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CAFE

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Climate Advanced Forecasting of sub seasonal Extremes

Climate extremes such as heat waves or tropical storms have huge social and economic impact. The forecasting of such extreme events at the sub-seasonal time scale (from 10 days to 3 months) is challenging. Since the atmosphere and... ver más

28/02/2023

CONSORCI CENTRE DE...

3M€

Presupuesto del proyecto: 3M€

Líder del proyecto

CONSORCI CENTRE DE RECERCA MATEMATICA Otra investigación y desarrollo experimental en ciencias naturales y técnicas otros tipos

TRL 4-5 | 50K€

Fecha límite participación Sin fecha límite de participación.

Ver 22 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2023-02-28

MSCA-ITN-2018: Innovative Training Networks

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Cerrada hace 7 años

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22 Participantes

CONSORCI CENTRE DE RECERCA M...

501.81K€ | Lider

COMEXI GROUP INDUSTRIES

471.88K€ | Participante

TUD

N.D. | Participante

TU BAF

252.79K€ | Participante

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Duración del proyecto: 54 meses Fecha Inicio: 2018-08-20
Fecha Fin: 2023-02-28

Líder del proyecto

CONSORCI CENTRE DE RECERCA MATEMATICA Otra investigación y desarrollo experimental en ciencias naturales y técnicas otros tipos

TRL 4-5 | 50K€

Presupuesto del proyecto 3M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto Climate extremes such as heat waves or tropical storms have huge social and economic impact. The forecasting of such extreme events at the sub-seasonal time scale (from 10 days to 3 months) is challenging. Since the atmosphere and the ocean are coupled systems of enormous complexity, in order to advance sub-seasonal predictability of extreme events, it is crucial to train a new kind of interdisciplinary top-level researchers. CAFE research is structured in three WP: Atmospheric and oceanic processes, Extreme events and Tools for predictability, and brings together an interdisciplinary team of scientists. Objectives: Study of the relation between RWPs and the large scale environment, and the resulting limit of predictability; Statistical characterization of MJO events, dependence on climatic factors, and simple modelling to evaluate predictability; Development of diagnosis tools for identification and tracking of the MJO, blocking, waves and oceanic structures; Analysis of climatic changes in weather patterns and their relation with new climatic phenomena and extreme events in Europe; Estimation of probabilities for severe damages due to extreme events associated to ENSO; Validation of the hypothesis of cascades of extreme events and effects of a non-stationary climate; Estimation of exceedance probabilities for intensity of severe atmospheric events, including windstorms and hurricanes; Assessment of the response of extreme weather events for different levels of stabilized global warming and comparison with their response to internal modes of climate variability; Development of a procedure to improve the predictability of the onset of monsoon; Advanced statistical analysis of dynamic associations between SSS and extreme precipitation events; Study of predictability of large-scale atmospheric flow patterns over the Mediterranean connected to extreme weather; Systematic quantification of the predictability potential of a SWG of analogues of atmospheric circulation.

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