Mr. Eoin Moran:

The Deputy has ventured into a major area of technicality but I will give him an answer. Part of the task of a weather forecaster is to try to provide information on what the weather may look like in the next five days, ten days, a two-week period or even a month. Sometimes one could look at a weather forecaster and decide that in actual fact he or she is predicting the predictability of the atmosphere, which is a chaotic system and is referred to as a dynamical system. The predictive capability and skill that we have, which is increasing at pace scientifically, is remarkable now compared with the past ten years. Every year we acquire another one day's predictive capability by using the very best forecasting capability in the world called an ensemble system. I will not go into the technicalities of the system. Suffice to say, instead of using one forecast we run 51 simultaneous forecasts on a super computer thus allowing us to capture the chaotic dynamical nature of the atmosphere, and all possible thermodynamic outcomes that could possibly occur in the next one to two weeks. This work is subject to continual refinement and tuning to capture all possible outcomes. The ECMWF model, which is the leading forecasting model in the world, is a leader in this area.

As we trend into the future and move into a warmer world the physics and dynamics of the atmosphere are going to change. The nature of extreme weather is something that we are going to have to work on quantifying, and we refer to this as the future weather challenge. Let us remember that there is a difference between climate and weather and I invoke the phrase that climate is what one expects and weather is what one gets. This is because, as we move into the warmer world scenarios, in the coming decades, we will see the chaotic face of weather and atmospheric dynamics emerging in that period. The science of meteorology and what we are learning from climate models are merging to encompass the capability, that we are learning from, climate models and forecasting models to improve our forecasting capability.