Summary
Understanding the impact of climate change on extreme rainfall is vital for informed mitigation and adaptation plans. However, climate models struggle to produce realistic rainfall.
SPLICER will provide unique insight into the origin of European rainfall errors in climate models and help improve future projections of extreme rainfall.
Our approach recognises that localised rainfall extremes are part of a multiscale process, starting with the global mean climate and mediated by synoptic weather precursors. We exploit two main novelties:
1) A ‘tiered model’ approach, considering global earth system models, regional models and novel km-scale models (also known as convection-permitting or storm-resolving) in a holistic framework.
2) A physically-based decomposition of rainfall drivers, into global, synoptic and local terms.
The analysis is supported by the adaptation of tools from the weather forecasting field, which will enable systematic identification and quantification of rainfall precursors in large multi-model datasets.
This interdisciplinary proposal will advance a new mindset linking weather, regional climate, and global climate modelling communities together, and build international research links between the networks of the fellow and the host institution.
Novel insights into changing local rainfall extremes will be directly communicated to stakeholders and the public, as well as scientific peers, ensuring societal impact.
The training goals of SPLICER are intrinsically integrated with research objectives, ensuring the fellow will develop transferable skills and competences (in particular; numerical modeling and stakeholder engagement), promising to improve academic and non-academic employability. The fellow will expand the host institution’s research capacity in understanding synoptic drivers of extreme events, and will contribute research-led teaching via provision of courses and workshops for graduate students, PhD and postdoctoral researchers.
SPLICER will provide unique insight into the origin of European rainfall errors in climate models and help improve future projections of extreme rainfall.
Our approach recognises that localised rainfall extremes are part of a multiscale process, starting with the global mean climate and mediated by synoptic weather precursors. We exploit two main novelties:
1) A ‘tiered model’ approach, considering global earth system models, regional models and novel km-scale models (also known as convection-permitting or storm-resolving) in a holistic framework.
2) A physically-based decomposition of rainfall drivers, into global, synoptic and local terms.
The analysis is supported by the adaptation of tools from the weather forecasting field, which will enable systematic identification and quantification of rainfall precursors in large multi-model datasets.
This interdisciplinary proposal will advance a new mindset linking weather, regional climate, and global climate modelling communities together, and build international research links between the networks of the fellow and the host institution.
Novel insights into changing local rainfall extremes will be directly communicated to stakeholders and the public, as well as scientific peers, ensuring societal impact.
The training goals of SPLICER are intrinsically integrated with research objectives, ensuring the fellow will develop transferable skills and competences (in particular; numerical modeling and stakeholder engagement), promising to improve academic and non-academic employability. The fellow will expand the host institution’s research capacity in understanding synoptic drivers of extreme events, and will contribute research-led teaching via provision of courses and workshops for graduate students, PhD and postdoctoral researchers.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101151904 |
| Start date: | 01-07-2024 |
| End date: | 30-06-2026 |
| Total budget - Public funding: | - 226 751,00 Euro |
Cordis data
Original description
Understanding the impact of climate change on extreme rainfall is vital for informed mitigation and adaptation plans. However, climate models struggle to produce realistic rainfall.SPLICER will provide unique insight into the origin of European rainfall errors in climate models and help improve future projections of extreme rainfall.
Our approach recognises that localised rainfall extremes are part of a multiscale process, starting with the global mean climate and mediated by synoptic weather precursors. We exploit two main novelties:
1) A ‘tiered model’ approach, considering global earth system models, regional models and novel km-scale models (also known as convection-permitting or storm-resolving) in a holistic framework.
2) A physically-based decomposition of rainfall drivers, into global, synoptic and local terms.
The analysis is supported by the adaptation of tools from the weather forecasting field, which will enable systematic identification and quantification of rainfall precursors in large multi-model datasets.
This interdisciplinary proposal will advance a new mindset linking weather, regional climate, and global climate modelling communities together, and build international research links between the networks of the fellow and the host institution.
Novel insights into changing local rainfall extremes will be directly communicated to stakeholders and the public, as well as scientific peers, ensuring societal impact.
The training goals of SPLICER are intrinsically integrated with research objectives, ensuring the fellow will develop transferable skills and competences (in particular; numerical modeling and stakeholder engagement), promising to improve academic and non-academic employability. The fellow will expand the host institution’s research capacity in understanding synoptic drivers of extreme events, and will contribute research-led teaching via provision of courses and workshops for graduate students, PhD and postdoctoral researchers.
Status
SIGNEDCall topic
HORIZON-MSCA-2023-PF-01-01Update Date
22-11-2024
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