Predictability of California's Winters

Our understanding of winter precipitation variability in California remains notably incomplete, particularly regarding multi-year droughts and instances when ENSO teleconnections diverge from established patterns. This knowledge gap suggests that climate change may be a factor in shaping California's winters in the 21st century. Although ENSO and winter teleconnection inconsistencies over California are sometimes linked to Northern Hemisphere atmospheric modes, as seen in 2015/2016, the complexity increases when examining extreme winter variations in non-ENSO years. For example, the droughts of 2013/2014 and the wet winter of 2016/2017 occurred with minimal ENSO influence. However, explaining California's winter patterns is not out of reach. To support this, I present an empirical model that predicts California winters (December-January-February) using tropical ocean forcings one month in advance (November preconditioning). This model explains 60% of the spatial variability in California's winter precipitation, challenging the prevailing view that only a third is attributable to oceanic factors. It reasonably reproduces over 80% of winter precipitation patterns from 1982 to 2022, including the anomalies of the 2015/16 winter, the 2013/14 drought, and the 2016/17 wet winter. These results indicate that enhancing Earth system predictability requires moving beyond traditional models and frameworks.