Sources of Subseasonal Predictability of Atmospheric Rivers

Abstract Atmospheric rivers (ARs) are characterized by intense lower tropospheric plumes of moisture transport that are frequently responsible for midlatitude wind and precipitation extremes. The prediction of ARs on subseasonal timescales is currently at a low level of skill, reflecting a need to improve our understanding of their underlying sources of predictability. Based on hindcast experiments from the Seamless System for Prediction and Earth System Research (SPEAR) at the Geophysical Fluid Dynamics Laboratory, we evaluate the global subseasonal prediction skill of wintertime AR statistics. Overall, the results from SPEAR are comparable to the European Centre for Medium-Range Weather Forecasts (ECMWF). Higher forecast skill is detected for strong AR activities than weak AR activities, despite that the occurrence frequency for weak ARs exceeds that of strong ARs. Importantly, we assess the sources of predictability and find that three most predictable modes of ARs in the North Pacific sector can be interpreted as arising from the influence of the El Niño–Southern Oscillation, the Pacific North American and the Arctic Oscillation patterns. Subseasonal AR forecast skill in western North America is modulated by different phases of these modes of large-scale seasonal variability highlighting the potential windows of opportunity for subseasonal AR forecasting.