The Project

The Project

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 Work Package:

  1. Atmospheric and oceanic processes
  2. Extreme events
  3. Tools for predictability.

The ultimate goal of the CAFE project is to improve the sub-seasonal predictability of extreme weather events through the interdisciplinary training of 12 ESRs in aspects such as climate science, complex networks and data analysis. Climate extremes such as heat waves, drought, extreme precipitation or cold surges have huge social and economic impacts that are expected to increase with climate change. Forecasting of such extreme events on the sub-seasonal time scale (from 10 days to about 3 months) is very challenging because of the poor understanding of phenomena that may increase predictability at this time scale, such as the Madden-Julian Oscillation, planetary waves and atmospheric blockings. Reliable sub-seasonal climate information is of great importance, allowing for early warnings and adequate mitigation strategies. The World Meteorological Organization World Weather Research Programme and World Climate Research Programme acknowledge the importance of sub-seasonal forecasts by running the Sub-seasonal to Seasonal Project.


  • Study of the relation between Rossby wave packets and the large scale environment, and the resulting limit of predictability.
  • Statistical characterization of Madden-Julian Oscillation events, dependence on climatic factors, and simple modelling to evaluate predictability.
  • Development of diagnosis tools for identification and tracking of the Madden-Julian Oscillation, 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 El Niño Southern Oscillation.
  • 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.