IMPASTO
Financiado
Inverse Modeling of PArameterized physics STochastic uncertainty using process l...
Inverse Modeling of PArameterized physics STochastic uncertainty using process level Observations
The emerging climate services in Europe and globally under the WMO GFCS critically depend on the science and application of Earth System (ES) modeling and prediction. An important aspect of the modelling and prediction challenge...
The emerging climate services in Europe and globally under the WMO GFCS critically depend on the science and application of Earth System (ES) modeling and prediction. An important aspect of the modelling and prediction challenge for the services is characterization of prediction uncertainty. Quantitative information about inherent uncertainty in the prediction is vital for risk assessments and decision support across public service and industry sectors. Over the past decades significant investments were made through the EC FPs into establishing the ES ensemble modeling and prediction capabilities that incorporate representation of sources of intrinsic uncertainty in the modeling systems and provide quantification of their impacts on seasonal to decadal climate prediction. The identified stakeholder priorities for the H2020 and beyond are in advancing of these prediction capabilities at regional level with high resolution models. This project is intended to contribute to the science of high resolution regional seasonal climate ensemble modeling, addressing the need for understanding and quantification of the prediction uncertainty at sub-regional and local scales. The research will focus on characterization of stochastic uncertainty associated with physical parameterizations in the regional ES models. The project will integrate the established ensemble modeling methodology from the foundational work with the global systems with a new approach to representing the stochastic uncertainty of physical parameterizations by means of inverse stochastic modeling using process-level observations. A long standing tradition in expert regional climate modeling at the hosting institution will be joined with the Researcher’s expertise and experience in geophysical modeling and cross-disciplinary methodology of data assimilation. The Researcher will be trained in the regional climate modeling and will apply the expertise to build a new research capacity at the hosting institution.
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Duración del proyecto: 24 meses
Fecha Inicio: 2020-04-03
Fecha Fin: 2022-04-30
Fecha Fin: 2022-04-30
Línea de financiación: concedida
El organismo H2020 notifico la concesión del proyecto el día 2022-04-30
Línea de financiación objetivo
El proyecto se financió a través de la siguiente ayuda:
WF-02-2019:
Widening Fellowships
Cerrada
hace 5 años
Presupuesto
El presupuesto total del proyecto asciende a
140K€
Líder del proyecto
Faculty of Media and Communications
No se ha especificado una descripción o un objeto social para esta compañía.
745.06K€ |
Participante