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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 (60 km in the midlatitudes and 30 km at the equator and poles), and river transport (55 km) 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 = −1.65 W/m2) and high equilibrium climate sensitivity (ECS = 5.3 K).

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.

Numerical weather, climate, or Earth system models involve the coupling of components. At a broad level, these components can be classified as the resolved fluid dynamics, unresolved fluid dynamical aspects (i.e., those represented by physical parameterizations such as subgrid-scale mixing), and nonfluid dynamical aspects such as radiation and microphysical processes. Typically, each component is developed, at least initially, independently.Once development ismature, the components are coupled to deliver a model of the required complexity. The implementation of the coupling can have a significant impact on the model.As the error associated with each component decreases, the errors introduced by the coupling will eventually dominate. Hence, any improvement in one of the components is unlikely to improve the performance of the overall system. The challenges associated with combining the components to create a coherentmodel are here termed physics-dynamics coupling. The issue goes beyond the coupling between the parameterizations and the resolved fluid dynamics. This paper highlights recent progress and some of the current challenges. It focuses on three objectives: to illustrate the phenomenology of the coupling problemwith references to examples in the literature, to show howthe problem can be analyzed, and to create awareness of the issue across the disciplines and specializations. The topics addressed are different ways of advancing full models in time, approaches to understanding the role of the coupling and evaluation of approaches, coupling ocean and atmosphere models, thermodynamic compatibility between model components, and emerging issues such as those that arise as model resolutions increase and/ormodels use variable resolutions.

We use three 150 year preindustrial simulations of the Community Earth System Model to quantify the impacts of El Niño-Southern Oscillation (ENSO) events on shortwave and longwave cloud radiative effects (CRESW and CRELW). Compared to recent observations from the Clouds and the Earth’s Radiant Energy System data set, the model simulation successfully reproduces larger variations of CRESW and CRELW over the tropics. The ENSO cycle is found to dominate interannual variations of cloud radiative effects. Simulated cooling (warming) effects from CRESW (CRELW) are strongest over the tropical western and central Pacific Ocean during warm ENSO events, with the largest difference between 20 and 60Wm-2, with weaker effects of 10-40Wm-2 over Indonesian regions and the subtropical Pacific Ocean. Sensitivity tests show that variations of cloud radiative effects are mainly driven by ENSO-related changes in cloud fraction. The variations in midlevel and high cloud fractions each account for approximately 20-50% of the interannual variations of CRESW over the tropics and almost all of the variations of CRELW between 60°S and 60°N. The variation of low cloud fraction contributes to most of the variations of CRESW over the midlatitude oceans. Variations in natural aerosol concentrations explained 10-30% of the variations of both CRESW and CRELW over the tropical Pacific, Indonesian regions, and the tropical Indian Ocean. Changes in natural aerosol emissions and concentrations enhance 3-5% and 1-3% of the variations of cloud radiative effects averaged over the tropics.

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth's clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol-cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol-cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol-cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty.

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth's clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol-cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol-cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol-cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty.

This study examines multiyear climate variability associated with sea salt aerosols and their contribution to the variability of shortwave cloud forcing (SWCF) using a 150 year simulation for preindustrial conditions of the Community Earth System Model version 1.0. The results suggest that changes in sea salt and related cloud and radiative properties on interannual timescales are dominated by the El Niño-Southern Oscillation cycle. Sea salt variability on longer (interdecadal) timescales is associated with low-frequency variability in the Pacific Ocean similar to the Interdecadal Pacific Oscillation but does not show a statistically significant spectral peak. A multivariate regression suggests that sea salt aerosol variability may contribute to SWCF variability in the tropical Pacific, explaining up to 20-30% of the variance in that region. Elsewhere, there is only a small sea salt aerosol influence on SWCF through modifying cloud droplet number and liquid water path that contributes to the change of cloud effective radius and cloud optical depth (and hence cloud albedo), producing a multiyear aerosol-cloud-wind interaction.

During El Niño years, fires in tropical forests and peatlands in equatorial Asia create large regional smoke clouds. We characterized the sensitivity of these clouds to regional drought, and we investigated their effects on climate by using an atmospheric general circulation model. Satellite observations during 2000–2006 indicated that El Niño-induced regional drought led to increases in fire emissions and, consequently, increases in aerosol optical depths over Sumatra, Borneo and the surrounding ocean. Next, we used the Community Atmosphere Model (CAM) to investigate how climate responded to this forcing. We conducted two 30 year simulations in which monthly fire emissions were prescribed for either a high (El Niño, 1997) or low (La Niña, 2000) fire year using a satellite-derived time series of fire emissions. Our simulations included the direct and semi-direct effects of aerosols on the radiation budget within the model. We assessed the radiative and climate effects of anthropogenic fire by analyzing the differences between the high and low fire simulations. Fire aerosols reduced net shortwave radiation at the surface during August–October by 19.1±12.9 W m−2(10%) in a region that encompassed most of Sumatra and Borneo (90° E–120° E, 5° S–5° N). The reductions in net shortwave radiation cooled sea surface temperatures (SSTs) and land surface temperatures by 0.5±0.3 and 0.4±0.2 °C during these months. Tropospheric heating from black carbon (BC) absorption averaged 20.5±9.3 W m−2 and was balanced by a reduction in latent heating. The combination of decreased SSTs and increased atmospheric heating reduced regional precipitation by 0.9±0.6 mm d−1 (10%). The vulnerability of ecosystems to fire was enhanced because the decreases in precipitation exceeded those for evapotranspiration. Together, the satellite and modeling results imply a possible positive feedback loop in which anthropogenic burning in the region intensifies drought stress during El Niño.

Boreal spring climate is uniquely susceptible to solar warming mechanisms because it has expansive snow cover and receives relatively strong insolation. Carbonaceous particles can influence snow coverage by warming the atmosphere, reducing surface-incident solar energy (dimming), and reducing snow reflectance after deposition (darkening). We apply a range of models and observations to explore impacts of these processes on springtime climate, drawing several conclusions: 1) Nearly all atmospheric particles (those with visible-band single-scatter albedo less than 0.999), including all mixtures of black carbon (BC) and organic matter (OM), increase net solar heating of the atmosphere-snow column. 2) Darkening caused by small concentrations of particles within snow exceeds the loss of absorbed energy from concurrent dimming, thus increasing solar heating of snowpack as well (positive net surface forcing). Over global snow, we estimate 6-fold greater surface forcing from darkening than dimming, caused by BC+OM. 3) Equilibrium climate experiments suggest that fossil fuel and biofuel emissions of BC+OM induce 95% as much springtime snow cover loss over Eurasia as anthropogenic carbon dioxide, a consequence of strong snow-albedo feedback and large BC+OM emissions from Asia. 4) Of 22 climate models contributing to the IPCC Fourth Assessment Report, 21 underpredict the rapid warming (0.64°C decade−1) observed over springtime Eurasia since 1979. Darkening from natural and anthropogenic sources of BC and mineral dust exerts 3-fold greater forcing on springtime snow over Eurasia (3.9 W m−2) than North America (1.2 W m−2). Inclusion of this forcing significantly improves simulated continental warming trends, but does not reconcile the low bias in rate of Eurasian spring snow cover decline exhibited by all models, likely because BC deposition trends are negative or near-neutral over much of Eurasia. Improved Eurasian warming may therefore relate more to darkening-induced reduction in mean snow cover.

We apply our Snow, Ice, and Aerosol Radiative (SNICAR) model, coupled to a general circulation model with prognostic carbon aerosol transport, to improve understanding of climate forcing and response from black carbon (BC) in snow. Building on two previous studies, we account for interannually varying biomass burning BC emissions, snow aging, and aerosol scavenging by snow meltwater. We assess uncertainty in forcing estimates from these factors, as well as BC optical properties and snow cover fraction. BC emissions are the largest source of uncertainty, followed by snow aging. The rate of snow aging determines snowpack effective radius (r e), which directly controls snow reflectance and the magnitude of albedo change caused by BC. For a reasonable r e range, reflectance reduction from BC varies threefold. Inefficient meltwater scavenging keeps hydrophobic impurities near the surface during melt and enhances forcing. Applying biomass burning BC emission inventories for a strong (1998) and weak (2001) boreal fire year, we estimate global annual mean BC/snow surface radiative forcing from all sources (fossil fuel, biofuel, and biomass burning) of +0.054 (0.007–0.13) and +0.049 (0.007–0.12) W m−2, respectively. Snow forcing from only fossil fuel + biofuel sources is +0.043 W m−2 (forcing from only fossil fuels is +0.033 W m−2), suggesting that the anthropogenic contribution to total forcing is at least 80%. The 1998 global land and sea-ice snowpack absorbed 0.60 and 0.23 W m−2, respectively, because of direct BC/snow forcing. The forcing is maximum coincidentally with snowmelt onset, triggering strong snow-albedo feedback in local springtime. Consequently, the “efficacy” of BC/snow forcing is more than three times greater than forcing by CO2. The 1998 and 2001 land snowmelt rates north of 50°N are 28% and 19% greater in the month preceding maximum melt of control simulations without BC in snow. With climate feedbacks, global annual mean 2-meter air temperature warms 0.15 and 0.10°C, when BC is included in snow, whereas annual arctic warming is 1.61 and 0.50°C. Stronger high-latitude climate response in 1998 than 2001 is at least partially caused by boreal fires, which account for nearly all of the 35% biomass burning contribution to 1998 arctic forcing. Efficacy was anomalously large in this experiment, however, and more research is required to elucidate the role of boreal fires, which we suggest have maximum arctic BC/snow forcing potential during April–June. Model BC concentrations in snow agree reasonably well (r = 0.78) with a set of 23 observations from various locations, spanning nearly 4 orders of magnitude. We predict concentrations in excess of 1000 ng g−1 for snow in northeast China, enough to lower snow albedo by more than 0.13. The greatest instantaneous forcing is over the Tibetan Plateau, exceeding 20 W m−2 in some places during spring. These results indicate that snow darkening is an important component of carbon aerosol climate forcing.

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.

n this study, we present the results of nitrogen deposition on land from a set of 29 simulations from six different tropospheric chemistry models pertaining to present-day and 2100 conditions. Nitrogen deposition refers here to the deposition (wet and dry) of all nitrogen-containing gas phase chemical species resulting from NOx (NO + NO2) emissions. We show that under the assumed IPCC SRES A2 scenario the global annual average nitrogen deposition over land is expected to increase by a factor of ∼2.5, mostly because of the increase in nitrogen emissions. This will significantly expand the areas with annual average deposition exceeding 1 gN/m2/year. Using the results from all models, we have documented the strong linear relationship between models on the fraction of the nitrogen emissions that is deposited, regardless of the emissions (present day or 2100). On average, approximately 70% of the emitted nitrogen is deposited over the landmasses. For present-day conditions the results from this study suggest that the deposition over land ranges between 25 and 40 Tg(N)/year. By 2100, under the A2 scenario, the deposition over the continents is expected to range between 60 and 100 Tg(N)/year. Over forests the deposition is expected to increase from 10 Tg(N)/year to 20 Tg(N)/year. In 2100 the nitrogen deposition changes from changes in the climate account for much less than the changes from increased nitrogen emissions.

The direct radiative forcing by aerosols over the Indian Ocean region is simulated for the Indian Ocean Experiment (INDOEX) Intensive Field Phase during Spring 1999. The forcing is calculated for the top-of-atmosphere (TOA), surface, and atmosphere by differencing shortwave fluxes computed with and without aerosols. The calculation includes the effects of sea-salt, sulfate, carbonaceous, and soil-dust aerosols. The aerosol distributions are obtained from a global aerosol simulation including assimilation of satellite retrievals of aerosol optical thickness (AOT). The time-dependent, three-dimensional aerosol distributions are derived with a chemical transport model driven with meteorological analyses for this period. The surface albedos are obtained from a land-surface model forced with an identical meteorological analysis and satellite-derived rainfall and insolation. These calculations are consistent with in situ observations of the surface insolation over the central Indian Ocean and with satellite measurements of the reflected shortwave radiation. The calculations show that the surface insolation under clear skies is reduced by as much as 40 W/m2 over the Indian subcontinent by natural and anthropogenic aerosols. This reduction in insolation is accompanied by an increase in shortwave flux absorbed in the atmosphere by 25 W/m2. The inclusion of clouds in the calculations changes the direct effect by less than 2 W/m2 over the Indian subcontinent, although the reduction is much larger over China. The magnitude of the difference between all-sky and clear-sky forcing is quite sensitive to the three-dimensional spatial relationship between the aerosol and cloud fields, and other estimates of the difference for the INDOEX Intensive Field Phase are as large as 5 W/m2.

A system for simulating aerosols has been developed using a chemical transport model together with an assimilation of satellite aerosol retrievals. The methodology and model components are described in this paper, and the modeled distribution of aerosols for the Indian Ocean Experiment (INDOEX) is presented by Rasch et al. [this issue]. The system generated aerosol forecasts to guide deployment of ships and aircraft during INDOEX. The system consists of the Model of Atmospheric Transport and Chemistry (MATCH) combined with an assimilation package developed for applications in atmospheric chemistry. MATCH predicts the evolution of sulfate, carbonaceous, and mineral dust aerosols, and it diagnoses the distribution of sea salt aerosols. The model includes a detailed treatment of the sources, chemical transformation, transport, and deposition of the aerosol species. The aerosol forecasts involve a two-stage process. During the assimilation phase the total column aerosol optical depth (AOD) is estimated from the model aerosol fields. The model state is then adjusted to improve the agreement between the simulated AOD and satellite retrievals of AOD. During the subsequent integration phase the aerosol fields are evolved using meteorological fields from an external model. Comparison of the modeled AOD against estimates of the AOD from INDOEX Sun photometer data show that the differences in daily means are -0.03 ± 0.06. Although the initial application is limited to the Indian Ocean, the methodology could be extended to derive global aerosol analyses combining in situ and remotely sensed aerosol observations. Copyright 2001 by the American Geophysical Union.

We describe the three-dimensional global stratospheric chemistry model developed under the NASA Global Modeling Initiative (GMI) to assess the possible environmental consequences from the emissions of a fleet of proposed high-speed civil transport aircraft. This model was developed through a unique collaboration of the members of the GMI team. Team members provided computational modules representing various physical and chemical processes, and analysis of simulation results through extensive comparison to observation. The team members' modules were integrated within a computational framework that allowed transportability and simulations on massively parallel computers. A unique aspect of this model framework is the ability to interchange and intercompare different submodules to assess the sensitivity of numerical algorithms and model assumptions to simulation results. In this paper, we discuss the important attributes of the GMI effort and describe the GMI model computational framework and the numerical modules representing physical and chemical processes. As an application of the concept, we illustrate an analysis of the impact of advection algorithms on the dispersion of a NOy-like source in the stratosphere which mimics that of a fleet of commercial supersonic transports (high-speed civil transport (HSCT)) flying between 17 and 20 km.

The NASA Atmospheric Effects of Aviation Project (AEAP) Global Modeling Initiative (GMI) three-dimensional (3-D) chemical transport model (CTM) was applied to assess the impact of a fleet of high-speed civil transports (HSCTs) on abundances of stratospheric ozone, total inorganic nitrogen (NOy), and H2O. This model is specifically designed to incorporate a diversity of approaches to chemical and physical processes related to the stratosphere in a single computing framework, facilitating the analysis of model component differences, modeling intercomparison and comparison with data. A proposed HSCT fleet scenario was adopted, in which the aircraft cruise in the lower stratosphere, emitting nitrogen oxides (NOx) and water (H2O). The model calculated an HSCT-induced change in Northern and Southern Hemisphere total column ozone of +0.2% and +0.05%, respectively. This change is the result of a balance between an increase in local ozone below approximately 25 km and a decrease above this altitude. When compared to available NOy observations, we find that the model consistently underestimates lower stratospheric NOy. This discrepancy is consistent with the model bias toward less negative ozone impact, when compared to results from other models. Additional analysis also indicates that for an HSCT assessment it is equally important for a model to accurately represent the lower stratospheric concentrations of ozone and H2O. The GMI model yields good agreement in comparisons to ozone data for present-day conditions, while H2O is constrained by climatology as much as possible; thus no further biases would be expected from these comparisons. Uncertainties due to discrepancies in the calculated age of air compared to that derived from measurements, and of the impact of emissions on heterogeneous and polar chemistry, are difficult to evaluate at this point.

We report on results from a World Climate Research Program workshop on representations ofscavenging and deposition processes in global transport models of the atmosphere. 15 modelswere evaluated by comparing simulations of radon, lead, sulfur dioxide, and sulfate against eachother, and against observations of these constituents. This paper provides a survey on the simulationdifferences between models. It identifies circumstances where models are consistent withobservations or with each other, and where they differ from observations or with each other. Thecomparison shows that most models are able to simulate seasonal species concentrations nearthe surface over continental sites to within a factor of 2 over many regions of the globe. Modelstend to agree more closely over source (continental ) regions than for remote (polar and oceanic)regions. Model simulations differ most strongly in the upper troposphere for species undergoingwet scavenging processes. There are not a sufficient number of observations to characterize theclimatology ( long-term average) of species undergoing wet scavenging in the upper troposphere.This highlights the need for either a different strategy for model evaluation (e.g., comparisons onan event by event basis) or many more observations of a few carefully chosen constituents.

The global modeling initiative (GMI) science team is developing a three-dimensional chemistry and transport model (CTM) for use in assessment of the atmospheric effects of aviation. This model must be documented, be validated against observations, use a realistic atmospheric circulation, and contain numerical transport and photochemical modules representing atmospheric processes. The model must retain computational efficiency for multiple scenarios and sensitivity studies. To meet these requirements, a facility model concept was developed in which the different components of the CTM are evaluated separately. The assessment of the impact on the stratosphere of the exhaust of supersonic aircraft will depend strongly on the meteorological fields used by the CTM. Three data sets for the stratosphere were considered: the National Center for Atmospheric Research Community Climate Model (CCM2), the Goddard Earth Observing System data assimilation system, and the Goddard Institute for Space Studies general circulation model. Objective criteria were developed to identify the data set that provides the best representation of the stratosphere. Simulations of gases with simple chemical control were chosen to test various aspects of model transport. The data sets were evaluated and graded on their performance on these tests. The CCM2 meteorological data set has the highest score and was selected for GMI. This objective model evaluation establishes a physical basis for interpretation of differences between models and observations. Further, the method provides a quantitative basis for defining model errors, for discriminating between different models, and for ready reevaluation of improved models. This will lead to higher confidence in assessment calculations.

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.