The role of internal variability in seasonal hindcast trend errors
Journal of Climate American Meteorological Society (2025)
Abstract:
Abstract Initialised hindcasts inherit knowledge of the observed climate state, so studies of multidecadal trends in seasonal and decadal hindcast models have focused on the ensemble-mean when benchmarking against observed trends. However, this neglects the role of short-timescale variability in contributing to longer-term trends, and hence trend errors. Using a single-model coupled hindcast ensemble, we generate a distribution of 10,000 hindcast trends over 1981-2022 by randomly sampling a single ensemble member in each year. We find that the hindcast model supports a wide range of trends in various features of the large-scale climate, even when sampled at leads of just 1-3 months following initialisation. The spread in hindcast global surface temperature trends is equivalent to approximately a sixth of the total observed warming over the same period, driven by large seasonal variability of temperatures over land. The hindcasts also lend support for observed poleward jet shifts, but the magnitude of the shifts varies widely across the ensemble. Our results show that a fair comparison of hindcast trends to observations should consider the full range of model trends, not only the ensemble mean. More broadly, we argue that the hindcast trend distribution offers a largely untapped tool for studying multidecadal climate trends in a very large ensemble, through exploiting existing hindcast data.Data-Driven Stochastic Parameterization of MCS Latent Heating in the Grey Zone
Copernicus Publications (2025)
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.A geochemical view on the ubiquity of CO2 on rocky exoplanets with atmospheres
Copernicus Publications (2025)
Abstract:
To aid the search for atmospheres on rocky exoplanets, we should know what to look for. An unofficial paradigm is to anticipate CO2 present in these atmospheres, through analogy to the solar system and through theoretical modelling. This CO2 would be outgassed from molten silicate rock produced in the planet’s mostly-solid interior—an ongoing self-cooling mechanism that should proceed, in general, so long as the planet has sufficient internal heat to lose.Outgassing of CO2 requires relatively oxidising conditions. Previous work has noted the importance of how oxidising the planet interior is (the oxygen fugacity), which depends strongly on its rock composition. Current models presume that redox reactions between iron species control oxygen fugacity. However, iron alone need not be the sole dictator of how oxidising a planet is. Indeed, carbon itself is a powerful redox element, with great potential to feed back upon the mantle redox state as it melts. Whilst Earth is carbon-poor, even a slightly-higher volatile endowment could trigger carbon-powered geochemistry.We offer a new framework for how carbon is transported from solid planetary interior to atmosphere. The model incorporates realistic carbon geochemistry constrained by recent experiments on CO2 solubility in molten silicate, as well as redox couplings between carbon and iron that have never before been applied to exoplanets. We also incorporate a coupled 1D energy- and mass-balance model to provide first-order predictions of the rate of volcanism.We show that carbon-iron redox coupling maintains interior oxygen fugacity in a narrow range: more reducing than Earth magma, but not reducing enough to destabilise CO2 gas. We predict that most secondary atmospheres, if present, should contain CO2, although the total pressure could be low. An atmospheric non-detection may indicate a planet either born astonishingly dry, or having shut off its internal heat engine.Photochemistry versus Escape in the Trappist-1 planets.
(2025)
Abstract:
Super-Earth lava planet from birth to observation: photochemistry, tidal heating, and volatile-rich formation
Copernicus Publications (2025)