Summary
Clouds may never have had a more important meaning to society as they have today. They regulate the Earth's energy balance and are key drivers of how climate responds to changing greenhouse gas levels. Moreover, they generate precipitation, which has a direct impact on the supply of fresh water on Earth. Clouds however are the most elusive component of the climate system, and the largest source of predictive error in any atmospheric and climate models. Of all cloud types, mixed-phase (consisting of both liquid water and ice) clouds are by far the most uncertain, while they dominate the energy balance and precipitation in many regions of the globe. At the heart of this uncertainty is the inability to capture ice crystal formation and the explosive multiplication that can occur, which in turn fundamentally affect cloud processes. The exact mechanisms involved and their relative importance remain unknown; as a result a description of these processes is currently missing in weather forecast and climate models. Our aim is to resolve this ice formation “paradox”, by quantitatively understanding the mechanisms responsible for enhanced cloud ice levels, and develop parameterizations of these processes for use in numerical models. For this purpose we will use state-of-the-art highresolution models, a unique laboratory dataset and in-situ observations, while our parameterizations will be tested in a weather forecast model. Our initial focus will be in the Arctic, the most climatically sensitive region of the planet, but results have the potential to improve mixed-phase cloud representation at lower latitudes as well. As clouds are a critical component of the climate system, improving cloud-ice representation in models is expected to result in more accurate weather predictions and future climate projections
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| Web resources: | https://cordis.europa.eu/project/id/898568 |
| Start date: | 01-09-2021 |
| End date: | 19-09-2023 |
| Total budget - Public funding: | 153 085,44 Euro - 153 085,00 Euro |
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Original description
Clouds may never have had a more important meaning to society as they have today. They regulate the Earth's energy balance and are key drivers of how climate responds to changing greenhouse gas levels. Moreover, they generate precipitation, which has a direct impact on the supply of fresh water on Earth. Clouds however are the most elusive component of the climate system, and the largest source of predictive error in any atmospheric and climate models. Of all cloud types, mixed-phase (consisting of both liquid water and ice) clouds are by far the most uncertain, while they dominate the energy balance and precipitation in many regions of the globe. At the heart of this uncertainty is the inability to capture ice crystal formation and the explosive multiplication that can occur, which in turn fundamentally affect cloud processes. The exact mechanisms involved and their relative importance remain unknown; as a result a description of these processes is currently missing in weather forecast and climate models. Our aim is to resolve this ice formation “paradox”, by quantitatively understanding the mechanisms responsible for enhanced cloud ice levels, and develop parameterizations of these processes for use in numerical models. For this purpose we will use state-of-the-art highresolution models, a unique laboratory dataset and in-situ observations, while our parameterizations will be tested in a weather forecast model. Our initial focus will be in the Arctic, the most climatically sensitive region of the planet, but results have the potential to improve mixed-phase cloud representation at lower latitudes as well. As clouds are a critical component of the climate system, improving cloud-ice representation in models is expected to result in more accurate weather predictions and future climate projectionsStatus
TERMINATEDCall topic
MSCA-IF-2019Update Date
28-04-2024
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