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1. Toward Understanding El Niño Southern-Oscillation’s Spatiotemporal Pattern Diversity

   https://doi.org/10.3389/feart.2022.899139  

   Jin, Fei-Fei (May 2022, Frontiers in Earth Science)

   The El Niño Southern Oscillation (ENSO) phenomenon, manifested by the great swings of large-scale sea surface temperature (SST) anomalies over the equatorial central to eastern Pacific oceans, is a major source of interannual global shifts in climate patterns and weather activities. ENSO’s SST anomalies exhibit remarkable spatiotemporal pattern diversity (STPD), with their spatial pattern diversity dominated by Central Pacific (CP) and Eastern Pacific (EP) El Niño events and their temporal diversity marked by different timescales and intermittency in these types of events. By affecting various Earth system components, ENSO and its STPD yield significant environmental, ecological, economic, and societal impacts over the globe. The basic dynamics of ENSO as a canonical oscillator generated by coupled ocean–atmosphere interactions in the tropical Pacific have been largely understood. A minimal simple conceptual model such as the recharge oscillator paradigm provides means for quantifying the linear and nonlinear seasonally modulated growth rate and frequency together with ENSO’s state-dependent noise forcing for understanding ENSO’s amplitude and periodicity, boreal winter-time phase locking, and warm/cold phase asymmetry. However, the dynamical mechanisms explaining the key features of ENSO STPD associated with CP and EP events remain to be better understood. This article provides a summary of the recent active research on the dynamics of ENSO STPD together with discussions on challenges and outlooks for theoretical, diagnostic, and numerical modeling approaches to advance our understanding and modeling of ENSO, its STPD, and their broad impacts. 

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2. Decadal Change of Combination Mode Spatiotemporal Characteristics due to an ENSO Regime Shift

   https://doi.org/10.1175/JCLI-D-19-0822.1  

   Jiang, Feng; Zhang, Wenjun; Stuecker, Malte F.; Jin, Fei-Fei (June 2020, Journal of Climate)

   Abstract Previous studies have shown that nonlinear atmospheric interactions between ENSO and the warm pool annual cycle generates a combination mode (C-mode), which is responsible for the termination of strong El Niño events and the development of the anomalous anticyclone over the western North Pacific (WNP). However, the C-mode has experienced a remarkable decadal change in its characteristics around the early 2000s. The C-mode in both pre- and post-2000 exhibits its characteristic anomalous atmospheric circulation meridional asymmetry but with somewhat different spatial structures and time scales. During 1979–99, the C-mode pattern featured prominent westerly surface wind anomalies in the southeastern tropical Pacific and anticyclonic anomalies over the WNP. In contrast, the C-mode-associated westerly anomalies were shifted farther westward to the central Pacific and the WNP anticyclone was farther westward extended and weaker after 2000. These different C-mode patterns were accompanied by distinct climate impacts over the Indo-Pacific region. The decadal differences of the C-mode are tightly connected with the ENSO regime shift around 2000; that is, the occurrence of central Pacific (CP) El Niño events with quasi-biennial and decadal periodicities increased while the occurrence of eastern Pacific (EP) El Niño events with quasi-quadrennial periodicity decreased. The associated near-annual combination tone periodicities of the C-mode also changed in accordance with these changes in the dominant ENSO frequency between the two time periods. Numerical model experiments further confirm the impacts of the ENSO regime shift on the C-mode characteristics. These results have important implications for understanding the C-mode dynamics and improving predictions of its climate impacts. 

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3. Cloud Radiative Feedbacks and El Niño–Southern Oscillation

   https://doi.org/10.1175/JCLI-D-18-0842.1  

   Middlemas, Eleanor A.; Clement, Amy C.; Medeiros, Brian; Kirtman, Ben (August 2019, Journal of Climate)

   null (Ed.)

   Abstract Cloud radiative feedbacks are disabled via “cloud-locking” in the Community Earth System Model, version 1.2 (CESM1.2), to result in a shift in El Niño–Southern Oscillation (ENSO) periodicity from 2–7 years to decadal time scales. We hypothesize that cloud radiative feedbacks may impact the periodicity in three ways: by 1) modulating heat flux locally into the equatorial Pacific subsurface through negative shortwave cloud feedback on sea surface temperature anomalies (SSTA), 2) damping the persistence of subtropical southeast Pacific SSTA such that the South Pacific meridional mode impacts the duration of ENSO events, or 3) controlling the meridional width of off-equatorial westerly winds, which impacts the periodicity of ENSO by initiating longer Rossby waves. The result of cloud-locking in CESM1.2 contrasts that of another study, which found that cloud-locking in a different global climate model led to decreased ENSO magnitude across all time scales due to a lack of positive longwave feedback on the anomalous Walker circulation. CESM1.2 contains this positive longwave feedback on the anomalous Walker circulation, but either its influence on the surface is decoupled from ocean dynamics or the feedback is only active on interannual time scales. The roles of cloud radiative feedbacks in ENSO in other global climate models are additionally considered. In particular, it is shown that one cannot predict the role of cloud radiative feedbacks in ENSO through a multimodel diagnostic analysis. Instead, they must be directly altered. 

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4. El Niño Detection Via Unsupervised Clustering of Argo Temperature Profiles

   https://doi.org/10.1029/2019JC015947  

   Houghton, Isabel A.; Wilson, James D. (September 2020, Journal of Geophysical Research: Oceans)

   Abstract Variability in the El Niño‐Southern Oscillation (ENSO) has global impacts on seasonal temperatures and rainfall. Current detection methods for extreme phases, which occur with irregular periodicity, rely upon sea surface temperature anomalies within a strictly defined geographic region of the Pacific Ocean. However, under changing climate conditions and ocean warming, these historically motivated indicators may not be reliable into the future. In this work, we demonstrate the power of data clustering as a robust, automatic way to detect anomalies in climate patterns. Ocean temperature profiles from Argo floats are partitioned into similar groups utilizing unsupervised machine learning methods. The automatically identified groups of measurements represent spatially coherent, large‐scale water masses in the Pacific, despite no inclusion of geospatial information in the clustering task. Further, spatiotemporal dynamics of the clusters are strongly indicative of El Niño events, the east Pacific warming phase of ENSO. The fitting of a cluster model on a collection of ocean profiles identifies changes in the vertical structure of the temperature profiles through reassignment to a different group, concisely capturing physical changes to the water column during an El Niño event, such as thermocline tilting. Clustering proves to be an effective tool for analysis of the irregularly sampled (in space and time) data from Argo floats and may serve as a novel approach for detecting anomalies given the freedom from thresholding decisions. Unsupervised machine learning could be particularly valuable due to its ability to identify patterns in data sets without user‐imposed expectations, facilitating further discovery of anomaly indicators. 

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5. Twenty-first century hydroclimate: A continually changing baseline, with more frequent extremes

   https://doi.org/10.1073/pnas.2108124119  

   Stevenson, Samantha; Coats, Sloan; Touma, Danielle; Cole, Julia; Lehner, Flavio; Fasullo, John; Otto-Bliesner, Bette (March 2022, Proceedings of the National Academy of Sciences)

   Variability in hydroclimate impacts natural and human systems worldwide. In particular, both decadal variability and extreme precipitation events have substantial effects and are anticipated to be strongly influenced by climate change. From a practical perspective, these impacts will be felt relative to the continuously evolving background climate. Removing the underlying forced trend is therefore necessary to assess the relative impacts, but to date, the small size of most climate model ensembles has made it difficult to do this. Here we use an archive of large ensembles run under a high-emissions scenario to determine how decadal “megadrought” and “megapluvial” events—and shorter-term precipitation extremes—will vary relative to that changing baseline. When the trend is retained, mean state changes dominate: In fact, soil moisture changes are so large in some regions that conditions that would be considered a megadrought or pluvial event today are projected to become average. Time-of-emergence calculations suggest that in some regions including Europe and western North America, this shift may have already taken place and could be imminent elsewhere: Emergence of drought/pluvial conditions occurs over 61% of the global land surface (excluding Antarctica) by 2080. Relative to the changing baseline, megadrought/megapluvial risk either will not change or is slightly reduced. However, the increased frequency and intensity of both extreme wet and dry precipitation events will likely present adaptation challenges beyond anything currently experienced. In many regions, resilience against future hazards will require adapting to an ever-changing “normal,” characterized by unprecedented aridification/wetting punctuated by more severe extremes. 

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