Climate dynamics

Abstract:

Survive or not survive, that is the question of the 500-hour JWST Rocky Worlds DDT Program. Whether a terrestrial planets’ atmosphere can suffer under the intense XUV of its host, or if it completely escapes, these are the questions we explore. Zahnle & Catling (2017) defined the Cosmic Shoreline, but recent observations from JWST reveal airless worlds around M-stars, calling for a refinement of this “receding” shoreline (Pass et al. 2025). M-stars spend a longer time in pre-main sequence, subjecting their orbiting worlds to some higher intensity XUV activity. This complicates our present understanding of this shoreline. Investigating chemical effects of planet-star interactions could be the key to a more complete picture of this shoreline.  We investigate the interplay between photochemistry, mixing, and escape of carbon dioxide atmospheres under intense and mild XUV fluxes as follow on work to both Johnstone et al. (2018) and Nakayama et al. (2022). We expand on this work by adopting thermal structure models from Nakayama et al. (2022) and apply them to identify key chemical pathways for escape. We create a reduced C-O chemical network including neutral and ionic species to identify these pathways. As photochemistry simulations take into account many reactions, these 1D calculations are too computationally expensive to be done in 3D. Although rudimentary at best, the mixing parameter– eddy diffusion term, K_zz, comprises the dynamical element of 1D photochemical simulations. Here, we consider the mixing of photochemical products in competition with escape to explore the chemical pathways of retention and loss. We compare the photochemical model results for active and inactive cases for the Trappist-1 system planets. Then, using the resulting composition-dependent heating and cooling rates for Trappist-1 planets, we assess their propensity for efficient atomic line cooling versus escape. We follow the work of Chatterjee & Pierrehumbert (2024) in this assessment.  Finally, using our pathway analysis, we find an analytical formula for calculating an energy-limited escape boundary for these planets based on composition.  It is important here to note the limitations of 1D work. First, there exists an exchange of rigor between modelling chemistry and dynamics. Insights from this work are ripe for implementation into 3D GCMs, especially in response to incorporating UV-driven processes for thermospheric modelling mentioned in Ding and Wordsworth (2019). Second, interaction with the interior is important in the early phase of planetary formation, i.e., the magma ocean phase. Due to exchange between atmosphere and magma early in the planet’s formation, incorporation with an interior-atmosphere model would better constrain higher pressure chemical abundances. Although this work focuses on the upper atmosphere, extrapolation to the surface environment is a key goal for understanding a planet.  Considering planet-star interaction is imperative for the selection of targets for observation. However, it is also important when considering anomalous detections of atmospheres around planets predicted to not have an atmosphere. This could be a first step in determining an atmosphere as non-primary and/or distinguishing between an airless planet and one with high altitude haze. 

Abstract:

Larger-than-Earth exoplanets are sculpted by strong stellar irradiation, but it is unknown whence they originate. Two propositions are that they formed with rocky interiors and hydrogen-rich envelopes (‘gas-dwarfs’), or with bulk compositions rich in water-ices (‘water-worlds’) . Multiple observations of super-Earth L 98-59 d have revealed its low bulk-density, consistent with substantial volatile content alongside a rocky/metallic interior, and recent JWST spectroscopy evidences a high mean molecular weight atmosphere. Its density and composition make it a waymarker for disentangling the processes which separate super-Earths and sub-Neptunes across geological timescales. We simulate the possible pathways for L 98-59 d from birth up to the present day using a comprehensive evolutionary modelling framework. Emerging from our calculations is a novel self-limiting mechanism between radiative cooling, tidal heating, and mantle rheology, which we term the 'radiation-tide-rheology feedback'. Coupled numerical modelling yields self-limiting tidal heating estimates that are up to two orders of magnitude lower than previous calculations, and yet are still large enough to enable the extension of primordial magma oceans to Gyr timescales. Our analysis indicates that the planet formed with a large amount (>1.8 mass%) of sulfur and hydrogen, and a chemically-reducing mantle; inconsistent with both the canonical gas-dwarf and water-world scenarios. A thick atmosphere and tidal heating sustain a permanent deep magma ocean, allowing the dissolution and retention of volatiles within its mantle. Transmission features can be explained by in-situ photochemical production of SO2 in a high-molecular weight H2-H2S background. These results subvert the emerging gas-dwarf vs. water-world dichotomy of small planet categorisation, inviting a more nuanced classification framework. We show that interactions between planetary interiors and atmospheres shape their observable characteristics over billions of years.

Abstract:

Mesoscale Convective Systems (MCSs), with length scales of 100 to 1000 km or more, fall into the "grey zone" of global models with grid spacings of 10s of km. Their under-resolved nature leads to model deficiencies in representing MCS latent heating, whose vertical structure critically shapes large-scale circulations. To address this challenge, we use analysis increments—the corrections applied by Data Assimilation (DA) to the model's prior state—from a 10 km Met Office operational forecast model to inform the development of a stochastic parameterization for MCS latent heating. To focus on errors in MCS feedback rather than errors due to a missing MCS, we select analysis increments from 1037 MCS tracks that the model successfully captures at the start of the DA cycle.A Machine Learning–based Gaussian Mixture Model reveals that the vertical structure of temperature analysis increments is probabilistically linked to the atmospheric environment. Bottom-heavy heating increments tend to occur in low Total Column Water Vapor (TCWV) conditions, suggesting that the model underestimates low-level convective heating in relatively dry environments. In contrast, top-heavy heating increments are linked to a moist layer overturning structure—characterized by high TCWV and strong vertical wind shear—indicating model underestimation of upper-level condensate detrainment in such environments. This probabilistic relationship is implemented in the Met Office operational forecast model as part of the MCS: PRIME stochastic scheme, which corrects MCS-related uncertainties during model integration. By enhancing top-heavy heating, the scheme backscatters kinetic energy from the mesoscale to larger scales, improving predictions of Indian seasonal rainfall and the Madden–Julian Oscillation (MJO). Future work will assess its impact on forecast busts and its potential to extend predictability.

Abstract:

Many Mediterranean‐type climates (MCs) have experienced wintertime drying trends since 1979. Using a dynamical adjustment method, we separate the effects of circulation‐induced drying trends from other residual trends. Our analysis reveals that circulation trends are the leading cause of the observed drying in Central Chile and the US Southwest, and that models show the drying across Southern Hemisphere MCs is independent of trends in the Southern Annular Mode. All Mediterranean‐type climates have exhibited residual drying trends from both internal variability and externally forced thermodynamic processes. Large ensembles suggest internal variability contributes significantly to the observed drying. However, in many regions the observed drying lies outside the ensemble distribution, raising questions about model accuracy.

Abstract:

<jats:title>Abstract</jats:title> <jats:p>The winter North Atlantic Oscillation (NAO) is the dominant pattern of atmospheric circulation variability over the North Atlantic region. It influences climate and weather such as surface air temperatures (SAT) downstream over Eurasia through establishing a large-scale teleconnection, but past studies on the NAO’s downstream teleconnection have been largely limited to observational data, and further evidence of downstream impacts and associated mechanisms from comprehensive climate modelling is desirable. This study quantifies and analyzes this teleconnection on an interannual timescale by using both ERA5 reanalysis, and five large ensembles from four climate simulation models. A particular focus is placed on dynamical pathways, as well as variability among ensemble members that modulates the teleconnection strength. Results suggest that NAO signals are propagated downstream by Rossby waves, efficiently transmitted through waveguides along both the polar and subtropical jet streams to Eastern Eurasia; while heat can be advected weakly from upstream, advection plays a rather local effect inducing temperature anomalies from the Pacific Ocean onshore. Multiple linear regression shows that internal climate variability significantly modulates the teleconnection: a more locally dominant NAO pattern, and narrower waveguides could strengthen the teleconnection. These two factors combine to explain up to 70% of variance in the teleconnection strength, with each contributing almost equally. Reanalysis data marginally agree with the regression model (1.9 standardized residuals higher in strength), suggesting potential model biases in jets and the NAO variability. Monitoring these modulating factors would be crucial to understanding downstream climate predictability and improving climate prediction models linked to the NAO.</jats:p>