Climate predictability arises when more slowly varying components of the climate system, like the ocean, significantly influence the atmosphere, especially when two-way interaction reinforces variability, or when external factors impact climate. The former is the case for seasonal prediction of the El Niño Southern Oscillation (ENSO).
While there is promise that climate can be predicted a decade in advance, especially for the North Atlantic region, predictions remain highly experimental. Thus, climate prediction is one of the main frontiers in climate research – ranked a Grand Challenge by the World Climate Research Programme.
To realize the full potential of climate prediction we must move beyond statistical approaches. However the development of skillful numerical climate prediction faces three major challenges:
- The mechanisms underlying prediction are incompletely understood and poorly represented in models.
- Data assimilation methods for combining model and observations must be adapted to the coupled climate system.
- The limits to climate prediction are largely unknown, delaying investment in operational systems.
The best possible climate prediction system for the Atlantic-Arctic sector can now be realized through a dedicated unit – the Bjerknes CPU – that provides the long-term perspective and resources required to meet these three key challenges. Find out more by navigating through our Research Activities below!