Carbon-climate feedbacks to spatial aerosol model implementation variations

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Monteiro, Giang Tran, Matthew J. Gidden, Nadine Mengis This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7502615/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Feb, 2026 Read the published version in npj Climate and Atmospheric Science → Version 1 posted 10 You are reading this latest preprint version Abstract Aerosols have played an important role in defining climate development over the historical period, due to their cooling impact in the atmosphere. However, as their emissions are expected to decrease in the upcoming decades, and therefore also their cooling effect, they will likely be associated with the future warming of the planet. Despite their importance, and the high uncertainty of their radiative forcing, aerosols inclusion or consideration in, for example, simple climate models, integrated assessment models and carbon metrics requires extensive simplifications and assumptions. Typically, interactions between physical and biogeochemical processes, as well as triggered feedbacks, are disregarded by such models and metrics, which is a potential further source of uncertainty in the aerosols’ led responses in a changing climate. By varying the spatial implementation of aerosols in an intermediate complexity model, we explore the variability in Earth system responses under a highly ambitious mitigation scenario due to a change in aerosols forcing. When spatial heterogeneities in forcing are disregarded, surface air temperature development can differ by almost 0.1°C, which would correspond to an approximate uncertainty of 200 GtCO 2 in estimates of remaining carbon budgets. The warming and cooling contributions of different Earth system processes, such as land carbon uptake or ocean heat uptake, are also seen to vary strongly depending on the spatial distribution of aerosols in the atmosphere. The main processes driving these responses are found to be land surface temperature and its impact on soil respiration, as well as ocean ventilation processes and sea ice cover changes. These findings highlight that the spatial distribution of aerosols is capable of triggering important climate feedbacks, which should not be disregarded when assessing climate development and simulated Earth system responses. These feedbacks will be instrumental in defining potential pathways for temperature stabilisation and evaluating, for example, remaining carbon budgets. Earth and environmental sciences/Climate sciences Earth and environmental sciences/Environmental sciences aerosol responses Earth system Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Aerosols are currently the largest source of uncertainty in evaluating the Earth’s climate feedbacks to anthropogenic forcing [ 1 ]. Overall, aerosols’ contribution is estimated as a net negative forcing of -1.1 [-1.7 to -0.4] W m − 2 between 1750–2019, the largest negative contribution to a change in effective radiative forcing. The magnitude of aerosols contribution is similar to, for example, that of non-CO 2 well-mixed greenhouse gases in the same period, which are responsible for a warming forcing of 1.16 [1.05 to 1.17] W m − 2 , with aerosols uncertainty, as expected, being much higher due to its distinct characteristics. From a physical point of view aerosols have a direct and an indirect effect on atmospheric radiative properties. Direct effects are due to their absorption and scattering impacts on the incoming solar shortwave radiation, while in the atmosphere aerosols can also interact with clouds, altering its microphysical characteristics and leading to an indirect effect on the properties of the atmosphere (see for example [ 2 – 5 ]). Furthermore, the aerosols distribution is spatially and temporally heterogeneous. Emission plumes from point sources, commonly associated with human activities, in combination with a short atmospheric residence time cause aerosol optical depth to be on average 1.4 times higher over land areas compared to over oceans [ 6 ]. Such characteristics of aerosols contribute to the current physical uncertainties of aerosol forcing, and also impact the range of future projections of this forcing, which is dependent additionally on future scenarios uncertainty. Scenario uncertainty in this context refers to deep uncertainty in future developments of aerosol emissions, which varies based on socio-economic choices and political decisions [ 7 , 8 ]. In an attempt to explore this source of uncertainty, integrated assessment models (IAMs) are used to develop a multitude of plausible socio-economic scenarios [ 8 ]. IAMs include representations of different economic sectors, socio-economic variables and technical parameters [ 9 ], to provide future scenarios of anthropogenic climate forcing. Due to their focus on the socio-economic systems, IAMs employ so-called simple climate models with various simplifications and assumptions. These involve both their representation of aerosols, with simplified patterns (see for example [ 10 ]), parametrization of radiative forcing impacts (e.g. [ 11 ] or scaling factors), as well as limitations on feedbacks between the carbon cycle and the climate [ 12 ]. Even in simple climate models with a more realistic representation of the carbon cycle, interactions between physical and biogeochemical components are not typically present in either these models or the IAMs, being provided only by the Earth system models [ 12 ]. These simplifications in the coupled components results in a lack of representation of carbon-climate feedbacks. Feedbacks between the carbon cycle and the climate relate to carbon exchanges between Earth’s components and how the efficiency of these processes is interconnected to changes in the climate, which in turn are directly affected by the weakening or strengthening of such fluxes [ 13 ]. The uptake of carbon by the ocean and the land, as well as permafrost carbon emissions, are among the processes that contribute to the reinforcement of these feedbacks and the uncertainty added to future CO 2 development projections and the associated surface air temperature (e.g. [ 14 , 15 ]). As a result, carbon cycle feedbacks will play a role in controlling temperature responses to emitted carbon, and add to the uncertainty of transient climate response to cumulative CO 2 emissions (TCRE) [ 16 ], carbon budgets [ 14 ] and ultimately whether temperature targets can be reached or not. Processes or components that alter these feedbacks are, therefore, of great importance to the assessment of future climate potential development, as is the case with aerosols. The spatially heterogenous distribution of aerosols can lead to heterogeneities in regional temperature patterns and the respective processes of carbon and heat uptake. As stated, the importance of carbon feedbacks to understand the development of the climate has been intensely discussed. However, similar to the assumptions made in simple climate models, metrics and linear models employed for the estimation of the remaining carbon budget commonly combine all non-CO 2 forcing into one globally aggregated value (e.g. [ 17 – 21 ]). They assume no non-linearities between forcing and carbon cycle responses, and disregard the spatial temporal differences between aerosols and other GHGs as well as their potential carbon climate feedbacks. In this study, we compare climate-carbon responses under distinct implementations of aerosols’ spatial forcing, in an attempt to disentangle the impact of reduced complexities, such as seen in simple climate models or linear metrics, on possible climate uncertainties for both the historical period and future scenarios. The use of distinct spatial implementations of aerosols is shown to have the potential to trigger carbon cycle feedbacks, and directly impact atmospheric carbon burden, temperature and other feedback processes. 2. Methods 2.1. Employed Earth system model and simulation scenario The results presented in the next section are simulated by an intermediate complexity model, the University of Victoria Earth System Climate Model - UVic ESCM version 2.10 [ 22 , 23 ]. It includes 19 ocean vertical levels, 14 terrestrial soil levels, permafrost and dynamic vegetation modules, on a 3.6°x1.8° horizontal grid. The atmosphere is represented by a two-dimensional energy moisture balance model [ 24 ], with a cloud mask integrated only onto the atmospheric albedo. This implies that changes in the aerosols’ implementations will alter only the direct effect of aerosols on the climate. Notwithstanding, the UVic ESCM has been shown to perform well in terms of carbon cycle and temperature responses in historical simulations [ 23 ], a relevant feature to the exploration of triggered feedbacks included here. In fact, the simplicity of this model in comparison to a fully-coupled one is an advantage that allows us to easily disentangle the effects of the different aerosol implementations. For the baseline scenario, we follow the CO 2 emissions trajectory of the UVic ESCM that resulted from the 1.5°C no overshoot scenario conceived for the Adaptive Emissions Reduction Approach [ 25 – 27 ]. This approach iteratively calculates the necessary CO 2 emissions trajectory for stabilising surface air temperature at 1.5°C on a 5-year basis, dependent only upon the simulated temperature and the previous radiative forcing and emissions pathways. The aerosol, the non-CO 2 greenhouse gases and the land use change forcings follow the Shared Socioeconomic Pathway 1 (SSP1 - [ 28 ]). The experiments start from the pre-industrial period in 1850, and are simulated until the end of the baseline scenario in 2100. For all aerosol implementation variation experiments described here, forcing other than aerosols are kept the same. 2.2. Aerosols implementation variations In this default setting, UVic ESCM treats aerosol forcing as spatially-masked yearly aerosol optical depth (AOD) data ( default simulation). The UVic ESCM aerosol forcing is based on the work from [ 29 ], who developed parametrizations of sulphate-like, and in smaller scale nitrate-like, aerosols optical properties. This is a plume-based model, where aerosols emissions originate from nine spatial plumes in distinct source regions, which are fitted to a present-day climatology, and scaled to match historical anthropogenic emissions in each region. The plumes represent both industrial emissions and biomass burning, with each’s respective seasonal cycle (more information on the temporal response component can be found in Figure S1 and associated text). In the UVic ESCM, aerosols emitted by plumes account only for direct radiative effects, and a scaling factor was implemented in tuning the model to historical period observations [ 23 ]. To explore the spatial dependencies in aerosol implementations, we design other narratives that support improved understanding of climate-carbon uncertainties: 1) To understand the impact of spatially resolved AOD forcing, we implement an area weighted globally averaged AOD forcing ( no plumes simulation) resulting in a different spatial temporal forcing (see Fig. 1 (a)). We then adjust the aerosol forcing data utilizing the UVic ESCM aerosol scaling factor, when necessary, to have the final effective radiative forcing with the same magnitude as that for the default simulation. Simulations such as no plume can denote implementations of global aerosol emissions forcing derived from integrated assessment models or from future scenarios that provide only the final global mean effective radiative forcing of non-CO 2 contributions without making assumptions about the source regions. 2) To disentangle ocean and land carbon-cycle impacts, we design a second idealised set of experiments, where we applied aerosol forcing over land or over ocean areas ( only land , and only ocean experiments, respectively). The remaining areas in each experiment are assumed to have no aerosols in the atmosphere above them. Once again, in this second set of experiments, the global total aerosol forcing is adjusted to have the final effective radiative forcing with the same magnitude as that in the default simulation. 3) Finally, to explore the carbon-climate impact of a Northern Hemisphere dominated aerosol spatial distribution compared to a Southern Hemisphere dominated distribution we design the final set of idealised experiments ( North Hemisphere (NH) and South Hemisphere (SH) experiments, respectively), acknowledging a likely southward strengthening of aerosol forcing in future scenarios [ 30 ]. The opposite hemisphere in each simulation is implemented with zero aerosol content. Finally, for consistency, the global total aerosol forcing is adjusted to have the final effective radiative forcing with the same magnitude as that in the default simulation. For the idealised experiments (in section 3.2 and 3.3), we used the no plumes simulation as a reference, since it allows for a clearer distinction of the responses. By prescribing these different narratives of the aerosol spatial implementations, we are able to investigate responses from carbon cycle and climate feedbacks, pointing out missing feedbacks in simplified aerosol representations. 2.3. Analysis framework To analyse the experiments and understand the distinct contribution from all forcings and the carbon cycle, heat fluxes and Earth system responses, we used FROT (Framework for radiative contribution to temperature response – [ 31 ]). Under FROT, all radiative forcing as well as system feedbacks are converted to the same metric (in W m − 2 ), which defines the final burden in the atmosphere driving the surface air temperature variability, named atmospheric radiative burden (ARB). ARB, as applied here, connects the cumulative impact the different climate components have had in the system throughout the experiment, using the simulated heat and carbon fluxes. This framework is ideally suited to compare the individual contributions of distinct processes to the temperature development and climate feedbacks in our different scenarios. More information on the individual simulated values for each contributor are explored over Table S1 . 3. Results 3.1. Carbon-climate feedbacks from spatially resolved aerosol implementations Despite the same global average aerosol forcing, the spatially resolved AOD implementation has a distinct radiative forcing pattern compared to the no plumes experiment, and the associated carbon-climate feedbacks cause differences in the simulated surface air temperature (Fig. 1 ). Removing the spatial aspect of the aerosol implementation, i.e., moving from default to no plumes , results in a simulated air temperature that is up to 0.096° C higher in the latter (Fig. 1 (d), purple line). The highest surface air temperature differences between the experiments default and no plumes are simulated, as expected, over the years when aerosols radiative forcing is strongest (negative most values in Fig. 1 (b)). More details on this mathematical relation can be found in the Supplementary Material (Figure S2). The main drivers of this temperature difference in terms of Earth system responses, are the impacts onto land carbon uptake and ocean heat uptake (contributing 71% and 23% to the gross warming in 2020 and 81% to the gross warming and 8% to the gross cooling by the end of the century, respectively). The no plumes experiment simulates a lower land carbon uptake (Fig. 1 (d) and Fig. 2 (a)) due to the relative reduction of the aerosol load over land areas, where the plumes are located. The driving process behind this reduced land carbon uptake is the increase in temperature-driven soil respiration (see SI Figure S3) due to the relatively lower cooling (i.e., warmer temperatures) by aerosols over land (Figure S4), especially in the Northern Hemisphere for higher latitudes during the historical phase and for mid latitude until the end of the century. A small increase in vegetation primary production is also seen associated with the relatively lower cooling, its contribution to carbon uptake being smaller than the simulated increase in soil carbon and respiration, resulting in comparatively lower carbon uptake. This reduction in terrestrial carbon uptake is most prominent in mid to high northern latitudes (Fig. 2 (a)), and in tropical and subtropical regions of the globe towards the end of the century. This southern shift corresponds well with the southward movement of the aerosol optical depth in the default experiment. The decrease in land carbon uptake in the experiment with globally uniform aerosol loads can be associated to differences in the vegetation cover of dominant plant functional types, specifically the needleleaf trees (for which vegetation carbon increases) and grasses and shrubs (which show a smaller carbon pool) (see Figure S4). On a smaller scale, ocean carbon uptake is overall increased especially in the Southern Hemisphere (see Figure S5). Additionally, having a globally uniform aerosol forcing implies a higher than default aerosol load over the ocean, which decreases the incoming shortwave radiation at the ocean surface and accordingly the ocean heat uptake. This signal is more pronounced in the Southern Hemisphere, due to its larger ocean areas (see Fig. 2 (b)). The Northern Hemisphere subtropical regions, in contrast, show an increase in ocean heat uptake. The Northern Hemisphere subpolar region shows changing signs in the ocean heat fluxes by the ocean, especially towards the end of the historical period, with periods of weakened fluxes in the case of globally uniform aerosol implementations. This is driven by differences in sea ice cover and ventilation depth in the high latitudes of the North Atlantic, where heat content stored in the ocean is higher as ventilation depth increases and sea ice area decreases with a spatially explicit aerosol forcing being implemented. The global aggregated signal is a reduction in ocean heat uptake in the no plumes experiment, which contributes to an increase in surface air temperature. 3.2. Carbon-climate responses from aerosols located only over specific areas To disentangle the land and ocean carbon-climate responses to spatial aerosol forcing we constrain the following experiments to exhibit aerosol forcing only over land or over the ocean, respectively. When aerosols are implemented uniformly over only land with a comparable global mean radiative forcing magnitude, land carbon uptake is increased relative to a simulation with globally uniform aerosol implementation (Fig. 3 (a)). The combined impact (see SI Figure S6 for more information) of decreased soil respiration due to lower temperatures and marginally increased vegetation primary production due to less heat stress contributes to a reduced atmospheric CO 2 concentration. Consequentially, when aerosols are implemented over only land maximum temperature differences to no plumes are ca. − 0.09°C. The main areas in which higher land carbon uptake can be seen are the mid- to high- latitude regions in the Northern Hemisphere and subtropical areas in the Southern Hemisphere (Fig. 4 (a)). These regional responses on land carbon uptake strengthen in the middle of the 21st century, indicating that, despite the decreasing forcing from the aerosols in the experiments, the climate-carbon effect persists. By the end of century, land carbon uptake contributes 94% to the gross cooling in the only land experiment in comparison to the no plumes experiment. This aerosol implementation with aerosols over only land shows an initial increase in ocean heat uptake (Fig. 3 (a)), dominated by an increase in heat uptake over the Southern Hemisphere (Fig. 4 (b)), which turns into a warming contribution in the middle of the 21st century (with 8.2% of gross warming by the end of the century). Additionally, we find a similar feature in this experiment comparison to the no plumes – default results, with ocean heat uptake sign alternation’s timing and magnitude in the northern high latitudes. We find that the only land experiment reinforces the effects seen in a more realistic aerosol implementation, i.e. with plumes. As before, the Southern Hemisphere, known to contribute the most to ocean heat uptake, is observed to have strengthened fluxes, while the Northern Hemisphere, which has a smaller role in ocean heat uptake, decreases its contribution to the ocean heat content. An interesting characteristic of the heat uptake process is that even if the forcing is implemented without spatial detailing of plumes , a very clear inter-hemispherical difference is present. Heat uptake is mediated by physical processes, which will define areas of release and uptake of heat, as well as the efficiency in these processes. It is important to highlight that the majority of the ocean areas in the experiments described here do not shift from uptake to release regions, for example, but instead remain with the exchange signature defined by the local physical processes. Aerosols implemented over only ocean affect both the carbon cycle and its feedbacks, leading to a decrease in land carbon uptake (Fig. 3 (b)). This response is extremely similar, but in opposite sign, to the only land simulation, with an overall much smaller magnitude. Detailed information on more specific responses for only ocean simulations can be found in the Supplementary Information (Figures S6, S7 and associated text). The patterns described here highlight the similarity of the only ocean simulation to the no plumes one. In a similar sense, the experiment only land is an imperfect analogue to the real world, presenting an enhanced sensitivity similar to observed historical responses, and expected future changes. 3.3. Carbon-climate responses from aerosols over only a hemisphere This final section explores the development of temperature as well as carbon and heat responses over hypothetical narratives in which aerosols are only present in one of the hemispheres. When aerosols are present only over the Northern Hemisphere , small anomalies are seen in ocean and land carbon uptake, as well as in heat uptake (Fig. 5 (a)). As a result, the temperature anomaly to annual no plumes does not surpass − 0.047°C throughout the simulation, being close to zero over the historical period, and negative by the end of the century. Towards the end of the 21st century, an increase in land carbon uptake dominates the cooling of the climate. This contribution, however, only accounts for about 70% of all cooling compared to no plumes , a smaller percentage than what is observed in other experiments. Further discussions on the driving mechanisms behind this simulation are provided in the Supplementary Information (see Figures S8 and S9). When atmospheric optical depth is non-zero only in the Southern Hemisphere surface air temperature is higher than in the default no plumes experiment over both the historical period and future development (Fig. 5 (b)). A larger response from the land carbon and permafrost uptake are noticeable, accounting for 71% and 15% of the warming by the end of the century compared to the no plumes experiment, respectively. Despite a slight increase in net primary production, higher soil respiration rates in the Southern Hemisphere only experiment cause a loss in the land carbon uptake (Figure S8). Most of the Northern Hemisphere sees a reduction in the land carbon uptake potential, both in terms of the historical period and future scenario until the end of the century (Fig. 6 (a)). Ocean heat uptake shows overall negative anomalies, i.e. less ocean heat uptake, contributing ca. 14% to the gross warming by the end of the century. This response is driven by a reduced uptake over the Southern Hemisphere (Fig. 6 (b)). The Northern Hemisphere on the contrary shows mostly an increase in heat uptake, associated to a reduced aerosol load in the atmosphere above it. However, high latitudes of the Northern Hemisphere also show short periods of reduced ocean heat fluxes over the historical period. The combined effect from these different ocean areas contributes to the lower heat uptake throughout the simulation. The final temperature anomalies to no plumes reach around 0.07°C. 4. Discussion 4.1. Aerosol implementation choices in model experiments impact carbon-climate feedbacks In the current study we have shown that aerosol implementation choices can lead to substantial differences in carbon and heat feedbacks, resulting in surface air temperature differences of up to almost 0.1°C, even if the same global mean radiative forcing is achieved. While such anomalies may appear small in magnitude, in an ambitious emissions mitigation setting such contributions are considerable, reducing the effective remaining carbon budget for a given temperature limit by ca. 200 GtCO 2 (using a TCRE estimate of 0.45°C per 1000 GtCO 2 [ 32 ]). Using more-idealised experiments, we were able to identify the driving processes behind the different Earth System responses, finding land surface temperature, soil respiration, ventilation depth, and sea ice extent to be dominating drivers due to the distinct aerosol implementation choices. In addition to distinct relative contributions of such drivers to the temperature development, the spatial different implementations are shown to trigger carbon and climate feedbacks that cause both cooling and warming in the Earth System depending on the implementation explored here. The contributions from land carbon uptake to temperature differences between the simulations can range between 70% of the warming to 94% of the cooling modelled. Similarly, permafrost varies from 6% of cooling to 15% of warming impact, while ocean heat uptake can contribute from 8% in cooling up to 14% in the warming of the planet between different simulations by the end of the century. Considering that simple climate models and integrated assessment models (IAMs) make use of simplifications for the natural system responses when providing potential future climate scenarios, our results show that these assumptions will contribute to an additional source of uncertainty in the aerosol impacts. We recommend that simple climate models add constrains that capture the regional aerosol variations of Earth system models, such that they can inform IAMs. Utilizing our intermediate complexity model as an example, it is possible to establish a mathematical relationship between the temperature difference from aerosol spatial implementations and the simulated aerosols radiative forcing, as shown for the no plumes case on the Supplementary Information (Figure S2). In a similar sense, a potential source of error is introduced when implementing aggregating or carbon-based metrics, as they include aerosols radiative forcing only in global terms, disregarding its spatial signal and feedback triggers. In both cases, expected atmospheric responses and global temperatures, as well as remaining carbon budgets will be over- or underestimated, as carbon-climate feedbacks are disregarded. 4.2. Further implications from aerosol implementations Even more specific conclusions can be drawn from mimicking Earth system situations as here, in addition to providing a clearer characterization of the impact aerosol pathway development assumptions have to future scenarios and model implementation, A first implication that can be obtained from expanding the findings reported here is that an appropriate aerosols implementation that allows for the inclusion of correct biophysical effects of triggered carbon-climate feedbacks will become of higher importance for upcoming model intercomparison efforts. Previous rounds of the Coupled Model Intercomparison Project (CMIP) included mostly concentrations driven experiments, where such impact sensitivities are not considered. However, future efforts are moving towards emissions-driven simulations [ 33 , 34 ], for which differences in aerosol forcing in the models will have an additional and non-neglectable impact on the carbon-climate feedbacks, associated processes and estimates of, for example, land and ocean carbon uptake as well as ocean heat uptake. Furthermore, one process understanding case that can be explored based on the results found here is that of the effects of heat uptake by the ocean in the experiment where aerosols are found uniquely over the Southern Hemisphere. For this experiment reductions in heat uptake, and in some regions increase in heat release, can be seen especially over the Atlantic and part of the Indian and Pacific sectors of the Southern Ocean (Figure S11). At the same time, the Northern Hemisphere’s subtropics to high latitudes in the Pacific show an increase in uptake, while other areas of release of heat have a decreased signal. This corroborates the hypothesis posed by [ 35 ] that the larger importance of the Southern Ocean for historical heat uptake compared to carbon uptake is a response to the higher aerosol burden over the global north (see more information on Figures S10 and S11, and associated text). Besides process understanding, the results introduced here prove relevant with societal implications. The simulated differences in uptake and release of carbon and heat reiterate that oversimplification of aerosols and its impacts on Earth System feedbacks will lead to uncertainties in the establishment of policy relevant estimates, such as for remaining carbon budgets for example. In fact, the uncertainty added simply by changing the spatial implementation of aerosols in models can account for about half of the remaining carbon budget with a 67% likelihood of limiting warming to 1.5°C [ 13 ]. While there is clear utility of simple metrics to help guide policy processes, it behoves the scientific community to build on these to better account for climate feedback uncertainties, since decisions steaming from such metrics will define climate mitigation and intervention efforts, strengthened economic development opportunities, energy source usage and societal transitions (e.g. [ 36 ]). One further direct example of policy informing outcomes from the experimental design explored here relates to the use of methods that alter atmospheric burden of aerosols. Aerosols-based solar radiation management (SRM), for instance, encompass techniques that deliberately manipulate the radiation budget of the planet. By changing regional distribution of aerosols, they will have a direct impact in the incoming solar shortwave radiation, but will, as shown here, also trigger carbon climate feedbacks, which are associated with uncertain outcomes and temperature development, with even potential regional warming (see Figure S4 (a)). This impact from aerosols redistribution on the carbon cycle has received very limited attention when it comes to such techniques, as well as in scientific research in general. It implies that a more thorough assessment of different aerosol injection strategies, including the types of investigation shown here, would be beneficial to further political decisions on climate intervention. 4.3. Final considerations and limitations The results introduced here corroborate the need for a less simplified consideration of aerosols impacts in the climate, due to associated triggered feedbacks. Caution should be taken, nevertheless, in understanding the temperature variability and individual climate component contributions presented here, as the model used, like any other model, has known shortcomings and biases. While UVic ESCM is able to properly reproduce historical temperature and carbon fluxes, ocean heat fluxes show biases, leading to a simulated higher ocean heat content change than historically observed, and vegetation carbon that is too high in a few regions [ 23 ]. These biases have an impact in the absolute flux values calculated here, for example leading to a likely exaggerated uptake and release of heat by the ocean. However, these characteristics do not alter the simulated patterns of triggered feedbacks between the different aerosols spatial implementations, as these model biases will be the same in the distinct simulations. The simplified nature of the atmospheric model present in UVic ESCM also restricts the analysis of a few processes and variables that are of interest. Foremost, as the model has non-interactive clouds, it does not include responsive indirect aerosol-cloud forcing. The presence of a cloud mask impacts the atmospheric and surface albedo, but interactions between aerosol atmospheric load and cloud formation processes are overlooked by this analysis. Additionally, while we are able to provide aggregate variables that can be included, e.g., in IAMs, to better understand the role of regional aerosol heterogeneity on global mean temperature, we are not able to provide all climatological information needed by downstream impact model frameworks. For example, variables related to precipitation cannot be reliably provided by the simplified two-dimensional atmosphere implemented in this model. In view of the possibilities presented by the model and experimental design included in the current analysis, we recommend that simpler climate models be parametrized to use IAMs regionalized aerosols emissions as inputs to allow for better responses, or improve their baseline approximations, in order to capture the range of uncertainty derived from Earth System responses. Even with the expected model caveats, through our analyses it is clear that estimating aerosols impacts in simple models and metrics has to be implemented with due caution and accounting for a range of possible sources of uncertainty. Disregarding climate feedbacks when incorporating or developing aerosols pathways may imply climate misestimations that account for a considerable headroom in terms of temperature targets under highly ambitious mitigation scenarios. Declarations Author Contribution E.A.M. conducted the analyses. E.A.M. and N.M. interpreted the results and were major contributors in writing the manuscript with added contributions from G.T. and M.J.G.. All authors read and approved the final manuscript. Acknowledgement E.A.M. thanks G.. The authors thank Makcim de Sisto for the useful discussions on simulated land responses. E.A.M. and N.M. are funded under the Emmy Noether scheme by the German Research Foundation (DFG) in the project ‘FOOTPRINTS - From carbOn remOval To achieving the PaRIs agreemeNt’s goal: Temperature Stabilisation’ (ME 5746/1-1). M.J.G. is also affiliated with Pacific Northwest National Laboratory, which did not provide specific support for this paper. 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Lett. 45 2795–804 Rogelj J, Forster P M, Kriegler E, Smith C J and Séférian R 2019 Estimating and tracking the remaining carbon budget for stringent climate targets Nature 571 335–42 Jenkins S, Cain M, Friedlingstein P, Gillett N, Walsh T and Allen M R 2021 Quantifying non-CO 2 contributions to remaining carbon budgets npj Clim Atmos Sci 4 47 Matthews H D, Tokarska K B, Rogelj J, Smith C J, MacDougall A H, Haustein K, Mengis N, Sippel S, Forster P M and Knutti R 2021 An integrated approach to quantifying uncertainties in the remaining carbon budget Commun Earth Environ 2 7 Weaver A J, Eby M, Wiebe E C, Bitz C M, Duffy P B, Ewen T L, Fanning A F, Holland M M, MacFadyen A, Matthews H D, Meissner K J, Saenko O, Schmittner A, Wang H and Yoshimori M 2001 The UVic earth system climate model: Model description, climatology, and applications to past, present and future climates Atmosphere-Ocean 39 361–428 Mengis N, Keller D P, MacDougall A H, Eby M, Wright N, Meissner K J, Oschlies A, Schmittner A, MacIsaac A J, Matthews H D and Zickfeld K 2020 Evaluation of the University of Victoria Earth System Climate Model version 2.10 (UVic ESCM 2.10) Geosci. 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Chang. 12 1136–42 Frölicher T L, Terhaar J, Fortunat J and Silvy Y 2022 Protocol for Adaptive Emission Reduction Approach (AERA) simulations (v2.0) Zenodo Silvy Y, Frölicher T L, Terhaar J, Joos F, Burger F A, Lacroix F, Allen M, Bernadello R, Bopp L, Brovkin V, Buzan J R, Cadule P, Dix M, Dunne J, Friedlingstein P, Georgievski G, Hajima T, Jenkins S, Kawamiya M, Kiang N Y, Lapin V, Lee D, Lerner P, Mengis N, Monteiro E A, Paynter D, Peters G P, Romanou A, Schwinger J, Sparrow S, Stofferahn E, Tjiputra J, Tourigny E and Ziehn T 2024 AERA-MIP: Emission pathways, remaining budgets and carbon cycle dynamics compatible with 1.5 o C and 2 o C global warming stabilization Earth System Dynamics 15 1591–628 Meinshausen M, Nicholls Z R J, Lewis J, Gidden M J, Vogel E, Freund M, Beyerle U, Gessner C, Nauels A, Bauer N, Canadell J G, Daniel J S, John A, Krummel P B, Luderer G, Meinshausen N, Montzka S A, Rayner P J, Reimann S, Smith S J, van den Berg M, Velders G J M, Vollmer M K and Wang R H J 2020 The shared socio-economic pathway (SSP) greenhouse gas concentrations and their extensions to 2500 Geoscientific Model Development 13 3571–605 Stevens B, Fiedler S, Kinne S, Peters K, Rast S, Müsse J, Smith S J and Mauritsen T 2017 MACv2-SP: a parameterization of anthropogenic aerosol optical properties and an associated Twomey effect for use in CMIP6 Geoscientific Model Development 10 433–52 Lund M T, Myhre, Gunnar G and Samset B H 2019 Anthropogenic aerosol forcing under the Shared Socioeconomic Pathways Atmospheric Chemistry and Physics 19 13827–39 Monteiro E A, Silvy Y, Hohn D, Burger F A, Frölicher T L and Mengis N 2024 FROT: A Framework to comprehensively describe radiative contributions to temperature responses Environmental Research Letters 19 124012 Canadell J G, Monteiro P M S, Costa M H, Cotrim da Cinha L, Cox P M, Eliseev A V, Henson S, Ishii M, Jaccard S L, Koven C, Lohila A, Patra P K, Piao S, Rogelj J, Syampungani S, Zaehle S and Zickfeld K 2021 Global Carbon and Other Biogeochemical Cycles and Feedbacks Climate Change 2021 – The Physical Science Basis: Working Group I Contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change ed V Masson-Delmotte, P Zhai, A Pirani, S L Connors, C Péan, S Berger, N Caud, Y Chen, L Goldfarb, M I Gomis, M Huang, K Leitzell, E Lonnoy, J B R Matthews, T K Maycock, T Waterfield, O Yelekçi, R Yu and B Zhou (Cambridge: Cambridge University Press) pp 673–816 Sanderson B M, Booth B B B, Dunne J P, Eyring V, Fisher R, Friedlingstein P, Gidden M J, Hajima T, Jones C D, Jones C, King A, Koven C, Lawrence D M, Lowe J, Mengis N, Peters G P, Rogelj J, Smith C, Snyder A C, Simpson I R, Swann A L S, Tebaldi C, Ilyina T, Schleussner C-F, Seferian R, Samset B H, Van Vuuren D and Zaehle S 2023 The need for carbon emissions-driven climate projections in CMIP7 EGUsphere 2023 1–51 Sanderson B M, Brovkin V, Fisher R, Hohn D, Ilyina T, Jones C, Koenigk T, Koven C, Li H, Lawrence D, Lawrence P, Liddicoat S, MacDougall A H, Mengis N, Nicholls Z, O’Rourke E, Romanou A, Sandstad M, Schwinger J, Seferian R, Sentman L T, Simpson I R, Smith C, Steinert N J, Swann A, Tjiputra J and Ziehn T 2024 flat10MIP: An emissions-driven experiment to diagnose the climate response to positive, zero, and negative CO2 emissions EGUsphere 2024 1–39 Williams R G, Meijers A J S, Roussenov V M, Katavouta A, Ceppi P, Rosser J P and Salvi P 2024 Asymmetries in the Southern Ocean contribution to global heat and carbon uptake Nature Climate Change 14 823–31 IPCC 2023 Climate Change 2023: Synthesis Report. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (Geneva, Switzerland) Additional Declarations No competing interests reported. Supplementary Files aerosolsSI.docx Cite Share Download PDF Status: Published Journal Publication published 03 Feb, 2026 Read the published version in npj Climate and Atmospheric Science → Version 1 posted Editorial decision: Revision requested 28 Oct, 2025 Reviews received at journal 27 Oct, 2025 Reviewers agreed at journal 11 Oct, 2025 Reviews received at journal 25 Sep, 2025 Reviewers agreed at journal 09 Sep, 2025 Reviewers agreed at journal 07 Sep, 2025 Reviewers invited by journal 05 Sep, 2025 Editor assigned by journal 05 Sep, 2025 Submission checks completed at journal 05 Sep, 2025 First submitted to journal 31 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7502615","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":512396981,"identity":"72cdaf0c-6bdf-4f3d-a53c-f3d31052c2a9","order_by":0,"name":"Estela A. Monteiro","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3klEQVRIiWNgGAWjYPACCQYG9gYYJ4EIDQdAWngOkKYFZBFcJQEt/GKHjz3+UGGRzy/5/OKDjzl2+QzsyQfwapGcnZZucOCMhOXM2TnFhjO3JVs28DzDb43B7RwziYNtEgZARpo07zZmAwaJHAO8WuzBWv4Btdw8k/6bd1s9UEv+B/y2SIO0NAC13GA/xsy77TDIFrw6GCRup6VJnDkmYSDZk8MsOXPbcQM2nmf4HcY/O/mYREVNnQE/+/GHHz5uqwYykh/gtwYBeCCGsxGrHgjYiTZ8FIyCUTAKRhgAABW1Q6uDTH8fAAAAAElFTkSuQmCC","orcid":"","institution":"GEOMAR Helmholtz Center for Ocean Research Kiel","correspondingAuthor":true,"prefix":"","firstName":"Estela","middleName":"A.","lastName":"Monteiro","suffix":""},{"id":512396982,"identity":"9140933b-5138-400a-bbd8-293022e74b91","order_by":1,"name":"Giang Tran","email":"","orcid":"","institution":"GEOMAR Helmholtz Center for Ocean Research Kiel","correspondingAuthor":false,"prefix":"","firstName":"Giang","middleName":"","lastName":"Tran","suffix":""},{"id":512396985,"identity":"04bd67fc-212f-48b3-8818-43ce888de5ec","order_by":2,"name":"Matthew J. Gidden","email":"","orcid":"","institution":"Center for Global Sustainability, University of Maryland","correspondingAuthor":false,"prefix":"","firstName":"Matthew","middleName":"J.","lastName":"Gidden","suffix":""},{"id":512396988,"identity":"26be2201-b58e-4617-9d7a-13ea98976966","order_by":3,"name":"Nadine Mengis","email":"","orcid":"","institution":"GEOMAR Helmholtz Center for Ocean Research Kiel","correspondingAuthor":false,"prefix":"","firstName":"Nadine","middleName":"","lastName":"Mengis","suffix":""}],"badges":[],"createdAt":"2025-08-31 19:53:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7502615/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7502615/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41612-026-01343-6","type":"published","date":"2026-02-03T15:59:28+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":91347427,"identity":"60473bb0-aad1-415f-8f83-99b5ce872d86","added_by":"auto","created_at":"2025-09-15 14:05:18","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":204824,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eComparison between the default and the no plumes experiment over 1850-2100: (a) Hovmöller diagram of the difference in aerosol optical depth (AOD) input to UVic ESCM version 2.10 between the no plumes and default experiments, (b)\u003c/em\u003e\u003cem\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/em\u003e\u003cem\u003esimulated globally averaged aerosols radiative forcing (W m\u003c/em\u003e\u003csup\u003e\u003cem\u003e-2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e) and (c)\u003c/em\u003e\u003cem\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/em\u003e\u003cem\u003esimulated globally averaged atmospheric carbon burden (ppm), in (b, c) for the no plumes (brown line) and default (blue line) experiments. (d) Stacked contributions (coloured bars—see legend) of difference in atmospheric radiative burden (ARB) between no plumes and default experiments from the start of the pre-industrial period in 1850 until the end of the 21\u003c/em\u003e\u003csup\u003e\u003cem\u003est\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e century. The black hatched bars indicate the net ARB difference from the sum of the considered contributions (referring to left y axis), while the purple line represents the temperature difference between the two experiments (referring to right y axis).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7502615/v1/4273ba00382d1e28cfcceaec.png"},{"id":91348659,"identity":"3aa7b0e9-05cc-4ffe-9a81-12078726ea1b","added_by":"auto","created_at":"2025-09-15 14:13:19","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":118677,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eTime-latitude Hovmöller diagram of the difference between experiments no plumes and default: (a)\u003c/em\u003e\u003cem\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/em\u003e\u003cem\u003efor land carbon uptake anomaly (PgC) and (b)\u003c/em\u003e\u003cem\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/em\u003e\u003cem\u003efor ocean heat uptake anomaly (W m\u003c/em\u003e\u003csup\u003e\u003cem\u003e-2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e), from the start of the pre-industrial period in 1850 until the end of the 21\u003c/em\u003e\u003csup\u003e\u003cem\u003est\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e century. Values are given for a rolling latitude average and positive values indicate higher fluxes on the no plumes experiment, while negative values indicate lower fluxes.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7502615/v1/0373fbb308aae97142636a53.png"},{"id":91347428,"identity":"5a42a7ec-d580-49d8-a537-c96f15792877","added_by":"auto","created_at":"2025-09-15 14:05:18","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":133510,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eComparison between the experiments with aerosols over only specific areas and the no plumes experiment: Stacked contributions to difference in atmospheric radiative burden (ARB) from all contributors (coloured bars—see legend) between (a) no plumes only land and no plumes and between (b) no plumes only ocean and no plumes, from the start of the pre-industrial period in 1850 until the end of the 21\u003c/em\u003e\u003csup\u003e\u003cem\u003est\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e century. The black hatched bars indicate the net ARB difference from the sum of the considered contributions (referring to left y axis), while the purple line represents the temperature difference between the two experiments (referring to right y axis). The inset figures show the radiative forcing from aerosol for the no plumes default simulation as a solid brown line, and the respective experiment as a dashed blue line.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7502615/v1/e3aa48eaff01e16ad1be56a0.png"},{"id":91347432,"identity":"d5685ee7-8ae6-4c02-91f6-4166e7cf2c7c","added_by":"auto","created_at":"2025-09-15 14:05:19","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":161748,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eTime-latitude Hovmöller diagram of the difference between experiments only land and no plumes: (a) for land carbon uptake anomaly (PgC) and (b)\u003c/em\u003e\u003cem\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/em\u003e\u003cem\u003efor ocean heat uptake anomaly (W m\u003c/em\u003e\u003csup\u003e\u003cem\u003e-2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e), from the start of the pre-industrial period in 1850 until the end of the 21\u003c/em\u003e\u003csup\u003e\u003cem\u003est\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e century. Values are given for a rolling latitude mean and positive values indicate higher fluxes on the only land experiments, while negative values indicate lower fluxes.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7502615/v1/64f91a015ef34789b4843676.png"},{"id":91347431,"identity":"c2417845-2730-4690-9ac4-c9fd666c55c6","added_by":"auto","created_at":"2025-09-15 14:05:18","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":122926,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eComparison between the experiments with aerosols over only one hemisphere and the no plumes experiment:\u003c/em\u003e\u003cem\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/em\u003e\u003cem\u003eStacked contributions to difference in atmospheric radiative burden (ARB) from all contributors (coloured bars—see legend) (a) between no plumes Northern Hemisphere and no plumes and (b)\u003c/em\u003e\u003cem\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/em\u003e\u003cem\u003ebetween no plumes Southern Hemisphere and no plumes, from the start of the pre-industrial period in 1850 until the end of the 21\u003c/em\u003e\u003csup\u003e\u003cem\u003est\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e century. The black hatched bars indicate the net burden from the sum of the contributors considered (referring to left y axis), while the purple line in represents the temperature variability (referring to right y axis). The inset figures show the radiative forcing from aerosol for the no plumes default simulation as a solid brown line, and the respective experiment as a dashed blue line.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7502615/v1/840df597561323b01536026d.png"},{"id":91347433,"identity":"598a1e80-bdcb-4a2a-876e-78fe911dedc6","added_by":"auto","created_at":"2025-09-15 14:05:19","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":142478,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eTime-latitude Hovmöller diagram of the difference between experiments only Southern Hemisphere and no plumes: (a) for land carbon uptake anomaly (PgC)\u003c/em\u003e\u003cem\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/em\u003e\u003cem\u003eand (b) for ocean heat uptake anomaly (W m\u003c/em\u003e\u003csup\u003e\u003cem\u003e-2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e), from the start of the pre-industrial period in 1850 until the end of the 21st century. Values are given for a rolling latitude mean and positive values indicate higher fluxes on the only Southern Hemisphere experiment, while negative values indicate lower fluxes.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7502615/v1/51232c85642b05fbb76d823f.png"},{"id":102234163,"identity":"6fcf81e2-1f31-473e-baf9-c53fd9a2f1c4","added_by":"auto","created_at":"2026-02-09 16:06:55","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1515554,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7502615/v1/b541bf9e-10c9-4654-95a7-91d016c844fd.pdf"},{"id":91347445,"identity":"278b3877-1e39-4f82-b920-391413a5d11c","added_by":"auto","created_at":"2025-09-15 14:05:19","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":4774633,"visible":true,"origin":"","legend":"","description":"","filename":"aerosolsSI.docx","url":"https://assets-eu.researchsquare.com/files/rs-7502615/v1/375dfdf0278be49eea108053.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Carbon-climate feedbacks to spatial aerosol model implementation variations","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eAerosols are currently the largest source of uncertainty in evaluating the Earth\u0026rsquo;s climate feedbacks to anthropogenic forcing [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Overall, aerosols\u0026rsquo; contribution is estimated as a net negative forcing of -1.1 [-1.7 to -0.4] W m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e between 1750\u0026ndash;2019, the largest negative contribution to a change in effective radiative forcing. The magnitude of aerosols contribution is similar to, for example, that of non-CO\u003csub\u003e2\u003c/sub\u003e well-mixed greenhouse gases in the same period, which are responsible for a warming forcing of 1.16 [1.05 to 1.17] W m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e, with aerosols uncertainty, as expected, being much higher due to its distinct characteristics. From a physical point of view aerosols have a direct and an indirect effect on atmospheric radiative properties. Direct effects are due to their absorption and scattering impacts on the incoming solar shortwave radiation, while in the atmosphere aerosols can also interact with clouds, altering its microphysical characteristics and leading to an indirect effect on the properties of the atmosphere (see for example [\u003cspan additionalcitationids=\"CR3 CR4\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]). Furthermore, the aerosols distribution is spatially and temporally heterogeneous. Emission plumes from point sources, commonly associated with human activities, in combination with a short atmospheric residence time cause aerosol optical depth to be on average 1.4 times higher over land areas compared to over oceans [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eSuch characteristics of aerosols contribute to the current physical uncertainties of aerosol forcing, and also impact the range of future projections of this forcing, which is dependent additionally on future scenarios uncertainty. Scenario uncertainty in this context refers to deep uncertainty in future developments of aerosol emissions, which varies based on socio-economic choices and political decisions [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In an attempt to explore this source of uncertainty, integrated assessment models (IAMs) are used to develop a multitude of plausible socio-economic scenarios [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. IAMs include representations of different economic sectors, socio-economic variables and technical parameters [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], to provide future scenarios of anthropogenic climate forcing. Due to their focus on the socio-economic systems, IAMs employ so-called simple climate models with various simplifications and assumptions. These involve both their representation of aerosols, with simplified patterns (see for example [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]), parametrization of radiative forcing impacts (e.g. [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] or scaling factors), as well as limitations on feedbacks between the carbon cycle and the climate [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Even in simple climate models with a more realistic representation of the carbon cycle, interactions between physical and biogeochemical components are not typically present in either these models or the IAMs, being provided only by the Earth system models [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. These simplifications in the coupled components results in a lack of representation of carbon-climate feedbacks.\u003c/p\u003e\u003cp\u003eFeedbacks between the carbon cycle and the climate relate to carbon exchanges between Earth\u0026rsquo;s components and how the efficiency of these processes is interconnected to changes in the climate, which in turn are directly affected by the weakening or strengthening of such fluxes [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The uptake of carbon by the ocean and the land, as well as permafrost carbon emissions, are among the processes that contribute to the reinforcement of these feedbacks and the uncertainty added to future CO\u003csub\u003e2\u003c/sub\u003e development projections and the associated surface air temperature (e.g. [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]). As a result, carbon cycle feedbacks will play a role in controlling temperature responses to emitted carbon, and add to the uncertainty of transient climate response to cumulative CO\u003csub\u003e2\u003c/sub\u003e emissions (TCRE) [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], carbon budgets [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] and ultimately whether temperature targets can be reached or not. Processes or components that alter these feedbacks are, therefore, of great importance to the assessment of future climate potential development, as is the case with aerosols. The spatially heterogenous distribution of aerosols can lead to heterogeneities in regional temperature patterns and the respective processes of carbon and heat uptake.\u003c/p\u003e\u003cp\u003eAs stated, the importance of carbon feedbacks to understand the development of the climate has been intensely discussed. However, similar to the assumptions made in simple climate models, metrics and linear models employed for the estimation of the remaining carbon budget commonly combine all non-CO\u003csub\u003e2\u003c/sub\u003e forcing into one globally aggregated value (e.g. [\u003cspan additionalcitationids=\"CR18 CR19 CR20\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]). They assume no non-linearities between forcing and carbon cycle responses, and disregard the spatial temporal differences between aerosols and other GHGs as well as their potential carbon climate feedbacks.\u003c/p\u003e\u003cp\u003eIn this study, we compare climate-carbon responses under distinct implementations of aerosols\u0026rsquo; spatial forcing, in an attempt to disentangle the impact of reduced complexities, such as seen in simple climate models or linear metrics, on possible climate uncertainties for both the historical period and future scenarios. The use of distinct spatial implementations of aerosols is shown to have the potential to trigger carbon cycle feedbacks, and directly impact atmospheric carbon burden, temperature and other feedback processes.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Employed Earth system model and simulation scenario\u003c/h2\u003e\u003cp\u003eThe results presented in the next section are simulated by an intermediate complexity model, the University of Victoria Earth System Climate Model - UVic ESCM version 2.10 [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. It includes 19 ocean vertical levels, 14 terrestrial soil levels, permafrost and dynamic vegetation modules, on a 3.6\u0026deg;x1.8\u0026deg; horizontal grid. The atmosphere is represented by a two-dimensional energy moisture balance model [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], with a cloud mask integrated only onto the atmospheric albedo. This implies that changes in the aerosols\u0026rsquo; implementations will alter only the direct effect of aerosols on the climate. Notwithstanding, the UVic ESCM has been shown to perform well in terms of carbon cycle and temperature responses in historical simulations [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], a relevant feature to the exploration of triggered feedbacks included here. In fact, the simplicity of this model in comparison to a fully-coupled one is an advantage that allows us to easily disentangle the effects of the different aerosol implementations.\u003c/p\u003e\u003cp\u003eFor the baseline scenario, we follow the CO\u003csub\u003e2\u003c/sub\u003e emissions trajectory of the UVic ESCM that resulted from the 1.5\u0026deg;C no overshoot scenario conceived for the Adaptive Emissions Reduction Approach [\u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. This approach iteratively calculates the necessary CO\u003csub\u003e2\u003c/sub\u003e emissions trajectory for stabilising surface air temperature at 1.5\u0026deg;C on a 5-year basis, dependent only upon the simulated temperature and the previous radiative forcing and emissions pathways. The aerosol, the non-CO\u003csub\u003e2\u003c/sub\u003e greenhouse gases and the land use change forcings follow the Shared Socioeconomic Pathway 1 (SSP1 - [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]). The experiments start from the pre-industrial period in 1850, and are simulated until the end of the baseline scenario in 2100. For all aerosol implementation variation experiments described here, forcing other than aerosols are kept the same.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Aerosols implementation variations\u003c/h2\u003e\u003cp\u003eIn this default setting, UVic ESCM treats aerosol forcing as spatially-masked yearly aerosol optical depth (AOD) data (\u003cem\u003edefault\u003c/em\u003e simulation). The UVic ESCM aerosol forcing is based on the work from [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], who developed parametrizations of sulphate-like, and in smaller scale nitrate-like, aerosols optical properties. This is a plume-based model, where aerosols emissions originate from nine spatial plumes in distinct source regions, which are fitted to a present-day climatology, and scaled to match historical anthropogenic emissions in each region. The plumes represent both industrial emissions and biomass burning, with each\u0026rsquo;s respective seasonal cycle (more information on the temporal response component can be found in Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e and associated text). In the UVic ESCM, aerosols emitted by plumes account only for direct radiative effects, and a scaling factor was implemented in tuning the model to historical period observations [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTo explore the spatial dependencies in aerosol implementations, we design other narratives that support improved understanding of climate-carbon uncertainties:\u003c/p\u003e\u003cp\u003e1) To understand the impact of spatially resolved AOD forcing, we implement an area weighted globally averaged AOD forcing (\u003cem\u003eno plumes\u003c/em\u003e simulation) resulting in a different spatial temporal forcing (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e (a)). We then adjust the aerosol forcing data utilizing the UVic ESCM aerosol scaling factor, when necessary, to have the final effective radiative forcing with the same magnitude as that for the \u003cem\u003edefault\u003c/em\u003e simulation.\u003c/p\u003e\u003cp\u003eSimulations such as \u003cem\u003eno plume\u003c/em\u003e can denote implementations of global aerosol emissions forcing derived from integrated assessment models or from future scenarios that provide only the final global mean effective radiative forcing of non-CO\u003csub\u003e2\u003c/sub\u003e contributions without making assumptions about the source regions.\u003c/p\u003e\u003cp\u003e2) To disentangle ocean and land carbon-cycle impacts, we design a second idealised set of experiments, where we applied aerosol forcing over land or over ocean areas (\u003cem\u003eonly land\u003c/em\u003e, and \u003cem\u003eonly ocean\u003c/em\u003e experiments, respectively). The remaining areas in each experiment are assumed to have no aerosols in the atmosphere above them. Once again, in this second set of experiments, the global total aerosol forcing is adjusted to have the final effective radiative forcing with the same magnitude as that in the \u003cem\u003edefault\u003c/em\u003e simulation.\u003c/p\u003e\u003cp\u003e3) Finally, to explore the carbon-climate impact of a Northern Hemisphere dominated aerosol spatial distribution compared to a Southern Hemisphere dominated distribution we design the final set of idealised experiments (\u003cem\u003eNorth Hemisphere (NH)\u003c/em\u003e and \u003cem\u003eSouth Hemisphere (SH)\u003c/em\u003e experiments, respectively), acknowledging a likely southward strengthening of aerosol forcing in future scenarios [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The opposite hemisphere in each simulation is implemented with zero aerosol content. Finally, for consistency, the global total aerosol forcing is adjusted to have the final effective radiative forcing with the same magnitude as that in the \u003cem\u003edefault\u003c/em\u003e simulation.\u003c/p\u003e\u003cp\u003eFor the idealised experiments (in section 3.2 and 3.3), we used the \u003cem\u003eno plumes\u003c/em\u003e simulation as a reference, since it allows for a clearer distinction of the responses. By prescribing these different narratives of the aerosol spatial implementations, we are able to investigate responses from carbon cycle and climate feedbacks, pointing out missing feedbacks in simplified aerosol representations.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Analysis framework\u003c/h2\u003e\u003cp\u003eTo analyse the experiments and understand the distinct contribution from all forcings and the carbon cycle, heat fluxes and Earth system responses, we used FROT (Framework for radiative contribution to temperature response \u0026ndash; [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]). Under FROT, all radiative forcing as well as system feedbacks are converted to the same metric (in W m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e), which defines the final burden in the atmosphere driving the surface air temperature variability, named atmospheric radiative burden (ARB). ARB, as applied here, connects the cumulative impact the different climate components have had in the system throughout the experiment, using the simulated heat and carbon fluxes. This framework is ideally suited to compare the individual contributions of distinct processes to the temperature development and climate feedbacks in our different scenarios. More information on the individual simulated values for each contributor are explored over Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e3.1. Carbon-climate feedbacks from spatially resolved aerosol implementations\u003c/h2\u003e\u003cp\u003eDespite the same global average aerosol forcing, the spatially resolved AOD implementation has a distinct radiative forcing pattern compared to the \u003cem\u003eno plumes\u003c/em\u003e experiment, and the associated carbon-climate feedbacks cause differences in the simulated surface air temperature (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Removing the spatial aspect of the aerosol implementation, i.e., moving from \u003cem\u003edefault\u003c/em\u003e to \u003cem\u003eno plumes\u003c/em\u003e, results in a simulated air temperature that is up to 0.096\u0026deg; C higher in the latter (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e (d), purple line). The highest surface air temperature differences between the experiments \u003cem\u003edefault\u003c/em\u003e and \u003cem\u003eno plumes\u003c/em\u003e are simulated, as expected, over the years when aerosols radiative forcing is strongest (negative most values in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e (b)). More details on this mathematical relation can be found in the Supplementary Material (Figure S2).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe main drivers of this temperature difference in terms of Earth system responses, are the impacts onto land carbon uptake and ocean heat uptake (contributing 71% and 23% to the gross warming in 2020 and 81% to the gross warming and 8% to the gross cooling by the end of the century, respectively). The \u003cem\u003eno plumes\u003c/em\u003e experiment simulates a lower land carbon uptake (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e (d) and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e (a)) due to the relative reduction of the aerosol load over land areas, where the plumes are located. The driving process behind this reduced land carbon uptake is the increase in temperature-driven soil respiration (see SI Figure S3) due to the relatively lower cooling (i.e., warmer temperatures) by aerosols over land (Figure S4), especially in the Northern Hemisphere for higher latitudes during the historical phase and for mid latitude until the end of the century. A small increase in vegetation primary production is also seen associated with the relatively lower cooling, its contribution to carbon uptake being smaller than the simulated increase in soil carbon and respiration, resulting in comparatively lower carbon uptake. This reduction in terrestrial carbon uptake is most prominent in mid to high northern latitudes (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e (a)), and in tropical and subtropical regions of the globe towards the end of the century. This southern shift corresponds well with the southward movement of the aerosol optical depth in the \u003cem\u003edefault\u003c/em\u003e experiment. The decrease in land carbon uptake in the experiment with globally uniform aerosol loads can be associated to differences in the vegetation cover of dominant plant functional types, specifically the needleleaf trees (for which vegetation carbon increases) and grasses and shrubs (which show a smaller carbon pool) (see Figure S4). On a smaller scale, ocean carbon uptake is overall increased especially in the Southern Hemisphere (see Figure S5).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAdditionally, having a globally uniform aerosol forcing implies a higher than default aerosol load over the ocean, which decreases the incoming shortwave radiation at the ocean surface and accordingly the ocean heat uptake. This signal is more pronounced in the Southern Hemisphere, due to its larger ocean areas (see Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e (b)). The Northern Hemisphere subtropical regions, in contrast, show an increase in ocean heat uptake. The Northern Hemisphere subpolar region shows changing signs in the ocean heat fluxes by the ocean, especially towards the end of the historical period, with periods of weakened fluxes in the case of globally uniform aerosol implementations. This is driven by differences in sea ice cover and ventilation depth in the high latitudes of the North Atlantic, where heat content stored in the ocean is higher as ventilation depth increases and sea ice area decreases with a spatially explicit aerosol forcing being implemented. The global aggregated signal is a reduction in ocean heat uptake in the \u003cem\u003eno plumes\u003c/em\u003e experiment, which contributes to an increase in surface air temperature.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e3.2. Carbon-climate responses from aerosols located only over specific areas\u003c/h2\u003e\u003cp\u003eTo disentangle the land and ocean carbon-climate responses to spatial aerosol forcing we constrain the following experiments to exhibit aerosol forcing only over land or over the ocean, respectively. When aerosols are implemented uniformly over \u003cem\u003eonly land\u003c/em\u003e with a comparable global mean radiative forcing magnitude, land carbon uptake is increased relative to a simulation with globally uniform aerosol implementation (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e (a)). The combined impact (see SI Figure S6 for more information) of decreased soil respiration due to lower temperatures and marginally increased vegetation primary production due to less heat stress contributes to a reduced atmospheric CO\u003csub\u003e2\u003c/sub\u003e concentration. Consequentially, when aerosols are implemented over \u003cem\u003eonly land\u003c/em\u003e maximum temperature differences to \u003cem\u003eno plumes\u003c/em\u003e are \u003cem\u003eca.\u003c/em\u003e \u0026minus;\u0026thinsp;0.09\u0026deg;C. The main areas in which higher land carbon uptake can be seen are the mid- to high- latitude regions in the Northern Hemisphere and subtropical areas in the Southern Hemisphere (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e (a)). These regional responses on land carbon uptake strengthen in the middle of the 21st century, indicating that, despite the decreasing forcing from the aerosols in the experiments, the climate-carbon effect persists. By the end of century, land carbon uptake contributes 94% to the gross cooling in the \u003cem\u003eonly land\u003c/em\u003e experiment in comparison to the \u003cem\u003eno plumes\u003c/em\u003e experiment.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThis aerosol implementation with aerosols over \u003cem\u003eonly land\u003c/em\u003e shows an initial increase in ocean heat uptake (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e (a)), dominated by an increase in heat uptake over the Southern Hemisphere (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e (b)), which turns into a warming contribution in the middle of the 21st century (with 8.2% of gross warming by the end of the century). Additionally, we find a similar feature in this experiment comparison to the \u003cem\u003eno plumes \u0026ndash; default\u003c/em\u003e results, with ocean heat uptake sign alternation\u0026rsquo;s timing and magnitude in the northern high latitudes. We find that the \u003cem\u003eonly land\u003c/em\u003e experiment reinforces the effects seen in a more realistic aerosol implementation, i.e. with plumes. As before, the Southern Hemisphere, known to contribute the most to ocean heat uptake, is observed to have strengthened fluxes, while the Northern Hemisphere, which has a smaller role in ocean heat uptake, decreases its contribution to the ocean heat content.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAn interesting characteristic of the heat uptake process is that even if the forcing is implemented without spatial detailing of \u003cem\u003eplumes\u003c/em\u003e, a very clear inter-hemispherical difference is present. Heat uptake is mediated by physical processes, which will define areas of release and uptake of heat, as well as the efficiency in these processes. It is important to highlight that the majority of the ocean areas in the experiments described here do not shift from uptake to release regions, for example, but instead remain with the exchange signature defined by the local physical processes.\u003c/p\u003e\u003cp\u003eAerosols implemented over \u003cem\u003eonly ocean\u003c/em\u003e affect both the carbon cycle and its feedbacks, leading to a decrease in land carbon uptake (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e (b)). This response is extremely similar, but in opposite sign, to the \u003cem\u003eonly land\u003c/em\u003e simulation, with an overall much smaller magnitude. Detailed information on more specific responses for \u003cem\u003eonly ocean\u003c/em\u003e simulations can be found in the Supplementary Information (Figures S6, S7 and associated text). The patterns described here highlight the similarity of the \u003cem\u003eonly ocean\u003c/em\u003e simulation to the \u003cem\u003eno plumes\u003c/em\u003e one. In a similar sense, the experiment \u003cem\u003eonly land\u003c/em\u003e is an imperfect analogue to the real world, presenting an enhanced sensitivity similar to observed historical responses, and expected future changes.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.3. Carbon-climate responses from aerosols over only a hemisphere\u003c/h2\u003e\u003cp\u003eThis final section explores the development of temperature as well as carbon and heat responses over hypothetical narratives in which aerosols are only present in one of the hemispheres.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWhen aerosols are present only over the \u003cem\u003eNorthern Hemisphere\u003c/em\u003e, small anomalies are seen in ocean and land carbon uptake, as well as in heat uptake (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e (a)). As a result, the temperature anomaly to \u003cem\u003eannual no plumes\u003c/em\u003e does not surpass \u0026minus;\u0026thinsp;0.047\u0026deg;C throughout the simulation, being close to zero over the historical period, and negative by the end of the century. Towards the end of the 21st century, an increase in land carbon uptake dominates the cooling of the climate. This contribution, however, only accounts for about 70% of all cooling compared to \u003cem\u003eno plumes\u003c/em\u003e, a smaller percentage than what is observed in other experiments. Further discussions on the driving mechanisms behind this simulation are provided in the Supplementary Information (see Figures S8 and S9).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWhen atmospheric optical depth is non-zero only in the \u003cem\u003eSouthern Hemisphere\u003c/em\u003e surface air temperature is higher than in the default \u003cem\u003eno plumes\u003c/em\u003e experiment over both the historical period and future development (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e (b)). A larger response from the land carbon and permafrost uptake are noticeable, accounting for 71% and 15% of the warming by the end of the century compared to the \u003cem\u003eno plumes\u003c/em\u003e experiment, respectively. Despite a slight increase in net primary production, higher soil respiration rates in the \u003cem\u003eSouthern Hemisphere only\u003c/em\u003e experiment cause a loss in the land carbon uptake (Figure S8). Most of the Northern Hemisphere sees a reduction in the land carbon uptake potential, both in terms of the historical period and future scenario until the end of the century (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e (a)). Ocean heat uptake shows overall negative anomalies, i.e. less ocean heat uptake, contributing \u003cem\u003eca.\u003c/em\u003e 14% to the gross warming by the end of the century. This response is driven by a reduced uptake over the Southern Hemisphere (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e (b)). The Northern Hemisphere on the contrary shows mostly an increase in heat uptake, associated to a reduced aerosol load in the atmosphere above it. However, high latitudes of the Northern Hemisphere also show short periods of reduced ocean heat fluxes over the historical period. The combined effect from these different ocean areas contributes to the lower heat uptake throughout the simulation. The final temperature anomalies to \u003cem\u003eno plumes\u003c/em\u003e reach around 0.07\u0026deg;C.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e4.1. Aerosol implementation choices in model experiments impact carbon-climate feedbacks\u003c/h2\u003e\u003cp\u003eIn the current study we have shown that aerosol implementation choices can lead to substantial differences in carbon and heat feedbacks, resulting in surface air temperature differences of up to almost 0.1\u0026deg;C, even if the same global mean radiative forcing is achieved. While such anomalies may appear small in magnitude, in an ambitious emissions mitigation setting such contributions are considerable, reducing the effective remaining carbon budget for a given temperature limit by \u003cem\u003eca.\u003c/em\u003e 200 GtCO\u003csub\u003e2\u003c/sub\u003e (using a TCRE estimate of 0.45\u0026deg;C per 1000 GtCO\u003csub\u003e2\u003c/sub\u003e [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]). Using more-idealised experiments, we were able to identify the driving processes behind the different Earth System responses, finding land surface temperature, soil respiration, ventilation depth, and sea ice extent to be dominating drivers due to the distinct aerosol implementation choices.\u003c/p\u003e\u003cp\u003eIn addition to distinct relative contributions of such drivers to the temperature development, the spatial different implementations are shown to trigger carbon and climate feedbacks that cause both cooling and warming in the Earth System depending on the implementation explored here. The contributions from land carbon uptake to temperature differences between the simulations can range between 70% of the warming to 94% of the cooling modelled. Similarly, permafrost varies from 6% of cooling to 15% of warming impact, while ocean heat uptake can contribute from 8% in cooling up to 14% in the warming of the planet between different simulations by the end of the century.\u003c/p\u003e\u003cp\u003eConsidering that simple climate models and integrated assessment models (IAMs) make use of simplifications for the natural system responses when providing potential future climate scenarios, our results show that these assumptions will contribute to an additional source of uncertainty in the aerosol impacts. We recommend that simple climate models add constrains that capture the regional aerosol variations of Earth system models, such that they can inform IAMs. Utilizing our intermediate complexity model as an example, it is possible to establish a mathematical relationship between the temperature difference from aerosol spatial implementations and the simulated aerosols radiative forcing, as shown for the \u003cem\u003eno plumes\u003c/em\u003e case on the Supplementary Information (Figure S2).\u003c/p\u003e\u003cp\u003eIn a similar sense, a potential source of error is introduced when implementing aggregating or carbon-based metrics, as they include aerosols radiative forcing only in global terms, disregarding its spatial signal and feedback triggers. In both cases, expected atmospheric responses and global temperatures, as well as remaining carbon budgets will be over- or underestimated, as carbon-climate feedbacks are disregarded.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e4.2. Further implications from aerosol implementations\u003c/h2\u003e\u003cp\u003eEven more specific conclusions can be drawn from mimicking Earth system situations as here, in addition to providing a clearer characterization of the impact aerosol pathway development assumptions have to future scenarios and model implementation,\u003c/p\u003e\u003cp\u003eA first implication that can be obtained from expanding the findings reported here is that an appropriate aerosols implementation that allows for the inclusion of correct biophysical effects of triggered carbon-climate feedbacks will become of higher importance for upcoming model intercomparison efforts. Previous rounds of the Coupled Model Intercomparison Project (CMIP) included mostly concentrations driven experiments, where such impact sensitivities are not considered. However, future efforts are moving towards emissions-driven simulations [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], for which differences in aerosol forcing in the models will have an additional and non-neglectable impact on the carbon-climate feedbacks, associated processes and estimates of, for example, land and ocean carbon uptake as well as ocean heat uptake.\u003c/p\u003e\u003cp\u003eFurthermore, one process understanding case that can be explored based on the results found here is that of the effects of heat uptake by the ocean in the experiment where aerosols are found uniquely over the Southern Hemisphere. For this experiment reductions in heat uptake, and in some regions increase in heat release, can be seen especially over the Atlantic and part of the Indian and Pacific sectors of the Southern Ocean (Figure S11). At the same time, the Northern Hemisphere\u0026rsquo;s subtropics to high latitudes in the Pacific show an increase in uptake, while other areas of release of heat have a decreased signal. This corroborates the hypothesis posed by [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] that the larger importance of the Southern Ocean for historical heat uptake compared to carbon uptake is a response to the higher aerosol burden over the global north (see more information on Figures S10 and S11, and associated text).\u003c/p\u003e\u003cp\u003eBesides process understanding, the results introduced here prove relevant with societal implications. The simulated differences in uptake and release of carbon and heat reiterate that oversimplification of aerosols and its impacts on Earth System feedbacks will lead to uncertainties in the establishment of policy relevant estimates, such as for remaining carbon budgets for example. In fact, the uncertainty added simply by changing the spatial implementation of aerosols in models can account for about half of the remaining carbon budget with a 67% likelihood of limiting warming to 1.5\u0026deg;C [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. While there is clear utility of simple metrics to help guide policy processes, it behoves the scientific community to build on these to better account for climate feedback uncertainties, since decisions steaming from such metrics will define climate mitigation and intervention efforts, strengthened economic development opportunities, energy source usage and societal transitions (e.g. [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]).\u003c/p\u003e\u003cp\u003eOne further direct example of policy informing outcomes from the experimental design explored here relates to the use of methods that alter atmospheric burden of aerosols. Aerosols-based solar radiation management (SRM), for instance, encompass techniques that deliberately manipulate the radiation budget of the planet. By changing regional distribution of aerosols, they will have a direct impact in the incoming solar shortwave radiation, but will, as shown here, also trigger carbon climate feedbacks, which are associated with uncertain outcomes and temperature development, with even potential regional warming (see Figure S4 (a)). This impact from aerosols redistribution on the carbon cycle has received very limited attention when it comes to such techniques, as well as in scientific research in general. It implies that a more thorough assessment of different aerosol injection strategies, including the types of investigation shown here, would be beneficial to further political decisions on climate intervention.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e4.3. Final considerations and limitations\u003c/h2\u003e\u003cp\u003eThe results introduced here corroborate the need for a less simplified consideration of aerosols impacts in the climate, due to associated triggered feedbacks. Caution should be taken, nevertheless, in understanding the temperature variability and individual climate component contributions presented here, as the model used, like any other model, has known shortcomings and biases. While UVic ESCM is able to properly reproduce historical temperature and carbon fluxes, ocean heat fluxes show biases, leading to a simulated higher ocean heat content change than historically observed, and vegetation carbon that is too high in a few regions [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. These biases have an impact in the absolute flux values calculated here, for example leading to a likely exaggerated uptake and release of heat by the ocean. However, these characteristics do not alter the simulated patterns of triggered feedbacks between the different aerosols spatial implementations, as these model biases will be the same in the distinct simulations.\u003c/p\u003e\u003cp\u003eThe simplified nature of the atmospheric model present in UVic ESCM also restricts the analysis of a few processes and variables that are of interest. Foremost, as the model has non-interactive clouds, it does not include responsive indirect aerosol-cloud forcing. The presence of a cloud mask impacts the atmospheric and surface albedo, but interactions between aerosol atmospheric load and cloud formation processes are overlooked by this analysis. Additionally, while we are able to provide aggregate variables that can be included, e.g., in IAMs, to better understand the role of regional aerosol heterogeneity on global mean temperature, we are not able to provide all climatological information needed by downstream impact model frameworks. For example, variables related to precipitation cannot be reliably provided by the simplified two-dimensional atmosphere implemented in this model.\u003c/p\u003e\u003cp\u003eIn view of the possibilities presented by the model and experimental design included in the current analysis, we recommend that simpler climate models be parametrized to use IAMs regionalized aerosols emissions as inputs to allow for better responses, or improve their baseline approximations, in order to capture the range of uncertainty derived from Earth System responses.\u003c/p\u003e\u003cp\u003eEven with the expected model caveats, through our analyses it is clear that estimating aerosols impacts in simple models and metrics has to be implemented with due caution and accounting for a range of possible sources of uncertainty. Disregarding climate feedbacks when incorporating or developing aerosols pathways may imply climate misestimations that account for a considerable headroom in terms of temperature targets under highly ambitious mitigation scenarios.\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eE.A.M. conducted the analyses. E.A.M. and N.M. interpreted the results and were major contributors in writing the manuscript with added contributions from G.T. and M.J.G.. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eE.A.M. thanks G.. The authors thank Makcim de Sisto for the useful discussions on simulated land responses. E.A.M. and N.M. are funded under the Emmy Noether scheme by the German Research Foundation (DFG) in the project \u0026lsquo;FOOTPRINTS - From carbOn remOval To achieving the PaRIs agreemeNt\u0026rsquo;s goal: Temperature Stabilisation\u0026rsquo; (ME 5746/1-1). M.J.G. is also affiliated with Pacific Northwest National Laboratory, which did not provide specific support for this paper.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data used for the results described in the manuscript is available at https://doi.org/10.5281/zenodo.17008260\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eForster P, Storelvmo T, Armour K, Collins W, Dufresne J-L, Frame D, Lunt D J, Mauritsen T, Palmer M D, Watanabe M, Wild M and Zhang H 2021 The Earth\u0026rsquo;s Energy Budget, Climate Feedbacks, and Climate Sensitivity \u003cem\u003eClimate Change 2021 \u0026ndash; The Physical Science Basis: Working Group I Contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change\u003c/em\u003e ed V Masson-Delmotte, P Zhai, A Pirani, S L Connors, C P\u0026eacute;an, S Berger, N Caud, Y Chen, L Goldfarb, M I Gomis, M Huang, K Leitzell, E Lonnoy, J B R Matthews, T K Maycock, T Waterfield, O Yelek\u0026ccedil;i, R Yu and B Zhou (Cambridge University Press) pp 923\u0026ndash;1054\u003c/li\u003e\n \u003cli\u003eGhan S J 2013 Technical Note: Estimating aerosol effects on cloud radiative forcing \u003cem\u003eAtmospheric Chemistry and Physics\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e 9971\u0026ndash;4\u003c/li\u003e\n \u003cli\u003eWestervelt D M, Horowitz L W, Naik V, Golaz J-C and Mauzerall D L 2015 Radiative forcing and climate response to projected 21st century aerosol decreases \u003cem\u003eAtmos. 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Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change\u003c/em\u003e (Geneva, Switzerland)\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"npj-climate-and-atmospheric-science","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"npjclimatsci","sideBox":"Learn more about [npj Climate and Atmospheric Science](http://www.nature.com/npjclimatsci/)","snPcode":"41612","submissionUrl":"https://submission.springernature.com/new-submission/41612/3","title":"npj Climate and Atmospheric Science","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"aerosol, responses, Earth system","lastPublishedDoi":"10.21203/rs.3.rs-7502615/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7502615/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAerosols have played an important role in defining climate development over the historical period, due to their cooling impact in the atmosphere. However, as their emissions are expected to decrease in the upcoming decades, and therefore also their cooling effect, they will likely be associated with the future warming of the planet. Despite their importance, and the high uncertainty of their radiative forcing, aerosols inclusion or consideration in, for example, simple climate models, integrated assessment models and carbon metrics requires extensive simplifications and assumptions. Typically, interactions between physical and biogeochemical processes, as well as triggered feedbacks, are disregarded by such models and metrics, which is a potential further source of uncertainty in the aerosols\u0026rsquo; led responses in a changing climate. By varying the spatial implementation of aerosols in an intermediate complexity model, we explore the variability in Earth system responses under a highly ambitious mitigation scenario due to a change in aerosols forcing. When spatial heterogeneities in forcing are disregarded, surface air temperature development can differ by almost 0.1\u0026deg;C, which would correspond to an approximate uncertainty of 200 GtCO\u003csub\u003e2\u003c/sub\u003e in estimates of remaining carbon budgets. The warming and cooling contributions of different Earth system processes, such as land carbon uptake or ocean heat uptake, are also seen to vary strongly depending on the spatial distribution of aerosols in the atmosphere. The main processes driving these responses are found to be land surface temperature and its impact on soil respiration, as well as ocean ventilation processes and sea ice cover changes. These findings highlight that the spatial distribution of aerosols is capable of triggering important climate feedbacks, which should not be disregarded when assessing climate development and simulated Earth system responses. These feedbacks will be instrumental in defining potential pathways for temperature stabilisation and evaluating, for example, remaining carbon budgets.\u003c/p\u003e","manuscriptTitle":"Carbon-climate feedbacks to spatial aerosol model implementation variations","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-15 14:05:14","doi":"10.21203/rs.3.rs-7502615/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-28T17:26:37+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-27T07:04:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"278815999597087050286174155278852605104","date":"2025-10-12T02:41:49+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-25T11:44:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"146412824800431229689097966939780728837","date":"2025-09-09T06:21:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"221291076772482537942432576249901491556","date":"2025-09-07T21:44:15+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-06T02:02:14+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-05T09:01:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-05T08:18:07+00:00","index":"","fulltext":""},{"type":"submitted","content":"npj Climate and Atmospheric Science","date":"2025-08-31T19:49:29+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"npj-climate-and-atmospheric-science","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"npjclimatsci","sideBox":"Learn more about [npj Climate and Atmospheric Science](http://www.nature.com/npjclimatsci/)","snPcode":"41612","submissionUrl":"https://submission.springernature.com/new-submission/41612/3","title":"npj Climate and Atmospheric Science","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"61e73370-c394-428c-86b2-5c3a6e971398","owner":[],"postedDate":"September 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":54423032,"name":"Earth and environmental sciences/Climate sciences"},{"id":54423033,"name":"Earth and environmental sciences/Environmental sciences"}],"tags":[],"updatedAt":"2026-02-09T16:03:02+00:00","versionOfRecord":{"articleIdentity":"rs-7502615","link":"https://doi.org/10.1038/s41612-026-01343-6","journal":{"identity":"npj-climate-and-atmospheric-science","isVorOnly":false,"title":"npj Climate and Atmospheric Science"},"publishedOn":"2026-02-03 15:59:28","publishedOnDateReadable":"February 3rd, 2026"},"versionCreatedAt":"2025-09-15 14:05:14","video":"","vorDoi":"10.1038/s41612-026-01343-6","vorDoiUrl":"https://doi.org/10.1038/s41612-026-01343-6","workflowStages":[]},"version":"v1","identity":"rs-7502615","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7502615","identity":"rs-7502615","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}