To meet the Paris Agreement targets we need large-scale deployment of carbon dioxide removal (CDR). Most of the literature focuses on the removal potential of CDR and the direct effect on temperature. Nevertheless, to design sustainable and robust mitigation strategies, we need to explore and quantify broader impacts of CDR on the Earth system. Although these effects on the Earth system have been identified, there is no comprehensive understanding of their magnitude if CDR is implemented on a large scale. The Planetary Boundary (PB) framework aims to maintain a safe operating system for humans. The PB framework, used with an Earth system model, could be used to systematically assess the positive or negative effects of different CDR methods on the Earth system features that are critical to human welfare.We use the University of Victoria Earth System Climate Model (UVic ESCM) to simulate large-scale ocean alkalinity enhancement (OAE), artificial upwelling (AU), reforestation (REF), and bioenergy with carbon capture and storage (BECCS), under the SSP1-2.6 control scenario. Our goal is to assess the efficiency and sustainability of the selected CDR methods. Therefore, we use the PB framework to quantify CDR’s impact on the PBs of climate change, ocean acidification, land system change, biochemical flows, freshwater change, and biosphere integrity. By doing so, we can assess whether, after implementing CDR, the PB control variables stay below the boundaries (safe operating space) or go beyond it to the increasing or high-risk zone.Our preliminary results show the impacts of OAE and REF on radiative forcing, CO2 concentration, ocean acidification, and land system change. In all the future scenarios, the radiative forcing level falls in the high-risk zone (3.00 Wm-2). In 2300, OAE and REF reduce the radiative forcing to 1.7 Wm-2, which gets closer to the upper end of the zone of increasing risk (1.5 Wm-2), but still in the high-risk zone. In 2100, the CO2 concentration decreases in all the future scenarios, getting closer to the upper end of the zone of increasing risk (450 ppm), only reached by REF. In 2300, the CO2 concentration further decreases, falling within the zone of increasing risk, with OAE and REF CO2 concentration of 383 and 387 ppm, respectively. REF almost reaches the PI forest coverage (92% in 2100, 96% in 2300), while OAE has a negligible impact on the land system change, staying, nevertheless, within the PB (75% of PI forest coverage). OAE has the highest impact on ocean acidification, quantified as surface ocean saturation state with respect to aragonite (Ωarag). OAE increases the surface ocean’s aragonite saturation state (2.63 Ωarag) close to the PB (2.75 Ωarag) in 2100, and it allows staying within the PB in 2300 (2.97 Ωarag). REF shows a similar increase in 2100, but a slightly smaller increase in 2300 (2.86 Ωarag) compared to OAE.To conclude, only in the far future, large-scale CDR will help stay within the PB or upper PB of most of the explored control variables; however, CDR impacts are mainly minor compared to SSP1-2.6.

Exploring uncertainty and internal variability across future emission pathways remains computationally demanding with state-of-the-art Earth system models (ESMs). We present a diffusion-based machine-learning emulator trained on output from the CESM2 large ensemble dataset to reproduce absolute annual-mean temperature and year to year variability, conditioned on anthropogenic co2 and sulfate emisisson from ssp3-7.0 scenario. The emulator employs a three-dimensional UNet architecture that learns the spatiotemporal distribution of global temperature fields in latitude–longitude–time space. Conditioning variables include cumulative CO₂ and aerosol emissions, enabling the generation of physically consistent climate responses under arbitrary emission trajectories.To enhance physical interpretability, we integrate explainable AI (XAI) methods, including gradient-based attribution and sensitivity analyses, to quantify how emission-related conditioning variables influence regional temperature responses. The emulator reduces computational cost by several orders of magnitude compared to full ESM simulations, enabling rapid scenario exploration and uncertainty assessment. This framework aims provides a scalable and interpretable pathway for fast climate response emulation

Abstract. Arctic amplification and its persistent underestimation in climate models underscore the importance of accurate representation of local Arctic feedback processes. Previous studies evaluating model data against measurements showed the importance of including local emissions, such as iodic acid and organic vapours, for an accurate representation of aerosols in the high Arctic. The MOSAiC expedition has produced a full year of data in the high Arctic, providing an opportunity to evaluate the performance of climate models in this region across strongly contrasting seasonal conditions. We evaluate four CMIP6 models and the chemistry-transport model TM5 using this data. CMIP6 models fail to capture the observed seasonal cycle and generally underestimate aerosol number concentration (CN), with the strongest underestimation in summer. To understand the cause of these model deficiencies, we conduct a sensitivity analysis using an ensemble of TM5 experiments by perturbing individual parameters and three reasons were identified. In summer, missing regional new particle formation (NPF) sources are the primary cause of the underestimation. Including methanesulphonic acid driven NPF improved the magnitude and seasonality of simulated CN. In winter and early spring, the model is missing aerosol sources such as blowing snow and lead emissions. During the Arctic haze period, the model underestimates the aerosol background concentration, possibly due to an underestimation of long-range transported aerosols. With cloud condensation nuclei (CCN), we observe a persistent underestimation even during periods of CN overestimation. These results identify gaps in Arctic aerosol representation in climate models that need to be addressed to improve climate projections.

Polar amplification (PA) is a robust feature of climate change in coupled atmosphere-ocean general circulation models (AOGCMs), yet its magnitude varies substantially across models. Prior work showed that PA and its drivers, primarily positive feedbacks, are strongly linked to the degree of sea ice loss. Here, we assess to what extent this intermodel spread narrows when sea ice and sea surface temperatures (SSTs) are prescribed in a coordinated set of atmosphere-only GCM (AGCM) simulations. Three AGCMs are forced with SST and sea ice fields from the SSP5-8.5 scenario of a single reference model. Comparisons between AGCM and AOGCM ensembles reveal that prescribing sea surface boundary conditions substantially reduces the spread in PA and associated amplifying feedbacks. This indicates that much of the divergence in coupled model projections arises from feedbacks operating on different patterns of SST warming and sea ice melt. Cloud feedbacks, in particular, exhibit strong sensitivity to SST warming patterns in regions that contribute prominently to intermodel differences in climate sensitivity, especially the southern midlatitudes. Remaining spread in AGCMs isolates intrinsic atmospheric model differences. The Arctic cloud feedback emerges as a major residual uncertainty, reflecting its state dependence on cloud properties such as liquid water path. Decomposing the AGCM response further shows that roughly three-quarters of Arctic amplification is driven by processes related to sea ice melt. Nevertheless, a weakened Arctic amplification persists without evolving future sea ice via temperature feedbacks. In contrast, Antarctic amplification remains more uncertain and is closely linked to historical sea ice amount, which partly determines the sea ice trajectory in future climates.

The year 2024 marked the first time global temperatures exceeded 1.5 degrees C, raising questions about climate projection accuracy and implications for climate goals. We quantify the timing and likelihood of first crossing 1.5 degrees C and higher global warming levels across CMIP6 models. The observed 2024 crossing occurred 3-7 years earlier than in CMIP6 projections. Models with high present-day warming rates predicted the timing of the 1.5 degrees C crossing more accurately, while the 2024 timing is likely affected by internal climate variability superimposed on the anthropogenic trend. A pre-mid-century 2 degrees C crossing is difficult to avoid even under stringent mitigation (75% of models crossing 2 degrees C under SSP1-2.6). However, while shifting from high (SSP5-8.5) to medium-high (SSP3-7.0) emissions delays a 3 degrees C crossing by 10 years, low-emission pathways (SSP1-2.6) avoid crossing this threshold in 85% of models. While near-term 2 degrees C exceedance is a significant risk, immediate mitigation remains critical to enable adaptation and avoid long-term warming.

Abstract. The Arctic and Antarctic regions experience significant climate impacts from aerosol-cloud-radiation interactions, yet the role of sea salt aerosols (SSA) emitted through blowing snow remains poorly quantified. This study implements a parameterization of the SSA production of blowing snow in both the TM5 global chemical transport model and the EC-Earth3 global climate model, for AMIP-type as well as transient (SSP3-7.0 for 2015–2051) experiments, assessing the contributions of the blowing snow process to aerosol mass, number, cloud condensation nuclei (CCN) and radiative forcing in both polar regions. Model results are evaluated against observations from the MOSAiC campaign and coastal stations (Villum, Zeppelin, Alert). EC-Earth3 Simulations show that blowing snow substantially increases SSA concentrations during polar winter and spring, especially in the Antarctic where enhancements can exceed 100 % increase in particle numbers, leading to improved agreement with surface and in situ observations. Regionally, TM5 reveals an increase in accumulation mode aerosol and CCN. The resulting surface radiative forcing is globally negative due to increased scattering of shortwave radiation, while enhanced CCN increases longwave cloud effects in the polar lower troposphere. Overall, this work demonstrates that including blowing snow SSA emissions is essential for realistically representing polar aerosol burdens, seasonal cycles, and climate feedbacks in global models.

Using a novel set of coordinated simulations from four different models, the response of the wintertime (December-February) North Atlantic jet stream and storm track to prescribed sea surface temperature increases and sea ice loss is analysed and the underlying physical mechanisms investigated. Three out of the four models show a southward shift of the upper-level jet stream with an increase in jet speed over Europe, where the contribution of sea surface temperatures dominates over the effects of sea ice loss. However, the remaining model lacks the increase in jet speed over Europe, which originates from opposite responses of similar magnitude due to the future sea surface temperatures and sea ice cover. The jet stream responses are primarily driven by the change in the meridional temperature gradient and, as a consequence, baroclinicity. At the same time, momentum flux convergence acts as a secondary amplifying and dampening factor. The same three models see a significant eastward shift of the extratropical cyclone track density, which is equally driven by changes to sea surface temperatures and sea ice cover. A consistent feature across all models is a decrease in the frequency of extratropical cyclones in the Mediterranean. The responses of extratropical cyclones to future sea ice cover and sea surface temperatures do not exceed the inter-model climatological differences. Notable differences in the future response of the jet stream and storm track occur, and thus considerable uncertainty remains in how the European climate will respond to a warmer climate.

As global warming progresses, weather conditions like daily temperature and precipitation are changing due to changes in their means and distributions of day-to-day variability. In this study, we show that changes in variability have a stronger influence on the number of extreme precipitation days than the change in the mean state in many locations. We analyze daily precipitation and maximum temperatures at four levels of global warming and under different emission scenarios for the Northern Hemisphere (NH) summer (June – August). Our analysis is based on initial condition large ensemble simulations from three fully coupled Earth System Models (MPI-ESM1-2-LR, CanESM5, and ACCESS-ESM1-5) contributing to the Climate Model Inter-comparison Project phase 6 (CMIP6). We also use information from the Precipitation Driver Response Model Intercomparison Project (PDRMIP) to discern the influence of different climate drivers (notably aerosols and greenhouse gases). We decompose the total changes in daily NH summer precipitation and daily maximum temperature into mean and variability components (standard deviation and skewness). Our results show that in many locations, variability exerts a stronger influence than mean changes on daily precipitation. Changes in the widths and shapes of precipitation distributions are especially dominating over mean changes in Asia, the Arctic and Sub-Saharan Africa. In contrast, temperature changes are primarily driven by changes in the mean state. For the near future (2020–2040), we find that reductions in aerosol emissions would increase the likelihood of extreme summertime precipitation only over Asia. This study emphasizes the importance of incorporating daily variability changes into climate change impact assessments and advocates that future emulator and impact model development should focus on improving the representation of daily variability.

Decreasing sea ice cover and warming sea surface temperatures (SSTs) impact the climate at both poles in uncertain ways. We aim to reduce the uncertainty by comparing output of 41-year-long simulations from four atmospheric general circulation models (AGCMs). In our “Baseline” simulations, the models use identical prescribed SSTs and sea ice cover conditions representative of 1950–1969. In three sensitivity experiments, the SSTs and sea ice cover are individually and simultaneously changed to conditions representative of 2080–2099 in a strong warming scenario. Overall, the models agree that warmer SSTs have a widespread impact on 2 m temperature and precipitation, while decreasing sea ice cover mainly causes a local response (i.e. the greatest warming occurs where sea ice is perturbed). Thus, decreasing sea ice cover causes greater changes in precipitation and temperature than in warmer SSTs in areas where sea ice cover is reduced, while warmer SSTs dominate the response elsewhere. In general, the response in temperature and precipitation to simultaneous changes in SSTs and sea ice cover is approximately equal to the sum due to individual changes, except in areas of sea ice decrease where the joint effect is smaller than the sum of the individual effects. The models agree less well on the magnitude and spatial distribution of the response in mean sea level pressure; i.e. uncertainties associated with atmospheric circulation responses are greater than uncertainties associated with thermodynamic responses. Furthermore, the circulation response to decreasing sea ice cover is sometimes significantly enhanced but sometimes counteracted by the response to warmer SSTs.

In 2020, motivated by improving air quality in major ports and shipping lanes, the International Maritime Organization imposed strict new regulations on the sulfur content of shipping fuel. This led to a rapid reduction in the number of observed ship tracks (linear tracks of clouds brightened by aerosol perturbations; Watson-Parris et al. 2022), and presumably a commensurate reduction in anthropogenic aerosol forcing. The magnitude of this forcing, and the resulting temperature change, are uncertain however. The recent confirmation that 2023 was the hottest year on record can only partly be explained by the onset of the El Niño phase of the El Niño-Southern Oscillation (ENSO). Such warming, in addition to the sizable warming in NH ocean basins- geographically collocated with shipping- raise the question of how much shipping emissions changes might have contributed to this signal, and any extreme weather events associated with it. In this study we aim to answer this question by utilizing a large ensemble of fully-coupled Community Earth System Model version 2 (CESM2) simulations with and without the shipping emissions changes. We leverage the CESM2 large ensemble and choose 20 simulations with varying ENSO conditions from which to branch off with shipping emissions reduced to 20% of their baseline value. These are integrated forward for another 20 years, while non-shipping emissions follow the SSP3-7.0 scenario, in order to robustly explore the transient climate response.In this talk we will highlight the forced climate response, focusing on temperature (T), precipitation (P), and atmospheric circulation, both globally and in key regions such as the North Atlantic. Given the change in ENSO phase during 2023, we will also describe how this climate response is modulated by different ENSO conditions, the Atlantic Multidecadal Variability and other modes of climate variability. The underlying relevant climate processes, including cloud dynamics, radiative imbalances at the top of the atmosphere, and daily variability will be summarized to link our single model study to observed changes.References:[1] Watson-Parris, D., Christensen, M., Laurenson, A., Clewley, D., Gryspeerdt, E., Stier, P. “Shipping regulations lead to large reduction in cloud perturbations”. PNAS 119 (41) e2206885119: https://doi.org/10.1073/pnas.2206885119 (2022)

Dramatic sea ice loss has recently occurred at both poles. Multiple studies have suggested that changes to sea ice can impact weather in both the polar regions and mid-latitudes. However, the current generation of climate models disagrees on the rate and location of sea ice loss, and on the rate of warming in the polar regions.Thus, the atmospheric response to sea ice loss within and outside the polar regions remains highly uncertain. To reduce this uncertainty, we have performed a set of coordinated simulations with four different atmospheric general circulation models (AGCMs) within the project “Climate Relevant interactions and feedbacks: the key role of sea ice and Snow in the polar and global climate system” (CRiceS). A baseline simulation and six perturbation simulations were performed, all of which were 40-years long and had prescribed sea surface temperatures (SSTs) and sea ice concentration. In the perturbation simulations, the SSTs and sea ice concentration were changed independently, and then both were changed together. The SST and sea ice concentrations were obtained from CMIP6 simulations with the Australian Earth system model ACCESS-ESM1.5. Monthly-mean SST and sea-ice area averaged over 20 years of simulation were taken from 1) the historical simulation (years 1950-1970, Baseline simulation), 2) the scenario SSP1-2.6 simulation (years 2080-2100), and 3) the scenario SSP5-8.5 simulation (years 2080-2100) and were then used as perpetual monthly average values of SSTs and sea ice fraction in our model simulations, thus eliminating inter-annual variability in SSTs and sea ice. This array of perturbation experiments, performed with four AGCMs, allows us to isolate atmospheric responses in polar regions and mid-latitudes that are due to SST or sea ice changes, examine the linearity of these feedbacks, and investigate the robustness of the atmospheric responses. The results of this coordinated modelling experiment show that the models agree well on the magnitude and spatial distribution of the 2-m temperature and precipitation response. Increasing SSTs has a larger and more spatially extensive impact on the overall response than decreases in sea ice, which primarily only cause a localised response in regions where sea ice disappears (most notably, a strong warming over the Arctic ocean in winter). The models agree less well on the magnitude and spatial distribution of the mean sea level pressure response, in particular over northern Europe and Antarctica, suggesting that modelled uncertainties associated with atmospheric circulation are larger than uncertainties associated with thermodynamics. These results and others, along with information about the openly available dataset, will be presented.

The impacts of global warming vary across regions. This paper studies the distributional implications of global warming impacts on household energy use for heating and cooling and the induced macroeconomic responses under different scenarios. Our research updates the direct impact of global warming on household energy demand in 140 regions worldwide by utilizing existing estimations of damage functions related to temperature changes. Subsequently, the updated direct impact is used in a global static computable general equilibrium (CGE) model to evaluate the macroeconomic responses. We find that at the global level, the market effects cause a reduction in the direct impact on the demand for oil and gas, while that for electricity displays a positive but moderate growth. Whereas the regional effects vary across countries and lead to changes in both directions, in which the autonomous adaptation embodied in the global market plays a vital role. Furthermore, we find strong inequality in the socioeconomic responses to global warming across regions. Notably, low-income countries are most strongly affected by increased primary energy use and decreased gross domestic product (GDP). Disparities in the impacts on carbon-based energy sources yield a near-perfect inequality as per the adjusted Gini index for CO2 emission changes, which potentially intensify the distributional consequences of global climate change.

BACKGROUND:Climate change scenarios illustrate various pathways in terms of global warming ranging from "sustainable development" (Shared Socioeconomic Pathway SSP1-1.9), the best-case scenario, to 'fossil-fueled development' (SSP5-8.5), the worst-case scenario. OBJECTIVES:We examined the extent to which increase in daily average urban summer temperature is associated with future cause-specific mortality and projected heat-related mortality burden for the current warming trend and these two scenarios. METHODS:We did an observational cohort study of 363,754 participants living in six cities in Finland. Using residential addresses, participants were linked to daily temperature records and electronic death records from national registries during summers (1 May to 30 September) 2000 to 2018. For each day of observation, heat index (average daily air temperature weighted by humidity) for the preceding 7 d was calculated for participants' residential area using a geographic grid at a spatial resolution of 1km×1km. We examined associations of the summer heat index with risk of death by cause for all participants adjusting for a wide range of individual-level covariates and in subsidiary analyses using case-crossover design, computed the related period population attributable fraction (PAF), and projected change in PAF from summers 2000-2018 compared with those in 2030-2050. RESULTS:During a cohort total exposure period of 582,111,979 summer days (3,880,746 person-summers), we recorded 4,094 deaths, including 949 from cardiovascular disease. The multivariable-adjusted rate ratio (RR) for high (≥21°C) vs. reference (14-15°C) heat index was 1.70 (95% CI: 1.28, 2.27) for cardiovascular mortality, but it did not reach statistical significance for noncardiovascular deaths, RR=1.14 (95% CI: 0.96, 1.36), a finding replicated in case-crossover analysis. According to projections for 2030-2050, PAF of summertime cardiovascular mortality attributable to high heat will be 4.4% (1.8%-7.3%) under the sustainable development scenario, but 7.6% (3.2%-12.3%) under the fossil-fueled development scenario. In the six cities, the estimated annual number of summertime heat-related cardiovascular deaths under the two scenarios will be 174 and 298 for a total population of 1,759,468 people. DISCUSSION:The increase in average urban summer temperature will raise heat-related cardiovascular mortality burden. The estimated magnitude of this burden is >1.5 times greater if future climate change is driven by fossil fuels rather than sustainable development. https://doi.org/10.1289/EHP12080.

Here we present for the first time a proof of concept for an emulation-based method that uses a large-eddy simulations (LESs) to present sub-grid cloud processes in a general circulation model (GCM). We focus on two key variables affecting the properties of shallow marine clouds: updraft velocity and precipitation formation. The LES is able to describe these processes with high resolution accounting for the realistic variability in cloud properties. We show that the selected emulation method is able to represent the LES outcome with relatively good accuracy and that the updraft velocity and precipitation emulators can be coupled with the GCM practically without increasing the computational costs. We also show that the emulators influence the climate simulated by the GCM but do not consistently improve or worsen the agreement with observations on cloud-related properties, although especially the updraft velocity at cloud base is better captured. A more quantitative evaluation of the emulator impacts against observations would, however, have required model re-tuning, which is a significant task and thus could not be included in this proof-of-concept study. All in all, the approach introduced here is a promising candidate for representing detailed cloud- and aerosol-related sub-grid processes in GCMs. Further development work together with increasing computing capacity can be expected to improve the accuracy and the applicability of the approach in climate simulations.

Anthropogenic aerosol emissions are expected to change rapidly over the coming decades, driving strong, spatially complex trends in temperature, hydroclimate, and extreme events both near and far from emission sources. Under-resourced, highly populated regions often bear the brunt of aerosols’ climate and air quality effects, amplifying risk through heightened exposure and vulnerability. However, many policy-facing evaluations of near-term climate risk, including those in the latest Intergovernmental Panel on Climate Change assessment report, underrepresent aerosols’ complex and regionally diverse climate effects, reducing them to a globally averaged offset to greenhouse gas warming. We argue that this constitutes a major missing element in society’s ability to prepare for future climate change. We outline a pathway towards progress and call for greater interaction between the aerosol research, impact modeling, scenario development, and risk assessment communities.

Recent years have seen unprecedented fire activity at high latitudes and knowledge of future wildfire risk is key for adaptation and risk management. Here we present a systematic characterization of the probability distributions (PDFs) of fire weather conditions, and how it arises from underlying meteorological drivers of change, in five boreal forest regions, for pre-industrial conditions and different global warming levels. Using initial condition ensembles from two global climate models to characterize regional variability, we quantify the PDFs of daily maximum surface air temperature (SAT max ), precipitation, wind, and minimum relative humidity (RH min ), and their evolution with global temperature. The resulting aggregate change in fire risk is quantified using the Canadian Fire Weather Index (FWI). In all regions we find increases in both means and upper tails of the FWI distribution, and a widening suggesting increased variability. The main underlying drivers are the projected increase in mean daily SAT max and decline in RH min , marked already at +1 and +2 °C global warming. The largest changes occur in Canada, where we estimate a doubling of days with moderate-or-higher FWI between +1 °C and +4 °C global warming, and the smallest in Alaska. While both models exhibit the same general features of change with warming, differences in magnitude of the shifts exist, particularly for RH min , where the bias compared to reanalysis is also largest. Given its importance for the FWI, RH min evolution is identified as an area in need of further research. While occurrence and severity of wildfires ultimately depend also on factors such as ignition and fuel, we show how improved knowledge of meteorological conditions conducive to high wildfire risk, already changing across the high latitudes, can be used as a first indication of near-term changes. Our results confirm that continued global warming can rapidly push boreal forest regions into increasingly unfamiliar fire weather regimes.