Multi-model Physically-based constrained decadal predictions of precipitation over Europe

Decadal climate predictions are our most reliable source of climate information for the near-term climate change. They can be very useful to develop climate services to users from sectors such as agriculture, industry, energy, water management, health, etc. However, before developing these climate services, an assessment of the forecast quality for the variables and regions of interest is needed. In this work, we consider the available retrospective decadal predictions (DCPP-A) contributing to phase 6 of the Coupled model Intercomparison Project (CMIP6) and analyze their skill to predict rainfall over Europe. Rainfall variability over Europe is strongly linked to variations in the North Atlantic jet stream. At multidecadal time scales, some studies have shown that the variability of the North Atlantic jet stream could be driven by low-frequency changes in the sea surface temperature over the north Atlantic associated with the Atlantic Multidecadal Variability. Retrospective decadal predictions present skill to predict the low-frequency variability of the SST associated with Atlantic Multidecadal Variability. However, they have difficulties in predicting precipitation variability over Europe. Here, we analyze the skill of DCPP-A models to predict precipitation over Europe, exploring the multimodel ensemble to identify the models with enhanced skill, investigating as well the underlying reasons. In particular, we look at the link between the local precipitation skill and the representation of key teleconnection mechanisms that connect European precipitation to other remote highly-predictable regions. Results from this study will contribute to a better understanding of the multidecadal European precipitation variability and will define benchmarks for improving its prediction in decadal forecast systems.