CMCC Seminar
CMCC-Bo meeting room (2nd floor) and via Zoom
April 23, h. 12:00 CEST
Speaker:
Ingo Richter
Application Laboratory, JAMSTEC
Abstract:
Global climate models (GCMs) are invariably subject to biases, some more than others. It is often assumed that such biases have a negative impact on seasonal prediction skill. Few studies, however, have confronted this issue head-on. Focusing on the tropical Atlantic, a region in which many GCMs struggle, I will show multiple lines of evidence indicating that, contrary to conventional wisdom, the impact of model biases on prediction skill is rather limited. This is not to say, however, that model predictions cannot be improved. In addition to model biases, prediction skill is also degraded by other factors, such as imperfect initialization. I will introduce a relatively simple scheme that aims to mitigate such initialization errors and their knock-on effects.
The seminar will be held in the CMCC-Bo meeting room (2nd floor) and via Zoom.<