Abstract 249

Abstract ID: 249

ENSO-MJO effects on the lifecycle of North Pacific Atmospheric Rivers

Lead Author: Laís Fernandes
Portland State University, United States of America

Keywords: ENSO-MJO Interaction, MJO-AR lifecycle relationships, North Pacific ARs, AR precipitation, AR extreme events

Abstract: This study investigates how the El Niño-Southern Oscillation influences the modulation of cold-season North Pacific atmospheric river (AR) lifecycle characteristics by the Madden-Julian Oscillation (MJO) and associated AR-landfall driven precipitation extremes over North America. For ARs that originate between 0°N-60°N and 100°E-100°W, MJO phases 6-8 are associated with the highest AR lifecycle frequency over the North Pacific compared to other MJO phases. During El Niño, the highest AR lifecycle frequency in MJO phases 6-8 in the subtropics shifts to the east compared to the climatological mean. This El Niño effect on the MJO-AR lifecycle relationship is stronger than the El Niño modulation alone. The El Niño background changes the key drivers of the MJO-AR lifecycle relationship in these MJO phases by shifting MJO-driven convection to the east of 180° and extending the North Pacific subtropical jet eastward. Under these conditions, a weakened MJO extratropical teleconnection is triggered east of 180° and results in a significant cyclonic circulation anomaly along the United States (US) coast. Consequently, under El Niño, landfalling North Pacific ARs in MJO phases 6-8 more often impact the southern tier of the US, enhancing positive precipitation anomalies and increasing the frequency of AR-related extreme precipitation events across California and even the southeast US. At the same time, enhanced negative precipitation anomalies and decreased frequency of AR extreme precipitation events occur over the northwestern US and western Canada. Results provide new useful insight into the drivers of AR and precipitation variability along the west coast of North America with novel implications for improving S2S predictions.

Paul Loikith (Portland State University)