From seasons to decades: Challenges and successes in climate predictions


André Düsterhus (ICARUS, Maynooth University): From seasons to decades: Challenges and successes in climate predictions

Sorbonne Université  4 place Jussieu  75005  Paris  Sorbonne Université LOCEAN Couloir 45-55 4e étage pièce 417

Date 06/06/2023
Organisateur LOCEAN


Climate models are an important tool to gain a better
understanding about the future of our climate. With them it is
possible to reliably predict and project various climate variables
over different scales. Seasonal-to-decadal predictions (S2D) combine
climate models with initialisation procedures and allow us beside the
important predictions to learn about the models themselves.

The North Atlantic sector is a great laboratory for such
investigations. By the interaction of multiple climate modes like the
NAO or AMOC it gives us a test ground, which allow us to make high
impact predictions for the European continent. Nevertheless, models
are not perfect and so offer us many challenges, which we counter with
the understanding of physical processes and the application of
innovative statistical procedures.

This talk will investigate predictability and its challenges in the
North Atlantic area from seasons to multiple decades. For this we will
take a look at the applicability of statistical procedures on seasonal
scales to post-process ensemble and to identify new ways to
potentially predict extremes in Europe. Furthermore, we take a look at
challenges in S2D predictions, like varying prediction skill and what
this might teach us about our models. The presentation will also take
a look at model potentials, like predicting more than ten years ahead
and whether it is possible to predict not only single values but also
full distributions.

Informations dates et horaires

Date & Time: Tue Jun 06 2023 11:00:00 GMT+0200 (Central European Summer Time)
Room: salle du LOCEAN, couloir 45-55, 4ème étage, pièce 417

Lien zoom: https://cnrs.zoom.us/j/95584655492?pwd=K3Jma2R2UHMxZDAxeXlrVmFPZ3NGZz09

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