Summary
Clouds are a key component of global climate. Alteration to simulated cloud in climate models has large surface temperature effects, yet we cannot validate model predictions for the future against observations. Reconstructions of major patterns in mid-Piacenzian Warm Period (mPWP) cloud can provide critical verification data from an analogous past climate to assess the cloud prediction ability of state-of-the-art climate models, however there are no known biological proxies for cloud in deep-time.
The aim of PReP is to develop proxies capable of reconstructing past cloud and to use them to establish a global cloud database for the mPWP, for testing cloud model prediction performance.
The development of biological proxies for cloud characteristics in deep-time will be pursued in two streams: statistical methods – testing cloud as an emergent property of existing palaeoclimate estimates and testing the extent to which existing palaeoclimate schemes can be expanded to predict cloud – and experimental methods – investigating a novel proxy for cloud through leaf micromorphological variation under cloud-mimicking light schemes. The methods will be used to reanalyse existing data for mPWP sites with the aim of establishing a global palaeocloud dataset for model verification within the Pliocene Modelling Intercomparison Project.
My experience in multiproxy palaeoclimate analysis, and Pliocene palaeoclimate specifically, combined with the interdisciplinary expertise at the University of Leeds in Pliocene climate modelling and applied statistics, and at the National University of Ireland, Galway in palaeobotany, will create the optimal intellectual environment to deliver the aims of the project. The experience of my host as a supervisor and mentor for early career researchers, and the supporting resources of the university for dissemination of results and exceptional training opportunities in both hard and soft skills, will facilitate independence in my research career.
The aim of PReP is to develop proxies capable of reconstructing past cloud and to use them to establish a global cloud database for the mPWP, for testing cloud model prediction performance.
The development of biological proxies for cloud characteristics in deep-time will be pursued in two streams: statistical methods – testing cloud as an emergent property of existing palaeoclimate estimates and testing the extent to which existing palaeoclimate schemes can be expanded to predict cloud – and experimental methods – investigating a novel proxy for cloud through leaf micromorphological variation under cloud-mimicking light schemes. The methods will be used to reanalyse existing data for mPWP sites with the aim of establishing a global palaeocloud dataset for model verification within the Pliocene Modelling Intercomparison Project.
My experience in multiproxy palaeoclimate analysis, and Pliocene palaeoclimate specifically, combined with the interdisciplinary expertise at the University of Leeds in Pliocene climate modelling and applied statistics, and at the National University of Ireland, Galway in palaeobotany, will create the optimal intellectual environment to deliver the aims of the project. The experience of my host as a supervisor and mentor for early career researchers, and the supporting resources of the university for dissemination of results and exceptional training opportunities in both hard and soft skills, will facilitate independence in my research career.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101017833 |
| Start date: | 17-05-2021 |
| End date: | 06-06-2023 |
| Total budget - Public funding: | 224 933,76 Euro - 224 933,00 Euro |
Cordis data
Original description
Clouds are a key component of global climate. Alteration to simulated cloud in climate models has large surface temperature effects, yet we cannot validate model predictions for the future against observations. Reconstructions of major patterns in mid-Piacenzian Warm Period (mPWP) cloud can provide critical verification data from an analogous past climate to assess the cloud prediction ability of state-of-the-art climate models, however there are no known biological proxies for cloud in deep-time.The aim of PReP is to develop proxies capable of reconstructing past cloud and to use them to establish a global cloud database for the mPWP, for testing cloud model prediction performance.
The development of biological proxies for cloud characteristics in deep-time will be pursued in two streams: statistical methods – testing cloud as an emergent property of existing palaeoclimate estimates and testing the extent to which existing palaeoclimate schemes can be expanded to predict cloud – and experimental methods – investigating a novel proxy for cloud through leaf micromorphological variation under cloud-mimicking light schemes. The methods will be used to reanalyse existing data for mPWP sites with the aim of establishing a global palaeocloud dataset for model verification within the Pliocene Modelling Intercomparison Project.
My experience in multiproxy palaeoclimate analysis, and Pliocene palaeoclimate specifically, combined with the interdisciplinary expertise at the University of Leeds in Pliocene climate modelling and applied statistics, and at the National University of Ireland, Galway in palaeobotany, will create the optimal intellectual environment to deliver the aims of the project. The experience of my host as a supervisor and mentor for early career researchers, and the supporting resources of the university for dissemination of results and exceptional training opportunities in both hard and soft skills, will facilitate independence in my research career.
Status
CLOSEDCall topic
MSCA-IF-2020Update Date
28-04-2024
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