Quasi-geostrophic Research Articles

Using Explainable AI and Transfer Learning to Understand and Predict the Maintenance of Atlantic Blocking With Limited Observational Data

AbstractBlocking events are an important cause of extreme weather, especially long‐lasting blocking events that trap weather systems in place. The duration of blocking events is, however, underestimated in climate models. Explainable Artificial Intelligence are a class of data analysis methods that can help identify physical causes of prolonged blocking events and diagnose model deficiencies. We demonstrate this approach on an idealized quasigeostrophic (QG) model developed by Marshall and Molteni (1993), https://doi.org/10.1175/1520‐0469(1993)050<1792:taduop>2.0.co;2. We train a convolutional neural network (CNN), and subsequently, build a sparse predictive model for the persistence of Atlantic blocking, conditioned on an initial high‐pressure anomaly. Shapley Additive ExPlanation (SHAP) analysis reveals that high‐pressure anomalies in the American Southeast and North Atlantic, separated by a trough over Atlantic Canada, contribute significantly to prediction of sustained blocking events in the Atlantic region. This agrees with previous work that identified precursors in the same regions via wave train analysis. When we apply the same CNN to blockings in the ERA5 atmospheric reanalysis, there is insufficient data to accurately predict persistent blocks. We partially overcome this limitation by pre‐training the CNN on the plentiful data of the Marshall‐Molteni model, and then using Transfer learning (TL) to achieve better predictions than direct training. SHAP analysis before and after TL allows a comparison between the predictive features in the reanalysis and the QG model, quantifying dynamical biases in the idealized model. This work demonstrates the potential for machine learning methods to extract meaningful precursors of extreme weather events and achieve better prediction using limited observational data.

The Energy Dispersion of Magnetic Rossby Waves in the Quasi-geostrophic Shallow Water Magnetohydrodynamic Theory

Abstract This research firstly comprehensively investigates the energy dispersion of magnetic Rossby waves in zonally non-uniform basic state by applying the quasi-geostrophic (QG) shallow water magnetohydrodynamic (SWMHD) equations. The eddy momentum and heat flux transported by Magnetic Rossby waves, which can be described by the group velocity vector, have significant impacts on the large-scale dynamics of various celestial bodies. The findings suggest that the energy dispersion paths, also called rays, are curves and restricted in limited regions in the non-uniform basic states, in contrast with straight lines in the uniform basic states. Furthermore, the limited propagative regions are influenced by three important meridional locations, which are defined as the symmetric turning location, the asymmetric turning location, and the critical location. The first two reflect rays and the third one acts as an asymptote. The propagative region that is enclosed by a turning location and a critical location is more general. Besides, the occurrence of the asymmetric turning location, which is mainly depended on the distribution of the zonal basic flow, is a quite new feature of the energy dispersion for magnetic Rossby waves since there is no asymmetric turning location for Rossby waves on the Earth’s atmosphere and ocean. The results have important applications in illustrating interactions between magnetic Rossby waves and zonally basic states and in explaining the maintenance of the zonal flow and meridional circulation of various celestial bodies.

Atmospheric Moisture Decreases Midlatitude Eddy Kinetic Energy

Abstract There is compelling evidence that atmospheric moisture may either increase or decrease midlatitude eddy kinetic energy (EKE). We reconcile these findings by using a hierarchy of idealized atmospheric models to demonstrate that moisture energizes individual eddies given fixed large-scale background winds and temperatures but makes those background conditions less favorable for eddy growth. For climates similar to the present day, the latter effect wins out, and moisture weakens midlatitude eddy activity. The model hierarchy includes a moist two-layer quasigeostrophic (QG) model and an idealized moist general circulation model (GCM). In the QG model, EKE increases when moisture is added to simulations with fixed baroclinicity, closely following a previously derived scaling. But in both models, moisture decreases EKE when environmental conditions are allowed to vary. We explain these results by examining the models’ mean available potential energy (MAPE) and by calculating terms in the models’ Lorenz energy cycles. In the QG model, the EKE decreases because precipitation preferentially forms on the poleward side of the jet, releasing latent heat where the model is relatively cold and decreasing the MAPE, hence the EKE. In the moist GCM, the MAPE primarily decreases because the midlatitude stability increases as the model is moistened, with reduced meridional temperature gradients playing a secondary role. Together, these results clarify moisture’s role in driving the midlatitude circulation and also highlight several drawbacks of QG models for studying moist processes in midlatitudes. Significance Statement Dry models of the atmosphere have played a central role in the study of large-scale atmospheric dynamics. But we know that moisture adds much complexity, associated with phase changes, its effect on atmospheric stability, and the release of latent heat during condensation. Here, we take an important step toward incorporating moisture into our understanding of midlatitude dynamics by reconciling two diverging lines of literature, which suggest that atmospheric moisture can either increase or decrease midlatitude eddy kinetic energy. We explain these opposing results by showing that moisture not only makes individual eddies more energetic but also makes the environment in which eddies form less favorable for eddy growth. For climates similar to the present day, the latter effect wins out such that moisture decreases atmospheric eddy kinetic energy. We demonstrate this point using several different idealized atmospheric models, which allow us to gradually add complexity and to smoothly vary between moist and dry climates. These results add fundamental understanding to how moisture affects midlatitude climates, including how its effects change in warmer and moisture climates, while also highlighting some drawbacks of the idealized atmospheric models.

Characterization of hydromagnetic waves propagating over a steady, non-axisymmetric background magnetic field

Motivated by recent observations of rapid (interannual) signals in the geomagnetic data, and by advances in numerical simulations approaching the Earth’s outer core conditions, we present a study on the dynamics of hydromagnetic waves evolving over a static base state. Under the assumption of timescales separation between the rapid waves and the slow convection, we linearize the classical magneto-hydrodynamics equations over a steady non-axisymmetric background magnetic field and a zero velocity field. The initial perturbation is a super-rotating pulse of the inner core, which sets the amplitude and length scales of the waves in the system. The initial pulse triggers axisymmetric, outward propagating torsional Alfvén waves, with characteristic thickness scaling with the magnetic Ekman number as E k M 1 / 4 . Because the background state is non-axisymmetric, the pulse also triggers non-axisymmetric, quasi-geostrophic (QG) Alfvén waves. As these latter waves propagate outwards, they turn into QG, magneto-Coriolis (QG-MC) waves as the Coriolis force supersedes inertia in the force balance. The period of the initial wave packet is preserved across the shell but the QG-MC wavefront disperses and a westward drift is observed after this transformation. Upon reaching the core surface, the westward drift of the QG-MC waves presents an estimated phase speed of about 1100 k m y − 1 . This analysis confirms the QG-MC nature of the rapid magnetic signals observed in geomagnetic field models near the Equator.

Distinct Impacts of Topographic versus Planetary PV Gradients on Baroclinic Turbulence

Abstract The impacts of topographic versus planetary potential vorticity (PV) gradients on fully developed geostrophic turbulence are often treated as dynamically equivalent in theoretical understanding and parameterizations of ocean mesoscale turbulence. Using a suite of homogeneous, two-layer quasigeostrophic (QG) turbulence simulations, we identify similarities and distinctions of topographic versus planetary PV gradients in modulating turbulent eddy energy and fluxes. We show that, while an elevated background PV gradient can suppress geostrophic turbulence, a positive (negative) bottom slope with respect to the orientation of isopycnal slope barotropizes (debarotropizes) the turbulent energy at large scales, which contrasts with a dynamically inert planetary PV gradient in the modewise energy transfer. Then, in the presence of weak bottom drag, a positive slope energizes large-scale along-slope jets and limits small-scale barotropic eddies, both of which yield stronger eddy suppression effects than from a planetary PV gradient; by contrast, a negative slope hinders along-slope jet formation by enhancing the dual-energy cascade cycling, which alleviates the topographic suppression on eddies. In the presence of strong bottom drag, a positive slope elevates barotropic eddy energy, which further enhances the eddy-driven fluxes; by contrast, a negative slope confines turbulent energy to the baroclinic mode, which is strongly damped, causing further weakened turbulent energy and eddy fluxes. A flow regime captured by linear QG theories also emerges as the turbulent energy cascade is jointly suppressed by negative slopes and strong bottom drag. This study provides insights into parameterizing mesoscale eddy effects across sloping bathymetry in predictive ocean models.

A Unified Formulation of Quasi‐Geostrophic and Shallow Water Equations via Projection

AbstractThis paper introduces a unified model for layered rotating shallow‐water (RSW) and quasi‐geostrophic (QG) equations, based on the intrinsic relationship between these two sets of equations. We propose a novel formulation of the QG equations as a projection of the RSW equations. This formulation uses the same prognostic variables as RSW, namely velocity and layer thickness, thereby restoring the proximity of these two sets of equations. It provides direct access to the ageostrophic velocities embedded within the geostrophic velocities resolved by the QG equations. This approach facilitates the study of differences between QG and RSW using a consistent numerical discretization. We demonstrate the effectiveness of this formulation through examples including vortex shear instability, double‐gyre circulation, and a simplified North Atlantic configuration.

Advancing neural network-based data assimilation for large-scale spatiotemporal systems with sparse observations

Data assimilation (DA) is a powerful technique for improving the forecast accuracy of dynamic systems by optimally integrating model forecasts with observations. Traditional DA approaches, however, encounter significant challenges when applied to complex, large-scale, highly nonlinear systems with sparse and noisy observations. To overcome these challenges, this study presents a new Neural Network-based Data Assimilation (DANet) model, specifically employing a Convolutional Long Short-Term Memory architecture. By leveraging the strengths of neural networks, DANet establishes the relationship among model forecasts, observations, and ground truth, facilitating efficient DA in large-scale spatiotemporal forecasting with sparse observations. The effectiveness of the DANet model is demonstrated through an initial case study of wind-driven oceanic flow forecasting, as described by a Quasi-Geostrophic (QG) model. Compared to the traditional Ensemble Kalman Filter (EnKF), DANet exhibits superior performance in cases involving both structured and unstructured sparse observations. This is evidenced by reduced Root Mean Square Errors (RMSEs) and improved correlation coefficients (R) and Structural Similarity Index. Moreover, DANet is seamlessly integrated with the QG model to operationally forecast vorticity and stream function in the long term, further confirming the accuracy and reliability of the DANet model. DANet achieves operational forecasting 60 times faster than EnKF, underscoring its efficiency and potential in DA advancement.

Surface Quasi Geostrophic Reconstruction of Vertical Velocities and Vertical Heat Fluxes in the Southern Ocean: Perspectives for SWOT

AbstractMesoscale currents account for 80% of the ocean's kinetic energy, whereas submesoscale currents capture 50% of the vertical velocity variance. SWOT's first sea surface height (SSH) observations have a spatial resolution an order of magnitude greater than traditional nadir‐looking altimeters and capture mesoscale and submesoscale features. This enables the derivation of submesoscale vertical velocities, crucial for the vertical transport of heat, carbon and nutrients between the ocean interior and the surface. This work focuses on a mesoscale energetic region south of Tasmania using a coupled ocean‐atmosphere simulation at km‐scale resolution and preliminary SWOT SSH observations. Vertical velocities (w), temperature anomalies and vertical heat fluxes (VHF) from the surface down to 1,000 m are reconstructed using effective surface Quasi‐Geostrophic (sQG) theory. An independent method for reconstructing temperature anomalies, mimicking an operational gridded product, is also developed. Results show that sQG reconstructs 90% of the modeled w and VHF rms at scales down to 30 km just below the mixed layer and 50%–70% of the rms for scales larger than 70 km at greater depth, with a spatial correlation of 0.6. The reconstruction is spectrally coherent for scales larger than 30–40 km at the surface, slightly degrading ( 0.55) at depth. Two temperature anomaly data sets yield similar results, indicating the dominance of w on VHF. The RMS of sQG and VHF derived from SWOT are twice as large as those derived from conventional altimetry, highlighting the potential of SWOT for reconstructing energetic meso and submesoscale dynamics in the ocean interior.

Zeitlin Truncation of a Shallow Water Quasi‐Geostrophic Model for Planetary Flow

AbstractIn this work, we consider a Shallow‐Water Quasi Geostrophic equation on the sphere, as a model for global large‐scale atmospheric dynamics. This equation, previously studied by Verkley (2009, https://doi.org/10.1175/2008jas2837.1) and Schubert et al. (2009, https://doi.org/10.3894/james.2009.1.2), possesses a rich geometric structure, called Lie‐Poisson, and admits an infinite number of conserved quantities, called Casimirs. In this paper, we develop a Casimir preserving numerical method for long‐time simulations of this equation. The method develops in two steps: first, we construct an N‐dimensional Lie‐Poisson system that converges to the continuous one in the limit N → ∞; second, we integrate in time the finite‐dimensional system using an isospectral time integrator, developed by Modin and Viviani (2020, https://doi.org/10.1017/jfm.2019.944). We demonstrate the efficacy of this computational method by simulating a flow on the entire sphere for different values of the Lamb parameter. We particularly focus on rotation‐induced effects, such as the formation of jets. In agreement with shallow water models of the atmosphere, we observe the formation of robust latitudinal jets and a decrease in the zonal wind amplitude with latitude. Furthermore, spectra of the kinetic energy are computed as a point of reference for future studies.

Inferring Tracer Diffusivity From Coherent Mesoscale Eddies

AbstractMixing along isopycnals plays an important role in the transport and uptake of oceanic tracers. Isopycnal mixing is commonly quantified by a tracer diffusivity. Previous studies have estimated the tracer diffusivity using the rate of dispersion of surface drifters, subsurface floats, or numerical particles advected by satellite‐derived velocity fields. This study shows that the diffusivity can be more efficiently estimated from the dispersion of coherent mesoscale eddies. Coherent eddies are identified and tracked as the persistent sea surface height extrema in both a two‐layer quasigeostrophic (QG) model and an idealized primitive equation (PE) model. The Lagrangian diffusivity is estimated using the tracks of these coherent eddies and compared to the diagnosed Eulerian diffusivity. It is found that the meridional coherent eddy diffusivity approaches a stable value within about 20–40 days in both models. In the QG model, the coherent eddy diffusivity is a good approximation to the upper‐layer tracer diffusivity in a broad range of flow regimes, except for small values of bottom friction or planetary vorticity gradient, where the motions of same‐sign eddies are correlated over long distances. In the PE model, the tracer diffusivity has a complicated vertical structure and the coherent eddy diffusivity is correlated with the tracer diffusivity at the e‐folding depth of the energy‐containing eddies where the intrinsic speed of the coherent eddies matches the rms eddy velocity. These results suggest that the oceanic tracer diffusivity at depth can be estimated from the movements of coherent mesoscale eddies, which are routinely tracked from satellite observations.

MQGeometry-1.0: a multi-layer quasi-geostrophic solver on non-rectangular geometries

Abstract. This paper presents MQGeometry, a multi-layer quasi-geostrophic (QG) equation solver for non-rectangular geometries. We advect the potential vorticity (PV) with finite volumes to ensure global PV conservation using a staggered discretization of the PV and stream function (SF). Thanks to this staggering, the PV is defined inside the domain, removing the need to define the PV on the domain boundary. We compute PV fluxes with upwind-biased interpolations whose implicit dissipation replaces the usual explicit (hyper-)viscous dissipation. The discretization presented here does not require tuning of any additional parameter, e.g., additional eddy viscosity. We solve the QG elliptic equation with a fast discrete sine transform spectral solver on rectangular geometry. We extend this fast solver to non-rectangular geometries using the capacitance matrix method. Subsequently, we validate our solver on a vortex-shear instability test case in a circular domain, on a vortex–wall interaction test case, and on an idealized wind-driven double-gyre configuration in an octagonal domain at an eddy-permitting resolution. Finally, we release a concise, efficient, and auto-differentiable PyTorch implementation of our method to facilitate future developments on this new discretization, e.g., machine-learning parameterization or data-assimilation techniques.

2D Surface Quasi Geostrophic Equations and its Regularity, A Numerical Study

In this article, we present some results on the numerical solutions of the 2-D Surface Quasi Geostrophic Equation (SQG) using the pseudospectral method along with an exponential filter. The global regularity of the solution of the inviscid SQG equation for general data remains an outstanding open problem. Our computations mainly focus on the inviscid and supercritical cases. We monitored the regions where the level curves come significantly close to one another, the L2 norm, and the growth of |∇⊥θ| throughout our computations. Our numerical findings show that there is no significant difference among the solutions of the supercritical, critical, and subcritical cases as we vary the values of the parameter α in the interval (0, 1).

Three-dimensional quasi-geostrophic vortices with vanishing amount of potential vorticity anomaly

We provide exact solutions of axisymmetric neutral vortices, that is, vortices with zero amount of potential vorticity anomaly (PVA), in three-dimensional (3D) quasi-geostrophic (QG) flows with distributed vorticity and density stratification. These solutions are linear combinations of PVA spherical layer-modes, which consist of conveniently normalized spherical Bessel functions of order 0, truncated by a zero of the spherical Bessel function of order 1. It is shown that, depending on the superposition of the different spherical layer-modes, some vortices remain axisymmetrically robust to small amplitude PVA perturbations, while other vortices evolve to stable QG tripoles. The robust axisymmetric 3D QG vortices analyzed here do not generate exterior potential flow and may provide an explanation to the persistence of baroclinic eddies in the ocean.

Uniform sparse domination and quantitative weighted boundedness for singular integrals and application to the dissipative quasi-geostrophic equation

In this paper, we consider a kind of singular integralsTλf(x)= p.v. ∫RnΩ(y)|y|n−λf(x−y)dy for any f∈Lq(Rn),1<q<∞ and 0<λ<n, which appear in the generalized 2D dissipative quasi-geostrophic (QG) equation(0.1)∂tθ+u⋅∇θ+κΛ2βθ=0,(x,t)∈R2×R+,κ>0, where u=−∇⊥Λ−2+2αθ, α∈[0,12] and β∈(0,1]. Firstly, we give a uniform sparse domination for this kind of singular integral operators. Secondly, we obtain the uniform quantitative weighted bounds for the operator Tλ with rough kernel. As an application, we obtain the uniform quantitative weighted bounds for the commutator [b,Tλ] with rough kernel and study solutions to the generalized 2D dissipative quasi-geostrophic (QG) equation.

Mesoscale and Synoptic Scale Analysis of Narrow Cold Frontal Rainband During a Landfalling Atmospheric River in California During January 2021

AbstractNarrow cold‐frontal rain bands (NCFR) often produce short‐duration and high‐intensity precipitation that can lead to flooding and debris flow in California (CA). On 27 January 2021, an atmospheric river (AR) associated with an intense surface cyclone made landfall over coastal northern CA, which featured a prominent NCFR. This study uses high‐resolution West Weather Research and Forecasting simulations to accurately resolve the gap and core structure of the NCFR and provide reliable precipitation estimations, compensating for limitations of radar and satellite observations. This NCFR was supported by robust synoptic‐scale quasi‐geostrophic (QG) forcing for ascent and frontogenesis. It propagated southward from Cape Mendocino to Big Sur in 12 hr before stalling and rotating counter‐clockwise in central/southern CA due to upstream Rossby wave breaking and an amplifying upper‐tropospheric trough. With the lower to middle tropospheric flow backed considerably to the south‐southwest over the NCFR, the increase of the vertical wind shear caused the transition from parallel to trailing stratiform precipitation. The stall and pivot of the AR and NCFR led to intense rainfall with a 2‐day precipitation accumulation greater than 300 mm over central CA. In addition, under the potential instability and frontogenesis, a moist absolutely unstable layer between 850 and 700 hPa was captured at the leading edge of the NCFR, which indicated slantwise deep layer lifting and high precipitation efficiency. This study reveals synoptic‐scale and mesoscale drivers of rainfall outside orographic lifting and reaffirms the importance of high‐resolution numerical modeling for the prediction of extreme precipitation and related natural hazards.

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.

Seasonal and Geographical Variations in Fundamental Weather Patterns during Extreme Precipitation as Identified from Omega Equation Forcing

Abstract We investigate the large-scale weather patterns during extreme precipitation (PEx) events over the conterminous United States (CONUS) by applying a version of the quasigeostrophic (QG) omega equation. This work aims to develop a climatology of the weather patterns most related to PEx events during current climate. Extreme events are examined for each of seven regions defined by consistent annual cycles of precipitation and spanning the CONUS. For the CONUS we train several self-organizing maps (SOM) on a pressure–time series of vertical velocity from each of the advective forcing terms in the QG omega equation for each extreme event. The unsupervised learning of the SOM allows us to identify the most descriptive set of nine patterns in vertical velocity associated with precipitation extremes. This method finds multiple frontal- and cyclone-driven patterns while grouping primarily convective events into one pattern. Frontal events include a synoptic pattern consistent with West Coast atmospheric river events as well as pattern groups linked to developing and to mature (“occluded”) frontal cyclones. The primary patterns found during PEx events vary seasonally and geographically. Frontal cyclone patterns are most common during PEx events during summer in the part of the Great Plains and during winter for the Northeast, Southeast, Pacific Northwest, and Southwest. Convection is the most common pattern during summer in all regions. Except in the Southeast, the annual cycles of monthly number of PEx events and average precipitation match well, partially validating our choice of regions to aggregate PEx events.

Intermittency Scaling for Mixing and Dissipation in Rotating Stratified Turbulence at the Edge of Instability

Many issues pioneered by Jackson Herring deal with how nonlinear interactions shape atmospheric dynamics. In this context, we analyze new direct numerical simulations of rotating stratified flows with a large-scale forcing, which is either random or quasi-geostrophic (QG). Runs were performed at a moderate Reynolds number Re and up to 1646 turn-over times in one case. We found intermittent fluctuations of the vertical velocity w and temperature θ in a narrow domain of parameters as for decaying flows. Preliminary results indicate that parabolic relations between normalized third- and fourth-order moments of the buoyancy flux ∝wθ and of the energy dissipation emerge in this domain, including for passive and active scalars, with or without rotation. These are reminiscent of (but not identical to) previous findings for other variables and systems such as oceanic and atmospheric flows, climate re-analysis data, fusion plasmas, the Solar Wind, or galaxies. For QG forcing, sharp scaling transitions take place once the Ozmidov length scale ℓOz is resolved—ℓOz being the scale after which a turbulent Kolmogorov energy spectrum likely recovers at high Re.

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.

Scaling for Saturated Moist Quasigeostrophic Turbulence

Abstract Much of our conceptual understanding of midlatitude atmospheric motion comes from two-layer quasigeostrophic (QG) models. Traditionally, these QG models do not include moisture, which accounts for an estimated 30%–60% of the available energy of the atmosphere. The atmospheric moisture content is expected to increase under global warming, and therefore, a theory for how moisture modifies atmospheric dynamics is crucial. We use a two-layer moist QG model with convective adjustment as a basis for analyzing how latent heat release and large-scale moisture gradients impact the scalings of a midlatitude system at the synoptic scale. In this model, the degree of saturation can be tuned independently of other moist parameters by enforcing a high rate of evaporation from the surface. This allows for study of the effects of latent heat release at saturation, without the intrinsic nonlinearity of precipitation. At saturation, this system is equivalent to the dry QG model under a rescaling of both length and time. This predicts that the most unstable mode shifts to smaller scales, the growth rates increase, and the inverse cascade extends to larger scales. We verify these results numerically and use them to verify a framework for the complete energetics of a moist system. We examine the spectral features of the energy transfer terms. This analysis shows that precipitation generates energy at small scales, while dry dynamics drive a significant broadening to larger scales. Cascades of energy are still observed in all terms, albeit without a clearly defined inertial range. Significance Statement The effect of moist processes, especially the impact of latent heating associated with condensation, on the size and strength of midlatitude storms is not well understood. Such insight is particularly needed in the context of global warming, as we expect moisture to play a more important role in a warmer world. In this study, we provide intuition into how including condensation can result in midlatitude storms that grow faster and have features on both larger and smaller scales than their dry counterparts. We provide a framework for quantifying these changes and verify it for the special case where it is raining everywhere. These findings can be extended to the more realistic situation where it is only raining locally.