Improved cloud phase retrievals based on remote-sensing observations have the potential to decrease the Southern Ocean shortwave cloud radiation bias ...
<!--!introduction!--> An accurate determination of location and amount of liquid water in clouds is crucial for precipitation formation, cloud lifetime, and cloud radiative effects. Most remote-sensing retrievals, such as Cloudnet use lidar measurements to infer the location of liquid cloud dr...
| Main Authors: | , , , , , |
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| Format: | Conference Object |
| Language: | unknown |
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GFZ German Research Centre for Geosciences
2023
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| Subjects: | |
| Online Access: | https://dx.doi.org/10.57757/iugg23-3856 https://gfzpublic.gfz-potsdam.de/pubman/item/item_5020689 |
| Summary: | <!--!introduction!--> An accurate determination of location and amount of liquid water in clouds is crucial for precipitation formation, cloud lifetime, and cloud radiative effects. Most remote-sensing retrievals, such as Cloudnet use lidar measurements to infer the location of liquid cloud droplets from measurements. However, lidar observations are of very limited use for optically thick or multilayer mixed-phase clouds (MPC) where they usually underestimate the presence of liquid water due to full signal attenuation, leading to large biases in simulated radiative fluxes. At the same time, general circulation models largely overestimate the downwelling shortwave radiation at the bottom of the atmosphere especially in the Southern Ocean regions. We argue that, in order to reduce this shortwave radiation bias in models, we first need better observational-based retrievals for supercooled-liquid detection that can be used for model validation. For this purpose, the machine-learning-based retrieval VOODOO ... : The 28th IUGG General Assembly (IUGG2023) (Berlin 2023) ... |
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