Tropical instability wave modulation of chlorophyll-a in the Equatorial Pacific

The global daily gap-free chlorophyll-a (Chl-a) data derived using the data interpolating empirical orthogonal functions (DINEOF) technique from observations of the Visible Infrared Imaging Radiometer Suite (VIIRS) in 2020 and the in situ measurements at the Tropical Ocean Atmosphere (TAO) moorings are used to characterize and quantify the biological variability modulated by the tropical instability wave (TIW). Our study aims to understand how ocean physical processes are linked to biological variability. In this study, we use the TAO in situ measurements and the coincident VIIRS Chl-a data to identify the mechanism that drives ocean biological variability corresponding to the TIW. Satellite observations show that the TIW-driven Chl-a variability stretched from 90°W to 160°E in the region. The enhanced Chl-a pattern propagated westward and moderately matched the cooler sea surface temperature (SST) patterns in the Equatorial Pacific Ocean. In fact, the Chl-a variation driven by the TIW is about ± 30% of mean Chl-a values. Furthermore, the time series of Chl-a at 140°W along the equator was found to be in phase with sea surface salinity (SSS) at 140°W along the equator at the TAO mooring since late May 2020. The cross-correlation coefficients with the maximum magnitude between Chl-a and SST, Chl-a and SSS, and Chl-a and dynamic height were –0.46, + 0.74, and –0.58, respectively, with the corresponding time lags of about 7 days, 1 day, and 8 days, respectively. The different spatial patterns of the cooler SST and enhanced Chl-a are attributed to the phase difference in Chl-a and SST. Indeed, a Chl-a peak normally coincided with a SSS peak and vice versa. This could be attributed to the consistency in the change in nutrient concentration with respect to the change of SSS. The vertical distributions of the temperature and salinity at 140°W along the equator reveal that the TIW leads to changes in both salinity and nutrient concentrations in the sea surface, and consequently drives the Chl-a variability from late May until the end of the year 2020.

Global contributions of mesoscale dynamics to meridional heat transport

Mesoscale ocean processes are prevalent in many parts of the global oceans and may contribute substantially to the meridional movement of heat. Yet earlier global surveys of meridional temperature fluxes and heat transport (HT) have not formally distinguished between mesoscale and large-scale contributions, or they have defined eddy contributions based on temporal rather than spatial characteristics. This work uses spatial filtering methods to separate large-scale (gyre and planetary wave) contributions from mesoscale (eddy, recirculation, and tropical instability wave) contributions to meridional HT. Overall, the mesoscale temperature flux (MTF) produces a net poleward meridional HT at midlatitudes and equatorward meridional HT in the tropics, thereby resulting in a net divergence of heat from the subtropics. In addition to MTF generated by propagating eddies and tropical instability waves, MTF is also produced by stationary recirculations near energetic western boundary currents, where the temperature difference between the boundary current and its recirculation produces the MTF. The mesoscale contribution to meridional HT yields substantially different results from temporally based “eddy” contributions to meridional HT, with the latter including large-scale gyre and planetary wave motions at low latitudes. Mesoscale temperature fluxes contribute the most to interannual and decadal variability of meridional HT in the Southern Ocean, the tropical Indo-Pacific, and the North Atlantic. Surface eddy kinetic energy (EKE) is not a good proxy for MTF variability in regions with the highest time-mean EKE, though it does explain much of the temperature flux variability in regions of modest time-mean EKE. This approach to quantifying mesoscale fluxes can be used to improve parameterizations of mesoscale effects in coarse-resolution models and assess regional impacts of mesoscale eddies and recirculations on tracer fluxes.

Anomalous Tropical Instability Wave activity hindered the development of the 2016/2017 La Niña

Although the 1997/98 and 2015/16 El Niño events are considered to be the strongest on record, their subsequent La Niña events exhibited contrasted evolutions. In this study, we demonstrate that the extremely strong period of Tropical Instability Waves (TIWs) at the beginning of boreal summer of 2016 played an important role in hindering the subsequent La Niña’s development by transporting extra off-equatorial heat into the Pacific cold tongue. By comparing the TIWs contribution based on an oceanic mixed-layer heat budget analysis for the 1998 and 2016 episodes, we establish that TIW-induced nonlinear dynamical heating (NDH) is a significant contributor to the El Niño-Southern Oscillation (ENSO) phase transition in 2016. TIW-induced NDH contributed to around 0.4°C per month warming during the early boreal summer (May-June) following the 2015/16 El Niño’s peak, which is found to be an essential inhibiting factor that prevented the subsequent La Niña’s growth. A time-mean eddy kinetic energy analysis reveals that anomalous TIWs during 2016 mainly gained their energy from the baroclinic instability conversion due to a strong SST warming in the northeastern off-equatorial Pacific that promoted an increased meridional SST gradient. This highlights the importance of accurately reproducing TIW activity in ENSO simulation and the benefit of off-equatorial SST anomalies in the eastern Pacific as an independent precursor for ENSO predictions.

Global contributions of mesoscale dynamics to meridional heat transport

Mesoscale ocean processes are prevalent in many parts of the global oceans, and may contribute substantially to the meridional movement of heat. Yet earlier global surveys of meridional heat transport (MHT) have not formally distinguished between mesoscale and large-scale contributions, or have defined eddy contributions based on temporal rather than spatial characteristics. This work uses spatial filtering methods to separate large-scale (gyre and planetary wave) contributions from mesoscale (eddy, recirculation, and tropical instability wave) contributions to MHT by extending beyond a previous effort for the North Atlantic Ocean. Overall, mesoscale temperature fluxes produce a net poleward MHT at mid-latitudes and equatorward MHT in the tropics, thereby resulting in a net divergence of heat from the subtropics. Mesoscale temperature fluxes are often concentrated near the energetic currents at western boundaries, and the temperature difference between the boundary current and its recirculation determines the direction of the mesoscale temperature flux. The mesoscale contribution to MHT yields substantially different results from temporally-based eddy contributions to MHT, with the latter contributed substantially by gyre and planetary wave motions at low latitudes. Mesoscale temperature fluxes contribute the most to interannual and decadal variability of MHT in the Southern Ocean, the tropical Indo-Pacific, and the North Atlantic. Surface eddy kinetic energy (EKE) is not a good proxy for mesoscale temperature flux variability in regions with the highest time-mean EKE, though it does explain much of the temperature flux variability in regions of modest time-mean EKE. This approach to quantifying mesoscale fluxes can be used to improve parameterizations of mesoscale effects in coarse-resolution models, and assess regional impacts of mesoscale eddies and recirculations on tracer fluxes.

On the Formation of a Subsurface Weakly Sheared Laminar Layer and an Upper Thermocline Strongly Sheared Turbulent Layer in the Eastern Equatorial Pacific: Interplays of Multiple-Time-Scale Equatorial Waves

The origins of an observed weakly sheared nonturbulent (laminar) layer (WSL), and a strongly sheared turbulent layer above the Equatorial Undercurrent core (UCL) in the eastern equatorial Pacific are studied, based mainly on the data from the Tropical Atmosphere and Ocean mooring array. Multiple-time-scale (from 3 to 25 days) equatorial waves were manifested primarily as zonal velocity oscillations with the maximum amplitudes (from 10 to 30 cm s−1) occurring at different depths (from the surface to 85-m depths) above the seasonal thermocline. The subsurface-intensified waves led to vertically out-of-phase shear variations in the upper thermocline via destructive interference with the seasonal zonal flow, opposing the tendency for shear instability. These waves were also associated with depth-dependent, multiple-vertical-scale stratification variations, with phase lags of π/2 or π, further altering stability of the zonal current system to vertical shear. The WSL and UCL were consequently formed by coupling of multiple equatorial waves with differing phases, particularly of the previously identified equatorial mode and subsurface mode tropical instability waves (with central period of 17 and 20 days, respectively, in this study), and subsurface-intensified waves with central periods of 6, 5, and 12 days and velocity maxima at 45-, 87-, and 40-m depths, respectively. In addition, a wave-like feature with periods of 50–90 days enhanced the shear throughout the entire UCL. WSLs and UCLs seem to emerge without a preference for particular tropical instability wave phases. The generation mechanisms of the equatorial waves and their joint impacts on thermocline mixing remain to be elucidated.

Purely satellite data–driven deep learning forecast of complicated tropical instability waves

Forecasting fields of oceanic phenomena has long been dependent on physical equation–based numerical models. The challenge is that many natural processes need to be considered for understanding complicated phenomena. In contrast, rules of the processes are already embedded in the time-series observation itself. Thus, inspired by largely available satellite remote sensing data and the advance of deep learning technology, we developed a purely satellite data–driven deep learning model for forecasting the sea surface temperature evolution associated with a typical phenomenon: a tropical instability wave. During the testing period of 9 years (2010–2019), our model accurately and efficiently forecasts the sea surface temperature field. This study demonstrates the strong potential of the satellite data–driven deep learning model as an alternative to traditional numerical models for forecasting oceanic phenomena.

Normal-mode Magnetoseismology as a Virtual Plasma Mass Density Instrument and Its Use in Investigation of Oxygen Torus during Magnetic Storms

<p>Previous studies have demonstrated that the field line resonance (FLR) frequencies detected on closed magnetospheric field lines can be used to estimate the plasma mass density in the inner magnetosphere. This method, also known as “normal-mode magnetoseismology,” can act as a virtual instrument that turns spacecraft measurements of magnetic and/or electric field into plasma mass density, which is a fundamental physical quantity that is difficult to measure directly but important to investigations involving the MHD timescales, reconnection rates, or instability/wave growth rates.</p><p>In this study, we use normal-mode magnetoseismology to help investigate the characteristics of the oxygen torus, which is the narrow region of enhanced O+ density in the vicinity of the plasmapause that may form during the storm recovery phase. The formation of the oxygen torus is still an outstanding question, and the geomagnetic mass spectrometer effect and the direct ring current heating of the ionosphere have been proposed as two possible causes. We identify the location and timing of oxygen torus occurrence by examining the FLR-inferred plasma mass densities in Magnetospheric Multiscale (MMS) and Van Allen Probes (RBSP) observations and compare them with the charge densities derived from the upper hybrid resonance frequency detected by the respective plasma wave experiments on the spacecraft. We find that, while MMS and RBSP could both observe clear enhancements of heavy ions during a magnetic storm, the degree and the width of O+ enhancement can vary with location. The timing of oxygen torus occurrence may differ from storm to storm. In RBSP measurements, we also compare the bulk densities with the partial densities of low-energy ions detected by the HOPE instrument. While the average ion mass can be greater for 30 eV – 1 keV ions than that for the bulk plasma in the oxygen torus, it is evident that the majority of the ions in the oxygen torus are below 30 eV, confirming the need to examine the bulk mass and charge densities through electromagnetic sounding methods.</p>

Nonlinearly most dangerous disturbance for high-speed boundary-layer transition

Laminar-to-turbulent transition in a zero-pressure-gradient boundary layer at Mach 4.5 is studied using direct numerical simulations. For a given level of total disturbance energy, the inflow spectrum was designed to correspond to the nonlinearly most dangerous condition that leads to the earliest possible transition Reynolds number. The synthesis of the inlet disturbance is formulated as a constrained optimization, where the control vector is comprised of the amplitudes and relative phases of the inlet modes; the constraints are the prescribed total energy and that the flow evolution satisfies the full nonlinear compressible Navier–Stokes equations; the cost function is defined in terms of the mean skin-friction coefficient and, once maximized, ensures the earliest possible transition location. An ensemble-variational (EnVar) technique is developed to solve the optimization problem. Starting from an initial guess, here a broadband disturbance, EnVar updates the estimate of the control vector at the end of each iteration using the gradient of the cost function, which is evaluated from the outcomes of an ensemble of possible solutions. Two inflow conditions are computed, each corresponding to a different level of energy, and their spectra are contrasted: the lower-energy case includes two normal acoustic waves and one oblique vorticity perturbation, whereas the higher-energy condition consists of oblique acoustic and vorticity waves. The focus is placed on the former case because it cannot be categorized as any of the classical breakdown scenarios (fundamental, subharmonic or oblique), while the higher-energy condition undergoes a second-mode oblique transition. At the lower energy level, the instability wave that initiates the rapid breakdown to turbulence is not present at the inlet plane. Instead, it appears at a downstream location after a series of nonlinear interactions that spur the fastest onset of turbulence. The results from the nonlinearly most potent inflow condition are also compared to other inlet disturbances that are selected solely based on linear theory, and which all yield relatively delayed transition onset.