Description: Originating in the equatorial Pacific, the El Niño–Southern Oscillation (ENSO) has highly consequential global impacts, motivating the need to understand its responses to anthropogenic warming. In this Review, we synthesize advances in observed and projected changes of multiple aspects of ENSO, including the processes behind such changes. As in previous syntheses, there is an inter-model consensus of an increase in future ENSO rainfall variability. Now, however, it is apparent that models that best capture key ENSO dynamics also tend to project an increase in future ENSO sea surface temperature variability and, thereby, ENSO magnitude under greenhouse warming, as well as an eastward shift and intensification of ENSO-related atmospheric teleconnections — the Pacific–North American and Pacific–South American patterns. Such projected changes are consistent with palaeoclimate evidence of stronger ENSO variability since the 1950s compared with past centuries. The increase in ENSO variability, though underpinned by increased equatorial Pacific upper-ocean stratification, is strongly influenced by internal variability, raising issues about its quantifiability and detectability. Yet, ongoing coordinated community efforts and computational advances are enabling long-simulation, large-ensemble experiments and high-resolution modelling, offering encouraging prospects for alleviating model biases, incorporating fundamental dynamical processes and reducing uncertainties in projections. Key points Under anthropogenic warming, the majority of climate models project faster background warming in the eastern equatorial Pacific compared with the west. The observed equatorial Pacific surface warming pattern since 1980, though opposite to the projected faster warming in the equatorial eastern Pacific, is within the inter-model range in terms of sea surface temperature (SST) gradients and is subject to influence from internal variability. El Niño–Southern Oscillation (ENSO) rainfall responses in the equatorial Pacific are projected to intensify and shift eastward, leading to an eastward intensification of extratropical teleconnections. ENSO SST variability and extreme ENSO events are projected to increase under greenhouse warming, with a stronger inter-model consensus in CMIP6 compared with CMIP5. However, the time of emergence for ENSO SST variability is later than that for ENSO rainfall variability, opposite to that for mean SST versus mean rainfall. Future ENSO change is likely influenced by past variability, such that quantification of future ENSO in the only realization of the real world is challenging. Although there is no definitive relationship of ENSO variability with the mean zonal SST gradient or seasonal cycle, palaeoclimate records suggest a causal connection between vertical temperature stratification and ENSO strength, and a greater ENSO strength since the 1950s than in past centuries, supporting an emerging increase in ENSO variability under greenhouse warming.

Description: El Niño events are characterized by surface warming of the tropical Pacific Ocean and weakening of equatorial trade winds that occur every few years. Such conditions are accompanied by changes in atmospheric and oceanic circulation, affecting global climate, marine and terrestrial ecosystems, fisheries and human activities. The alternation of warm El Niño and cold La Niña conditions, referred to as the El Niño–Southern Oscillation (ENSO), represents the strongest year-to-year fluctuation of the global climate system. Here we provide a synopsis of our current understanding of the spatio-temporal complexity of this important climate mode and its influence on the Earth system.

Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Sutton, A. J., Feely, R. A., Maenner-Jones, S., Musielwicz, S., Osborne, J., Dietrich, C., Monacci, N., Cross, J., Bott, R., Kozyr, A., Andersson, A. J., Bates, N. R., Cai, W., Cronin, M. F., De Carlo, E. H., Hales, B., Howden, S. D., Lee, C. M., Manzello, D. P., McPhaden, M. J., Melendez, M., Mickett, J. B., Newton, J. A., Noakes, S. E., Noh, J. H., Olafsdottir, S. R., Salisbury, J. E., Send, U., Trull, T. W., Vandemark, D. C., & Weller, R. A. Autonomous seawater pCO(2) and pH time series from 40 surface buoys and the emergence of anthropogenic trends. Earth System Science Data, 11(1), (2019):421-439, doi:10.5194/essd-11-421-2019.

Description: Ship-based time series, some now approaching over 3 decades long, are critical climate records that have dramatically improved our ability to characterize natural and anthropogenic drivers of ocean carbon dioxide (CO2) uptake and biogeochemical processes. Advancements in autonomous marine carbon sensors and technologies over the last 2 decades have led to the expansion of observations at fixed time series sites, thereby improving the capability of characterizing sub-seasonal variability in the ocean. Here, we present a data product of 40 individual autonomous moored surface ocean pCO2 (partial pressure of CO2) time series established between 2004 and 2013, 17 also include autonomous pH measurements. These time series characterize a wide range of surface ocean carbonate conditions in different oceanic (17 sites), coastal (13 sites), and coral reef (10 sites) regimes. A time of trend emergence (ToE) methodology applied to the time series that exhibit well-constrained daily to interannual variability and an estimate of decadal variability indicates that the length of sustained observations necessary to detect statistically significant anthropogenic trends varies by marine environment. The ToE estimates for seawater pCO2 and pH range from 8 to 15 years at the open ocean sites, 16 to 41 years at the coastal sites, and 9 to 22 years at the coral reef sites. Only two open ocean pCO2 time series, Woods Hole Oceanographic Institution Hawaii Ocean Time-series Station (WHOTS) in the subtropical North Pacific and Stratus in the South Pacific gyre, have been deployed longer than the estimated trend detection time and, for these, deseasoned monthly means show estimated anthropogenic trends of 1.9±0.3 and 1.6±0.3 µatm yr−1, respectively. In the future, it is possible that updates to this product will allow for the estimation of anthropogenic trends at more sites; however, the product currently provides a valuable tool in an accessible format for evaluating climatology and natural variability of surface ocean carbonate chemistry in a variety of regions. Data are available at https://doi.org/10.7289/V5DB8043 and https://www.nodc.noaa.gov/ocads/oceans/Moorings/ndp097.html (Sutton et al., 2018).

Description: We gratefully acknowledge the major funders of the pCO2 and pH observations: the Office of Oceanic and Atmospheric Research of the National Oceanic and Atmospheric Administration, US Department of Commerce, including resources from the Ocean Observing and Monitoring Division of the Climate Program Office (fund reference number 100007298) and the Ocean Acidification Program. We rely on a long list of scientific partners and technical staff who carry out buoy maintenance, sensor deployment, and ancillary measurements at sea. We thank these partners and their funders for their continued efforts in sustaining the platforms that support these long-term pCO2 and pH observations, including the following institutions: the Australian Integrated Marine Observing System, the Caribbean Coastal Ocean Observing System, Gray's Reef National Marine Sanctuary, the Marine and Freshwater Research Institute, the Murdock Charitable Trust, the National Data Buoy Center, the National Science Foundation Division of Ocean Sciences, NOAA–Korean Ministry of Oceans and Fisheries Joint Project Agreement, the Northwest Association of Networked Ocean Observing Systems, the Research Moored Array for African-Asian-Australian Monsoon Analysis and Prediction (i.e., RAMA), the University of Washington, the US Integrated Ocean Observing System, and the Washington Ocean Acidification Center. The open ocean sites are part of the OceanSITES program of the Global Ocean Observing System and the Surface Ocean CO2 Observing Network. All sites are also part of the Global Ocean Acidification Observing Network. This paper is PMEL contribution number 4797.