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| Funder | Natural Environment Research Council |
|---|---|
| Recipient Organization | University of Leeds |
| Country | United Kingdom |
| Start Date | Sep 30, 2022 |
| End Date | Jun 29, 2026 |
| Duration | 1,368 days |
| Number of Grantees | 2 |
| Roles | Student; Supervisor |
| Data Source | UKRI Gateway to Research |
| Grant ID | 2748901 |
This project combines weather-scale and climate modelling with satellite data to understand ice formation in clouds and the effect on future climate.
Climate models are very poor at representing the mixture of ice and supercooled water drops in clouds. Models therefore diverge dramatically in the amounts of ice and water that they simulate and the agreement with satellite observations is extremely poor for many models. The formation of ice crystals in a cloud reduces cloud reflectivity and can even result in the complete removal of cloud water through strong precipitation, leading to substantial reductions in cloud coverage.
The huge range of model predictions is partly due to inadequate (and sometimes non-physical) representations of ice-related processes in models, with most models even neglecting any representation of the particles that trigger ice formation - ice-nucleating particles (INPs).
Ice formation is a critical process in determining the magnitude of cloud feedbacks (how much a change in cloud properties in a future climate could alter the climate). It therefore represents a major uncertainty in climate projections. Two key factors determining the strength of the feedback for mixed-phase clouds are the amount of ice in present-day clouds and the response of this ice content to increases in temperature or other alterations in the meteorological conditions.
This project will use satellite observations to understand and then constrain these factors in the UK Earth System Model (UKESM).
University of Leeds
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