Role of Low-Frequency Wind Variability in Inducing WWBs during the onset of super El Niños

In this study, the effect of multiple timescale wind fields on the westerly wind bursts (WWBs) was investigated during the onset of super (1982, 1997, and 2015) and moderate El Niño events. The results revealed that extreme WWBs during the onset of the super El Niño group were attributed to low-frequency westerly (≥90 days, LFW), medium-frequency westerly (20–90 days, MFW, or intraseasonal) and high-frequency westerly (≤10 days, HFW) components, accounting for approximately 51%, 33% and 16%, respectively. Thus, the extreme WWBs during the onset of super El Niños were primarily contributed by LFWs and MFWs. By contrast, the WWBs during the onset of moderate El Niños were determined primarily by MFWs (38%) and HFWs (35%), whereas the LFW contribution is relatively small (27%). A further analysis indicated that LFWs during the onset of the super El Niños were primarily a response to a positive SST anomaly in the tropical to eastern North Pacific resembling the Pacific Meridional Mode (PMM), which had persisted during the preceding 9–12 months in the extratropical eastern North Pacific. A significant lagged correlation between the tropical and extratropical North Pacific SST was identified, and their correlation has become stronger since the late 1980s. MFWs during the onset of the super El Niños were primarily associated with the Madden-Julian Oscillation.

Non-Linear Processes in the Gironde River Plume (North-East Atlantic): Instabilities and Mixing

Instability and mixing are ubiquitous processes in river plumes but their small spatial and temporal scales often limit their observation and analysis. We investigate flow instability and mixing processes in the Gironde river plume (Bay of Biscay, North-East Atlantic ocean) in response to air-sea fluxes, tidal currents, and winds. High-resolution numerical simulations are conducted in March (average river discharge) and in August (low discharge) to explore such processes. Two areas of the Gironde river plume (the bulge and the coastal current) experience different instabilities: barotropic, baroclinic, symmetric, and/or vertical shear instabilities. Energy conversion terms reveal the coexistence of barotropic and baroclinic instabilities in the bulge and in the coastal current during both months. These instabilities are intensified over the whole domain in August and over the inner-shelf in March. The Hoskins criterion indicates that symmetric instability exists in most parts of the plume during both periods. The evolution of the Gironde plume with the summer stratification, tidal currents and winds favors its development. During both seasons, ageostrophic flow and large Rossby numbers characterize rapidly-growing and small-scale frontal baroclinic and symmetric instabilities. The transition between these instabilities is investigated with an EKE decomposition on the modes of instability. In the frontal region of the plume, during both months, symmetric instabilities grow first followed by baroclinic and mixed ones, during wind bursts and/or high discharge events. In contrast, when the wind is weak or relaxing, baroclinic instabilities grow first followed by symmetric and then mixed ones. Their growth periods range from a few hours to a few days. Mixing at the ocean surface is analyzed via Potential Vorticity (PV) fluxes. The net injection of PV at the ocean surface occurs at submesoscale buoyant fronts of the Gironde plume during both months. Vertical mixing at these fronts has similar magnitude as the wind-driven and surface buoyancy fluxes. During both months, the frontal region of the plume is restratified during wind relaxation events and/or high river discharge events through frontogenetic processes. Conversely, wind bursts destratify the frontal plume interior through non-conservative PV fluxes.

ENSO Diversity in a Tropical Stochastic Skeleton Model for the MJO, El Niño, and Dynamic Walker Circulation

The El Niño-Southern Oscillation (ENSO) diversity has a significant impact on global climate and seasonal prediction. However, it is still a challenging problem for present-day global climate models to simulate different types of ENSO events with realistic features simultaneously. In this paper, a tropical stochastic skeleton model for the interactions among wind bursts and the Madden-Julian Oscillation (MJO), the El Niño, and the Walker circulation is developed to reproduce both dynamical and statistical features of the ENSO diversity. In this model, the intraseasonal component with state-dependent noise captures general features of wind bursts and the MJO, both of which play important roles in triggering the El Niño. The thermocline feedback is the dominant mechanism for generating the eastern Pacific (EP) El Niño, while a nonlinear zonal advection is incorporated into the model that contributes to the central Pacific (CP) El Niño. Besides, a simple but effective stochastic process describing the multidecadal variation of the background Walker circulation modulates the spatial patterns and occurrence frequency of the EP and CP El Niño. This model succeeds in simulating the quasi-regular moderate EP El Niño, the super El Niño, and the CP El Niño as well as the La Niña simultaneously. It also captures the observed non-Gaussian characteristics of sea surface temperature anomalies in different Niño regions. Individual case studies highlight the outstanding skill of the model in reproducing the observed El Niño episodes and their underlying mechanisms.

The Niño 3.4 prediction skill of empirically adjusted wind power

Wind power, defined as the energy received by the ocean from wind, has been identified as a potentially viable precursor of ENSO. The correlation between tropical Pacific wind power anomalies and eastern equatorial Pacific sea surface temperature anomalies can be enhanced over a range of lead times by applying an empirical adjusted framework that accounts for both the underlying climatological state upon which a wind power perturbation acts and the directionality of wind anomalies. Linear regression is used to assess the seasonal prediction skill of adjusted wind power in comparison to unadjusted, as well as the conventional ENSO predictors wind stress and warm water volume. The forecast skill of each regression model is evaluated in a 1800-year preindustrial climate simulation (CESM-LENS), as well as 23 years of observations. The simulation results show that each predictor’s effectiveness varies considerably with sample, providing a measure of the uncertainty involved in evaluating prediction skill based on the short observational record. The influence of climatological biases is however a demonstrable concern for results from the simulated climate system. Despite the short record, the observational analysis indicates that adjusted wind power skill is comparable to the conventional dynamical predictors and notably is significantly more predictable than unadjusted wind power when initialized in the summer. Moreover, the adjusted framework results in a reduction of error when evaluating wind power associated with wind bursts, reinforcing previous findings that the adjusted framework is particularly useful for capturing the ENSO response to westerly wind bursts.