Hola,
¿eres nuevo aquí?

Regístrate gratis y conecta tu empresa con financiación pública, partners y proyectos.

Tengo cuenta

Regístrate

Ver video

CausalBoost

Financiado

Cerrado

Using causal discovery algorithms to boost subseasonal to seasonal forecast skil...

Using causal discovery algorithms to boost subseasonal to seasonal forecast skill of Mediterranean rainfall The Mediterranean region (MED) is a hotspot of anthropogenic climate change and impacts are probably already felt today; recent heatwaves and persistent droughts have led to crop failures, wild fires and water shortages, causing l... ver más

28/02/2022

THE UNIVERSITY OF...

213K€

Presupuesto del proyecto: 213K€

Líder del proyecto

THE UNIVERSITY OF READING No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2022-02-28

MSCA-IF-2018: Individual Fellowships

I+D

Cerrada hace 6 años

0% 100%

Características del participante

Este proyecto no cuenta con búsquedas de partenariado abiertas en este momento.

Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

1 Participantes

THE UNIVERSITY OF READING

212.93K€ | Lider

Proyectos interesantes

PREVENT

Environmental S...

Data Science

3M€ Cerrado

CGL2017-86415-R

Environmental S...

Data Science

133K€ Cerrado

SPECS

Environmental S...

Data Science

12M€ Cerrado

INTEXseas

Environmental S...

Data Science

3M€ Cerrado

PACE

Environmental S...

Data Science

188K€ Cerrado

CGL2011-24458

Environmental S...

Data Science

244K€ Cerrado

Conecta tu I+D

¿Tienes un proyecto y buscas un partner? Gracias a nuestro motor inteligente podemos recomendarte los mejores socios y ponerte en contacto con ellos. Te lo explicamos en este video

Duración del proyecto: 34 meses Fecha Inicio: 2019-04-12
Fecha Fin: 2022-02-28

Líder del proyecto

THE UNIVERSITY OF READING No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 213K€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto The Mediterranean region (MED) is a hotspot of anthropogenic climate change and impacts are probably already felt today; recent heatwaves and persistent droughts have led to crop failures, wild fires and water shortages, causing large economic losses. Climate models robustly project further warming and drying of the region, putting it at risk of desertification. The particular vulnerability of this water-limited region to climatic changes has created an urgent need for reliable forecasts of rainfall on subseasonal to seasonal (S2S) timescales, i.e. 2 weeks up to a season ahead. This S2S time-range is particularly crucial, as the prediction lead time is long enough to implement adaptation measures, and short enough to be of immediate relevance for decision makers. However, predictions on lead-times beyond approximately 10 days fall into the so-called weather-climate prediction gap, with operational forecast models only providing marginal skill. The reasons for this are a range of fundamental challenges, including a limited causal understanding of the underlying sources of predictability. The proposed research effort aims to improve S2S forecasts of MED rainfall by taking an innovative, interdisciplinary approach that combines novel causal discovery algorithms from complex system science with operational forecast models. This will overcome current limitations of conventional statistical methods to identify relevant sources of predictability and to evaluate modelled teleconnection processes. The outcomes of this project will (i) identify key S2S drivers of MED rainfall, (ii) systematically evaluate them in forecast models, (iii) derive process-based bias corrections to (iv) boost forecast skill. My strong background in both causal inference techniques and atmospheric dynamics puts me in a unique position to lead this innovative effort and to achieve real progress in reducing the weather-climate prediction gap for the MED region.

Conecta tu I+D

Entra hoy

¿Olvidé mi contraseña?

Financiación

Empresas

CTIs/Universidades

Proyectos

Investigadores