The impact of SST-forced and unforced teleconnections on 2015/16 El Niño winter precipitation over the western United States

• Published in: Journal of Climate
• Main Authors: Lim, Young-Kwon, Schubert, Siegfried D., Chang, Yehui, Molod, Andrea M., Pawson, Steven
• Format: Text
• Language: English
• Published: 2018
• Subjects: Article; Arctic; Merra; Pacific; North Atlantic; North Atlantic oscillation
• Online Access: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6121706/; http://www.ncbi.nlm.nih.gov/pubmed/30197468; https://doi.org/10.1175/JCLI-D-17-0218.1

The factors impacting western U.S. winter precipitation during the 2015/16 El Niño are investigated using the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) data, and simulations with the Goddard Earth Observing System version 5 (GEOS-5) atmospheric general circulation model forced with specified sea surface temperatures (SSTs). Results reveal that the simulated response to the tropical Pacific SST associated with the 2015/16 El Niño was to produce wetter than normal conditions over much of the west coast including California – a result at odds with the negative precipitation anomalies observed over much of the Southwestern U.S. It is shown that two factors acted to partly counter the canonical ENSO response in that region. First, a potentially predictable but modest response to the unusually strong and persistent warm SST in the northeastern Pacific decreased precipitation in the Southwestern U.S. by increasing sea level pressure, driving anticyclonic circulation and atmospheric descent, and reducing moisture transport into that region. Second, large-scale unforced (by SST) components of atmospheric variability (consisting of the leading modes of unpredictable intra-ensemble variability) resembling the positive phase of the North Atlantic Oscillation and Arctic Oscillation are found to be an important contributor to the drying over the western U.S. While a statistical reconstruction of the precipitation from our simulations that account for internal atmospheric variability does much to close the gap between the ensemble mean and observed precipitation in the Southwestern U.S., some differences remain, indicating that model error is also playing a role.