Project description
Understanding the mechanisms of enhanced cloud ice levels in mixed-phase clouds
Clouds regulate the Earth’s energy balance and play an important role in the climate's response to changing greenhouse gas levels. They also create precipitation that affects the supply of fresh water on Earth. However, clouds – in particular mixed-phase clouds, which consist of both liquid water and ice – are the largest source of predictive error in any atmospheric and climate models. Focussing on mixed-phase clouds, the EU-funded SIMPHAC project intends to gain a quantitative understanding of the mechanisms responsible for enhanced cloud ice levels. It further aims to parametrise these processes for use in numerical models. To this end, it will use high-resolution models, a unique laboratory data set and in situ observations. This work will pave the way for more accurate weather predictions and climate projections.
Objective
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
Fields of science
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Programme(s)
Funding Scheme
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)Coordinator
70013 Irakleio
Greece