Sources of Atmospheric Rivers and Precipitation Predictability
Atmospheric rivers (ARs) produce much winter precipitation across the western US. Yet accurate predictions of ARs and precipitation remain challenging. One barrier is we don’t fully understand the impacts of climate variability on western US hydroclimate. Two prominent modes of climate variability are the El Niño/Southern Oscillation (ENSO) and Madden‐Julian Oscillation. The barrier limits the predictive skills of ARs and precipitation.
A better understanding of the sources of AR and precipitation predictability will help us improve their predictions. With extreme El Niño events, we can expect increased landfalling ARs and precipitation. With different phases of the Madden‐Julian Oscillation, landfalling AR activity may be enhanced or suppressed. The impacts are further regulated by the El Niño/Southern Oscillation. With improved predictions, governments and stakeholders will be better informed to manage water resources and drought and flood risks.
This study aims to assess the sources of subseasonal‐to‐seasonal predictability of atmospheric rivers (ARs) and precipitation in the western US. A large ensemble of regional climate model simulations from 1981 to 2017 was used. The researchers examined the relationships between two climate modes, the El Niño/Southern Oscillation (ENSO) and Madden‐Julian Oscillation (MJO), and winter hydroclimate in the western US. They found that there exists some uncertainty in the ENSO‐AR connection due to the impacts of ENSO indices and datasets. But extreme El Niño events defined by the ENSO longitude index are usually linked to increased landfalling AR activity and precipitation. The MJO can enhance or suppress landfalling AR activity, depending on the phase of MJO and time lag. Furthermore, two phases of ENSO (La Niña and El Niño) modulate the MJO‐AR relationship differently. The findings highlight the need to evaluate concurrent effects of different climate modes on ARs and precipitation. They may shed light on a path toward more accurate subseasonal‐to‐seasonal prediction of ARs and precipitation over the western US.