*Dillon J Amaya1,2, Yu Kosaka3, Wenyu Zhou4, Yu Zhang5, Shang-Ping Xie6, Arthur J Miller6
(1.Cooperative Institute for Research in Environmental Sciences, 2.University of Colorado Boulder, 3.University of Tokyo, 4.Pacific Northwest National Laboratory, 5.Ocean University of China, 6.Scripps Institution of Oceanography)
Keywords:Climate Variability, ENSO, Teleconnection, Tropics, Air-Sea Interactions, Climate Model
Studies have indicated that North Pacific sea surface temperature (SST) variability can significantly modulate the El Nino–Southern Oscillation (ENSO), but there has been little effort to put these extratropical–tropical interactions into the context of historical events. To quantify the role of the North Pacific in pacing the timing and magnitude of observed ENSO, we use a fully coupled climate model to produce an ensemble of North Pacific Ocean–Global Atmosphere (nPOGA) SST pacemaker simulations. In nPOGA, SST anomalies are restored back to observations in the North Pacific (>15°N) but are free to evolve throughout the rest of the globe. We find that North Pacific SST has significantly influenced observed ENSO variability, accounting for approximately 15% of the total variance in boreal fall and winter. The connection between the North and tropical Pacific arises from two physical pathways: 1) a wind–evaporation–SST (WES) propagating mechanism, and 2) a Gill-like atmospheric response associated with anomalous deep convection in boreal summer and fall, which we refer to as the summer deep convection (SDC) response. The SDC response accounts for 25% of the observed zonal wind variability around the equatorial date line. On an event-by-event basis, nPOGA most closely reproduces the 2014/15 and the 2015/16 El Ninos. In particular, we show that the 2015 Pacific Meridional Mode event increased wind forcing along the equator by 20%, potentially contributing to the extreme nature of the 2015/16 El Nino. Our results illustrate the significant role of extratropical noise in pacing the initiation and magnitude of ENSO events and may improve the predictability of ENSO on seasonal time scales.