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H2020Doctoral network2019–2023

CAFE · Climate Advanced Forecasting of sub-seasonal Extremes

Horizon 2020 — Marie Skłodowska-Curie Actions

Duration
2019-03-01 → 2023-02-28
EU contribution
€3,155,772
Participants
20
Scheme
MSCA-ITN

Lines connect the coordinator with its partners.

Results in brief

Climate Advanced Forecasting of sub-seasonal Extremes

Climate extremes such as heat waves or tropical storms have huge social and economic impact, and they are increasing due to climate change. Reliable forecasting of such extreme events at the sub-seasonal time scale (from 10 days to 3 months) is of great importance, allowing for early warnings and adequate mitigation strategies, reducing damage and saving human lives. The World Meteorological Organization (WMO), the World Weather Research Programme and World Climate Research Programme acknowledge the importance of sub-seasonal forecasts by running the Sub-seasonal to Seasonal Prediction Project. Delivering reliable and timely information on extremes is an enormous challenge due to the complexity of the atmosphere-ocean coupled system, which requires an interdisciplinary effort of meteorologists, climate scientists, mathematicians, statisticians, and non-linear physicists. Advancing the understanding of phenomena (Madden-Julian Oscillation, planetary waves, and atmospheric blocking) which are believed to act as sources of predictability of extremes at this scale is fundamental, as well as translating this knowledge into tools for prediction. The ultimate goal of the project "CAFE" (Climate Advanced Forecasting of sub-seasonal Extremes) is to train a new generation of interdisciplinary scientists to move forward this area of knowledge, in order to advance three scientific objectives, during the project and beyond: 1. Understanding the phenomena behind the sub-seasonal variability (blockings, Madden-Julian Oscillation, Rossby Wave packets, etc.). 2. Improving the detection and analysis of weather extremes and their possible increase with global warming. 3. Developing a diverse range of tools to improve forecasting of extremes at the sub-seasonal scale.

Data: CORDIS, © European Union

Project objective

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.

Original text from CORDIS.

Participants

  • Consorci Centre de Recerca Matematica · BellaterraCoordinatorSpain
  • AGENCIA ESTATAL CONSEJO SUPERIOR DE INVESTIGACIONES CIENTIFICAS · MadridSpain
  • COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES · ParisFrance
  • EUROPEAN CENTRE FOR MEDIUM-RANGE WEATHER FORECASTS · READINGUnited Kingdom
  • Guy Carpenter · LondonUnited Kingdom
  • HUMBOLDT-UNIVERSITAET ZU BERLIN · BerlinGermany
  • MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EV · MUNCHENGermany
  • METEO-FRANCE · Saint Mande CedexFrance
  • MUNCHENER RUCKVERSICHERUNGS-GESELLSCHAFT AG · MUNCHENGermany
  • POTSDAM-INSTITUT FUR KLIMAFOLGENFORSCHUNG EV · PotsdamGermany
  • PREDICTIA INTELLIGENT DATA SOLUTIONS SL · SANTANDERSpain
  • SERVEI METEROLOGIC DE CATALUNYA · BARCELONASpain
  • SUEZ ARIA TECHNOLOGIES · NANTERREFrance
  • TECHNISCHE UNIVERSITAET BERGAKADEMIE FREIBERG · FreibergGermany
  • TECHNISCHE UNIVERSITAET DRESDEN · DresdenGermany
  • UNIVERSIDAD DE LA REPUBLICA · MontevideoUruguay
  • UNIVERSITAT AUTONOMA DE BARCELONA · Cerdanyola Del VallesSpain
  • UNIVERSITAT DE LES ILLES BALEARS · PALMA DE MALLORCASpain
  • UNIVERSITAT POLITECNICA DE CATALUNYA · BARCELONASpain
  • UNIVERSITE PAUL SABATIER TOULOUSE III · Toulouse Cedex 9France

Links

Data: CORDIS, © European Union