Climate Model Of Intermediate Complexity Research Articles

Converged ensemble simulations of climate: possible trends in total solar irradiance cannot explain global warming alone

We address the hypothetical question of whether an increasing total solar irradiance (TSI) trend, without anthropogenic contributions, could be sufficient to explain the ongoing global warming. To this end, the intermediate-complexity climate model PlaSim is used. To consider the total internal variability, we present a set of ensemble simulations, with different forcing histories in TSI and CO2 concentration, that have converged sufficiently tightly to the relevant probability distributions to provide a satisfactory bound on any spurious trend possibly arising from a sampling bias; similar bounds on any other unforced contributions to ensemble mean trends are also estimated. A key point is the consideration, among the forcing histories, the steepest increasing trend in TSI that is still consistent with observations according to a recent study; thereby, we essentially revisit corresponding TSI reconstructions, more than 20 years after their last modeling-based evaluation, by improving the analysis through taking care of all possible sources of error or uncertainty and incorporating data that have become available since then. Without any change in CO2 concentration, our TSI trend (i.e., and upper bound on actual TSI trends) is found to be insufficient to produce outcomes compatible with the observational record in global mean surface temperature (GMST) with a nonnegligible probability. We formalize our statement for quantifiers of GMST trends through evaluating their distributions over the ensemble, and we speculate that the hypothesis about the exclusive role of an increasing TSI remains implausible even beyond our particular model setup. At the same time, if we consider a constant TSI, and the observational record in CO2 concentration is applied as forcing, the simulation results and the recorded GMST match well. While we currently need to leave the question of a precise attribution open, we conclude by pointing out that an attribution of the ongoing global warming to an increasing TSI alone could be made plausible only if a bias in the set of land-based instrumental temperature measurements were increasing more rapidly than commonly estimated; an assessment of the latter possibility is out of the scope of our study, as well as addressing solar forcing mechanisms beyond the effect of TSI.

Modelling water isotopologues (1H2H16O, 1H217O) in the coupled numerical climate model iLOVECLIM (version 1.1.5)

Abstract. Stable water isotopes are used to infer changes in the hydrological cycle for different climate periods and various climatic archives. Following previous developments of δ18O in the coupled climate model of intermediate complexity, iLOVECLIM, we present here the implementation of the 1H2H16O and 1H217O water isotopes in the different components of this model and calculate the associated secondary markers deuterium excess (d-excess) and oxygen-17 excess (17O-excess) in the atmosphere and ocean. So far, the latter has only been modelled by the atmospheric model LMDZ4. Results of a 5000-year equilibrium simulation under preindustrial conditions are analysed and compared to observations and several isotope-enabled models for the atmosphere and ocean components. In the atmospheric component, the model correctly reproduces the first-order global distribution of the δ2H and d-excess as observed in the data (R=0.56 for δ2H and 0.36 for d-excess), even if local differences are observed. The model–data correlation is within the range of other water-isotope-enabled general circulation models. The main isotopic effects and the latitudinal gradient are properly modelled, similarly to previous water-isotope-enabled general circulation model simulations, despite a simplified atmospheric component in iLOVECLIM. One exception is observed in Antarctica where the model does not correctly estimate the water isotope composition, a consequence of the non-conservative behaviour of the advection scheme at a very low moisture content. The modelled 17O-excess presents a too-important dispersion of the values in comparison to the observations and is not correctly reproduced in the model, mainly because of the complex processes involved in the 17O-excess isotopic value. For the ocean, the model simulates an adequate isotopic ratio in comparison to the observations, except for local areas such as the surface of the Arabian Sea, a part of the Arctic and the western equatorial Indian Ocean. Data–model evaluation also presents a good match for the δ2H over the entire water column in the Atlantic Ocean, reflecting the influence of the different water masses.

Multi-decadal pacemaker simulations with an intermediate-complexity climate model

Abstract. In this paper, we first describe the main features of a new version of the International Centre for Theoretical Physics global atmospheric model (SPEEDY) with improved simulation of surface fluxes and the formulation of a three-layer thermodynamic ocean model (TOM3) suitable to explore the coupled extratropical response to tropical ocean variability. Then, we present results on the atmospheric model climatology, highlighting the impact of the modifications introduced in the model code, and show how important features of interdecadal and interannual variability are simulated in a “pacemaker” coupled ensemble of 70-year runs, where portions of the tropical Indo-Pacific are constrained to follow the observed variability. Despite the very basic representation of variations in greenhouse forcing and heat transport to the deep ocean (below the 300 m domain of the TOM3 model), the coupled ensemble reproduces the variations in surface temperature over land and sea with very good accuracy, confirming the role of the Indo-Pacific as a “pacemaker” for the natural fluctuations of global-mean surface temperatures found in earlier studies. Atmospheric zonal-mean temperature trends over 50 years are also realistically simulated in the extratropical lower troposphere and up to 100 hPa in the tropics. On the interannual scale, sea-surface temperature (SST) variability in sub-tropical and tropical regions not affected by SST relaxation is underestimated (mostly because of the absence of dynamically induced variability), while extratropical SST variability during the cold seasons is comparable to that observed. Atmospheric teleconnection patterns and their connections with SST are reproduced with high fidelity, although with local differences in the amplitude of regional features (such as a larger-than-observed response of extratropical SST to North Atlantic Oscillation variability). The SPEEDY-TOM3 model also reproduces the observed connection between averages of surface heat fluxes over the oceans and land surface air temperature in the wintertime northern extratropics. Overall, as in earlier versions of SPEEDY, the fidelity of the simulations (both in terms of climatological means and variability) is higher near the surface and in the lower troposphere, while the negative impacts of the coarse vertical resolution and simplified parameterizations are mostly felt in the stratosphere. However, the improved simulation of surface heat fluxes and their impact on extratropical SST variability in this model version (obtained at a very modest computational cost) make the SPEEDY-TOM3 model a suitable tool to investigate the coupled response of the extratropical circulation to interannual and inter-decadal changes of tropical SST in ensemble experiments.

SPEEDY-NEMO: performance and applications of a fully-coupled intermediate-complexity climate model

A fully-coupled general circulation model of intermediate complexity is documented. The study presents an overview of the model climatology and variability, with particular attention to the phenomenology of processes that are relevant for the predictability of the climate system on seasonal-to-decadal time-scales. It is shown that the model can realistically simulate the general circulation of the atmosphere and the ocean, as well as the major modes of climate variability on the examined time-scales: e.g. El Niño-Southern Oscillation, North Atlantic Oscillation, Tropical Atlantic Variability, Pacific Decadal Variability, Atlantic Multi-decadal Variability. Potential applications of the model are discussed, with emphasis on the possibility of generating sets of low-cost large-ensemble retrospective forecasts. We argue that the presented model is suitable to be employed in traditional and innovative model experiments that can play a significant role in future developments of seasonal-to-decadal climate prediction.

Simulating AMOC tipping driven by internal climate variability with a rare event algorithm

This study investigates the possibility of Atlantic Meridional Overturning Circulation (AMOC) noise-induced tipping solely driven by internal climate variability without applying external forcing that alter the radiative forcing or the North Atlantic freshwater budget. We address this hypothesis by applying a rare event algorithm to ensemble simulations of present-day climate with an intermediate complexity climate model. The algorithm successfully identifies trajectories leading to abrupt AMOC slowdowns, which are unprecedented in a 2000-year control run. Part of these AMOC weakened states lead to collapsed state without evidence of AMOC recovery on multi-centennial time scales. The temperature and Northern Hemisphere jet stream responses to these internally-induced AMOC slowdowns show strong similarities with those found in externally forced AMOC slowdowns in state-of-the-art climate models. The AMOC slowdown seems to be initially driven by Ekman transport due to westerly wind stress anomalies in the North Atlantic and subsequently sustained by a complete collapse of the oceanic convection in the Labrador Sea. These results demonstrate that transitions to a collapsed AMOC state purely due to internal variability in a model simulation of present-day climate are rare but theoretically possible. Additionally, these results show that rare event algorithms are a tool of valuable and general interest to study tipping points since they introduce the possibility of collecting a large number of tipping events that cannot be sampled using traditional approaches. This opens the possibility of identifying the mechanisms driving tipping events in complex systems in which little a-priori knowledge is available.

Extreme heat wave sampling and prediction with analog Markov chain and comparisons with deep learning

Abstract We present a data-driven emulator, a stochastic weather generator (SWG), suitable for estimating probabilities of prolonged heat waves in France and Scandinavia. This emulator is based on the method of analogs of circulation to which we add temperature and soil moisture as predictor fields. We train the emulator on an intermediate complexity climate model run and show that it is capable of predicting conditional probabilities (forecasting) of heat waves out of sample. Special attention is payed that this prediction is evaluated using a proper score appropriate for rare events. To accelerate the computation of analogs, dimensionality reduction techniques are applied and the performance is evaluated. The probabilistic prediction achieved with SWG is compared with the one achieved with a convolutional neural network (CNN). With the availability of hundreds of years of training data, CNNs perform better at the task of probabilistic prediction. In addition, we show that the SWG emulator trained on 80 years of data is capable of estimating extreme return times of order of thousands of years for heat waves longer than several days more precisely than the fit based on generalized extreme value distribution. Finally, the quality of its synthetic extreme teleconnection patterns obtained with SWG is studied. We showcase two examples of such synthetic teleconnection patterns for heat waves in France and Scandinavia that compare favorably to the very long climate model control run.

A Multicloud Model for Coastal Convection

Coastal convection is often organized into multiple mesoscale systems that propagate in either direction across the coastline (i.e., landward and oceanward). These systems interact non-trivially with synoptic and intraseasonal disturbances such as convectively coupled waves and the Madden–Julian oscillation. Despite numerous theoretical and observational efforts to understand coastal convection, global climate models still fail to represent it adequately, mainly because of limitations in spatial resolution and shortcomings in the underlying cumulus parameterization schemes. Here, we use a simplified climate model of intermediate complexity to simulate coastal convection under the influence of the diurnal cycle of solar heating. Convection is parameterized via a stochastic multicloud model (SMCM), which mimics the subgrid dynamics of organized convection due to interactions (through the environment) between the cloud types that characterize organized tropical convection. Numerical results demonstrate that the model is able to capture the key modes of coastal convection variability, such as the diurnal cycle of convection and the accompanying sea and land breeze reversals, the slowly propagating mesoscale convective systems that move from land to ocean and vice-versa, and numerous moisture-coupled gravity wave modes. The physical features of the simulated modes, such as their propagation speeds, the timing of rainfall peaks, the penetration of the sea and land breezes, and how they are affected by the latitudinal variation in the Coriolis force, are generally consistent with existing theoretical and observational studies.

Modelling the effect of aerosol and greenhouse gas forcing on the South Asian and East Asian monsoons with an intermediate-complexity climate model

Abstract. The South Asian and East Asian summer monsoons are globally significant meteorological features, creating a strongly seasonal pattern of precipitation, with the majority of the annual precipitation falling between June and September. The stability the monsoons is of extreme importance for a vast range of ecosystems and for the livelihoods of a large share of the world's population. Simulations are performed with an intermediate-complexity climate model in order to assess the future response of the South Asian and East Asian monsoons to changing concentrations of aerosols and greenhouse gases. The radiative forcing associated with absorbing aerosol loading consists of a mid-tropospheric warming and a compensating surface cooling, which is applied to India, Southeast Asia, and eastern China both concurrently and independently. The primary effect of increased absorbing aerosol loading is a decrease in summer precipitation in the vicinity of the applied forcing, although the regional responses vary significantly. The decrease in precipitation is not ascribable to a decrease in the precipitable water and instead derives from a reduction in the precipitation efficiency due to changes in the stratification of the atmosphere. When the absorbing aerosol loading is added in all regions simultaneously, precipitation in eastern China is most strongly affected, with a quite distinct transition to a low precipitation regime as the radiative forcing increases beyond 60 W m−2. The response is less abrupt as we move westward, with precipitation in southern India being least affected. By applying the absorbing aerosol loading to each region individually, we are able to explain the mechanism behind the lower sensitivity observed in India and attribute it to remote absorbing aerosol forcing applied over eastern China. Additionally, we note that the effect on precipitation is approximately linear with the forcing. The impact of doubling carbon dioxide levels is to increase precipitation over the region while simultaneously weakening the circulation. When the carbon dioxide and absorbing aerosol forcings are applied at the same time, the carbon dioxide forcing partially offsets the surface cooling and reduction in precipitation associated with the absorbing aerosol response. Assessing the relative contributions of greenhouse gases and aerosols is important for future climate scenarios, as changes in the concentrations of these species has the potential to impact monsoonal precipitation.

Tracing the Snowball bifurcation of aquaplanets through time reveals a fundamental shift in critical-state dynamics

Abstract. The instability with respect to global glaciation is a fundamental property of the climate system caused by the positive ice-albedo feedback. The atmospheric concentration of carbon dioxide (CO2) at which this Snowball bifurcation occurs changes through Earth's history, most notably because of the slowly increasing solar luminosity. Quantifying this critical CO2 concentration is not only interesting from a climate dynamics perspective but also constitutes an important prerequisite for understanding past Snowball Earth episodes, as well as the conditions for habitability on Earth and other planets. Earlier studies are limited to investigations with very simple climate models for Earth's entire history or studies of individual time slices carried out with a variety of more complex models and for different boundary conditions, making comparisons and the identification of secular changes difficult. Here, we use a coupled climate model of intermediate complexity to trace the Snowball bifurcation of an aquaplanet through Earth's history in one consistent model framework. We find that the critical CO2 concentration decreased more or less logarithmically with increasing solar luminosity until about 1 billion years ago but dropped faster in more recent times. Furthermore, there was a fundamental shift in the dynamics of the critical state about 1.2 billion years ago (unrelated to the downturn in critical CO2 values), driven by the interplay of wind-driven sea-ice dynamics and the surface energy balance: for critical states at low solar luminosities, the ice line lies in the Ferrel cell, stabilised by the poleward winds despite moderate meridional temperature gradients under strong greenhouse warming. For critical states at high solar luminosities, on the other hand, the ice line rests at the Hadley cell boundary, stabilised against the equatorward winds by steep meridional temperature gradients resulting from the increased solar energy input at lower latitudes and stronger Ekman transport in the ocean.

Rare Event Simulation of Extreme European Winter Rainfall in an Intermediate Complexity Climate Model

AbstractWe test the application of a rare event simulation (RES) algorithm to accelerate the sampling of extreme winter rainfall over Europe in a climate model. The genealogical particle analysis algorithm, an ensemble method that interrupts the simulation at intermediate times to clone realizations in which an extreme event is developing, is applied to the intermediate complexity general circulation model PlaSim. We show that the algorithm strongly reduces the numerical effort required to estimate probabilities of extremes, demonstrating the potential of RES of seasonal precipitation extremes.

Milankovitch-paced erosion in the southern Central Andes

It has long been hypothesized that climate can modify both the pattern and magnitude of erosion in mountainous landscapes, thereby controlling morphology, rates of deformation, and potentially modulating global carbon and nutrient cycles through weathering feedbacks. Although conceptually appealing, geologic evidence for a direct climatic control on erosion has remained ambiguous owing to a lack of high-resolution, long-term terrestrial records and suitable field sites. Here we provide direct terrestrial field evidence for long-term synchrony between erosion rates and Milankovitch-driven, 400-kyr eccentricity cycles using a Plio-Pleistocene cosmogenic radionuclide paleo-erosion rate record from the southern Central Andes. The observed climate-erosion coupling across multiple orbital cycles, when combined with results from the intermediate complexity climate model CLIMBER-2, are consistent with the hypothesis that relatively modest fluctuations in precipitation can cause synchronous and nonlinear responses in erosion rates as landscapes adjust to ever-evolving hydrologic boundary conditions imposed by oscillating climate regimes.

High-latitude precipitation as a driver of multicentennial variability of the AMOC in a climate model of intermediate complexity

Centennial-scale variability of the Atlantic Meridional Overturning Circulation (AMOC) in the absence of external forcing has been identified in several climate models, but proposed mechanisms differ considerably. Therefore, better understanding of processes governing AMOC variability at these timescales is needed. Here, we analyze numerical simulations with PlaSim-LSG, an Earth System Model Intermediate Complexity (EMIC), which exhibits strong multicentennial oscillations of AMOC strength under constant pre-industrial boundary conditions. We identify a novel mechanism in which these oscillations are driven by salinity anomalies from the Arctic Ocean, which can be attributed to changes in high-latitude precipitation. We further corroborate our findings by conducting a set of millennial-length sensitivity experiments, and we interpret the mechanism by formulating a three-box model which qualitatively reproduces regular oscillations of the AMOC. While PlaSim-LSG lacks complexity compared to state-of-the-art models, our results reveal that precipitation minus evaporation (P–E) change in the Arctic is a physically plausible driver of centennial-scale AMOC variability. We discuss how this mechanism might be most relevant in climate states warmer than the present-day, raising questions about the state-dependence of multicentennial AMOC variability.

Calibration and Uncertainty Quantification of a Gravity Wave Parameterization: A Case Study of the Quasi‐Biennial Oscillation in an Intermediate Complexity Climate Model

AbstractThe drag due to breaking atmospheric gravity waves plays a leading order role in driving the middle atmosphere circulation, but as their horizontal wavelength range from tens to thousands of kilometers, part of their spectrum must be parameterized in climate models. Gravity wave parameterizations prescribe a source spectrum of waves in the lower atmosphere and allow these to propagate upwards until they either dissipate or break, where they deposit drag on the large‐scale flow. These parameterizations are a source of uncertainty in climate modeling which is generally not quantified. Here, we explore the uncertainty associated with a non‐orographic gravity wave parameterization given an assumed parameterization structure within a global climate model of intermediate complexity, using the Calibrate, Emulate and Sample (CES) method. We first calibrate the uncertain parameters that define the gravity wave source spectrum in the tropics, to obtain climate model settings that are consistent with properties of the primary mode of tropical stratospheric variability, the Quasi‐Biennial Oscillation (QBO). Then we use a Gaussian process emulator to sample the calibrated distribution of parameters and quantify the uncertainty of these parameter choices. We find that the resulting parametric uncertainties on the QBO period and amplitude are of a similar magnitude to the internal variability under a 2xCO2 forcing.

Thawing Permafrost as a Nitrogen Fertiliser: Implications for Climate Feedbacks

Studies for the northern high latitudes suggest that, in the near term, increased vegetation uptake may offset permafrost carbon losses, but over longer time periods, permafrost carbon decomposition causes a net loss of carbon. Here, we assess the impact of a coupled carbon and nitrogen cycle on the simulations of these carbon fluxes. We present results from JULES-IMOGEN—a global land surface model coupled to an intermediate complexity climate model with vertically resolved soil biogeochemistry. We quantify the impact of nitrogen fertilisation from thawing permafrost on the carbon cycle and compare it with the loss of permafrost carbon. Projections show that the additional fertilisation reduces the high latitude vegetation nitrogen limitation and causes an overall increase in vegetation carbon uptake. This is a few Petagrams of carbon (Pg C) by year 2100, increasing to up to 40 Pg C by year 2300 for the RCP8.5 concentration scenario and adds around 50% to the projected overall increase in vegetation carbon in that region. This nitrogen fertilisation results in a negative (stabilising) feedback on the global mean temperature, which could be equivalent in magnitude to the positive (destabilising) temperature feedback from the loss of permafrost carbon. This balance depends on the future scenario and initial permafrost carbon. JULES-IMOGEN describes one representation of the changes in Arctic carbon and nitrogen cycling in response to climate change. However there are uncertainties in the modelling framework, model parameterisation and missing processes which, when assessed, will provide a more complete picture of the balance between stabilising and destabilising feedbacks.

Earth system model parameter adjustment using a Green's functions approach

Abstract. We demonstrate the practicality and effectiveness of using a Green's functions estimation approach for adjusting uncertain parameters in an Earth system model (ESM). This estimation approach has previously been applied to an intermediate-complexity climate model and to individual ESM components, e.g., ocean, sea ice, or carbon cycle components. Here, the Green's functions approach is applied to a state-of-the-art ESM that comprises a global atmosphere/land configuration of the Goddard Earth Observing System (GEOS) coupled to an ocean and sea ice configuration of the Massachusetts Institute of Technology general circulation model (MITgcm). Horizontal grid spacing is approximately 110 km for GEOS and 37–110 km for MITgcm. In addition to the reference GEOS-MITgcm simulation, we carried out a series of model sensitivity experiments, in which 20 uncertain parameters are perturbed. These “control” parameters can be used to adjust sea ice, microphysics, turbulence, radiation, and surface schemes in the coupled simulation. We defined eight observational targets: sea ice fraction, net surface shortwave radiation, downward longwave radiation, near-surface temperature, sea surface temperature, sea surface salinity, and ocean temperature and salinity at 300 m. We applied the Green's functions approach to optimize the values of the 20 control parameters so as to minimize a weighted least-squares distance between the model and the eight observational targets. The new experiment with the optimized parameters resulted in a total cost reduction of 9 % relative to a simulation that had already been adjusted using other methods. The optimized experiment attained a balanced cost reduction over most of the observational targets. We also report on results from a set of sensitivity experiments that are not used in the final optimized simulation but helped explore options and guided the optimization process. These experiments include an assessment of sensitivity to the number of control parameters and to the selection of observational targets and weights in the cost function. Based on these sensitivity experiments, we selected a specific definition for the cost function. The sensitivity experiments also revealed a decreasing overall cost as the number of control variables was increased. In summary, we recommend using the Green's functions estimation approach as an additional fine-tuning step in the model development process. The method is not a replacement for modelers' experience in choosing and adjusting sensitive model parameters. Instead, it is an additional practical and effective tool for carrying out final adjustments of uncertain ESM parameters.

The longtime global climatic consequences modeling of the Chicxulub asteroid impact event

Studies indicate the mass death of a significant number of biological groups on Earth, in particular - dinosaurs, at the end of the Cretaceous period 66 million years ago. Currently, there are two main theories: large-scale volcanic eruptions and the asteroid impact that formed the Chicxulub crater (Mexico). The production of sulfur-containing gases from the Earth’s surface layers vapors during impact is considered a main source of climatic effects, as they form stratospheric sulfate aerosols that block sunlight and thus cool the Earth’s atmosphere and interfere with photosynthesis. It is presented an application of the 3-D coupled global hydrodynamic climate model of intermediate complexity, including ocean model, sea ice evolution model and energy - moisture balance atmosphere model to study this asteroid impact effects on the Earth’s climate. The model continents and ocean depths distribution corresponds to Cretaceous period. A series of calculations with different residence times and deposition times of the stratosphere aerosol have been carried out. It was found that, depending on the stratosphere aerosol time parameters, the global annual average surface air temperature decreased by 18°C - 27°C, remained below zero for 4 - 30 years, and a recovery time of more than 30 years was observed.

The Drake Passage opening from an experimental fluid dynamics point of view

Pronounced global cooling around the Eocene–Oligocene transition (EOT) was a pivotal event in Earth’s climate history, controversially associated with the opening of the Drake Passage. Using a physical laboratory model we revisit the fluid dynamics of this marked reorganization of ocean circulation. Here we show, seemingly contradicting paleoclimate records, that in our experiments opening the pathway yields higher values of mean water surface temperature than the “closed” configuration. This mismatch points to the importance of the role ice albedo feedback plays in the investigated EOT-like transition, a component that is not captured in the laboratory model. Our conclusion is supported by numerical simulations performed in a global climate model (GCM) of intermediate complexity, where both “closed” and “open” configurations were explored, with and without active sea ice dynamics. The GCM results indicate that sea surface temperatures would change in the opposite direction following an opening event in the two sea ice dynamics settings, and the results are therefore consistent both with the laboratory experiment (slight warming after opening) and the paleoclimatic data (pronounced cooling after opening). It follows that in the hypothetical case of an initially ice-free Antarctica the continent could have become even warmer after the opening, a scenario not indicated by paleotemperature reconstructions.

Dynamical landscape and multistability of a climate model.

We apply two independent data analysis methodologies to locate stable climate states in an intermediate complexity climate model and analyse their interplay. First, drawing from the theory of quasi-potentials, and viewing the state space as an energy landscape with valleys and mountain ridges, we infer the relative likelihood of the identified multistable climate states and investigate the most likely transition trajectories as well as the expected transition times between them. Second, harnessing techniques from data science, and specifically manifold learning, we characterize the data landscape of the simulation output to find climate states and basin boundaries within a fully agnostic and unsupervised framework. Both approaches show remarkable agreement, and reveal, apart from the well known warm and snowball earth states, a third intermediate stable state in one of the two versions of PLASIM, the climate model used in this study. The combination of our approaches allows to identify how the negative feedback of ocean heat transport and entropy production via the hydrological cycle drastically change the topography of the dynamical landscape of Earth’s climate.

Characterisation of Atlantic meridional overturning hysteresis using Langevin dynamics

Abstract. Hysteresis diagrams of the Atlantic meridional overturning circulation (AMOC) under freshwater forcing from climate models of intermediate complexity are fitted to a simple model based on the Langevin equation. A total of six parameters are sufficient to quantitatively describe the collapses seen in these simulations. Reversing the freshwater forcing results in asymmetric behaviour that is less well captured and appears to require a more complicated model. The Langevin model allows for comparison between models that display an AMOC collapse. Differences between the climate models studied here are mainly due to the strength of the stable AMOC and the strength of the response to a freshwater forcing.

Ozone depletion-induced climate change following a 50 pc supernova

Ozone in Earth's atmosphere is known to have a radiative forcing effect on climate. Motivated by geochemical evidence for one or more nearby supernovae about 2.6 million years ago, we have investigated the question of whether a supernova at about 50 pc could cause a change in Earth's climate through its impact on atmospheric ozone concentrations. We used the "Planet Simulator" (PlaSim) intermediate-complexity climate model with prescribed ozone profiles taken from existing atmospheric chemistry modeling. We found that the effect on globally averaged surface temperature is small, but localized changes are larger and differences in atmospheric circulation and precipitation patterns could have regional impacts.