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Ice-nucleating particles (INPs) in the Southern Ocean (SO) atmosphere have significant impacts on cloud radiative and microphysical properties. Yet, INP prediction skill in climate models remains poorly understood, in part because of the lack of long-term measurements. Here we show, for the first time, how model-simulated INP concentrations compare with year-round INP measurements during the Macquarie Island Cloud Radiation Experiment (MICRE) campaign from 2017–2018. We simulate immersion-mode INP concentrations using the Energy Exascale Earth System Model version 1 (E3SMv1) by combining simulated aerosols with recently developed deterministic INP parameterizations and the native classical nucleation theory (CNT) for mineral dust in E3SMv1. Because MICRE did not collect aerosol measurements of super-micron particles, which are more effective ice nucleators, we evaluate the model's aerosol fields at other high-latitude sites using long-term in situ observations of dust and sea spray aerosol. We find that the model underestimates dust and overestimates sea spray aerosol concentrations by 1 to 2 orders of magnitude for most of the high-latitude sites in the Southern Hemisphere. We next compare predicted INP concentrations with concentrations of INPs collected on filter samples (typically for 2 or 3 d) and processed offline using the Colorado State University ice spectrometer (IS) in immersion freezing mode. We find that when deterministic parameterizations for both dust and sea spray INPs are used, simulated INPs are within a factor of 10 of observed INPs more than 60 % of the time during summer. Our results also indicate that the E3SM's current treatment of mineral dust immersion freezing in the SO is impacted by compensating biases – an underprediction of dust amount was compensated by an overprediction of its effectiveness as INPs. We also perform idealized droplet freezing experiments to quantify the implications of the time-dependent behavior assumed by the E3SM's CNT-parameterization and compare with the ice spectrometer observations. We find that the E3SM CNT 10 s diagnostic used in this study is a reasonable approximation of the exact formulation of CNT, when applied to ice spectrometer measurements in low-INP conditions similar to Macquarie Island. However, the linearized 10 s diagnostic underestimates the exact formula by an order of magnitude or more in places with high-INP conditions like the Sahara. Overall, our findings suggest that it is important to correct the biases in E3SM's simulated dust life cycle and update E3SM's INP parameterizations. INP prediction errors of 2 to 3 orders of magnitude can have considerable impacts on the simulated cloud and radiative properties in global climate models. On comparing INP concentrations during MICRE against ship-based campaigns, Measurements of Aerosols, Radiation, and Clouds over the Southern Ocean (MARCUS) and Antarctic Circumnavigation Expedition (ACE), we find that INPs from the latter are significantly higher only in regions closer to Macquarie Island. This alludes to the fact that physical, chemical and biological processes affecting INP concentrations as stimulated by the island could be partly responsible for the high INP concentrations observed at Macquarie Island during the MICRE campaign. Therefore, improvements to both aerosol simulation and INP parameterizations are required to adequately simulate INPs and their cloud impacts in E3SM. It will be helpful to include a parallel measurement of the size-resolved aerosol composition and explore opportunities for long-term measurement platforms in future field campaigns studying INP sources in remote marine regions.

The effective radiative forcing of anthropogenic aerosols (ERFaer) is an important measure of the anthropogenic aerosol effects simulated by a global climate model. Here we analyze ERFaer simulated by the E3SM version 1 (E3SMv1) atmospheric model using both century-long free-running atmosphere–land simulations and short nudged simulations. We relate the simulated ERFaer to characteristics of the aerosol composition and optical properties, and we evaluate the relationships between key aerosol and cloud properties. In terms of historical changes from the year 1870 to 2014, our results show that the global mean anthropogenic aerosol burden and optical depth increase during the simulation period as expected, but the regional averages show large differences in the temporal evolution. The largest regional differences are found in the emission-induced evolution of the burden and optical depth of the sulfate aerosol: a strong decreasing trend is seen in the Northern Hemisphere high-latitude region after around 1970, while a continued increase is simulated in the tropics. The relationships between key aerosol and cloud properties (relative changes between pre-industrial and present-day conditions) also show evident changes after 1970, diverging from the linear relationships exhibited for the period of 1870–1969. In addition to the regional differences in the simulated relationships, a reduced sensitivity in cloud droplet number and other cloud properties to aerosol perturbations is seen when the aerosol perturbation is large. Consequently, the global annual mean ERFaer magnitude does not increase after around 1970. The ERFaer in E3SMv1 is relatively large compared to the recently published multi-model estimates; the primary reason is the large indirect aerosol effect (i.e., through aerosol–cloud interactions). Compared to other models, E3SMv1 features large relative changes in the cloud droplet effective radius in response to aerosol perturbations. Large sensitivity is also seen in the liquid cloud optical depth, which is determined by changes in both the effective radius and liquid water path. Aerosol-induced changes in liquid and ice cloud properties in E3SMv1 are found to have a strong correlation, as the evolution of anthropogenic sulfate aerosols affects both the liquid cloud formation and the homogeneous ice nucleation in cirrus clouds (that causes a large effect on longwave ERFaer). As suggested by a previous study, the large ERFaer appears to be one of the reasons why the model cannot reproduce the observed global mean temperature evolution in the second half of the 20th century. Sensitivity simulations are performed to understand which parameterization and/or parameter changes have a large impact on the simulated ERFaer. The ERFaer estimates in E3SMv1 for the shortwave and longwave components are sensitive to the parameterization changes in both liquid and ice cloud processes. When the parameterization of ice cloud processes is modified, the top-of-model forcing changes in the shortwave and longwave components largely offset each other, so the net effect is negligible. This suggests that, to reduce the magnitude of the net ERFaer, it would be more effective to reduce the anthropogenic aerosol effect through liquid or mixed-phase clouds.

Sea spray aerosol is one of the major sources of atmospheric particulate matter globally. It has increasingly been recognized that organic matter derived from ocean biological precursors contributes significantly to the composition of submicron sea spray and may modify sea spray aerosol impacts on clouds and climate. This paper describes the implementation of the OCEANFILMS (Organic Compounds from Ecosystems to Aerosols: Natural Films and Interfaces via Langmuir Molecular Surfactants) parameterization for sea spray organic aerosol emissions in a global Earth system model, the Energy Exascale Earth System Model (E3SM). OCEANFILMS is a physically based model that links sea spray chemistry with ocean biogeochemistry using a Langmuir partitioning approach. We describe the implementation details of OCEANFILMS within E3SM, compare simulated aerosol fields with observations, and investigate impacts on simulated clouds and climate. Four sensitivity cases are tested, in which organic emissions either strictly add to or strictly replace sea salt emissions (in mass and number) and are either fully internally or fully externally mixed with sea salt. The simulation with internally mixed, added organics agrees reasonably well with observed seasonal cycles of organic matter in marine aerosol and has been selected as the default configuration of the E3SM. In this configuration, sea spray organic aerosol contributes an additional source of cloud condensation nuclei, adding up to 30 cm−3 to Southern Ocean boundary-layer cloud condensation nuclei concentrations (supersaturation = 0.1 %). The addition of this new aerosol source strengthens shortwave radiative cooling by clouds by −0.36 W m−2 in the global annual mean and contributes more than −3.5 W m−2 to summertime zonal mean cloud forcing in the Southern Ocean, with maximum zonal mean impacts of about −4 W m−2 around 50–60∘ S. This is consistent with a previous top-down, satellite-based empirical estimate of the radiative forcing by sea spray organic aerosol over the Southern Ocean. Through its mechanistic approach, OCEANFILMS offers a path towards improved understanding of the feedbacks between ocean biology, sea spray organic matter, and climate.

Mixed-phase clouds are frequently observed in high-latitude regions and have important impacts on the surface energy budget and regional climate. Marine organic aerosol (MOA), a natural source of aerosol emitted over ∼ 70 % of Earth's surface, may significantly modify the properties and radiative forcing of mixed-phase clouds. However, the relative importance of MOA as a source of ice-nucleating particles (INPs) in comparison to mineral dust, and MOA's effects as cloud condensation nuclei (CCN) and INPs on mixed-phase clouds are still open questions. In this study, we implement MOA as a new aerosol species into the Community Atmosphere Model version 6 (CAM6), the atmosphere component of the Community Earth System Model version 2 (CESM2), and allow the treatment of aerosol–cloud interactions of MOA via droplet activation and ice nucleation. CAM6 reproduces observed seasonal cycles of marine organic matter at Mace Head and Amsterdam Island when the MOA fraction of sea spray aerosol in the model is assumed to depend on sea spray biology but fails when this fraction is assumed to be constant. Model results indicate that marine INPs dominate primary ice nucleation below 400 hPa over the Southern Ocean and Arctic boundary layer, while dust INPs are more abundant elsewhere. By acting as CCN, MOA exerts a shortwave cloud forcing change of −2.78 W m−2 over the Southern Ocean in the austral summer. By acting as INPs, MOA enhances the longwave cloud forcing by 0.35 W m−2 over the Southern Ocean in the austral winter. The annual global mean net cloud forcing changes due to CCN and INPs of MOA are −0.35 and 0.016 W m−2, respectively. These findings highlight the vital importance for Earth system models to consider MOA as an important aerosol species for the interactions of biogeochemistry, hydrological cycle, and climate change.

We present the analysis of global sympagic primary production (PP) from 300 years of pre-industrial and historical simulations of the E3SMv1.1-BGC model. The model includes a novel, eight-element sea ice biogeochemical component, MPAS-Seaice zbgc, which is resolved in three spatial dimensions and uses a vertical transport scheme based on internal brine dynamics. Modeled ice algal chlorophyll-a concentrations and column-integrated values are broadly consistent with observations, though chl-a profile fractions indicate that upper ice communities of the Southern Ocean are underestimated. Simulations of polar integrated sea ice PP support the lower bound in published estimates for both polar regions with mean Arctic values of 7.5 and 15.5 TgC/a in the Southern Ocean. However, comparisons of the polar climate state with observations, using a maximal bound for ice algal growth rates, suggest that the Arctic lower bound is a significant underestimation driven by biases in ocean surface nitrate, and that correction of these biases supports as much as 60.7 TgC/a of net Arctic PP. Simulated Southern Ocean sympagic PP is predominantly light-limited, and regional patterns, particularly in the coastal high production band, are found to be negatively correlated with snow thickness.

We present a framework for estimating concentrations of episodically elevated high-temperature marine ice nucleating particles (INPs) in the sea surface microlayer and their subsequent emission into the atmospheric boundary layer. These episodic INPs have been observed in multiple ship-based and coastal field campaigns, but the processes controlling their ocean concentrations and transfer to the atmosphere are not yet fully understood. We use a combination of empirical constraints and simulation outputs from an Earth system model to explore different hypotheses for explaining the variability of INP concentrations, and the occurrence of episodic INPs, in the marine atmosphere. In our calculations, we examine the following two proposed oceanic sources of high-temperature INPs: heterotrophic bacteria and marine biopolymer aggregates (MBPAs). Furthermore, we assume that the emission of these INPs is determined by the production of supermicron sea spray aerosol formed from jet drops, with an entrainment probability that is described by Poisson statistics. The concentration of jet drops is derived from the number concentration of supermicron sea spray aerosol calculated from model runs. We then derive the resulting number concentrations of marine high-temperature INPs (at 253 K) in the atmospheric boundary layer and compare their variability to atmospheric observations of INP variability. Specifically, we compare against concentrations of episodically occurring high-temperature INPs observed during field campaigns in the Southern Ocean, the Equatorial Pacific, and the North Atlantic. In this case study, we evaluate our framework at 253 K because reliable observational data at this temperature are available across three different ocean regions, but suitable data are sparse at higher temperatures. We find that heterotrophic bacteria and MBPAs acting as INPs provide only a partial explanation for the observed high INP concentrations. We note, however, that there are still substantial knowledge gaps, particularly concerning the identity of the oceanic INPs contributing most frequently to episodic high-temperature INPs, their specific ice nucleation activity, and the enrichment of their concentrations during the sea–air transfer process. Therefore, targeted measurements investigating the composition of these marine INPs and drivers for their emissions are needed, ideally in combination with modeling studies focused on the potential cloud impacts of these high-temperature INPs.

We present a framework for estimating concentrations of episodically elevated high-temperature marine ice nucleating particles (INPs) in the sea surface microlayer and their subsequent emission into the atmospheric boundary layer. These episodic INPs have been observed in multiple ship-based and coastal field campaigns, but the processes controlling their ocean concentrations and transfer to the atmosphere are not yet fully understood. We use a combination of empirical constraints and simulation outputs from an Earth System Model to explore different hypotheses for explaining the variability of INP concentrations, and the occurrence of episodic INPs, in the marine atmosphere. In our calculations, we examine two proposed oceanic sources of high-temperature INPs: heterotrophic bacteria and marine biopolymer aggregates (MBPAs). Furthermore, we assume that the emission of these INPs is determined by the production of supermicron sea spray aerosol formed from jet drops, with an entrainment probability that is described by Poisson statistics. The concentration of jet drops is derived from the number concentration of supermicron sea spray aerosol calculated from model runs. We then derive the resulting number concentrations of marine high-temperature INPs (≥ 253 K) in the atmospheric boundary layer and compare their variability to atmospheric observations of INP variability. Specifically, we compare against concentrations of episodically occurring high-temperature INPs observed during field campaigns in the Southern Ocean, the Equatorial Pacific, and the North Atlantic. We find that heterotrophic bacteria and MBPAs acting as INPs provide only a partial explanation for the observed high INP concentrations. We note, however, that there are still substantial knowledge gaps, particularly concerning the identity of the oceanic INPs contributing most frequently to episodic high-temperature INPs, their specific ice nucleation activity, and the enrichment of their concentrations during the sea-air transfer process. Therefore, targeted measurements investigating the composition of these marine INPs as well as drivers for their emission are needed, ideally in combination with modeling studies focused on the potential cloud impacts of these high-temperature INPs.

We document the configuration, tuning, and evaluation of a modified version of the Community Earth System Model version 1 (Hurrell et al., 2013, https://doi.org/10.1175/BAMS-D-12), introduced here as E3SMv0‐HiLAT, intended for study of high‐latitude processes. E3SMv0‐HiLAT incorporates changes to the atmospheric model affecting aerosol transport to high northern latitudes and to reduce shortwave cloud bias over the Southern Ocean. An updated sea ice model includes biogeochemistry that is coupled to an extended version of the ocean model's biogechemistry. This enables cloud nucleation to depend on the changing marine emissions of aerosol precursors, which may be expected in scenarios with strongly changing sea ice extent, oceanic stratification and associated nutrient availability, and atmospheric state. An evaluation of the basic preindustrial state of E3SMv0‐HiLAT is presented in order to ensure that its climate is adequate to support future experimentation. Additional capability is not achieved without some cost, relative to the extraordinarily well‐tuned model from which it was derived. In particular, a reduction of bias in cloud forcing achieved over the Southern Hemisphere also allows for greater Southern Ocean sea ice extent, a tendency that has been partially but not fully alleviated through experimentation and tuning. The most interesting change in the behavior of the model may be its response to greenhouse gas forcing: While the climate sensitivity is found to be essentially unchanged from that of Community Earth System Model version 1, the adjusted radiative forcing has increased from within one standard deviation above that of Coupled Model Intercomparison Project Phase 5 models to nearly two standard deviations.

This work documents the first version of the U.S. Department of Energy (DOE) new Energy Exascale Earth System Model (E3SMv1). We focus on the standard resolution of the fully coupled physical model designed to address DOE mission-relevant water cycle questions. Its components include atmosphere and land (110-km grid spacing), ocean and sea ice (60km in the midlatitudes and 30km at the equator and poles), and river transport (55km) models. This base configuration will also serve as a foundation for additional configurations exploring higher horizontal resolution as well as augmented capabilities in the form of biogeochemistry and cryosphere configurations. The performance of E3SMv1 is evaluated by means of a standard set of Coupled Model Intercomparison Project Phase 6 (CMIP6) Diagnosis, Evaluation, and Characterization of Klima simulations consisting of a long preindustrial control, historical simulations (ensembles of fully coupled and prescribed SSTs) as well as idealized CO2 forcing simulations. The model performs well overall with biases typical of other CMIP-class models, although the simulated Atlantic Meridional Overturning Circulation is weaker than many CMIP-class models. While the E3SMv1 historical ensemble captures the bulk of the observed warming between preindustrial (1850) and present day, the trajectory of the warming diverges from observations in the second half of the twentieth century with a period of delayed warming followed by an excessive warming trend. Using a two-layer energy balance model, we attribute this divergence to the model's strong aerosol-related effective radiative forcing (ERFari+aci=−1.65W/m2) and high equilibrium climate sensitivity (ECS=5.3K).

Soil dusts are an important source of aerosol in agricultural regions and can affect the Earth’s radiation budget through the modification of cloud properties, and in particular, through their ability to act as ice nucleating particles. In order to impact cloud properties, agricultural soil dusts need to be transported from the point of emission to cloud-relevant altitudes. Vertical transport within the planetary boundary layer is strongly controlled by turbulence and is challenging to represent accurately in regional and global models. Large-eddy simulations (LES) are run at resolutions capable of resolving most of the turbulent energy directly and can thus better simulate vertical transport. In this study, we leverage the LES ARM Symbiotic Simulation and Observation (LASSO) large-eddy simulations to simulate vertical transport of agricultural dust within the turbulent boundary layer using a modified version of the stochastic dispersion model FLEXPART-WRF. We find that the modified model is better capable of simulating particle transport due to turbulence, and that particle size was the greatest factor in determining particle lifetime. Individual meteorology and particle density had intermediate effects upon particle transport, while release height had little effect upon simulation results. Finally, we utilize a quasi-single column model (QSCM) approach to determine how our results compare to a parameterized treatment of turbulence. The QSCM simulations led to greater tracer transport out of the boundary layer, with ramifications for any studies utilizing a Lagrangian stochastic model to understand tracer dispersion. These results highlight the importance of accurately simulating turbulence for understanding particle transport.

Sea spray emissions are an important source for ice nucleating particles (INPs) over remote ocean regions. Over the past years, our understanding of marine organic surfactants acting as INPs has advanced a lot. However, there are still significant knowledge gaps regarding the role of larger marine biogenic particles (e.g. polymers, diatom fragments, protists and bacteria) which are potentially the drivers of episodically observed high INP concentrations.In this study, we use a combination of ARM (Atmospheric Radiation Measurement) observations and output from E3SM (Energy Exascale Earth System Model) simulation runs to investigate the impact of larger marine biogenic particles acting as INPs. We use heterotrophic bacteria and nanogels (polymeric particles) as two hypothesized classes of marine INPs which can get transported across the sea-air interface. Based on the offline-calculated concentrations of these ice nucleating entities in the ocean surface layer, we conduct sensitivity studies to estimate INP concentration ranges, relying on current knowledge of enrichment factors and ice nucleation activities (e.g., ns values from McCluskey et al. (2018)). In comparison to observations of episodic high INP concentrations, our estimated concentrations are consistently lower. However, one of the main conclusions of our study is that large uncertainties regarding the links between ocean biology, organic matter in sea spray and ice nucleation properties, remain. Therefore, comprehensive observational datasets, including sea spray size distributions, aerosol and INP compositions, and ice nucleation efficiencies of individual marine species, are needed.

Graph theoretical methods have revolutionized the exploration of complex systems across scientific disciplines. Here, we demonstrate their applicability to the investigation and comparison of three widely-used atmospheric chemical mechanisms of varying complexity: the Master Chemical Mechanism v3.3, GEOS-Chem v12.6, and the Super-Fast chemical mechanism. We investigate these mechanisms using a class of graphical models known as species-reaction graphs and find similarities between these chemical reaction systems and other systems arising in nature. Several graph theoretical properties are consistent across mechanisms, including strong dynamical system disequilibrium and clustering of chemically-related species. This formalism also reveals key differences between the mechanisms, some of which have characteristics inconsistent with domain knowledge; for example, isoprene and peroxy radical chemistry exhibit substantially different graph properties in each mechanism. Graph theoretical methods provide a promising set of tools for investigating atmospheric chemical mechanisms, complementing existing computational approaches, and potentially opening new avenues for scientific discovery.

To resolve the various types of biological ice nuclei (IN) with atmospheric models, an extension of the empirical parameterization (EP) (Phillips et al. 2008; 2013) is proposed to predict the active IN from multiple groups of primary biological aerosol particles (PBAPs). Our approach is to utilize coincident observations of PBAP sizes, concentrations, biological composition, and ice-nucleating ability. The parameterization organizes the PBAPs into five basic groups: fungal spores, bacteria, pollen, viral particles, plant/animal detritus, algae, and their respective fragments. This new biological component of the EP was constructed by fitting predicted concentrations of PBAP IN to those observed at the Amazon Tall Tower Observatory (ATTO) site located in the central Amazon. The fitting parameters for pollen and viral particles, plant/animal detritus, which are much less active as IN than fungal and bacterial groups, are constrained based on their ice nucleation activity from the literature. The parameterization has empirically derived dependencies on the surface area of each group (except algae), and the effects of variability in their mean sizes and number concentrations are represented via their influences on the surface area. The concentration of active algal IN is estimated from literature-based measurements.Predictions of this new biological component of the EP are consistent with previous laboratory and field observations not used in its construction. The EP scheme was implemented in a 0D parcel model. It confirms that biological IN account for most of the total IN activation at temperatures warmer than −20°C and at colder temperatures dust and soot become increasingly more important to ice nucleation.

Author(s): Burrows, SM; Maltrud, M; Yang, X; Zhu, Q; Jeffery, N; Shi, X; Ricciuto, D; Wang, S; Bisht, G; Tang, J; Wolfe, J; Harrop, BE; Singh, B; Brent, L; Baldwin, S; Zhou, T; Cameron-Smith, P; Keen, N; Collier, N; Xu, M; Hunke, EC; Elliott, SM; Turner, AK; Li, H; Wang, H; Golaz, JC; Bond-Lamberty, B; Hoffman, FM; Riley, WJ; Thornton, PE; Calvin, K; Leung, LR | Abstract: This paper documents the biogeochemistry configuration of the Energy Exascale Earth System Model (E3SM), E3SMv1.1-BGC. The model simulates historical carbon cycle dynamics, including carbon losses predicted in response to land use and land cover change, and the responses of the carbon cycle to changes in climate. In addition, we introduce several innovations in the treatment of soil nutrient limitation mechanisms, including explicit dependence on phosphorus availability. The suite of simulations described here includes E3SM contributions to the Coupled Climate-Carbon Cycle Model Intercomparison Project and other projects, as well as simulations to explore the impacts of structural uncertainty in representations of nitrogen and phosphorus limitation. We describe the model spin-up and evaluation procedures, provide an overview of results from the simulation campaign, and highlight key features of the simulations. Cumulative warming over the twentieth century is similar to observations, with a midcentury cold bias offset by stronger warming in recent decades. Ocean biomass production and carbon uptake are underpredicted, likely due to biases in ocean transport leading to widespread anoxia and undersupply of nutrients to surface waters. The inclusion of nutrient limitations in the land biogeochemistry results in weaker carbon fertilization and carbon-climate feedbacks than exhibited by other Earth System Models that exclude those limitations. Finally, we compare with an alternative representation of terrestrial biogeochemistry, which differs in structure and in initialization of soil phosphorus. While both configurations agree well with observational benchmarks, they differ significantly in their distribution of carbon among different pools and in the strength of nutrient limitations.

The new Energy Exascale Earth System Model Version 1 (E3SMv1) developed for the U.S. Department of Energy has significant new treatments of aerosols and light‐absorbing snow impurities as well as their interactions with clouds and radiation. This study describes seven sets of new aerosol‐related treatments (involving emissions, new particle formation, aerosol transport, wet scavenging and resuspension, and snow radiative transfer) and examines how they affect global aerosols and radiative forcing in E3SMv1. Altogether, they give a reduced total aerosol radiative forcing (−1.6 W/m2) and sensitivity in cloud liquid water to aerosols, but an increased sensitivity in cloud droplet size to aerosols. A new approach for H2SO4 production and loss largely reduces a low bias in small particles concentrations and leads to substantial increases in cloud condensation nuclei concentrations and cloud radiative cooling. Emitting secondary organic aerosol precursor gases from elevated sources increases the column burden of secondary organic aerosol, contributing substantially to global clear‐sky aerosol radiative cooling (−0.15 out of −0.5 W/m2). A new treatment of aerosol resuspension from evaporating precipitation, developed to remedy two shortcomings of the original treatment, produces a modest reduction in aerosols and cloud droplets; its impact depends strongly on the model physics and is much stronger in E3SM Version 0. New treatments of the mixing state and optical properties of snow impurities and snow grains introduce a positive present‐day shortwave radiative forcing (0.26 W/m2), but changes in aerosol transport and wet removal processes also affect the concentration and radiative forcing of light‐absorbing impurities in snow/ice.

The Sahara in North Africa and the Gobi and Taklamakan deserts in Asia are the primary sources of mobilized dust in the atmosphere, with regional or global airborne transport estimated at 2 to 5 billion tonnes per year. Annual Asian dust plumes take about 7 to 10d to cross the Pacific Ocean, and often reach the northwest USA between late February and May. In contrast, the peak season for the movement of African dust storms to the southeastern USA is typically June to August, and dust plumes take about 5 to 7d to reach Florida. Although studies have documented that a wide range of bacteria, fungi, archaea, and viruses in dust plumes reach the USA each year, little is known about temporal and spatial variability in the microbial biodiversity in transoceanic dust plumes, or the effect on the deposition environments. A scoping study (called the Transoceanic Aerobiology Biodiversity Study) was conducted to develop field-based campaigns centered on examining the abundance, diversity, survival, and impact of microorganisms in transoceanic dust plumes arriving in the continental USA from Asia and Africa. This effort identified Science Questions (SQs) and Knowledge Gaps(KGs) that are highly relevant toward an understanding of the microbial diversity, transport, survival, and dispersal in transoceanic dusts. Science Questions were defined as broad science topics in transoceanic dust plume microbiology that were underexplored by the aerobiology community. Knowledge Gaps were defined as specific project-level research questions for each SQ that represented important topics in the study of transoceanic aerobiology. NASA's Biodiversity Office [NNX16AQ38G]; National Science Foundation grant from the Division of Environmental Biology [1241161, 1643288]; Earth and Biological Sciences Directorate Program Development Funds at Pacific Northwest National Laboratory; U.S. Geological Survey's Environmental Health Toxic Substances Hydrology and Contaminate Biology Programs The project was supported by a scoping study Grant from NASA's Biodiversity Office (Grant #NNX16AQ38G). Partial support to BC was provided by a National Science Foundation grant from the Division of Environmental Biology (1241161 and 1643288). Partial support to SB was funded by the Earth and Biological Sciences Directorate Program Development Funds at Pacific Northwest National Laboratory. DG was partially supported by the U.S. Geological Survey's Environmental Health Toxic Substances Hydrology and Contaminate Biology Programs. Public domain – authored by a U.S. government employee

Evaluating a climate model’s fidelity (ability to simulate observed climate) is a critical step in establishing confidence in the model’s suitability for future climate projections, and in tuning climate model parameters. Model developers use their judgement in determining which trade-offs between different aspects of model fidelity are acceptable. However, little is known about the degree of consensus in these evaluations, and whether experts use the same criteria when different scientific objectives are defined. Here, we report on results from a broad community survey studying expert assessments of the relative importance of different output variables when evaluating a global atmospheric model’s mean climate. We find that experts adjust their ratings of variable importance in response to the scientific objective, for instance, scientists rate surface wind stress as significantly more important for Southern Ocean climate than for the water cycle in the Asian watershed. There is greater consensus on the importance of certain variables (e.g., shortwave cloud forcing) than others (e.g., aerosol optical depth). We find few differences in expert consensus between respondents with greater or less climate modeling experience, and no statistically significant differences between the responses of climate model developers and users. The concise variable lists and community ratings reported here provide baseline descriptive data on current expert understanding of certain aspects of model evaluation, and can serve as a starting point for further investigation, as well as developing more sophisticated evaluation and scoring criteria with respect to specific scientific objectives.

The conservation of total water is an important numerical feature for global Earth system models. Even small conservation problems in the water budget can lead to systematic errors in century-long simulations. This study quantifies and reduces various sources of water conservation error in the atmosphere component of the Energy Exascale Earth System Model. Several sources of water conservation error have been identified during the development of the version 1 (V1) model. The largest errors result from the numerical coupling between the resolved dynamics and the parameterized sub-grid physics. A hybrid coupling using different methods for fluid dynamics and tracer transport provides a reduction of water conservation error by a factor of 50 at 1∘ horizontal resolution as well as consistent improvements at other resolutions. The second largest error source is the use of an overly simplified relationship between the surface moisture flux and latent heat flux at the interface between the host model and the turbulence parameterization. This error can be prevented by applying the same (correct) relationship throughout the entire model. Two additional types of conservation error that result from correcting the surface moisture flux and clipping negative water concentrations can be avoided by using mass-conserving fixers. With all four error sources addressed, the water conservation error in the V1 model becomes negligible and insensitive to the horizontal resolution. The associated changes in the long-term statistics of the main atmospheric features are small. A sensitivity analysis is carried out to show that the magnitudes of the conservation errors in early V1 versions decrease strongly with temporal resolution but increase with horizontal resolution. The increased vertical resolution in V1 results in a very thin model layer at the Earth's surface, which amplifies the conservation error associated with the surface moisture flux correction. We note that for some of the identified error sources, the proposed fixers are remedies rather than solutions to the problems at their roots. Future improvements in time integration would be beneficial for V1.

Aerosols of biological origin play a vital role in the Earth system, particularly in the interactions between atmosphere, biosphere, climate, and public health. Airborne bacteria, fungal spores, pollen, and other bioparticles are essential for the reproduction and spread of organisms across various ecosystems, and they can cause or enhance human, animal, and plant diseases. Moreover, they can serve as nuclei for cloud droplets, ice crystals, and precipitation, thus influencing the hydrological cycle and climate. The sources, abundance, composition, and effects of biological aerosols and the atmospheric microbiome are, however, not yet well characterized and constitute a large gap in the scientific understanding of the interaction and co-evolution of life and climate in the Earth system. This review presents an overview of the state of bioaerosol research, highlights recent advances, and outlines future perspectives in terms of bioaerosol identification, characterization, transport, and transformation processes, as well as their interactions with climate, health, and ecosystems, focusing on the role bioaerosols play in the Earth system.

Experts in data and physical sciences have to regularly grapple with the problem of competing models. Be it analytical or physics-based models, a cross-cutting challenge for experts is to reliably diagnose which model outcomes appropriately predict or simulate real-world phenomena. Expert judgment involves reconciling information across many, and often, conflicting criteria that describe the quality of model outcomes. In this paper, through a design study with climate scientists, we develop a deeper understanding of the problem and solution space of model diagnostics, resulting in the following contributions: i) a problem and task characterization using which we map experts' model diagnostics goals to multi-way visual comparison tasks, ii) a design space of comparative visual cues for letting experts quickly understand the degree of disagreement among competing models and gauge the degree of stability of model outputs with respect to alternative criteria, and iii) design and evaluation of MyriadCues, an interactive visualization interface for exploring alternative hypotheses and insights about good and bad models by leveraging comparative visual cues. We present case studies and subjective feedback by experts, which validate how MyriadCues enables more transparent model diagnostic mechanisms, as compared to the state of the art.

Author(s): Rasch, PJ; Xie, S; Ma, PL; Lin, W; Wang, H; Tang, Q; Burrows, SM; Caldwell, P; Zhang, K; Easter, RC; Cameron-Smith, P; Singh, B; Wan, H; Golaz, JC; Harrop, BE; Roesler, E; Bacmeister, J; Larson, VE; Evans, KJ; Qian, Y; Taylor, M; Leung, LR; Zhang, Y; Brent, L; Branstetter, M; Hannay, C; Mahajan, S; Mametjanov, A; Neale, R; Richter, JH; Yoon, JH; Zender, CS; Bader, D; Flanner, M; Foucar, JG; Jacob, R; Keen, N; Klein, SA; Liu, X; Salinger, AG; Shrivastava, M; Yang, Y | Abstract: The Energy Exascale Earth System Model Atmosphere Model version 1, the atmospheric component of the Department of Energy's Energy Exascale Earth System Model is described. The model began as a fork of the well-known Community Atmosphere Model, but it has evolved in new ways, and coding, performance, resolution, physical processes (primarily cloud and aerosols formulations), testing and development procedures now differ significantly. Vertical resolution was increased (from 30 to 72 layers), and the model top extended to 60 km (~0.1 hPa). A simple ozone photochemistry predicts stratospheric ozone, and the model now supports increased and more realistic variability in the upper troposphere and stratosphere. An optional improved treatment of light-absorbing particle deposition to snowpack and ice is available, and stronger connections with Earth system biogeochemistry can be used for some science problems. Satellite and ground-based cloud and aerosol simulators were implemented to facilitate evaluation of clouds, aerosols, and aerosol-cloud interactions. Higher horizontal and vertical resolution, increased complexity, and more predicted and transported variables have increased the model computational cost and changed the simulations considerably. These changes required development of alternate strategies for tuning and evaluation as it was not feasible to “brute force” tune the high-resolution configurations, so short-term hindcasts, perturbed parameter ensemble simulations, and regionally refined simulations provided guidance on tuning and parameterization sensitivity to higher resolution. A brief overview of the model and model climate is provided. Model fidelity has generally improved compared to its predecessors and the CMIP5 generation of climate models.

Primary biological aerosol particles (PBAPs) may impact human health and aerosol-cloud-climate interactions. The role of PBAPs in the earth system is associated with large uncertainties, for example of source estimates and the atmospheric lifetime. We used a chemistry-climate model to simulate PBAPs in the atmosphere including bacteria and fungal spores. Three fungal spore emission parameterizations have been evaluated against an updated set of spore counts synthesized from observations reported in the literature. The comparison indicates an optimal fit for the emission parameterization proposed by Heald and Spracklen (2009) and adapted by Hoose et al. (2010) for particle sizes of 5 µm or 3 µm, although the model still overpredicts PBAP concentrations in some locations. The correlations between the spore count observations and meteorological parameters simulated by the model show a strong dependence on the leaf area index in non-urban areas and the specific humidity in urban areas. Additional evaluation was performed by comparing our combined bacteria and fungal spore simulations to a global dataset of fluorescent biological aerosol particle (FBAP) concentrations. The model predicts the total sum of measured PBAP concentrations relatively well, typically within a factor of two of FBAP. Further, the modeled fungal spore results deviate from the FBAP concentrations when used as a rough proxy for spores, depending on the particle size used in the parametrization. Uncertainties related to technical aspects of the FBAP and direct-counting spore measurements challenge the ability to further refine quantitative comparison on this scale. Additional long-term data of better quality are needed to improve emission parameterizations.

In the Amazon basin, particles containing mixed sodium salts are routinely observed and are attributed to marine aerosols transported from the Atlantic Ocean. Using chemical imaging analysis, we show that, during the wet season, fungal spores emitted by the forest biosphere contribute at least 30% (by number) to sodium salt particles in the central Amazon basin. Hydration experiments indicate that sodium content in fungal spores governs their growth factors. Modeling results suggest that fungal spores account for ~69% (31–95%) of the total sodium mass during the wet season and that their fractional contribution increases during nighttime. Contrary to common assumptions that sodium-containing aerosols originate primarily from marine sources, our results suggest that locally-emitted fungal spores contribute substantially to the number and mass of coarse particles containing sodium. Hence, their role in cloud formation and contribution to salt cycles and the terrestrial ecosystem in the Amazon basin warrant further consideration., Salt particles in the Amazon basin are typically attributed to marine aerosols transported from the Atlantic Ocean. Here the authors show the potential importance of fungal spores as a source of sodium-salt particles in the Amazon rainforest.

Here we show that the addition of chemical interactions between soluble monosaccharides and an insoluble lipid surfactant monolayer improves agreement of modeled sea spray chemistry with observed marine aerosol chemistry. In particular, the alkane:hydroxyl mass ratio in modeled sea spray organic matter is reduced from a median of 2.73 to a range of 0.41–0.69, reducing the discrepancy with previous Fourier transform infrared spectroscopy (FTIR) observations of clean marine aerosol (ratio: 0.24–0.38). The overall organic fraction of submicron sea spray also increases, allowing organic mass fractions in the range 0.5–0.7 for submicron sea spray particles over highly active phytoplankton blooms. Sum frequency generation experiments support the modeling approach by demonstrating that soluble monosaccharides can strongly adsorb to a lipid monolayer likely via Coulomb interactions under appropriate conditions. These laboratory findings motivate further research to determine the relevance of coadsorption mechanisms for real-world, sea spray aerosol production.

Biogenic aerosols are relevant for the Earth system, climate, and public health on local, regional, and global scales. Up to now, however, little is known about the diversity and biogeography of airborne microorganisms. We present the first DNA-based analysis of airborne fungi on global scales, showing pronounced geographic patterns and boundaries. In particular we found that the ratio of species richness between Basidiomycota and Ascomycota is much higher in continental air than in marine air. This may be an important difference between the "blue ocean" and "green ocean" regimes in the formation of clouds and precipitation, for which fungal spores can act as nuclei. Our findings also suggest that air flow patterns and the global atmospheric circulation are important for the evolution of microbial ecology and for the understanding of global changes in biodiversity.

The OCEANFILMS parameterization for sea-spray organic aerosol emissions has been implemented into a global Earth system model, the Energy Exascale Earth System Model (E3SM). OCEANFILMS is a physically-based model that links sea spray chemistry with ocean biogeochemistry using a Langmuir partitioning approach. Here we describe the implementation within E3SM and investigate the impacts of the parameterization on the model's aerosols, clouds and climate. Four sensitivity cases are tested, in which organic emissions either strictly add to or strictly replace sea salt emissions (in mass and number), and are either fully internally or fully externally mixed with sea salt. The simulation with internally-mixed, added organics agrees best with observed seasonal cycles of organic matter in marine aerosol. In this configuration, marine organic aerosols contribute an additional source of cloud condensation nuclei, adding up to 30 cm−3 to Southern Ocean boundary-layer CCN concentrations (supersaturation = 0.1 %). The addition of this new aerosol source strengthens shortwave radiative cooling by clouds by −0.36 W/m2 in the global annual mean, and contributes more than −3.5 W/m2 to summertime zonal mean cloud forcing in the Southern Ocean, with maximum zonal mean impacts of about −4 W/m2 around 50° S–60° S. This is consistent with a previous top-down, satellite-based empirical estimate of the radiative forcing by marine organic aerosol over the Southern Ocean.

Primary biological aerosol particles (PBAPs) may impact human health and aerosol-climate interactions. The role of PBAPs in the earth system is associated with large uncertainties, related to source estimates and atmospheric transport. We used a chemistry-climate model to simulate PBAPs in the atmosphere including bacteria, fungal spores and pollen. Three fungal spore emission parameterizations have been evaluated against an updated set of spore counts synthesized from observations reported in the literature. The comparison indicates an optimal fit for the emission parameterization proposed by Heald and Spracklen (2009), although the model significantly over-predicts PBAP concentrations in some locations. Additional evaluation was performed by comparing our combined bacteria and fungal spore simulations to a global dataset of fluorescent biological aerosol particle (FBAP) concentrations. The model predicts the sum total of measured PBAP concentrations relatively well, with an over- or under-prediction of less than a factor of 2 compared to FBAP. The ratio of bacteria to fungal spores reflects a greater difference, however, and the simulated bacteria concentrations outnumber the simulated fungal spore concentrations in almost all locations. Further, the modeled fungal spore results under-predict the FBAP concentrations, which are used here as a rough proxy for spores. Uncertainties related to technical aspects of the FBAP and direct-counting spore measurements challenge the ability to further refine quantitative comparison on this scale. We estimate that the global PBAPs mass concentration (apart from desert dust and sea salt aerosols), i.e. of fungal spores and pollen, amounts to 19 % and 52 % of the total aerosol mass, respectively.

The presence of a large fraction of organic matter in primary sea spray aerosol (SSA) can strongly affect its cloud condensation nuclei activity and interactions with marine clouds. Global climate models require new parameterizations of the SSA composition in order to improve the representation of these processes. Existing proposals for such a parameterization use remotely sensed chlorophyll a concentrations as a proxy for the biogenic contribution to the aerosol. However, both observations and theoretical considerations suggest that existing relationships with chlorophyll a, derived from observations at only a few locations, may not be representative for all ocean regions. We introduce a novel framework for parameterizing the fractionation of marine organic matter into SSA based on a competitive Langmuir adsorption equilibrium at bubble surfaces. Marine organic matter is partitioned into classes with differing molecular weights, surface excesses, and Langmuir adsorption parameters. The classes include a lipid-like mixture associated with labile dissolved organic carbon (DOC), a polysaccharide-like mixture associated primarily with semilabile DOC, a protein-like mixture with concentrations intermediate between lipids and polysaccharides, a processed mixture associated with recalcitrant surface DOC, and a deep abyssal humic-like mixture. Box model calculations have been performed for several cases of organic adsorption to illustrate the underlying concepts. We then apply the framework to output from a global marine biogeochemistry model, by partitioning total dissolved organic carbon into several classes of macromolecules. Each class is represented by model compounds with physical and chemical properties based on existing laboratory data. This allows us to globally map the predicted organic mass fraction of the nascent submicron sea spray aerosol. Predicted relationships between chlorophyll a and organic fraction are similar to existing empirical parameterizations, but can vary between biologically productive and nonproductive regions, and seasonally within a given region. Major uncertainties include the bubble film thickness at bursting, and the variability of organic surfactant activity in the ocean, which is poorly constrained. In addition, polysaccharides may enter the aerosol more efficiently than Langmuir adsorption would suggest. Potential mechanisms for enrichment of polysaccharides in sea spray include the formation of marine colloidal particles that may be more efficiently swept up by rising bubbles, and cooperative adsorption of polysaccharides with proteins or lipids. These processes may make important contributions to the aerosol, but are not included here. This organic fractionation framework is an initial step towards a closer linking of ocean biogeochemistry and aerosol chemical composition in Earth system models. Future work should focus on improving constraints on model parameters through new laboratory experiments or through empirical fitting to observed relationships in the real ocean and atmosphere, as well as on atmospheric implications of the variable composition of organic matter in sea spray.

The oceans represent a significant global source of atmospheric aerosols. Sea spray aerosol (SSA) particles comprise sea salts and organic species in varying proportions. In addition to size, the overall composition of SSA particles determines how effectively they can form cloud droplets and ice crystals. Thus, understanding the factors controlling SSA composition is critical to predicting aerosol impacts on clouds and climate. It is often assumed that submicrometer SSAs are mainly formed by film drops produced from bursting bubble-cap films, which become enriched with hydrophobic organic species contained within the sea surface microlayer. In contrast, jet drops formed from the base of bursting bubbles are postulated to mainly produce larger supermicrometer particles from bulk seawater, which comprises largely salts and water-soluble organic species. However, here we demonstrate that jet drops produce up to 43% of total submicrometer SSA number concentrations, and that the fraction of SSA produced by jet drops can be modulated by marine biological activity. We show that the chemical composition, organic volume fraction, and ice nucleating ability of submicrometer particles from jet drops differ from those formed from film drops. Thus, the chemical composition of a substantial fraction of submicrometer particles will not be controlled by the composition of the sea surface microlayer, a major assumption in previous studies. This finding has significant ramifications for understanding the factors controlling the mixing state of submicrometer SSA particles and must be taken into consideration when predicting SSA impacts on clouds and climate.

Despite the huge extent of the ocean's surface, until now relatively little attention has been paid to the sea surface microlayer (SML) as the ultimate interface where heat, momentum and mass exchange between the ocean and the atmosphere takes place. Via the SML, large-scale environmental changes in the ocean such as warming, acidification, deoxygenation, and eutrophication potentially influence cloud formation, precipitation, and the global radiation balance. Due to the deep connectivity between biological, chemical, and physical processes, studies of the SML may reveal multiple sensitivities to global and regional changes. Understanding the processes at the ocean's surface, in particular involving the SML as an important and determinant interface, could therefore provide an essential contribution to the reduction of uncertainties regarding ocean-climate feedbacks. This review identifies gaps in our current knowledge of the SML and highlights a need to develop a holistic and mechanistic understanding of the diverse biological, chemical, and physical processes occurring at the ocean-atmosphere interface. We advocate the development of strong interdisciplinary expertise and collaboration in order to bridge between ocean and atmospheric sciences. Although this will pose significant methodological challenges, such an initiative would represent a new role model for interdisciplinary research in Earth System sciences.

Scientists often use specific data analysis and presentation methods familiar within their domain. But does high familiarity drive better analytical judgment? This question is especially relevant when familiar methods themselves can have shortcomings: many visualizations used conventionally for scientific data analysis and presentation do not follow established best practices. This necessitates new methods that might be unfamiliar yet prove to be more effective. But there is little empirical understanding of the relationships between scientists' subjective impressions about familiar and unfamiliar visualizations and objective measures of their visual analytic judgments. To address this gap and to study these factors, we focus on visualizations used for comparison of climate model performance. We report on a comprehensive survey-based user study with 47 climate scientists and present an analysis of: i) relationships among scientists' familiarity, their perceived levels of comfort, confidence, accuracy, and objective measures of accuracy, and ii) relationships among domain experience, visualization familiarity, and post-study preference.

Ice nucleating particles (INP) are known to affect the amount of ice in mixed-phase clouds, thereby influencing many of their properties. The atmospheric INP concentration changes by orders of magnitude from terrestrial to marine environments, which typically contain much lower concentrations. Many modelling studies use parameterizations for heterogeneous ice nucleation and cloud ice processes that do not account for this difference because they were developed based on measurements predominantly from terrestrial environments. Errors in the assumed INP concentration will influence the simulated amount of ice in mixed-phase clouds, leading to errors in top-of-atmosphere radiative flux and ultimately the climate sensitivity of climate models. Here we develop a global model of INP concentrations relevant for mixed-phase clouds based on laboratory and field measurements of ice nucleation by K-feldspar (an ice-active component of desert dust) and marine organic aerosols (from sea spray). The simulated global distribution of INP concentrations based on these two-species agrees much better with currently available ambient measurements than when INP concentrations are assumed to depend only on temperature or particle size. Underestimation of INP concentrations in some terrestrial locations may be due to neglect of INP from other terrestrial sources. Our model indicates that, on a monthly or yearly average basis, desert dusts dominate the contribution to the INP population over much of the world, but marine organics become increasingly important in the world's remote oceans and can dominate in the Southern Ocean at some time of the year. Furthermore, we show that day-to-day variability is important and since desert dust aerosol tends to be sporadic, marine organics dominate the INP population on many days per month in much of the mid and high latitude northern hemisphere. This study advances our understanding of which aerosol species need to be included in order to adequately describe the global and regional distribution of INP in models, which will guide ice nucleation researchers on where to focus future laboratory and field work.