shortwave radiation at the surface especially in the Southern Ocean regions. To reduce this SW radiation bias in models, we first need better observational-based retrievals for liquid detection which can later be used for model validation. To address this, a machine-learning-based liquid-layer detection method called VOODOO was employed in a proof-of-concept study using a single column radiative transfer model to compare shortwave cloud radiative effects of liquid-containing clouds detected by Cloudnet and VOODOO to ground-based and satellite observations. Results showed a reduction in shortwave radiation bias, indicating that liquid-layer detection with machine-learning retrievals can improve radiative transfer simulations. Other/Unknown Material Southern Ocean The Winnower Southern Ocean |
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Open Polar |
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The Winnower |
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description |
Accurately identifying liquid water layers in mixed-phase clouds is crucial for estimating cloud radiative effects. Lidar-based retrievals are limited in optically thick or multilayer clouds, leading to positive biases in simulated shortwave radiative fluxes. At the same time, general circulation models also tend to overestimate the downwelling shortwave radiation at the surface especially in the Southern Ocean regions. To reduce this SW radiation bias in models, we first need better observational-based retrievals for liquid detection which can later be used for model validation. To address this, a machine-learning-based liquid-layer detection method called VOODOO was employed in a proof-of-concept study using a single column radiative transfer model to compare shortwave cloud radiative effects of liquid-containing clouds detected by Cloudnet and VOODOO to ground-based and satellite observations. Results showed a reduction in shortwave radiation bias, indicating that liquid-layer detection with machine-learning retrievals can improve radiative transfer simulations. |
format |
Other/Unknown Material |
author |
Schimmel, Willi Velasco, Carola Barrientos Witthuhn, Jonas Radenz, Martin González, Boris Barja Kalesse-Los, Heike |
spellingShingle |
Schimmel, Willi Velasco, Carola Barrientos Witthuhn, Jonas Radenz, Martin González, Boris Barja Kalesse-Los, Heike Improved cloud phase retrievals based on remote-sensing observations have the potential to decrease the Southern Ocean shortwave cloud radiation bias |
author_facet |
Schimmel, Willi Velasco, Carola Barrientos Witthuhn, Jonas Radenz, Martin González, Boris Barja Kalesse-Los, Heike |
author_sort |
Schimmel, Willi |
title |
Improved cloud phase retrievals based on remote-sensing observations have the potential to decrease the Southern Ocean shortwave cloud radiation bias |
title_short |
Improved cloud phase retrievals based on remote-sensing observations have the potential to decrease the Southern Ocean shortwave cloud radiation bias |
title_full |
Improved cloud phase retrievals based on remote-sensing observations have the potential to decrease the Southern Ocean shortwave cloud radiation bias |
title_fullStr |
Improved cloud phase retrievals based on remote-sensing observations have the potential to decrease the Southern Ocean shortwave cloud radiation bias |
title_full_unstemmed |
Improved cloud phase retrievals based on remote-sensing observations have the potential to decrease the Southern Ocean shortwave cloud radiation bias |
title_sort |
improved cloud phase retrievals based on remote-sensing observations have the potential to decrease the southern ocean shortwave cloud radiation bias |
publisher |
Authorea, Inc. |
publishDate |
2023 |
url |
http://dx.doi.org/10.22541/essoar.168182347.76241143/v1 |
geographic |
Southern Ocean |
geographic_facet |
Southern Ocean |
genre |
Southern Ocean |
genre_facet |
Southern Ocean |
op_doi |
https://doi.org/10.22541/essoar.168182347.76241143/v1 |
_version_ |
1800738713171394560 |