Exceptionally strong easterly wind burst stalling El Ni?o of 2014

Intraseasonal wind bursts in the tropical Pacific are believed to affect the evolution and diversity of El Niño events. In particular, the occurrence of two strong westerly wind bursts (WWBs) in early 2014 apparently pushed the ocean–atmosphere system toward a moderate to strong El Niño—potentially an extreme event according to some climate models. However, the event’s progression quickly stalled, and the warming remained very weak throughout the year. Here, we find that the occurrence of an unusually strong basin-wide easterly wind burst (EWB) in June was a key factor that impeded the El Niño development. It was shortly after this EWB that all major Niño indices fell rapidly to near-normal values; a modest growth resumed only later in the year. The easterly burst and the weakness of subsequent WWBs resulted in the persistence of two separate warming centers in the central and eastern equatorial Pacific, suppressing the positive Bjerknes feedback critical for El Niño. Experiments with a climate model with superimposed wind bursts support these conclusions, pointing to inherent limits in El Niño predictability. Furthermore, we show that the spatial structure of the easterly burst matches that of the observed decadal trend in wind stress in the tropical Pacific, suggesting potential links between intraseasonal wind bursts and decadal climate variations.El Niño, the warm phase of the El Niño–Southern Oscillation (ENSO), is characterized by anomalously warm water appearing in the central and eastern equatorial Pacific every 2–7 years, driven by tropical ocean–atmosphere interactions with far-reaching global impacts (recent reviews are in refs. 1–3). These interactions and El Niño development involve several important feedbacks, including the positive Bjerknes feedback [zonal wind relaxation leads to the reduction of the zonal sea surface temperature (SST) gradient and further wind relaxation] (4). Since the year 2000, there has been a shift in the observed properties of El Niño, including its magnitude, frequency, and spatial structure of temperature anomalies (5, 6). For example, El Niño events occurred more frequently than during the previous two decades, but all were weak, and none reached the extreme magnitude of the 1982 and 1997 events. Concurrently, the rise of global mean surface temperature has slowed down with the so-called global warming hiatus (7–9). The stalled development of the 2014 El Niño presents a showcase to explore the relevant connection and mechanisms of these changes.At the beginning of 2014, many in the scientific community anticipated that a moderate to strong El Niño could develop by the end of the year (10–14) (Fig. S1). In March, the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center announced an “El Niño watch” based on predictions made by dynamical and statistical models (12), attracting attention of the general public. Admittedly, these predictions encompassed large uncertainties because of the stochastic nature of the tropical climate system (15–17). In May, the National Aeronautics and Space Administration (NASA) suggested that 2014 could potentially rival the strongest on-record event of 1997/19998 (Fig. 1B), while acknowledging the large existing uncertainty (14); their projection was supported by satellite observations of strong Kelvin waves evident in sea surface height (SSH) (Fig. 2C). The spread of spring forecast plumes from some climate models, for example that of the European Centre for Medium-Range Weather Forecasts (ECMWF), included the possibility of a failed El Niño (Fig. S1) but only as a low-probability outcome involving unusual instances of weather noise. The observed development fell near the limit of these forecast possibilities after June and July, and eventually, the 2014 warm event barely qualified as El Niño (Fig. 1A).Open in a separate windowFig. 1.El Niño development in (A and C) 2014 and (B and D) 1997. (A and B) Evolution of the Niño3, Niño4, and Niño3.4 indices; the first two indices describe SST anomalies (in degrees Celsius) in the eastern and central equatorial Pacific, respectively, whereas the last index covers the region in between. (C and D) Variation in the zonal wind stress indices. These indices are obtained by averaging wind stress anomalies (in 10⁻² newtons per meter²) in the equatorial Pacific zonally and between 5 °S and 5 °N and then selecting negative (blue; easterly anomalies), positive (red; westerly anomalies), or full values (black) (Materials and Methods). The spatial averaging is intended to take into account both the magnitude and the fetch of the wind bursts. During 2014, two early year WWBs were followed by an exceptional EWB in June (highlighted by pink and blue, respectively). This easterly burst apparently led to a rapid decrease of the Niño indices (A). In contrast, the 1997 El Niño exhibited persistent westerly wind activity throughout the year. The graphs start on January 1.Open in a separate windowFig. 2.Spatiotemporal evolution of the 2014 El Niño. (A–D) Hovmöller diagrams for anomalies in (A) SST, (B) zonal wind stress, (C) SSH, and (D) surface zonal currents in the equatorial Pacific. Time goes downward. The SSH and surface velocity plots highlight the eastward propagating downwelling Kelvin waves, especially pronounced early in the year, and a strong upwelling Kelvin wave midyear. (E and F) El Niño development in 2014 (black line) compared with several historical (E) EP and (F) CP events. The diagrams show the position of the Warm Pool Eastern Edge (degrees of longitude) vs. the Niño3 SST (degrees Celsius) for different months of the year. The Warm Pool Eastern Edge is defined as the position of the 29 °C isotherm at the equator. Numbers indicate monthly averages (1, January; 2, February, etc.). The light vertical line marks the Dateline. In 2014, both the warm pool displacement and Niño3 SST anomalies were exceptionally large during May (month 5), were similar to those in 1997 and 1982 (the strongest events of the 20th century), and then, rapidly decreased by August (month 8).Open in a separate windowFig. S1.The El Niño spring forecasts of the Niño3.4 index from the European Centre for Medium-Range Weather Forecasts (ECMWF). Red lines show 50 ensemble members of the forecast plume initiated in March of 2014; the black dotted line indicates the observed Niño3.4 index. The observed development fell outside the forecast plume in June and July and remained beyond the typical forecast spread after that. Adapted from ref. 13.The question then arises as to which dynamic factors controlled the temporal and spatial development in the tropical Pacific in 2014. This warm event began with a rapid growth, such that, in early June, all major Niño indices (Materials and Methods) along the equator were nearly identical to those during the same time of 1997 (Fig. 1 A and B). A substantial warming also developed along the Peruvian coast (Fig. 3A). Then, the event’s progression slowed down or even reversed. By year end, the equatorial warming barely exceeded 1 °C, but the SST anomaly stretched uncharacteristically across the entire equatorial Pacific almost uniformly (Figs. 1A and ​and2A).2A). Accordingly, the major goal of this study is to investigate this unusual development, identify the main factors that impeded this event, and explore its broad implications.Open in a separate windowFig. 3.The June of 2014 EWB in satellite-based data. (A) The spatial structure of anomalies in surface winds (vectors; in meters per second) and SST (colors; in degrees Celsius) on June 12, 2014, when the burst was strongest. (B) Daily vs. weekly mean values of the zonal wind stress index (10⁻² newtons per meter²) for the period 1988–2014. The blue cross marks the peak value of the June of 2014 EWB. The wind stress index is defined as anomalous zonal wind stress averaged in the equatorial Pacific zonally and between 5 °S and 5 °N (Materials and Methods). Black circles are for the year 2014, red circles are for all El Niño years before 2014, and gray circles are for all other years (La Niña or neutral). Note that the June of 2014 EWB appears strongest in the satellite record for not only daily data but also, weekly averaged values, which confirms that the observations are robust.     

Contribution of solar radiation to decadal temperature variability over land

Global air temperature has become the primary metric for judging global climate change. The variability of global temperature on a decadal timescale is still poorly understood. This paper examines further one suggested hypothesis, that variations in solar radiation reaching the surface (R_s) have caused much of the observed decadal temperature variability. Because R_s only heats air during the day, its variability is plausibly related to the variability of diurnal temperature range (daily maximum temperature minus its minimum). We show that the variability of diurnal temperature range is consistent with the variability of R_s at timescales from monthly to decadal. This paper uses long comprehensive datasets for diurnal temperature range to establish what has been the contribution of R_s to decadal temperature variability. It shows that R_s over land globally peaked in the 1930s, substantially decreased from the 1940s to the 1970s, and changed little after that. Reduction of R_s caused a reduction of more than 0.2 °C in mean temperature during May to October from the 1940s through the 1970s, and a reduction of nearly 0.2 °C in mean air temperature during November to April from the 1960s through the 1970s. This cooling accounts in part for the near-constant temperature from the 1930s into the 1970s. Since then, neither the rapid increase in temperature from the 1970s through the 1990s nor the slowdown of warming in the early twenty-first century appear to be significantly related to changes of R_s.Global temperature has become the primary metric for judging global climate change, although many other factors are recognized to be of comparable importance. The overall increase of global temperature over the last century has been largely attributed to the increase of greenhouse gases (1). Less well understood are the reasons for the variability of this increase on a decadal timescale. In particular, warming from 1900 to 1940 was followed by three decades of flat or slightly decreasing temperature, then three decades of very rapid temperature increase, then so far in this century, very little additional increase. The two most plausible explanations for the decadal variability are natural climate variability and variable degrees of cooling from anthropogenic releases of sulfur gas producing sulfate aerosols (2). This effect has long been proposed as a mechanism to counter greenhouse warming (3), has become the basis for many geoengineering proposals (4), and has been used to attribute the lack of warming so far this century to the rapid growth of aerosols in Asia (5).Besides the difference in sign of their temperature effects, sulfate aerosols are distinguished from greenhouse gases in that they only affect daytime radiation, i.e., surface incident solar radiation (R_s). Some kinds of natural variability can also act through affecting R_s, i.e., those involving cloud properties.Changes of aerosol loading and cloud properties likely caused the rapid decrease of R_s, measured at the surface from the 1950s to the 1980s, referred to as “global dimming,” and its partial recovery after that (6). The plausible suggestion was made by Wild et al. (7) that the rapid warming in the late twentieth century was a consequence of the cessation of global dimming, possibly in part from the imposition of controls on sulfur emission in the industrialized nations (8, 9).This paper examines further the hypothesis that variations in R_s have caused much of the observed decadal variability in the rate of warming. Direct measurements of R_s cannot be quantitatively related to such variability because they have been limited in their geographical coverage. The approach used here is to examine a global land dataset of diurnal temperature range (DTR). This concept is not new, indeed, Wild et al. (7) noted (compare with their figure 2) that the global pattern of DTR was similar to that of their global dimming and brightening. The present paper develops the longest and most comprehensive dataset for DTR possible, and, with some plausible assumptions, establishes what the contribution of R_s has been to decadal temperature variability. It indicates that a decrease of R_s from the 1940s through the 1970s reduced the global temperature trend over that period. However, global temperature does not appear to have been significantly affected by changing R_s after that. The method is limited in that it is only applicable over land. As the effects of aerosols are likely to be less over ocean, especially in the Southern Hemisphere, this approach may exaggerate the actual effect of aerosols on global temperature trends.     

Pacific decadal oscillation hindcasts relevant to near-term climate prediction

Decadal-scale climate variations over the Pacific Ocean and its surroundings are strongly related to the so-called Pacific decadal oscillation (PDO) which is coherent with wintertime climate over North America and Asian monsoon, and have important impacts on marine ecosystems and fisheries. In a near-term climate prediction covering the period up to 2030, we require knowledge of the future state of internal variations in the climate system such as the PDO as well as the global warming signal. We perform sets of ensemble hindcast and forecast experiments using a coupled atmosphere-ocean climate model to examine the predictability of internal variations on decadal timescales, in addition to the response to external forcing due to changes in concentrations of greenhouse gases and aerosols, volcanic activity, and solar cycle variations. Our results highlight that an initialization of the upper-ocean state using historical observations is effective for successful hindcasts of the PDO and has a great impact on future predictions. Ensemble hindcasts for the 20th century demonstrate a predictive skill in the upper-ocean temperature over almost a decade, particularly around the Kuroshio-Oyashio extension (KOE) and subtropical oceanic frontal regions where the PDO signals are observed strongest. A negative tendency of the predicted PDO phase in the coming decade will enhance the rising trend in surface air-temperature (SAT) over east Asia and over the KOE region, and suppress it along the west coasts of North and South America and over the equatorial Pacific. This suppression will contribute to a slowing down of the global-mean SAT rise.     

Nonlinear Laplacian spectral analysis for time series with intermittency and low-frequency variability

Many processes in science and engineering develop multiscale temporal and spatial patterns, with complex underlying dynamics and time-dependent external forcings. Because of the importance in understanding and predicting these phenomena, extracting the salient modes of variability empirically from incomplete observations is a problem of wide contemporary interest. Here, we present a technique for analyzing high-dimensional, complex time series that exploits the geometrical relationships between the observed data points to recover features characteristic of strongly nonlinear dynamics (such as intermittency and rare events), which are not accessible to classical singular spectrum analysis. The method employs Laplacian eigenmaps, evaluated after suitable time-lagged embedding, to produce a reduced representation of the observed samples, where standard tools of matrix algebra can be used to perform truncated singular-value decomposition despite the nonlinear geometrical structure of the dataset. We illustrate the utility of the technique in capturing intermittent modes associated with the Kuroshio current in the North Pacific sector of a general circulation model and dimensional reduction of a low-order atmospheric model featuring chaotic intermittent regime transitions, where classical singular spectrum analysis is already known to fail dramatically.     

Greenhouse warming and the 21st century hydroclimate of southwestern North America

Climate models robustly predict that the climate of southwestern North America, defined as the area from the western Great Plains to the Pacific Ocean and from the Oregon border to southern Mexico, will dry throughout the current century as a consequence of rising greenhouse gases. This regional drying is part of a general drying of the subtropics and poleward expansion of the subtropical dry zones. Through an analysis of 15 coupled climate models it is shown here that the drying is driven by a reduction of winter season precipitation associated with increased moisture divergence by the mean flow and reduced moisture convergence by transient eddies. Due to the presence of large amplitude decadal variations of presumed natural origin, observations to date cannot confirm that this transition to a drier climate is already underway, but it is anticipated that the anthropogenic drying will reach the amplitude of natural decadal variability by midcentury. In addition to this drop in total precipitation, warming is already causing a decline in mountain snow mass and an advance in the timing of spring snow melt disrupting the natural water storage systems that are part of the region’s water supply system. Uncertainties in how radiative forcing will impact the tropical Pacific climate system create uncertainties in the amplitude of drying in southwest North America with a La Niña-like response creating a worst case scenario of greater drying.     

Recurrent jellyfish blooms are a consequence of global oscillations

A perceived recent increase in global jellyfish abundance has been portrayed as a symptom of degraded oceans. This perception is based primarily on a few case studies and anecdotal evidence, but a formal analysis of global temporal trends in jellyfish populations has been missing. Here, we analyze all available long-term datasets on changes in jellyfish abundance across multiple coastal stations, using linear and logistic mixed models and effect-size analysis to show that there is no robust evidence for a global increase in jellyfish. Although there has been a small linear increase in jellyfish since the 1970s, this trend was unsubstantiated by effect-size analysis that showed no difference in the proportion of increasing vs. decreasing jellyfish populations over all time periods examined. Rather, the strongest nonrandom trend indicated jellyfish populations undergo larger, worldwide oscillations with an approximate 20-y periodicity, including a rising phase during the 1990s that contributed to the perception of a global increase in jellyfish abundance. Sustained monitoring is required over the next decade to elucidate with statistical confidence whether the weak increasing linear trend in jellyfish after 1970 is an actual shift in the baseline or part of an oscillation. Irrespective of the nature of increase, given the potential damage posed by jellyfish blooms to fisheries, tourism, and other human industries, our findings foretell recurrent phases of rise and fall in jellyfish populations that society should be prepared to face.