Quasi-geostrophic Dynamics Research Articles

Statistics of inhomogeneous turbulence in large-scale quasigeostrophic dynamics.

A remarkable feature of two-dimensional turbulence is the transfer of energy from small to large scales. This process can result in the self-organization of the flow into large, coherent structures due to energy condensation at the largest scales. We investigate the formation of this condensate in a quasigeostropic flow in the limit of small Rossby deformation radius, namely the large-scale quasigeostrophic model. In this model potential energy is transferred up-scale while kinetic energy is transferred down-scale in a direct cascade. We focus on a jet mean flow and carry out a thorough investigation of the second-order statistics for this flow, combining a quasilinear analytical approach with direct numerical simulations. We show that the quasilinear approach applies in regions where jets are strong and is able to capture all second-order correlators in that region, including those related to the kinetic energy. This is a consequence of the blocking of the direct cascade by the mean flow in jet regions, suppressing fluctuation-fluctuation interactions. The suppression of the direct cascade is demonstrated using a local coarse-graining approach allowing us to measure space dependent interscale kinetic energy fluxes, which we show are concentrated in between jets in our simulations. We comment on the possibility of a similar direct cascade arrest in other two-dimensional flows, arguing that it is a special feature of flows in which the fluid element interactions are local in space.

Minimal chaotic models from the Volterra gyrostat

Low-order models obtained through Galerkin projection of several physically important systems (e.g., Rayleigh–Bénard convection, mid-latitude quasi-geostrophic dynamics, and vorticity dynamics) appear in the form of coupled gyrostats. Forced dissipative chaos is an important phenomenon in these models, and this paper introduces and identifies “minimal chaotic models” (MCMs), in the sense of having the fewest external forcing and linear dissipation terms, for the class of models arising from an underlying gyrostat core. The identification of MCMs reveals common conditions for chaos across a wide variety of physical systems. It is shown here that a critical distinction is whether the gyrostat core (without forcing or dissipation) conserves energy, depending on whether the sum of the quadratic coefficients is zero. The paper demonstrates that, for the energy-conserving condition of the gyrostat core, the requirement of a characteristic pair of fixed points that repel the chaotic flow dictates placement of forcing and dissipation in the minimal chaotic models. In contrast if the core does not conserve energy, the forcing can be arranged in additional ways for chaos to appear in the subclasses where linear feedbacks render fewer invariants in the gyrostat core. In all cases, the linear mode must experience dissipation for chaos to arise. The Volterra gyrostat presents a clear example where the arrangement of fixed points circumscribes more complex dynamics.

A surrogate non-intrusive reduced order model of quasi-geostrophic turbulence dynamics based on a combination of LSTM and different approaches of DMD

Mathematical modeling is applied to study phenomena and system behavior.In various engineering fields, many physical phenomena are illustrated using a set of differential equations.In many real-world applications, the mathematical models are very complex, and numerical simulations in high-dimensional systems are challenging.Examples of these problems are large-scale physical problems such as geophysical, which have high temporal and spatial variations.In these problems, model order reduction is a useful method for achieving an appropriate approximation because it can significantly decrease computational costs.Deep learning has recently been used to explore information from data and make predictions.There are several methods for dimensionality reduction.In this paper, we combine the dynamic mode decomposition (DMD) and the long short-term memory (LSTM) network.This is because LSTM can predict nonlinear systems and time series data.We use LSTM and DMD to predict nonlinear systems and reduce dimensions, respectively.Four common DMD schemes have been applied for dimensionality reduction.The common geophysical dataset has been used to evaluate the performance of the proposed method.Finally, we compare the variations of the modal coefficients which are obtained from snapshots projection and the reduced-order model.These results show the high accuracy of our proposed method.One of the things that is important is the time complexity of algorithm implementation.The time complexity of the proposed method is 10 times faster when 15 modes are used for modeling than when all features are used.

Eddy‐Mean Flow Interaction With a Multiple Scale Quasi Geostrophic Model

AbstractParameterization of mesoscale eddies in coarse resolution ocean models is necessary to include the effect of eddies on the large‐scale oceanic circulation. We propose to use a multiple‐scale Quasi‐Geostrophic (MSQG) model to capture the eddy dynamics that develop in response to a prescribed large‐scale flow. The MSQG model consists in extending the traditional quasi geostrophic (QG) dynamics to include the effects of a variable Coriolis parameter and variable background stratification. Solutions to this MSQG equation are computed numerically and compared to a full primitive equation model. The large‐scale flow field permits baroclinically unstable QG waves to grow. These instabilities saturate due to non‐linearities and a filtering method is applied to remove large‐scale structures that develop due to the upscale cascade. The resulting eddy field represents a dynamically consistent response to the prescribed background flow, and can be used to rectify the large‐scale dynamics. Comparisons between Gent‐McWilliams eddy parameterization and the present solutions show large regions of agreement, while also indicating areas where the eddies feed back onto the large scale in a manner that the Gent‐McWilliams parameterization cannot capture. Also of interest is the time variability of the eddy feedback which can be used to build stochastic eddy parameterizations.

Suitable region of dynamic optimal interpolation for efficiently altimetry sea surface height mapping

The dynamic optimal interpolation (DOI) method is a technique based on quasi-geostrophic dynamics for merging multi-satellite altimeter along-track observations to generate gridded absolute dynamic topography (ADT). Compared with the linear optimal interpolation (LOI) method, the DOI method can improve the accuracy of gridded ADT locally but with low computational efficiency. Consequently, considering both computational efficiency and accuracy, the DOI method is more suitable to be used only for regional applications. In this study, we propose to evaluate the suitable region for applying the DOI method based on the correlation between the absolute value of the Jacobian operator of the geostrophic stream function and the improvement achieved by the DOI method. After verifying the LOI and DOI methods, the suitable region was investigated in three typical areas: the Gulf Stream (25°N-50°N, 55°W-80°W), the Japanese Kuroshio (25°N-45°N, 135°E−155°E), and the South China Sea (5°N-25°N, 100°E−125°E). We propose to use the DOI method only in regions outside the equatorial region and where the absolute value of the Jacobian operator of the geostrophic stream function is higher than 1 × 10−11.

Observed Oceanic Surface Modes in the Northern South China Sea

Abstract Using observations and theoretical models, a substantial topographic modulation on the quasigeostrophic (QG) dynamics, which results in a primary surface mode distinct from the classic first baroclinic (BC1) mode with a flat bottom, is revealed in the northern South China Sea (NSCS). In contrast to open oceans, the surface-intensified modes decay downward more rapidly over the continental slope of the NSCS, with a mean e-folding scale of approximately 1/5 of water depth. The subinertial flow variability appears to be vertically incoherent, with planetary and topographic Rossby waves dominating in the upper and deep layers, respectively. With a larger deformation radius (Rd), the surface-mode Rossby waves propagate at a phase speed ∼1.5 times of that of the BC1 mode. Moreover, the modal structures can be substantially modified by seasonal NSCS circulation, which is significantly enhanced over continental slopes. Analysis of the triad interactions further implies that the short waves tend to transfer energy to larger scales via the inverse cascade and only those with wavelengths larger than Rd ≈ 70 km in the NSCS can persist because of a slower unstable growth rate but a higher fraction of upscale energy transfer. The present theory excludes the bottom-trapped mode, which is closely associated with topographic Rossby waves and is observed to be significant in the abyssal NSCS. Hence, a complete normal-mode basis for any QG state is required for a study that focuses on flow variability throughout the water column. Our findings provide an insight into the vertical partition of horizontal kinetic energy for QG motions, as well as the relevant oceanic variation in marginal seas.

A direct derivation of the Gent–McWilliams/Redi diffusion tensor from quasi-geostrophic dynamics

The transport induced by ocean mesoscale eddies remains unresolved in most state-of-the-art climate models and needs to be parametrized instead. The natural scale separation between the forcing and the emergent turbulent flow calls for a diffusive parametrization, where the eddy-induced fluxes are related to the large-scale gradients by a diffusion tensor. The standard parametrization scheme in climate modelling consists in adopting the Gent–McWilliams/Redi (GM/R) form for the diffusion tensor, initially put forward based on physical intuition and educated guesses before being put on firm analytical footing using a thickness-weighted average (TWA). In the present contribution, we provide a direct derivation of this diffusion tensor from the quasi-geostrophic (QG) dynamics of a horizontally homogeneous three-dimensional patch of ocean hosting a large-scale vertically sheared zonal flow on the $\beta$ plane. The derivation hinges on the identification of a useful cross-invariant defined as the product of the buoyancy and QG potential vorticity fluctuations. While less general than the TWA approach, the present QG framework leads to rigorous constraints on the diffusion tensor. First, there is no diapycnal diffusivity arising in the QG GM/R tensor for low viscosity and small-scale diffusivities. The diffusion tensor then involves only two vertically dependent coefficients, namely the GM transport coefficient $K_{GM}(z)$ and the Redi diffusivity $K_R(z)$ . Second, as identified already by previous authors, the vertical structures of the two coefficients are related by the so-called Taylor–Bretherton relation. Finally, while the two coefficients differ generically in the interior of the water column, we show that they are equal to one another near the surface and near the bottom of the domain for low-enough dissipative coefficients. We illustrate these findings by simulating numerically the QG dynamics of a horizontally homogeneous patch of ocean hosting a vertically sheared zonal current resembling the Antarctic Circumpolar Current.

Two-Layer Ocean Circulation Model with Variational Control of Turbulent Viscosity Coefficient

The development of a variational method for solving the problem of quasi-geostrophic dynamics in a two-layer periodic channel is considered. The development of the method is as follows. First, the formulation of the variational problem is generalized: the turbulent exchange coefficient of a quasi-geostrophic potential vorticity (QGPV) is included in the control vector. Secondly, the solution area more accurately describes the size of the Antarctic Circumpolar Current (ACC). Using the selection of linear meridional transport and the expansion of the solution in a Fourier series, the problem is reduced to a nonlinear system of ordinary differential equations (ODEs) in time. The doubly connected domain leads to the fact that the solution of the ODE must satisfy an additional stationary relation that determines the transport of the ACC. The variational algorithm is reduced to solving a system of forward and adjoint equations minimizing the mean squared error of the stationary relation. The QGPV turbulent exchange coefficient is determined in the process of solving the optimal problem. The numerical runs are carried out for a periodic channel simulating the water area of the ACC in the Southern Ocean. The characteristics of stationary current regimes are studied for different values of the model parameters. Typical is a sinusoidal circulation in both layers with a linear transfer with the wind, depending on the bottom topography. In some cases, under the sinusoidal, in the lower layer, a cellular circulation is formed, and sometimes an undercurrent occurs. In this case, the solution of the optimal problem is characterized by a low value of the turbulent viscosity coefficient and a low transport in the lower layer.

Elastic Interaction Between a Mesoscale Eddy‐Pair and an Axisymmetrical Eddy

AbstractWe investigate numerically the elastic interaction between an eddy‐pair and an axisymmetrical eddy in inviscid isochoric two‐dimensional (2D) flows, as well as in three‐dimensional (3D) flows under the quasi‐geostrophic (QG) approximation. The eddy‐pair is a straight moving Lamb‐Chaplygin dipole where the absolute value of either its positive or negative amount of vorticity equals the vorticity of the axisymmetrical eddy. The results for the 2D and 3D cases show that interactions with almost no vorticity exchange, or vorticity loss to the background field between ocean eddies, but causing changes in their displacement velocity, are possible. When the eddy‐pair approaches the axisymmetrical eddy, their respective potential flows interact, the eddy‐pair's trajectory acquires curvature and their vorticity poles separate. In the QG dynamics, the eddies suffer little vertical deformation, being the barotropic effects dominant. At the moment of highest interaction, the anticyclonic eddy of the pair elongates, simultaneously the cyclonic eddy of the pair evolves toward spherical geometry, and the axisymmetrical eddy acquires prolate ellipsoidal geometry in the vertically stretched QG space. Once the eddy‐pair moves away from the axisymmetrical eddy, its poles close, returning to their original geometry, and the anticyclonic and cyclonic eddies continue as an eddy‐pair with a straight trajectory but along a new direction. The interaction is sensitive to the initial conditions and, depending on the initial position of the eddy‐pair, as well as on small changes in the vorticity distribution of the axisymmetrical eddy, inelastic interactions may instead occur.

Back-and-forth nudging for the quasi-geostrophic ocean dynamics with altimetry: Theoretical convergence study and numerical experiments with the future SWOT observations

<p style='text-indent:20px;'>In data assimilation for geophysical problems, the increasing amount of satellite data to analyze makes it more and more challenging to guarantee near real time forecasting. Thus, low time and memory consuming data assimilation methods become very attractive. The back-and-forth nudging (BFN) method is a non-classical data assimilation method that can be seen as a deterministic and smoothing version of the Kalman filter. From a practical point of view, the BFN method is very valuable for its simplicity of implementation (no optimization, no differentiation, ...) and its rapidity of convergence. Under observability conditions, we prove the mathematical convergence of BFN at deep layers for a multi-layer quasi-geostrophic (MQG) ocean circulation model using an infinite dimensional variant of LaSalle's invariance principle. We also extend the BFN to the problem of joint state-parameter identification. The numerical experiments, performed on 120km large swath sea surface height (SSH) simulated data of the Surface Water Ocean Topography (SWOT) satellite, show the high robustness of the algorithm to uncertainties and the few iterations needed to reach convergence, whereas some problems remain due to non-reversibility properties in time. We also give a strategy to improve geophysical model accuracy, considering the large number of uncertain parameters inherent to models and their impacts on state estimation performance. We propose here a joint state-parameter estimation, tested on the baroclinic wavenumber as an unobserved parameter.</p>

Transport and emergent stratification in the equilibrated Eady model: the vortex-gas scaling regime

We numerically and theoretically investigate the Boussinesq Eady model, where a rapidly rotating density-stratified layer of fluid is subject to a meridional temperature gradient in thermal wind balance with a uniform vertically sheared zonal flow. Through a suite of numerical simulations, we show that the transport properties of the resulting turbulent flow are governed by quasigeostrophic (QG) dynamics in the rapidly rotating strongly stratified regime. The ‘vortex gas’ scaling predictions put forward in the context of the two-layer QG model carry over to this fully three-dimensional system: the functional dependence of the meridional flux on the control parameters is the same, the two adjustable parameters entering the theory taking slightly different values. In line with the QG prediction, the meridional heat flux is depth-independent. The vertical heat flux is such that turbulence transports buoyancy along isopycnals, except in narrow layers near the top and bottom boundaries, the thickness of which decreases as the diffusivities go to zero. The emergent (re)stratification is set by a simple balance between the vertical heat flux and diffusion along the vertical direction. Overall, this study demonstrates how the vortex-gas scaling theory can be adapted to quantitatively predict the magnitude and vertical structure of the meridional and vertical heat fluxes, and of the emergent stratification, without additional fitting parameters.

Characterization of intraseasonal fluctuations in the abyssal South China Sea: An insight into the energy pathway

Energetics of the abyssal ocean account greatly for the redistribution and dissipation of global oceanic energy. In this study, we characterize the intraseasonal fluctuations in the deep South China Sea (SCS) and evaluate the relevant energy budget using observations and numerical simulations. The results indicate substantial geographical inhomogeneity in the intraseasonal energy reservoir. The high-energy zones are located in the northwest of the Luzon Strait, northern slopes, deep western boundary current region, and southwestern cyclonic gyre region, where the intraseasonal fluctuations account for about 70% of the deep energy variability. Vorticity and divergence patterns of the intraseasonal motions are suggestive of quasigeostrophic dynamics, which are mostly attributed to the hybrid topographic–planetary Rossby waves. The flow field exhibits a weak lateral shear and appears to have symmetric instability with negative vorticity skewness, particularly over the sloping topography. Energetics analysis demonstrates that the intraseasonal fluctuations in the abyssal SCS obtain energy primarily from the upper layer through pressure work, while secondarily from advective transport and cross-scale transfer due to instability of the deep circulation. To reach equilibrium, the energy gained is mostly damped by dissipations. As another reference in the marginal sea with intensive mixing, our study highlights the potential universality in how the intraseasonal energy is fueled and dissipated in the abyss.

Point-vortex dynamics in three-dimensional ageostrophic balanced flows

Geophysical turbulent flows, characterized by rapid rotation, quantified by small Rossby number, and stable stratification, often self-organize into a collection of coherent vortices, referred to as a vortex gas. The lowest-order asymptotic expansion in Rossby number is quasigeostrophy, which has purely horizontal velocities and cyclone–anticyclone antisymmetry. Ageostrophic effects are important components of many geophysical flows and, as such, these phenomena are not well modelled by quasigeostrophy. The next-order correction in Rossby number, which includes ageostrophic effects, is the so-called balanced dynamics. Balanced dynamics includes ageostrophic vertical velocity and breaks the geostrophic cyclone–anticyclone antisymmetry. Point-vortex solutions are well known in two-dimensional and quasigeostrophic dynamics and are useful for studying the vortex-gas regime of geophysical turbulence. Here, we find point-vortex solutions in fully three-dimensional continuously stratified QG $^{+1}$ dynamics, a particular formulation of balanced dynamics. Simulations of QG $^{+1}$ point vortices show several interesting features not captured by quasigeostrophic point vortices including significant vertical transport on long time scales. The ageostrophic component of QG $^{+1}$ point vortex point-vortex dynamics renders them useful in modelling flows where quasigeostrophy filters out important physical processes.

Practical Dynamical-Statistical Reconstruction of Ocean’s Interior from Satellite Observations

The algorithms based on Surface Quasi-Geostrophic (SQG) dynamics have been developed and validated by many researchers through model products, however it is still doubtful whether these SQG-based algorithms are worth using in terms of observed data. This paper analyzes the factors impeding the practical application of SQG and makes amends by a simple “first-guess (FG) framework”. The proposed framework includes the correction of satellite salinity and the estimation of the FG background, making the SQG-based algorithms applicable in realistic circumstances. The dynamical-statistical method SQG-mEOF-R is thereafter applied to satellite data for the first time. The results are compared with two dynamical algorithms, SQG and isQG, and three empirical algorithms, multivariate linear regression (MLR), random forest (RF), and mEOF-R. The validation against Argo profiles showed that the SQG-mEOF-R presents a robust performance in mesoscale reconstruction and outperforms the other five algorithms in the upper layers. It is promising that the SQG-mEOF-R and the FG framework are applicable to operational reconstruction.

Diagnosing Cross‐Scale Kinetic Energy Exchanges From Two Submesoscale Permitting Ocean Models

AbstractFine‐scale motions (<100 km) contribute significantly to the exchanges and dissipation of kinetic energy in the upper ocean. However, knowledge of ocean kinetic energy at fine‐scales (in terms of density and transfers) is currently limited due to the lack of sufficient observational data sets at these scales. The sea‐surface height measurements of the upcoming Surface Water and Ocean Topography (SWOT) altimeter mission should provide information on kinetic energy exchanges in the upper ocean down to 10–15 km. Numerical ocean models, able to describe ocean dynamics down to ∼10 km, have been developed in anticipation of the SWOT mission. In this study, we use two state‐of‐the‐art, realistic, North Atlantic simulations, with horizontal resolutions ∼1.5 km, to investigate the distribution and exchanges of kinetic energy at fine‐scales in the open ocean. Our results show that the distribution of kinetic energy at fine‐scales approximately follows the predictions of quasigeostrophic dynamics in summertime but is somewhat consistent with submesoscale fronts‐dominated regimes in wintertime. The kinetic energy spectral fluxes are found to exhibit both inverse and forward cascade over the top 1,000 m, with a maximum inverse cascade close to the average energy‐containing scale. The forward cascade is confined to the ocean surface and shows a strong seasonality, both in magnitude and range of scales affected. Our analysis further indicates that high‐frequency motions (<1 day) play a key role in the forward cascade and that the estimates of the spectral fluxes based on geostrophic velocities fail to capture some quantitative aspects of kinetic energy exchanges across scales.

Mapping Altimetry in the Forthcoming SWOT Era by Back-and-Forth Nudging a One-Layer Quasigeostrophic Model

AbstractDuring the past 25 years, altimetric observations of the ocean surface from space have been mapped to provide two dimensional sea surface height (SSH) fields that are crucial for scientific research and operational applications. The SSH fields can be reconstructed from conventional altimetric data using temporal and spatial interpolation. For instance, the standard Developing Use of Altimetry for Climate Studies (DUACS) products are created with an optimal interpolation method that is effective for both low temporal and low spatial resolution. However, the upcoming next-generation SWOT mission will provide very high spatial resolution but with low temporal resolution. The present paper makes the case that this temporal–spatial discrepancy induces the need for new advanced mapping techniques involving information on the ocean dynamics. An algorithm is introduced, dubbed the BFN-QG, that uses a simple data assimilation method, the back-and-forth nudging (BNF), to interpolate altimetric data while respecting quasigeostrophic (QG) dynamics. The BFN-QG is tested in an observing system simulation experiments and compared to the DUACS products. The experiments consider as reference the high-resolution numerical model simulation NATL60 from which are produced realistic data: four conventional altimetric nadirs and SWOT data. In a combined nadirs and SWOT scenario, the BFN-QG substantially improves the mapping by reducing the root-mean-square errors and increasing the spectral effective resolution by 40 km. Also, the BFN-QG method can be adapted to combine large-scale corrections from nadir data and small-scale corrections from SWOT data so as to reduce the impact of SWOT correlated noises and still provide accurate SSH maps.

Eady edge waves, frontal wave-trains and type-B cyclogenesis

Eady edge waves (EEWs) propagate on surface baroclinic zones and they resemble synoptic and sub-synoptic scale frontal wave-trains. The wave-trains are frequently depicted on surface charts, and occur per se on a front with a local baroclinicity extremum. The possible linkage of EEWs to frontal waves is explored within the framework of so-called ‘surface quasi-geostrophic dynamics’ by establishing the properties of free and forced EEWs propagating on an ambient flow comprising a laterally confined baroclinic zone. It is shown that the dispersion properties of the free EEWs modes are influenced significantly both by the zone’s baroclinicity extremum and by key features that are akin to those of cold and warm fronts. In particular the larger-scale waves are nondispersive and a local wave-packet can retain coherency, the leading modes on a pseudo-cold front possess a phase speed related to the baroclinicity extremum, whereas waves on a pseudo-warm front propagate in the reverse direction. Also theoretical considerations demonstrate that forced modes can undergo resonant secular growth. It is further shown that transient or sustained forcing of a front by an upper-tropospheric potential vorticity anomaly (sic. short-wave trough) can serve to instigate features akin to frontal wave-trains and type-B cyclogenesis. More generally the study hints at the significance for NWP of a front’s structure and its dispersion properties, and that an element of predictability is introduced by the latter features due to dynamical scale selection.

Hopf bifurcations and transitions of two-dimensional Quasi-Geostrophic flows

This study examines the Hopf (double Hopf) bifurcations and transitions of two dimensional quasi-geostrophic (QG) flows that model various large-scale oceanic and atmospheric circulations. Using the Kolmogorov function to represent an external forcing in the tropical region, it is shown that the equilibrium of the QG model loses its stability if the combination of the Rossby number, the Ekman number, and the eddy viscosity satisfies a specific condition. Further use of the center manifold technique reveals two different types of the dynamical transition from either a pair of simple complex eigenvalues or a double pair of complex conjugate eigenvalues. These dynamical transitions are confirmed in the numerical analyses of the QG dynamics at the equilibrium, which capture Hopf (double Hopf) bifurcations due to the existence of a nonzero imaginary part of the first eigenvalue. The transition from a pair of simple complex eigenvalues is of particular interest, because it indicates the existence of a stable periodic pattern that is similar to atmospheric easterly waves and related tropical cyclone formation in the tropical atmosphere.

Wave–vortex interactions and effective mean forces: three basic problems

Three examples of wave–vortex interaction are studied, in analytically tractable weak refraction regimes with attention to the mean recoil forces, local and remote, that are associated with refractive changes in wave pseudomomentum fluxes. Wave-induced mean forces of this kind can be persistent, with cumulative effects, even in the absence of wave dissipation. In each example, a single wavetrain propagates past a single vortex. In the first two examples, in a two-dimensional, non-rotating acoustic or shallow-water setting, the focus is on whether or not the wavetrain overlaps the vortex core. In the overlapping case, the recoil has a local contribution given by the Craik–Leibovich force on the vortex core, the vector product of Stokes drift and mean vorticity. (For a quantum vortex this contribution is called the Iordanskii force arising from the Aharonov–Bohm effect on a phonon current.) However, in all except one special limiting case there are additional “remote” contributions, mediated by Stokes-drift-induced return flows that can intersect the vortex core well away from locations where the waves are refracted. The third example is a non-overlapping, remote-recoil-only example in a rapidly rotating frame, in which the waves are deep-water gravity waves and the mean flow obeys shallow-water quasigeostrophic dynamics. Contrary to what might at first be thought, the Ursell “anti-Stokes flow” induced by the rotation – an Eulerian-mean flow tending to cancel the Stokes drift – fails to suppress remote recoil. There are nontrivial open questions about extending these results to regimes of stronger refraction, especially regarding the scope of the “pseudomomentum rule” for the wave-induced recoil forces.

Atmospheric rivers and water fluxes in precipitating quasi‐geostrophic turbulence

AbstractMost of the poleward transport of water can be accounted for by long narrow corridors known as Atmospheric Rivers (ARs). ARs are typically associated with extratropical cyclones and, for dry extratropical cyclones, an idealized prototype has previously been provided by quasi‐geostrophic (QG) dynamics. However, there are few if any studies that investigate ARs in a QG framework. Here, the overarching question is: do idealized ARs appear in moist QG dynamics? A precipitating quasi‐geostrophic (PQG) model is explored as a possible prototype for ARs and associated water transport. The set‐up uses numerical simulations of geostrophic turbulence with precipitation, in a single phase. The simulations are shown to produce idealized ARs, and they have reasonably realistic statistics for such a simple set‐up. For instance, the model ARs occur roughly as frequently as in nature, based on commonly used AR identification algorithms. To produce ARs in this model, it is found that two key ingredients are needed beyond the dry QG framework: precipitation and a meridional moisture gradient. If either of these two ingredients is too weak, then less realistic ARs are produced. In addition, for a range of precipitation rates, a large fraction of the meridional moisture transport is due to ARs.