Maximizing ENSO as a source of western US hydroclimate predictability

Patricola, Christina M.; O’Brien, John P.; Risser, Mark D.; Rhoades, Alan M.; O’Brien, Travis A.; Ullrich, Paul A.; Stone, Dáithí A.; Collins, William D.

doi:10.1007/s00382-019-05004-8

Title: Maximizing ENSO as a source of western US hydroclimate predictability

Journal Article · Wed Oct 16 00:00:00 EDT 2019 · Climate Dynamics

DOI:https://doi.org/10.1007/s00382-019-05004-8· OSTI ID:1619322

; O’Brien, John P.; Risser, Mark D.; Rhoades, Alan M.; O’Brien, Travis A.; Ullrich, Paul A.; Stone, Dáithí A.; Collins, William D.

Abstract Until recently, the El Niño–Southern Oscillation (ENSO) was considered a reliable source of winter precipitation predictability in the western US, with a historically strong link between extreme El Niño events and extremely wet seasons. However, the 2015–2016 El Niño challenged our understanding of the ENSO-precipitation relationship. California precipitation was near-average during the 2015–2016 El Niño, which was characterized by warm sea surface temperature (SST) anomalies of similar magnitude compared to the extreme 1997–1998 and 1982–1983 El Niño events. We demonstrate that this precipitation response can be explained by El Niño’s spatial pattern, rather than internal atmospheric variability. In addition, observations and large-ensembles of regional and global climate model simulations indicate that extremes in seasonal and daily precipitation during strong El Niño events are better explained using the ENSO Longitude Index (ELI), which captures the diversity of ENSO’s spatial patterns in a single metric, compared to the traditional Niño3.4 index, which measures SST anomalies in a fixed region and therefore fails to capture ENSO diversity. The physically-based ELI better explains western US precipitation variability because it tracks the zonal shifts in tropical Pacific deep convection that drive teleconnections through the response in the extratropical wave-train, integrated vapor transport, and atmospheric rivers. This research provides evidence that ELI improves the value of ENSO as a predictor of California’s seasonal hydroclimate extremes compared to traditional ENSO indices, especially during strong El Niño events.

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Research Organization:: Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: USDOE; USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23), Climate and Environmental Sciences Division (SC-23.1 )

Grant/Contract Number:: AC02-05CH11231; SC0016605

OSTI ID:: 1619322

Alternate ID(s):: OSTI ID: 1581377

Journal Information:: Climate Dynamics, Journal Name: Climate Dynamics Vol. 54 Journal Issue: 1-2; ISSN 0930-7575

Publisher:: Springer Science + Business MediaCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 40 works

Citation information provided by
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54 ENVIRONMENTAL SCIENCES
precipitation
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extreme events
predictability
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