Explore the vast range of titles available.

The Indian summer monsoon is influenced by numerous factors, including aerosol-induced changes to clouds, surface and atmospheric heating, and atmospheric circulation. Most previous studies assessing the effect of aerosols on monsoon rainfall have focussed on the local impact of aerosols on precipitation on monthly to seasonal timescales. Here, we show that desert dust aerosol levels over the Arabian Sea, West Asia and the Arabian Peninsula are positively correlated with the intensity of the Indian summer monsoon, using satellite data and models; a lead–lag analysis indicates that dust and precipitation vary in concert over timescales of about a week. Our analysis of global climate model simulations indicates that by heating the atmosphere, dust aerosols induce large-scale convergence over North Africa and the Arabian Peninsula, increasing the flow of moisture over India within a week. According to these simulations, dust-induced heating of the atmosphere over North Africa and West Asia rapidly modulates monsoon rainfall over central India. The Indian summer monsoon is influenced by numerous factors, including aerosol-induced changes to clouds, surface and atmospheric heating, and atmospheric circulation. An analysis of satellite data and global climate model simulations suggests that dust aerosol levels over the Arabian Sea, West Asia and the Arabian Peninsula are positively correlated with the intensity of the Indian summer monsoon.

This study provides comprehensive insight into the notable differences in clouds and precipitation simulated by the Energy Exascale Earth System Model Atmosphere Model version 0 and version 1 (EAMv1). Several sensitivity experiments are conducted to isolate the impact of changes in model physics, resolution, and parameter choices on these differences. The overall improvement in EAMv1 clouds and precipitation is primarily attributed to the introduction of a simplified third‐order turbulence parameterization Cloud Layers Unified By Binormals (along with the companion changes) for a unified treatment of boundary layer turbulence, shallow convection, and cloud macrophysics, though it also leads to a reduction in subtropical coastal stratocumulus clouds. This lack of stratocumulus clouds is considerably improved by increasing vertical resolution from 30 to 72 layers, but the gain is unfortunately subsequently offset by other retuning to reach the top‐of‐atmosphere energy balance. Increasing vertical resolution also results in a considerable underestimation of high clouds over the tropical warm pool, primarily due to the selection for numerical stability of a higher air parcel launch level in the deep convection scheme. Increasing horizontal resolution from 1° to 0.25° without retuning leads to considerable degradation in cloud and precipitation fields, with much weaker tropical and subtropical short‐ and longwave cloud radiative forcing and much stronger precipitation in the intertropical convergence zone, indicating poor scale awareness of the cloud parameterizations. To avoid this degradation, significantly different parameter settings for the low‐resolution (1°) and high‐resolution (0.25°) were required to achieve optimal performance in EAMv1. Plain Language Summary The Energy Exascale Earth System Model (E3SM) is a new and ongoing U.S. Department of Energy (DOE) climate modeling effort to develop a high‐resolution Earth system model specifically targeting next‐generation DOE supercomputers to meet the science needs of the nation and the mission needs of DOE. The increase of model resolution along with improvements in representing cloud and convective processes in the E3SM atmosphere model version 1 has led to quite significant model behavior changes from its earlier version, particularly in simulated clouds and precipitation. To understand what causes the model behavior changes, this study conducts sensitivity experiments to isolate the impact of changes in model physics, resolution, and parameter choices on these changes. Results from these sensitivity tests and discussions on the underlying physical processes provide substantial insight into the model errors and guidance for future E3SM development. Key Points CLUBB along with the companion changes in EAMv1 primarily account for the overall improvements in clouds and precipitation simulation Underestimate of coastal Sc in EAMv1 is due to CLUBB and model tuning; increased vertical resolution partially offsets this degradation The poor scale awareness of EAMv1 requires retuning as resolution increases, which has a large impact on model cloud behavior

The global source–receptor relationships of sulfate concentrations, and direct and indirect radiative forcing (DRF and IRF) from 16 regions/sectors for years 2010–2014 are examined in this study through utilizing a sulfur source-tagging capability implemented in the Community Earth System Model (CESM) with winds nudged to reanalysis data. Sulfate concentrations are mostly contributed by local emissions in regions with high emissions, while over regions with relatively low SO2 emissions, the near-surface sulfate concentrations are primarily attributed to non-local sources from long-range transport. Regional source efficiencies of sulfate concentrations are higher over regions with dry atmospheric conditions and less export, suggesting that lifetime of aerosols, together with regional export, is important in determining regional air quality. The simulated global total sulfate DRF is −0.42 W m−2, with −0.31 W m−2 contributed by anthropogenic sulfate and −0.11 W m−2 contributed by natural sulfate, relative to a state with no sulfur emissions. In the Southern Hemisphere tropics, dimethyl sulfide (DMS) contributes 17–84 % to the total DRF. East Asia has the largest contribution of 20–30 % over the Northern Hemisphere mid- and high latitudes. A 20 % perturbation of sulfate and its precursor emissions gives a sulfate incremental IRF of −0.44 W m−2. DMS has the largest contribution, explaining −0.23 W m−2 of the global sulfate incremental IRF. Incremental IRF over regions in the Southern Hemisphere with low background aerosols is more sensitive to emission perturbation than that over the polluted Northern Hemisphere.

Previous studies have noticed that the Coupled Model Intercomparison Project Phase 6 (CMIP6) models with a stronger cooling from aerosol‐cloud interactions (ACI) also have an enhanced warming from positive cloud feedback, and these two opposing effects are counter‐balanced in simulations of the historical period. However, reasons for this anti‐correlation are less explored. In this study, we perturb the cloud ice microphysical processes to obtain cloud liquid of varying amounts in two Earth System Models (ESMs). We find that the model simulations with a larger liquid water path (LWP) tend to have a stronger cooling from ACI and a stronger positive cloud feedback. More liquid clouds in the mean‐state present more opportunities for anthropogenic aerosol perturbations and also weaken the negative cloud feedback at middle to high latitudes. This work, from a cloud state perspective, emphasizes the influence of the mean‐state LWP on effective radiative forcing due to ACI (ERFACI). Plain Language Summary Since the preindustrial era, emissions of greenhouse gases (GHGs) and aerosols have both increased substantially. Planetary warming from the elevated GHGs causes changes in cloud distribution and properties, thereby imposing feedbacks on the climate system. At the same time, aerosols from air pollution exert a cooling effect by modifying cloud properties and lifetime. Cloud feedback and aerosol‐cloud interactions (ACI) are two critical factors for understanding the past and projecting the future climate change. In this study, we examine the relationships of ACI and cloud feedback with the mean‐state cloud liquid water amount predicted from simulations with two different Earth system models. We find that both the effective radiative forcing due to aerosol‐cloud interactions (ERFACI) and the cloud feedback are modulated by mean‐state liquid water path (LWP). The warming induced by cloud feedback and cooling by ACI counteracts each other. Our study suggests that the mean‐state LWP is an important factor influencing both ERFACI and the cloud feedback, and is a useful index for the future climate projection. Key Points Effective radiative forcing due to aerosol‐cloud interactions strengthens with the increase of mean‐state LWP in two Earth System Models Cloud radiative feedback increases monotonically with the increase of mean‐state LWP Mean‐state LWP is a good predictor for both ERFACI and cloud radiative feedback

Wintertime aerosol pollution in the North China Plain has increased over the past several decades as anthropogenic emissions in China have increased, and has dramatically escalated since the beginning of the 21 st century, but the causes and their quantitative attributions remain unclear. Here we use an aerosol source tagging capability implemented in a global aerosol-climate model to assess long-term trends of PM 2.5 (particulate matter less than 2.5 μm in diameter) in the North China Plain. Our analysis suggests that the impact of China’s increasing domestic emissions on PM 2.5 concentrations over the last two decades of 20 th century was partially offset (13%) by decreasing foreign emission over this period. As foreign emissions stabilized after 2000, their counteracting effect almost disappeared, uncovering the impact of China’s increasing domestic emissions that had been partially offset in previous years by reductions in foreign emissions. A slowdown in the impact from foreign emission reductions together with weakening winds explain 25% of the increased PM 2.5 trend over 2000–2014 as compared to 1980–2000. Further reductions in foreign emissions are not expected to relieve China’s pollution in the future. Reducing local emissions is the most certain way to improve future air quality in the North China Plain.

The vertical distribution of biomass burning aerosol (BBA) is important in regulating their impacts on weather and climate. The plume‐rise process affects the injection height of BBA and interacts with the air parcel lifting and cloud processes. However, these processes are not represented in most global climate models. In this study, we replaced the fixed vertical profiles of monthly BBA emissions in the Department of Energy's Energy Exascale Earth System Model version 1 (E3SMv1) with an interactive fire plume‐rise model. The vertical distribution of BBA emissions was calculated as a function of ambient thermodynamic conditions from the host E3SMv1, with distributions of fire sizes and sensible heat fluxes derived from the observations. The maximum fire radiative power (FRP) technique was used to determine the fire size. Scaling‐FRP technique is used to calculate the wildfire heat release. Daily BBA emission, superimposed with a fire diurnal cycle retrieved from the satellite observation, was included in model simulations. The model shows improved agreement with satellite retrievals and in situ measurement during the National Oceanic and Atmospheric Administration Wildfire Experiment for Cloud chemistry, Aerosol absorption, and Nitrogen campaign. The model‐observation comparison demonstrates the importance of the plume‐rise model and fire diurnal cycle assumption in determining the BBA fields. We also find that E3SMv1 with new features produces a larger carbonaceous aerosol burden, leading to 0.13 W m−2 warming at the top of atmosphere compared to the default E3SMv1. This highlights the importance of accurately representing the BBA injection height and indicates a no‐linear nature in the BBA‐induced radiative effect. Plain Language Summary In this study, we replaced fixed vertical profiles of biomass burning aerosols (BBA) used in the default doe's Energy Exascale Earth System Model version 1 (E3SMv1) with an interactive fire plume‐rise model and fire diurnal cycle assumption. The BBA vertical profiles predicted by the model with the new features are in better agreement with the satellite observations and in situ aircraft observations compared to the default version. In addition, the inclusion of the plume‐rise model and fire diurnal assumption also lead to a warming effect as strong as 0.13 W m−2. Key Points We incorporate an interactive fire plume‐rise model and fire diurnal cycle in the Energy Exascale Earth System Model version 1 (E3SMv1) The new features in E3SMv1 generate biomass burning aerosol vertical profiles that agree better with the observations than the default ones The E3SMv1 with plume‐rise model and fire diurnal cycle causes a 0.13 W m−2 warming effect compared to the default one

Aerosol-cloud interactions remain a major uncertainty in climate research. Studies have indicated that model estimates of cloud susceptibility to aerosols frequently exceed satellite estimates, motivating model reformulations to increase agreement. Here we show that conventional ways of using satellite information to estimate susceptibility can serve as only a weak constraint on models because the estimation is sensitive to errors in the retrieval procedures. Using instrument simulators to investigate differences between model and satellite estimates of susceptibilities, we find that low aerosol loading conditions are not well characterized by satellites, but model clouds are sensitive to aerosol perturbations in these conditions. We quantify the observational requirements needed to constrain models, and find that the nighttime lidar measurements of aerosols provide a better characterization of ten- uous aerosols. We conclude that observational uncertainties and limitations need to be accounted for when assessing the role of aerosols in the climate system.

A Lagrangian framework is used to evaluate aerosol–cloud interactions in the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) version 1 (E3SMv1) for measurements taken at Graciosa Island in the Azores where a U.S. Department of Energy Atmosphere Radiation Measurement (ARM) site is located. This framework uses direct measurements of cloud condensation nuclei (CCN) concentration (instead of relying on satellite retrievals of aerosol optical depth) and incorporates a suite of ground-based ARM measurements, satellite retrievals, and meteorological reanalysis products that when applied to over a 1500 trajectories provides key insights into the evolution of low-level clouds and aerosol radiative forcing that is not feasible from a traditional Eulerian analysis framework. Significantly lower concentrations (40 %) of surface CCN concentration are measured when precipitation rates in 48 h back trajectories average above 1.2 mm d−1 in the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) product. The depletion of CCN concentration when precipitation rates are elevated is nearly twice as large in the ARM observations compared to E3SMv1 simulations. The model CCN concentration bias remains significant despite modifying the autoconversion and accretion rates in warm clouds. As the clouds in trajectories associated with larger surface-based CCN concentration advect away from Graciosa Island, they maintain higher values of droplet number concentrations (Nd) over multiple days in observations and E3SM simulations compared to trajectories that start with lower CCN concentrations. The response remains robust even after controlling for meteorological factors such as lower troposphere stability, the degree of cloud coupling with the surface, and island wake effects. E3SMv1 simulates a multi-day aerosol effect on clouds and a Twomey radiative effect that is within 30 % of the ARM and satellite observations. However, the mean cloud droplet concentration is more than 2–3 times larger than in the observations. While Twomey radiative effects are similar amongst autoconversion and accretion sensitivity experiments, the liquid water path and cloud fraction adjustments are positive when using a regression model as opposed to negative when using the present-day minus pre-industrial aerosol emissions approach. This result suggests that tuning the autoconversion and accretion alone is unlikely to produce the desired aerosol susceptibilities in E3SMv1.

Dust emissions related to anthropogenic activities (i.e., anthropogenic dust) is not represented in most global climate models and its radiative impact remains unassessed. In this study, we develop a new and physically based method to parameterize anthropogenic dust emission from agricultural sources (i.e., agricultural dust, or AD) based on the DOE's Energy Exascale Earth System Model version 1 (E3SMv1). This method relates AD emission to the crop land use fraction in the E3SMv1 land component. Major AD sources simulated by our parameterization include those over Central America, the Sahel, North India, and North China. The annual averaged AD emission with diameter less than 10 μm is 567 Tg yr−1 in present‐day (year 2000), which contributes to 13.3% of total dust emission. Model evaluation against satellite and ground‐based observations shows that the new parameterization can represent AD emissions and global dust cycle reasonably well. We find that the total dust emission increases by 13.1% (495 Tg yr−1) from 1850 to 2000 due to the cropland land use fraction changes without considering the impact from climate changes. This induces a net dust direct effective radiative forcing of −0.041 W m−2 at top of the atmosphere. This dust‐induced cooling exceeds 10% of the total anthropogenic aerosol direct effective radiative forcing from 1750 to 2014 estimated by the Intergovernmental Panel on Climate Change Sixth Assessment Report. Our findings indicate an important role of anthropogenic dust in global climate change, which should be included in future climate change assessments. Plain Language Summary Anthropogenic activities can induce dust emissions, but the anthropogenic dust emission is not well represented in most global climate models. In this study, we implement a parameterization that accounts for the anthropogenic dust emission from agricultural sources in a global climate model, which physically relates agricultural dust (AD) emission to cropland fraction. Our modeling results show that 13.3% global dust emission in the present day is AD emission, which includes those over Central America, the Sahel, North India, and North China. Due to agricultural expansion, total dust emission increases by 13.1% from pre‐industrial to present day, which is dominated by the increase in AD emission. This historical increase results in cooling effect of dust on climate through scattering and absorbing radiation, which exceeds 10% of the estimate by the Intergovernmental Panel on Climate Change Sixth Assessment Report. Our findings indicate an important role of dust in global climate change, which should be included in future climate change assessments. Key Points An agricultural dust emission parameterization is developed and implemented in a global climate model Our parameterization predicts that 13.3% of the total dust emission in present day is agricultural dust emission Total dust emission increases by 13.1% from pre‐industrial to present day, which results in a dust direct radiative forcing of −0.041 W m−2

The direct radiative forcing of black carbon aerosol (BC) on the Earth system remains unsettled, largely due to the uncertainty with physical properties of BC throughout their lifecycle. Here we show that ambient chamber measurements of BC properties provide a novel constraint on the crude BC aging representation in climate models. Observational evidence for significant absorption enhancement of BC can be reproduced when the aging processes in the four‐mode version of the Modal Aerosol Module (MAM4) aerosol scheme in the Community Atmosphere Model version 5 are calibrated by the recent in situ chamber measurements. An observation‐based scaling method is developed in the aging timescale calculation to alleviate the influence of biases in the simulated model chemical composition. Model sensitivity simulations suggest that the different monolayer settings in the BC aging parameterization of MAM4 can cause as large as 26% and 24% differences in BC burden and radiative forcing, respectively. We also find that an increase in coating materials (e.g., sulfate and secondary organic aerosols) reduces BC lifetime by increasing the hygroscopicity of the mixture but enhances its absorption, resulting in a net increase in BC direct radiative forcing. Our results suggest that accurate simulations of BC aging processes as well as other aerosol species are equally important in reducing the uncertainty of BC forcing estimation. Plain Language Summary Following carbon dioxide, black carbon particle (BC) is the second climate warming agent in the Earth system. However, BC radiative effect in most global climate models (GCM) varies by a factor of 2. The uncertainty mainly arises from the transformation of BC in the atmosphere during its lifecycle and the corresponding treatment in models. Recently, a series of BC chamber experiments were conducted over two polluted regions around the world, Beijing, China, and Houston, USA, to characterize BC aging processes. In this study, we capitalize those direct observations to calibrate a key parameter associated with BC lifetime and physical property in a GCM. Our work also illustrates the importance of the coating materials of aged BC on its radiative and climate impacts. Hence, our study calls on the deployment of the ambient smoke chamber over more places and development of a reliable aerosol composition data set with a global coverage to better constrain the BC forcing assessment. Key Points Atmospheric black carbon aging processes in CAM5 are constrained by chamber experiments The calibrated model shows that coating results in net enhancement in BC forcing in spite of a reduction in BC lifetime Modeled BC direct radiative forcing varies up to 26% due to the uncertainties in BC aging parameterization and coating aerosol mass