Search for: All records

Abstract An intermediate-complexity general circulation model is used to disentangle changes in the large-scale zonally asymmetric circulation in response to rising greenhouse gases. Particular focus is on the anomalous ridge that develops over the Mediterranean in future climate projections, directly associated with reduced winter precipitation over the region. Specifically, we examine changes in stationary waves forced by land–sea contrast, horizontal oceanic heat fluxes, and orography, following a quadrupling of CO₂. The stationary waves associated with these three drivers depend strongly on the climatological state, precluding a linear decomposition of their responses to warming. However, our modeling framework still allows a process-oriented approach to quantify the key drivers and mechanisms of the response. A combination of three similarly important mechanisms is found responsible for the rain-suppressing ridge. The first is part of a global response to warming: elongation of intermediate-scale stationary waves in response to strengthened subtropical winds aloft, previously found to account for hydroclimatic changes in southwestern North America. The second is regional: a downstream response to the North Atlantic warming hole and enhanced warming of the Eurasian landmass relative to the Atlantic Ocean. A third contribution to the Mediterranean Ridge is a phase shift of planetary wave 3, primarily associated with an altered circulation response to orographic forcing. Reduced land–sea contrast in the Mediterranean basin, previously thought to contribute substantially to Mediterranean drying, has a negligible effect in our integrations. This work offers a mechanistic analysis of the large-scale processes governing projected Mediterranean drying, lending increased understanding and credibility to climate model projections. 

Abstract. The number density of ozone, [O3], maximizes around 26 km in the tropics, protecting life from harmful ultraviolet (UV) light without poisoning it at the surface. Textbooks explain this interior maximum with two paradigms: (1) the source-controlled paradigm explains [O3] as maximizing where its source maximizes between abundant photons aloft and abundant [O2] below, and (2) the source / sink competition paradigm, inspired by the Chapman cycle, explains ozone as scaling with [O2] and the photolytic source / sink ratio. However, each paradigm's prediction for the altitude of peak [O3] is off by 10 km, reflecting their well-known omission of ozone sinks from catalytic cycles and transport. We present a minimal, steady-state theory for the tropical stratospheric [O3] maximum, accurate to within 1 km and formulated in terms of the dominant ozone sinks. These sinks are represented simply by augmenting the Chapman cycle with linear damping of O and O3, leading to the Chapman+2 model. The Chapman+2 model correctly simulates peak tropical [O3] at 26 km, yet this peak is not explained by either paradigm. Instead, the peak is newly explained by the transition from an O-damped regime aloft to an O3-damped regime below. An explicit analytical expression is derived for ozone under gray radiation. This theory accurately predicts an interior maximum of ozone and correctly predicts that an increase in top-of-atmosphere UV light will lead to a downward shift in the peak [O3] due to a downward shift in the regime transition, a result not even qualitatively predicted by the existing paradigms. 

Abstract In response to rising , chemistry‐climate models (CCMs) project that extratropical stratospheric ozone will increase, except around 10 and 17 km. We call the muted increases or reductions at these altitudes the “double dip.” The double dip results from surface warming (not stratospheric cooling). Using an idealized photochemical‐transport model, surface warming is found to produce the double dip via tropospheric expansion, which converts ozone‐rich stratospheric air into ozone‐poor tropospheric air. The lower dip results from expansion of the extratropical troposphere, as previously understood. The upper dip results from expansion of the tropical troposphere, low‐ozone anomalies from which are then transported into the extratropics. Large seasonality in the double dip in CCMs can be explained, at least in part, by seasonality in the stratospheric overturning circulation. The remote effects of the tropical tropopause on extratropical ozone complicate the use of (local) tropopause‐following coordinates to remove the effects of global warming. 

The ozone layer is often noted to exhibit self-healing, whereby depletion of ozone aloft induces ozone increases below, explained as resulting from enhanced ozone production due to the associated increase in ultraviolet (UV) radiation below. Similarly, ozone enhancement aloft can reduce ozone below (reverse self-healing). This paper considers self-healing and reverse self-healing to manifest a general mechanism we call photochemical adjustment, whereby ozone perturbations lead to a downward cascade of anomalies in UV and ozone. Conventional explanations for self-healing imply that photochemical adjustment is stabilizing, damping perturbations towards the surface. However, photochemical adjustment can be destabilizing if the enhanced UV disproportionately increases the ozone sink, as can occur if the enhanced UV photolyzes ozone to produce atomic oxygen, which speeds up catalytic destruction of ozone. We analyze photochemical adjustment in two linear ozone models (Cariolle v2.9 and LINOZ), finding that (1) photochemical adjustment is destabilizing above 40 km in the tropical stratosphere and (2) self-healing often represents only a small fraction of the total photochemical stabilization. The destabilizing regime above 40 km is reproduced in a much simpler model: the Chapman cycle augmented with destruction of O and O3 by generalized catalytic cycles and transport (the Chapman+2 model). The Chapman+2 model reveals that photochemical destabilization occurs where the ozone sink is more sensitive than the source to perturbations in overhead column ozone, which is found to occur when the window of overlapping absorption by O2 and O3 is optically unsaturated, i.e., when overhead slant column ozone is below approximately 10^18 molec. cm−2. 

Abstract Two key challenges in the development of data‐driven gravity‐wave parameterizations are generalization, how to ensure that a data‐driven scheme trained on the present‐day climate will continue to work in a new climate regime, and calibration, how to account for biases in the “host” climate model. Both problems depend fundamentally on the response to out‐of‐sample inputs compared with the training dataset, and are often conflicting. The ability to generalize to new climate regimes often goes hand in hand with sensitivity to model biases. To probe these challenges, we employ a one‐dimensional (1D) quasibiennial oscillation (QBO) model with a stochastic source term that represents convectively generated gravity waves in the Tropics with randomly varying strengths and spectra. We employ an array of machine‐learning models consisting of a fully connected feed‐forward neural network, a dilated convolutional neural network, an encoder–decoder, a boosted forest, and a support‐vector regression model. Our results demonstrate that data‐driven schemes trained on “observations” can be critically sensitive to model biases in the wave sources. While able to emulate accurately the stochastic source term on which they were trained, all of our schemes fail to simulate fully the expected QBO period or amplitude, even with the slightest perturbation to the wave sources. The main takeaway is that some measures will always be required to ensure the proper response to climate change and to account for model biases. We examine one approach based on the ideas of optimal transport, where the wave sources in the model are first remapped to the observed one before applying the data‐driven scheme. This approach is agnostic to the data‐driven method and guarantees that the model adheres to the observational constraints, making sure the model yields the right results for the right reasons. 

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. 

We extend the Matsuno–Gill model, originally developed on the equatorial$$\beta$$-plane, to the surface of the sphere. While on the$$\beta$$-plane the non-dimensional model contains a single parameter, the damping rate$$\gamma$$, on a sphere the model contains a second parameter, the rotation rate$$\epsilon ^{1/2}$$(Lamb number). By considering the different combinations of damping and rotation, we are able to characterize the solutions over the$$(\gamma, \epsilon ^{1/2})$$plane. We find that the$$\beta$$-plane approximation is accurate only for fast rotation rates, where gravity waves traverse a fraction of the sphere's diameter in one rotation period. The particular solutions studied by Matsuno and Gill are accurate only for fast rotation and moderate damping rates, where the relaxation time is comparable to the time on which gravity waves traverse the sphere's diameter. Other regions of the parameter space can be described by different approximations, including radiative relaxation, geostrophic, weak temperature gradient and non-rotating approximations. The effect of the additional parameter introduced by the sphere is to alter the eigenmodes of the free system. Thus, unlike the solutions obtained by Matsuno and Gill, where the long-term response to a symmetric forcing consists solely of Kelvin and Rossby waves, the response on the sphere includes other waves as well, depending on the combination of$$\gamma$$and$$\epsilon ^{1/2}$$. The particular solutions studied by Matsuno and Gill apply to Earth's oceans, while the more general$$\beta$$-plane solutions are only somewhat relevant to Earth's troposphere. In Earth's stratosphere, Venus and Titan, only the spherical solutions apply. 

Abstract Atmospheric regime transitions are highly impactful as drivers of extreme weather events, but pose two formidable modeling challenges: predicting the next event (weather forecasting) and characterizing the statistics of events of a given severity (the risk climatology). Each event has a different duration and spatial structure, making it hard to define an objective “average event.” We argue here that transition path theory (TPT), a stochastic process framework, is an appropriate tool for the task. We demonstrate TPT’s capacities on a wave–mean flow model of sudden stratospheric warmings (SSWs) developed by Holton and Mass, which is idealized enough for transparent TPT analysis but complex enough to demonstrate computational scalability. Whereas a recent article (Finkel et al. 2021) studied near-term SSW predictability, the present article uses TPT to link predictability to long-term SSW frequency. This requires not only forecasting forward in time from an initial condition, but also backward in time to assess the probability of the initial conditions themselves. TPT enables one to condition the dynamics on the regime transition occurring, and thus visualize its physical drivers with a vector field called the reactive current . The reactive current shows that before an SSW, dissipation and stochastic forcing drive a slow decay of vortex strength at lower altitudes. The response of upper-level winds is late and sudden, occurring only after the transition is almost complete from a probabilistic point of view. This case study demonstrates that TPT quantities, visualized in a space of physically meaningful variables, can help one understand the dynamics of regime transitions. 

Abstract An intermediate-complexity moist general circulation model is used to investigate the factors controlling the magnitude of the surface impact from Southern Hemisphere springtime ozone depletion. In contrast to previous idealized studies, a model with full radiation is used; furthermore, the model can be run with a varied representation of the surface, from a zonally uniform aquaplanet to a configuration with realistic stationary waves. The model captures the observed summertime positive Southern Annular Mode response to stratospheric ozone depletion. While synoptic waves dominate the long-term poleward jet shift, the initial response includes changes in planetary waves that simultaneously moderate the polar cap cooling (i.e., a negative feedback) and also constitute nearly one-half of the initial momentum flux response that shifts the jet poleward. The net effect is that stationary waves weaken the circulation response to ozone depletion in both the stratosphere and troposphere and also delay the response until summer rather than spring when ozone depletion peaks. It is also found that Antarctic surface cooling in response to ozone depletion helps to strengthen the poleward shift; however, shortwave surface effects of ozone are not critical. These surface temperature and stationary wave feedbacks are strong enough to overwhelm the previously recognized jet latitude/persistence feedback, potentially explaining why some recent comprehensive models do not exhibit a clear relationship between jet latitude/persistence and the magnitude of the response to ozone. The jet response is shown to be linear with respect to the magnitude of the imposed stratospheric perturbation, demonstrating the usefulness of interannual variability in ozone depletion for subseasonal forecasting.