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Monthly to decadal applications

Number of tropical storms in the North Atlantic predicted for July-November 2009.

Using output from dynamical and statistical forecasting systems, we derive generic climate predictions and user-relevant applications on monthly to decadal timescales.

Long-range predictions, from dynamical or empirical methods, often refer to large-scale phenomena (e.g. ENSONAO) or give information on large-area averages. The variables for which predictions are made are most often meteorological (e.g. temperature, rainfall).

Users' needs are typically related to their economic or social activities which translate into specific, non-meteorological variables (e.g. flow into lakes, crop production, number of storms in an ocean basin).

Our work involves tailoring prediction model output to match the needs of users.

Key aims

  • To combine output from dynamical and empirical models; theoretical studies and expert judgment; to derive monthly, seasonal and decadal predictions for global and regional scales.

  • To develop user-relevant applications.

  • To support international seasonal forecasting activities.

Current activities

  • Research into seasonal prediction applications

  • Monthly forecast products 

  • Support to seasonal predictions in Africa

  • Seasonal tropical storm predictions 

  • Predictability of extremes on monthly to decadal timescales 

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