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The difficulties in using conventional mitigation techniques to maintain global mean temperatures well below 2 °C compared with preindustrial levels have been well documented, leading to so-called ‘climate intervention’ or ‘geoengineering’ research whereby the planetary albedo is increased to counterbalance global warming and ameliorate some impacts of climate change. In the scientific literature, the most prominent climate intervention proposal is that of stratospheric aerosol injection (SAI), although proposals for marine cloud brightening (MCB) have also received considerable attention. In this study, we design a new MCB experiment (G6MCB) for the UKESM1 Earth system model which follows the same baseline and cooling scenarios as the well-documented G6sulfur SAI scenario developed by the Geoengineering Model Intercomparison Project (GeoMIP) and compare the results from G6MCB with those from G6sulfur. The deployment strategy used in G6MCB injects sea-salt aerosol into four cloudy areas of the eastern Pacific. Despite MCB being intended as a technique to modify clouds, much of the radiative effect in G6MCB is found to derive from the direct interaction of the injected sea-salt aerosols with solar radiation. The results show that while G6MCB can achieve its target in terms of reducing high-end global warming to moderate levels, there are several side-effects. Some are common to SAI, including overcooling of the tropics, and residual warming of mid-and high latitudes. Others side effects specific to common choices of MCB regions include changes in monsoon precipitation, year-round increases in precipitation over Australia and the maritime continent and increased sea-level rise around western Australia and the maritime continent; these results are all consistent with a permanent and very strong La Niña-like response being induced in G6MCB. It should be stressed that the results are extremely dependent upon the strategy chosen for MCB deployment. As demonstrated by the development of SAI strategies which can achieve multiple temperature targets and ameliorate some of the residual impacts of climate change, much further work is required in multiple models to obtain a robust understanding of the practical scope, limitations, perils and pitfalls of any proposed MCB deployment.

The availability of training data remains a significant obstacle for the implementation of machine learning in scientific applications. In particular, estimating how a system might respond to external forcings or perturbations requires specialized labeled data or targeted simulations, which may be computationally intensive to generate at scale. In this study, we propose a novel solution to this challenge by utilizing a principle from statistical physics known as the Fluctuation-Dissipation Theorem (FDT) to discover knowledge using an AI model that can rapidly produce scenarios for different external forcings. By leveraging FDT, we are able to extract information encoded in a large dataset produced by Earth System Models, which includes 8250 years of internal climate fluctuations, to estimate the climate system's response to forcings. Our model, AiBEDO, is capable of capturing the complex, multi-timescale effects of radiation perturbations on global and regional surface climate, allowing for a substantial acceleration of the exploration of the impacts of spatially-heterogenous climate forcers. To demonstrate the utility of AiBEDO, we use the example of a climate intervention technique called Marine Cloud Brightening, with the ultimate goal of optimizing the spatial pattern of cloud brightening to achieve regional climate targets and prevent known climate tipping points. While we showcase the effectiveness of our approach in the context of climate science, it is generally applicable to other scientific disciplines that are limited by the extensive computational demands of domain simulation models. Source code of AiBEDO framework is made available at https://github.com/kramea/kdd_aibedo. A sample dataset is made available at https://doi.org/10.5281/zenodo.7597027. Additional data available upon request.

An earlier study evaluating the dust life cycle in the Energy Exascale Earth System Model (E3SM) Atmosphere Model version 1 (EAMv1) has revealed that the simulated global mean dust lifetime is substantially shorter when higher vertical resolution is used, primarily due to significant strengthening of dust dry removal in source regions. This paper demonstrates that the sequential splitting of aerosol emissions, dry removal, and turbulent mixing in the model's time integration loop, especially the calculation of dry removal after surface emissions and before turbulent mixing, is the primary reason for the vertical resolution sensitivity reported in that earlier study. Based on this reasoning, we propose a simple revision to the numerical process coupling scheme, which moves the application of the surface emissions to after dry removal and before turbulent mixing. The revised scheme allows newly emitted particles to be transported aloft by turbulence before being removed from the atmosphere, and hence better resembles the dust life cycle in the real world. Sensitivity experiments are conducted and analyzed to evaluate the impact of the revised coupling on the simulated aerosol climatology in EAMv1.

As global temperatures increase, sea ice loss will increasingly enable commercial shipping traffic to cross the Arctic Ocean, where the ships' gas and particulate emissions may have strong regional effects. Here we investigate impacts of shipping emissions on Arctic climate using a fully coupled Earth system model (CESM 1.2.2) and a suite of newly developed projections of 21st-century trans-Arctic shipping emissions. We find that trans-Arctic shipping will reduce Arctic warming by nearly 1 °C by 2099, due to sulfate-driven liquid water cloud formation. Cloud fraction and liquid water path exhibit significant positive trends, cooling the lower atmosphere and surface. Positive feedbacks from sea ice growth-induced albedo increases and decreased downwelling longwave radiation due to reduced water vapor content amplify the cooling relative to the shipping-free Arctic. Our findings thus point to the complexity in Arctic climate responses to increased shipping traffic, justifying further study and policy considerations as trade routes open.

Anthropogenic emissions and land use changes have modified atmospheric aerosol concentrations and size distributions over time. Understanding preindustrial conditions and changes in organic aerosol due to anthropogenic activities is important because these features (1) influence estimates of aerosol radiative forcing and (2) can confound estimates of the historical response of climate to increases in greenhouse gases. Secondary organic aerosol (SOA), formed in the atmosphere by oxidation of organic gases, represents a major fraction of global submicron-sized atmospheric organic aerosol. Over the past decade, significant advances in understanding SOA properties and formation mechanisms have occurred through measurements, yet current climate models typically do not comprehensively include all important processes. This review summarizes some of the important developments during the past decade in understanding SOA formation. We highlight the importance of some processes that influence the growth of SOA particles to sizes relevant for clouds and radiative forcing, including formation of extremely low volatility organics in the gas phase, acid-catalyzed multiphase chemistry of isoprene epoxydiols, particle-phase oligomerization, and physical properties such as volatility and viscosity. Several SOA processes highlighted in this review are complex and interdependent and have nonlinear effects on the properties, formation, and evolution of SOA. Current global models neglect this complexity and nonlinearity and thus are less likely to accurately predict the climate forcing of SOA and project future climate sensitivity to greenhouse gases. Efforts are also needed to rank the most influential processes and nonlinear process-related interactions, so that these processes can be accurately represented in atmospheric chemistry-climate models. Plain Language Summary Secondary organic aerosol (SOA), formed in the atmosphere by oxidation of organic gases, often represents a major fraction of global submicron-sized atmospheric organic aerosol. Myriad processes affect SOA formation, several of which relate to interactions between natural biogenic emissions and predominantly anthropogenic species such as SO2, NOx, sulfate, nitrate, and ammonium. Many of these key processes are nonlinear and can be synergistic or act to compensate each other in terms of climate forcing. Current atmospheric chemistry-climate models mostly do not treat these processes. We highlight a number of process-level mechanisms related to the interactions between anthropogenic and biogenic SOA precursors, for which the corresponding impacts on the radiative effects of SOA need to be investigated in atmospheric chemistry-climate models. Ultimately, climate models need to capture enough important features of the chemical and dynamic evolution of SOA, in terms of both aerosol number and aerosol mass, as a function of atmospheric variables and anthropogenic perturbations to reasonably predict the spatial and temporal distributions of SOA. A better understanding of SOA formation mechanisms and physical properties is needed to improve estimates of the extent to which anthropogenic emissions and land use changes have modified global aerosol concentrations and size distributions since preindustrial times.

Geophysical models of the atmosphere and ocean invariably involve parameterizations. These represent two distinct areas: Subgrid processes that the model cannot resolve, and diabatic sources in the equations, due to radiation for example. Hence, coupling between these physics parameterizations and the resolved fluid dynamics and also between the dynamics of the air and water, is necessary. In this paper weather and climate models are used to illustrate the problems. Nevertheless the same applies to other geophysical models. This coupling is an important aspect of geophysical models. However, often model development is strictly segregated into either physics or dynamics. As a consequence, this area has many unanswered questions. Recent developments in the design of dynamical cores, extended process physics and predicted future changes of the computational infrastructure are increasing complexity. This paper reviews the state-of-the-art of the physics-dynamics coupling in geophysical models, surveys the analysis techniques, and illustrates open questions in this field. This paper focuses on two objectives: To illustrate the phenomenology of the coupling problem with references to examples in the literature and to show how the problem can be analysed. Proposals are made on how to advance the understanding and upcoming challenges with emerging modeling strategies. This paper is of interest to model developers who aim to improve the models and have to make choices on and test new implementations, to users who have to understand choices presented to them and finally users of outputs, who have to distinguish physical features from numerical problems in the model data.

Since the winter of 2013–2014, California has experienced its most severe drought in recorded history, causing statewide water stress, severe economic loss and an extraordinary increase in wildfires. Identifying the effects of global warming on regional water cycle extremes, such as the ongoing drought in California, remains a challenge. Here we analyse large-ensemble and multi-model simulations that project the future of water cycle extremes in California as well as to understand those associations that pertain to changing climate oscillations under global warming. Both intense drought and excessive flooding are projected to increase by at least 50% towards the end of the twenty-first century; this projected increase in water cycle extremes is associated with a strengthened relation to El Niño and the Southern Oscillation (ENSO)—in particular, extreme El Niño and La Niña events that modulate California’s climate not only through its warm and cold phases but also its precursor patterns.

There are large uncertainties in global climate models predictions of black carbon (BC) in the Arctic that could be due to uncertainties in anthropogenic and biomass burning emissions, errors arising from physics parameterizations, and inadequate spatial resolution. In addition to contributing to uncertainties in simulated aerosol radiative forcing, black carbon deposited on snow alters its albedo and consequently the rate of melting. In this study, WRF-Chem is used to simulate the emission, transport, and fate of black carbon during March and April of 2008 using a domain that encompasses most of the northern hemisphere. This period is chosen because a number of field campaigns (e.g. ARCTAS, ISDAC, POLARCAT) took place as part of the International Polar Year that collected measurements of BC and other aerosols that can be used to evaluate model performance in this region. The simulations employ physics parameterizations from the Community Atmosphere Model v5.1 that have recently been ported to the WRF model and made available in the v3.5 release. This includes the Modal Aerosol Model (MAM) that is computationally more efficient than the MADE/SORGAM and MOSAIC aerosol models available in WRF-Chem and is therefore more feasible for long-term simulation periods. Sensitivity simulations are performed that examine the impact of emission estimates and wet removal on BC concentrations over the Arctic in relation to the observations. This includes quantifying the impact of the newly developed emissions inventory (developed within the EU project ECLIPSE) that contains a first estimate for a source of BC emissions (gas flaring) adjacent to the Arctic Ocean that has been previously omitted from most studies.

International audience; Marine cloud brightening through sea spray injection has been proposed as a method of temporarily alleviating some of the impacts of anthropogenic climate change, as part of a set of technologies called geoengineering. We outline here a proposal for three coordinated climate modeling experiments to test aspects of sea spray geoengineering, to be conducted under the auspices of the Geoengineering Model Intercomparison Project (GeoMIP). The first, highly idealized, experiment (G1ocean-albedo) involves a uniform increase in ocean albedo to offset an instantaneous quadrupling of CO2 concentrations from preindustrial levels. Results from a single climate model show an increased land-sea temperature contrast, Arctic warming, and large shifts in annual mean precipitation patterns. The second experiment (G4cdnc) involves increasing cloud droplet number concentration in all low-level marine clouds to offset some of the radiative forcing of an RCP4.5 scenario. This experiment will test the robustness of models in simulating geographically heterogeneous radiative flux changes and their effects on climate. The third experiment (G4sea-salt) involves injection of sea spray aerosols into the marine boundary layer between 30°S and 30°N to offset 2 W m-2 of the effective radiative forcing of an RCP4.5 scenario. A single model study shows that the induced effective radiative forcing is largely confined to the latitudes in which injection occurs. In this single model simulation, the forcing due to aerosol-radiation interactions is stronger than the forcing due to aerosol-cloud interactions. Key Points Outline of three marine cloud brightening experiments Land-sea contrast is an important feature of marine cloud brightening Direct effect of sea salt injection may be greater than indirect effect ©2013. American Geophysical Union. All Rights Reserved.

Aerosol indirect effects continue to constitute one of the most important uncertaintiesfor anthropogenic climate perturbations. Within the international AEROCOM initiative,the representation of aerosol-cloud-radiation interactions in ten different general cir-culation models (GCMs) is evaluated using three satellite datasets. The focus is on stratiform liquid water clouds since most GCMs do not include ice nucleation effects,and none of the models explicitly parameterizes aerosol effects on convective clouds.We compute statistical relationships between aerosol optical depth (τa) and variouscloud and radiation quantities in a manner that is consistent between the models andthe satellite data. It is found that the model-simulated influence of aerosols on cloud droplet number concentration (Nd) compares relatively well to the satellite data at leastover the ocean. The relationship betweenτaand liquid water path is simulated muchtoo strongly by the models. It is shown that this is partly related to the representationof the second aerosol indirect effect in terms of autoconversion. A positive relationshipbetween total cloud fraction (fcld) andτaas found in the satellite data is simulated by the majority of the models, albeit less strongly than that in the satellite data in most of them.In a discussion of the hypotheses proposed in the literature to explain the satellite-derived strongfcld–τarelationship, our results indicate that none can be identified asunique explanation. Relationships similar to the ones found in satellite data betweenτaand cloud top temperature or outgoing long-wave radiation (OLR) are simulated by only a few GCMs. The GCMs that simulate a negative OLR –τarelationship show a strongpositive correlation betweenτaandfcld. The short-wave total aerosol radiative forc-ing as simulated by the GCMs is strongly influenced by the simulated anthropogenicfraction ofτa, and parameterisation assumptions such as a lower bound onNd. Never-theless, the strengths of the statistical relationships are good predictors for the aerosol forcings in the models. An estimate of the total short-wave aerosol forcing inferred fromthe combination of these predictors for the modelled forcings with the satellite-derivedstatistical relationships yields a global annual mean value of−1.5±0.5 Wm−2. An alternative estimate obtained by scaling the simulated clear- and cloudy-sky forcingswith estimates of anthropogenicτaand satellite-retrievedNd–τaregression slopes,respectively, yields a global annual mean clear-sky (aerosol direct effect) estimate of−0.4±0.2 Wm−2and a cloudy-sky (aerosol indirect effect) estimate of−0.7±0.5 Wm−2, with a total estimate of−1.2±0.4 Wm−2., Atmospheric Chemistry and Physics Discussions, 9 (3), ISSN:1680-7375, ISSN:1680-7367

Aerosol indirect effects continue to constitute one of the most important uncertainties for anthropogenic climate perturbations. Within the international AEROCOM initiative, the representation of aerosol-cloud-radiation interactions in ten different general circulation models (GCMs) is evaluated using three satellite datasets. The focus is on stratiform liquid water clouds since most GCMs do not include ice nucleation effects, and none of the model explicitly parameterises aerosol effects on convective clouds. We compute statistical relationships between aerosol optical depth (tau a) and various cloud and radiation quantities in a manner that is consistent between the models and the satellite data. cloud droplet number concentration (N d) compares relatively well to the satellite data at least over the ocean. The relationship between (tau a) and liquid water path is simulated much too strongly by the models. This suggests that the implementation of the second aerosol indirect effect mainly in terms of an autoconversion parameterisation has to be revisited in the GCMs. A positive relationship between total cloud fraction (fcld) and tau a as found in the satellite data is simulated by the majority of the models, albeit less strongly than that in the satellite data in most of them. In a discussion of the hypotheses proposed in the literature to explain the satellite-derived strong fcld–tau a relationship, our results indicate that none can be identified as a unique explanation. Relationships similar to the ones found in satellite data between tau a and cloud top temperature or outgoing long-wave radiation (OLR) are simulated by only a few GCMs. The GCMs that simulate a negative OLR - tau a relationship show a strong positive correlation between tau a and fcld. The short-wave total aerosol radiative forcing as simulated by the GCMs is strongly influenced by the simulated anthropogenic fraction of tau a, and parameterisation assumptions such as a lower bound on Nd. Nevertheless, the strengths of the statistical relationships are good predictors for the aerosol forcings in the models. An estimate of the total short-wave aerosol forcing inferred from the combination of these predictors for the modelled forcings with the satellite-derived statistical relationships yields a global annual mean value of −1.5±0.5Wm−2. In an alternative approach, the radiative flux perturbation due to anthropogenic aerosols can be broken down into a component over the cloud-free portion of the globe (approximately the aerosol direct effect) and a component over the cloudy portion of the globe (approximately the aerosol indirect effect). An estimate obtained by scaling these simulated clearand cloudy-sky forcings with estimates of anthropogenic tau a and satellite-retrieved Nd–tau a regression slopes, respectively, yields a global, annual-mean aerosol direct effect estimate of −0.4±0.2Wm−2 and a cloudy-sky (aerosol indirect effect) estimate of −0.7±0.5Wm−2, with a total estimate of −1.2±0.4Wm−2.

Aerosols produced in the lower stratosphere can brighten the planet and counteract some of the effects of global warming. We explore scenarios in which the amount of precursors and the size of the aerosol are varied to assess their interactions with the climate system. Stratosphere-troposphere exchange processes change in response to greenhouse gas forcing and respond to geoengineering by aerosols. Nonlinear feedbacks influence the amount of aerosol required to counteract the warming. More aerosol precursor must be injected than would be needed if stratosphere troposphere exchange processes did not change in response to greenhouse gases or aerosols. Aerosol particle size has an important role in modulating the energy budget. A prediction of aerosol size requires a much more complex representation and assumptions about the delivery mechanism beyond the scope of this study, so we explore the response when particle size is prescribed. More aerosol is required to counteract greenhouse warming if aerosol particles are as large as those seen during volcanic eruptions (compared to the smaller aerosols found in quiescent conditions) because the larger particles are less effective at scattering incoming energy, and trap some outgoing energy. About 1.5 Tg S/yr are found to balance a doubling of CO2 if the particles are small, while perhaps double that may be needed if the particles reach the size seen following eruptions.

Desert dust simulations generated by the National Center for Atmospheric Research's Community Climate System Model for the current climate are shown to be consistent with present day satellite and deposition data. The response of the dust cycle to last glacial maximum, preindustrial, modern, and doubled-carbon dioxide climates is analyzed. Only natural (non-land use related) dust sources are included in this simulation. Similar to some previous studies, dust production mainly responds to changes in the source areas from vegetation changes, not from winds or soil moisture changes alone. This model simulates a +92%, +33%, and −60% change in dust loading for the last glacial maximum, preindustrial, and doubled-carbon dioxide climate, respectively, when impacts of carbon dioxide fertilization on vegetation are included in the model. Terrestrial sediment records from the last glacial maximum compiled here indicate a large underestimate of deposition in continental regions, probably due to the lack of simulation of glaciogenic dust sources. In order to include the glaciogenic dust sources as a first approximation, we designate the location of these sources, and infer the size of the sources using an inversion method that best matches the available data. The inclusion of these inferred glaciogenic dust sources increases our dust flux in the last glacial maximum from 2.1 to 3.3 times current deposition.

Aerosols exert myriad influences on the earth's environment and climate, and on human health. The complexity of aerosol-related processes requires that information gathered to improve our understanding of climate change must originate from multiple sources, and that effective strategies for data integration need to be established. While a vast array of observed and modeled data are becoming available, the aerosol research community currently lacks the necessary tools and infrastructure to reap maximum scientific benefit from these data. Spatial and temporal sampling differences among a diverse set of sensors, nonuniform data qualities, aerosol mesoscale variabilities, and difficulties in separating cloud effects are some of the challenges that need to be addressed. Maximizing the long-term benefit from these data also requires maintaining consistently well-understood accuracies as measurement approaches evolve and improve. Achieving a comprehensive understanding of how aerosol physical, chemical, and radiative processes impact the earth system can be achieved only through a multidisciplinary, inter-agency, and international initiative capable of dealing with these issues. A systematic approach, capitalizing on modern measurement and modeling techniques, geospatial statistics methodologies, and high-performance information technologies, can provide the necessary machinery to support this objective. We outline a framework for integrating and interpreting observations and models, and establishing an accurate, consistent, and cohesive long-term record, following a strategy whereby information and tools of progressively greater sophistication are incorporated as problems of increasing complexity are tackled. This concept is named the Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON). To encompass the breadth of the effort required, we present a set of recommendations dealing with data interoperability; measurement and model integration; multisensor synergy; data summarization and mining; model evaluation; calibration and validation; augmentation of surface and in situ measurements; advances in passive and active remote sensing; and design of satellite missions. Without an initiative of this nature, the scientific and policy communities will continue to struggle with understanding the quantitative impact of complex aerosol processes on regional and global climate change and air quality.

Simulations of 222Rn and other short-lived tracers are used to evaluate and intercompare the representations of convective and synoptic processes in 20 global atmospheric transport models. Results show that most established three-dimensional models simulate vertical mixing in the troposphere to within the constraints offered by the observed mean 222Rn concentrations and that subgrid parameterization of convection is essential for this purpose. However, none of the models captures the observed variability of 222Rn concentrations in the upper troposphere, and none reproduces the high 222Rn concentrations measured at 200 hPa over Hawaii. The established three-dimensional models reproduce the frequency and magnitude of high-222Rn episodes observed at Crozet Island in the Indian Ocean, demonstrating that they can resolve the synoptic-scale transport of continental plumes with no significant numerical diffusion. Large differences between models are found in the rates of meridional transport in the upper troposphere (interhemispheric exchange, exchange between tropics and high latitudes). The four two-dimensional models which participated in the intercomparison tend to underestimate the rate of vertical transport from the lower to the upper troposphere but show concentrations of 222Rn in the lower troposphere that are comparable to the zonal mean values in the three-dimensional models.

Nudging as an assimilation technique has seen increased use in recent years in the development and evaluation of climate models. Constraining the simulated wind and temperature fields using global weather reanalysis facilitates more straightforward comparison between simulation and observation, and reduces uncertainties associated with natural variabilities of the large-scale circulation. On the other hand, the forcing introduced by nudging can be strong enough to change the basic characteristics of the model climate. In the paper we show that for the Community Atmosphere Model version 5 (CAM5), due to the systematic temperature bias in the standard model and the sensitivity of simulated ice formation to anthropogenic aerosol concentration, nudging towards reanalysis results in substantial reductions in the ice cloud amount and the impact of anthropogenic aerosols on long-wave cloud forcing. In order to reduce discrepancies between the nudged and unconstrained simulations, and meanwhile take the advantages of nudging, two alternative experimentation methods are evaluated. The first one constrains only the horizontal winds. The second method nudges both winds and temperature, but replaces the long-term climatology of the reanalysis by that of the model. Results show that both methods lead to substantially improved agreement with the free-running model in terms of the top-of-atmosphere radiation budget and cloud ice amount. The wind-only nudging is more convenient to apply, and provides higher correlations of the wind fields, geopotential height and specific humidity between simulation and reanalysis. Results from both CAM5 and a second aerosol–climate model ECHAM6-HAM2 also indicate that compared to the wind-and-temperature nudging, constraining only winds leads to better agreement with the free-running model in terms of the estimated shortwave cloud forcing and the simulated convective activities. This suggests nudging the horizontal winds but not temperature is a good strategy for the investigation of aerosol indirect effects since it provides well-constrained meteorology without strongly perturbing the model's mean climate., Atmospheric Chemistry and Physics, 14 (16), ISSN:1680-7375, ISSN:1680-7367