Collection Nonlinear and stochastic methods in climate and geophysical fluid dynamics
Organizer(s)
Date(s)
24/04/2024
Numerical Modelling applied to Weather Prediction and Climate Studies
Numerical models of the Earth-system are essential tools to understand how the system evolved and will evolve in the future. This is true whether we are aiming to understand and predict the time evolution of weather patterns, or to estimate how the past climate changed and which way the future climate could evolve.
Advances in the models’ formulation in the past decades, among which the adoption of more sophisticated data-assimilation methods and the paradigm shift from single to ensemble forecasts, have made it possible to extend the forecast skill horizon for weather prediction. Together with model improvements, the introduction of stochastic terms in the numerical model equations has led to more accurate and reliable simulations. In climate studies, the application of data-assimilation methods to past data has allowed us to reconstruct the evolution of the past climate, and ensembles of projects allow us to estimate how the future Earth climate will look like, under a range of emission scenarii.
Weather and climate needs have led, in the past decade, to an increasing convergence between the models used for weather prediction and for climate studies, and this has generated benefits for both communities. Indeed, the fact that the same ‘model’ is used over the different time scales, have forced developers to apply more thorough quality controls, with the end result being more accurate and reliable simulations. Improvements developed by one community have brought benefits to both.
During my seminar, I will briefly illustrate what is a numerical model of the Earth-system and how they are initialized to generate a weather forecast, and I will illustrate open challenges on which people are working on. I will also discuss how the same model can be used to reconstruct the past climate, and generate future climate scenario.
