In 2009 the World Meteorological Organization (WMO) Commission of Atmospheric Sciences (CAS) requested that WCRP, together with the World Weather Research Programme (WWRP) and the Observing System Research and Predictability Experiment (THORPEX), set up a collaborative structure for subseasonal prediction. As a result, the Subseasonal-to-Seasonal (S2S) Prediction Project began in 2013.

Take part in the Seasonal-to-Subseasonal Project Review!

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  1. To improve forecast skill and understanding on the subseasonal to seasonal timescale with special emphasis on high-impact weather events
  2. To promote the initiatives uptake by operational centres and exploitation by the applications community
  3. To capitalize on the expertise of the weather and climate research communities to address issues of importance to the Global Framework for Climate Services

Research Priorities

  1. Evaluate potential predictability of subseasonal events, including identifying windows of opportunity for increased forecast skill.
  2. Understand systematic errors and biases in the subseasonal to seasonal forecast range
  3. Compare, verify and test multi-model combinations from these forecasts and quantify their uncertainty.
  4. Focus on some specific extreme event case studies.

Scientific issues

  1. Identify sources of predictability at the sub-seasonal to seasonal time-range.
  2. Prediction of the MJO and its impacts in numerical models
  3. Teleconnections — forecasts of opportunity
  4. Monsoon prediction.
  5. Rainfall predictability and extreme events
  6. Polar prediction and sea-ice
  7. Stratospheric processes

Modelling issues

  1. Role of resolution
  2. Role of ocean-atmosphere coupling
  3. Teleconnections — forecasts of opportunity
  4. Systematic errors.
  5. Initialisation strategies for subseasonal prediction
  6. Ensemble generation
  7. Spread/skill relationship
  8. Verification


Steering Group and Liaison Group

For further information please visit the Seasonal-to-Subseasonal (S2S) Prediction Project website.

Seasonal-to-Subseasonal (S2S) Prediction Project