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Abstract Representing mixing state of black carbon (BC) is challenging for global climate models (GCMs). The Community Atmosphere Model version 6 (CAM6) with the four‐mode version of the Modal Aerosol Module (MAM4) represents aerosols as fully internal mixtures with uniform composition within each aerosol mode, resulting in high degree of internal mixing of BC with non‐BC species and large mass ratio of coating to BC (RBC, the mass ratio of non‐BC species to BC in BC‐containing particles). To improve BC mixing state representation, we coupled a machine learning (ML) model of BC mixing state index trained on particle‐resolved simulations to the CAM6 with MAM4 (MAM4‐ML). In MAM4‐ML, we use RBC to partition accumulation mode particles into two new modes, BC‐free particles and BC‐containing particles. We adjust RBC to make the modeled BC mixing state index (χmode) match the one predicted by the ML model (χML). On a global average, the mass fraction of BC‐containing particles in accumulation mode decreases from 100% (MAM4‐default) to 48% (MAM4‐ML). The globally averaged χmode decreases from 78% (MAM4‐default) to 63% (MAM4‐ML, 19% reduction) and agrees well with χML (66%). The RBC decreases by 52% for accumulation mode and better agrees with observations. The hygroscopicity drops by 9% for BC‐containing particles in accumulation mode, leading to a 20% reduction in the BC activation fraction. The surface BC concentration increases most (6.9%) in the Arctic, and the BC burden increases by 4%, globally. Our study highlights the application of the ML model for improving key aerosol processes in GCMs.

Abstract Wildfire emission inventories are usually applied with biome‐scale emission factors for atmospheric modeling. However, emission factors measured for different plant species vary substantially within the same biome. We apply the species‐specific emission factors and refine the Fire Emission Inventory‐northern Eurasia (FEI‐NE), and derive the wildfire black carbon emission inventory in northern Eurasia from 2002 to 2015. Our new inventory produces 61% more black carbon emissions than current estimates based on Global Fire Emission Database (GFED) and 33% less than FEI‐NE. Model simulations with different inventories are compared with ground‐based and satellite retrievals of aerosol absorption optical depth (AAOD). Compared with the Ozone Monitoring Instrument, the normalized root mean square deviation of AAOD over northern Eurasia is reduced from 1.0 under FEI‐NE to 0.95 through application of the new inventory. This study reveals the importance of applying sub‐biome‐scale emission factors for wildfire inventories development and revisiting emissions uncertainty in atmospheric modeling.

Abstract Precipitation has been hypothesized to play a key role in the determination of cloud fraction (CF). The relationships between CF and rain rate (R) in marine boundary layer clouds were studied based on long‐term satellite retrievals. We find that both CF and R increase with cloud geometric width (CGW) and thickness (CGT). Increased CGW causes increased R even without cloud deepening, but increasing CGW beyond 15 km leads to a slight decrease in R. Coincident change in CF and R with increased CGW causes a spurious positive CF‐R relationship. When fixing CGT and CGW, CF generally decreases monotonically with increasing R, and the dependence generally weakens with warmer sea surface temperature and thinner, larger clouds. This finding supports well the hypothesis that aerosols could increase cloudiness by suppressing precipitation. This study also emphasizes the importance of cloud morphology in marine boundary layer cloud studies connected to precipitation processes.

Biomass burning emissions have been shown to influence clouds in the Atlantic, but its influence in other regions is not well known. Here, the authors show that biomass burning aerosols increase the low-cloud cover over subtropical southeastern Asia by a similar magnitude than over the Atlantic.

Abstract We propose a parameterization scheme of convective organization effects based on a moisture‐distribution approach, which can reflect aggregation of convective cells within a model grid as well as the interaction between convection and spatial heterogeneity in free‐troposphere moisture. With this concept, convective cells in an aggregated state are surrounded by air that is moister than the grid‐mean condition, which provides a “shielding” effect favorable for deeper convective updrafts. Such effects are represented quantitatively via utilizing a schematic diagram about the geometric interpretation of convective cluster, dry area, and their contact area, in which both the convective cluster size and dry area fraction increase during the development of convection. Our sensitivity analyses indicate that the new scheme performs well in capturing the mean precipitation features. Excluding the convective organization effects in the model leads to a considerable reduction in the simulated precipitation magnitude. Notably, there exists an inverse relationship between background mean moisture condition and sub‐grid moisture variability for a given rain rate, suggesting that with a high spatial heterogeneity in free‐troposphere moisture, convection can still develop and maintain its strength under relatively dry background conditions, consistent with the convection‐permitting model simulation. Overall, our new parameterization of convective organization effects can successfully reproduce the relationship between precipitation and sub‐grid moisture variability, which is a missing element in traditional convection parameterization schemes but important for the simulations of precipitation variability at various scales in climate models.

Future projection of diffusion conditions associated with extreme haze events over eastern China is of great importance to government emission regulations and public human health. Here, the diffusion conditions and their changes under future warming scenarios are examined. The relative strength of haze events in the Northern China Plain region increase from 150% during 2006–15 to 190% during 2090–99 under RCP8.5 scenarios, induced by a stronger and longer-lasting anticyclone anomaly in eastern China. The strengthened anticyclone anomaly is mainly induced by increased northern wave train convergence emanating from the Barents–Kara Sea, and the longer duration of the anticyclone anomaly is mainly induced by stronger local feedback that can extract more energy from the basic state to maintain the anticyclone anomaly in eastern China. Aerosol reduction is found to play a dominant role in strengthening the upstream wave train near the Barents–Kara Sea and the downstream anticyclone in eastern China, while the effects from increased greenhouse gases are small. The results of this study indicate that future aerosol emissions reduction can induce deteriorating diffusion conditions, suggesting more stringent regulations on aerosol emissions in China are needed to meet air quality standards.

Model biases and internal variability are a cause for uncertainties in climate projections. Here, the authors show that 45% of projected uncertainty in the western Pacific Subtropical High can be reduced by correcting sea surface temperature biases in the equatorial Pacific and beneath marine stratocumulus clouds.

Abstract This study evaluates the precipitation over East Asia simulated by the variable resolution CAM‐MPAS featuring the Model for Prediction Across Scales (MPAS) atmospheric dynamical core coupled with the physics parameterizations of the Community Atmosphere Model (CAM) version 5.4. Two CAM‐MPAS experiments, one with a global quasi‐uniform resolution mesh of 120 km (MPAS‐UR) and the other with a variable resolution mesh of 30–120 km refined over East Asia (MPAS‐VR), are conducted from 1989 to 2005 following the Atmospheric Model Intercomparison Project protocol. Two regional climate model simulations at ∼25 km resolution from the Coordinated Regional Downscaling Experiment East Asia second plan are also analyzed for comparison. Results show that CAM‐MPAS performs better than the selected regional models in simulating the precipitation climatology over East Asia. Compared with MPAS‐UR, MPAS‐VR with refinement over East Asia better simulates the precipitation over and around the Tibetan Plateau (TP), the upper‐level circulation, the precipitation frequency and intensity in various regions of China, and the interannual precipitation pattern associated with the East Asian summer monsoon. Both decreased grid spacing and the use of finer‐scale terrain information contribute to the improvements in MPAS‐VR relative to MPAS‐UR. However, decreased grid spacing is more essential for simulating the precipitation magnitude over TP and the location of peak precipitation south of TP, likely due to the better resolved physical and dynamical processes associated with orographic precipitation. The 30–120 km CAM‐MPAS model is shown to be a promising tool for precipitation simulation over East Asia.

Abstract In this study, a higher‐order closure scheme known as Cloud Layers Unified By Binormals (CLUBB) is coupled with a cloud top radiative cooling scheme (RAD). The cloud top radiative cooling scheme treats the buoyancy flux generated near the top of the boundary layer which helps the CLUBB scheme to better represent the radiation‐turbulence interaction on the condition of coarse vertical resolution. CLUBB with RAD is found to improve subtropical low‐cloud simulations, and the improvement is particularly evident for nocturnal stratocumulus. The improvements are caused by the stronger and more symmetric vertical turbulent mixing in the boundary layer, as CLUBB with RAD increases the variance of vertical velocity and vertical turbulent transports and reduces the skewness of vertical velocity by enhancing the radiative cooling effects and buoyancy fluxes at the cloud layer. The pumping effect related to the stronger vertical turbulent transports further cools and dries the lower boundary layer, which increases the local surface heating fluxes and further improves the low‐cloud simulations.

Abstract We modify the Zhang‐McFarlane (ZM) deep convection scheme in the Community Atmosphere Model version 5 to couple it with a unified parameterization for boundary‐layer turbulence and shallow convection, that is, Cloud Layers Unified by Binormals (CLUBB). By assuming a lognormal distribution of entrainment rate across the entire moist convective regimes, we link mass fluxes between shallow and deep convection, which are partitioned by the entrainment rate of the shallowest deep convective plume. Hence, a new deep convective closure is established which is coupled to the sub‐grid vertical motion variability in CLUBB. The convection feedback (or memory) effects are also considered to decrease the entrainment spectrum width and enhance the vertical velocity variability that further affect deep convection. Results show that the revised scheme improves the precipitation simulations in terms of the mean state and variability at various timescales, such as the alleviated double‐intertropical convergence zone and more realistic simulations of the seasonal variation of monsoon precipitation over East Asia, Madden‐Julian Oscillation, and precipitation diurnal phase propagations downstream of large terrains. The improvements are still seen in many aspects such as the mean‐state precipitation when turning off the convection feedback impacts in the revised scheme, emphasizing the benefits of using the modified mass‐flux closure. However, the convection feedbacks have considerable effects on the precipitation diurnal cycle simulations over regions with late‐afternoon precipitation peaks. Overall, the revised scheme provides a unified treatment for sub‐grid vertical motions across regimes of boundary‐layer turbulence, shallow convection, and deep convection, leading to better‐simulated precipitation at various timescales.

Abstract Assumed‐PDF (probability density function) higher‐order turbulence closures (APHOCs) are now widely used for parameterizing boundary layer turbulence and shallow convection in Earth system models (ESMs). A better understanding of the resolution‐dependent behavior of APHOCs is essential for improving the performance of next‐generation ESMs with intended horizontal resolutions finer than 10 km. In this study, we evaluate the PDF family of Analytic double‐Gaussian 1 implemented in Cloud Layers Unified By Binormals (CLUBB) over a range of spatial scales (Dx) from 2 to 100 km. A 120‐km‐wide large eddy simulation (LES) for a continental convection case during 2016 Holistic Interactions of Shallow Clouds, Aerosols, and Land‐Ecosystems (HI‐SCALE) field campaign serves as benchmark to evaluate the PDF closure using an off‐line approach. We find during the shallow convection period, the CLUBB PDF closure tends to produce positive biases of cloud properties and liquid water flux near cloud base for all scales of analysis. It produces negative biases for these variables near cloud top that are more severe for Dx larger than 25 km. Results show that replacing the CLUBB‐parameterized moisture and temperature skewnesses with LES‐derived ones can fix most of the biases if clipping of input moments is allowed to prevent the occurrence of unrealizable solutions. Overall, the performance of the PDF closure is better for smaller Dx = 2–5 km than for larger Dx = 50–100 km; for a given grid spacing, it is better when the convective clouds become deeper in the late afternoon. Likely causes for the resolution dependence and implications for improving the PDF closure are discussed.

Abstract In order to improve the physical consistency between shallow and deep convection, we modify the deep convective closure in the Community Atmosphere Model version 5 (CAM5) coupled with a third‐order turbulence closure parameterization (i.e., Cloud Layers Unified by Binormals [CLUBB]). The revised closure reserves a portion of the total convective available potential energy for shallow convection via utilizing the heating and moistening profiles from CLUBB to distribute moisture and energy between shallow and deep convection. Simulations at two resolutions (i.e., 2° and 0.5°, respectively) are conducted to investigate the impacts of convective closure on the simulated precipitation diurnal variations. Results from low‐resolution simulations show that the revised closure suppresses deep convection until the lower troposphere is sufficiently moistened by shallow convection, which improves the precipitation diurnal variation simulations compared with the default closure, with the precipitation diurnal peak over tropical lands delayed from 12LST to 19LST. The revised closure better simulates the diurnal variations for precipitation over the Asian monsoon region, such as the delayed precipitation onset, but still fails to well capture the nighttime peak for precipitation there. This deficiency is alleviated to some extent when applying the revised closure in high‐resolution simulations, but nighttime precipitation is still underestimated probably because key processes responsible for nighttime convection are missing. Overall, our results indicate that establishing the consistency between shallow and deep convection is critical for the precipitation diurnal cycle simulations.

Surface ozone is substantially affected by climate change through the modulation of key meteorological parameters such as temperature. While the changes in temperature under a warming climate manifest in changes of both the mean and higher-order statistical moments, their individual role in ozone concentration changes has not been broadly investigated. To address this gap, we use a novel approach to isolate the impacts of mean warming and changes in higher-order moments of temperature on ozone over the southeastern U.S. (SEUS) and western U.S. (WUS) by the mid-21st century based on simulations under Technology Driver Model A1B and B2 scenarios from a regional modeling framework (Weather Research and Forecasting model coupled with Chemistry (WRF/Chem)). Mean warming generally dominates the impacts of climate change on ozone, and higher-order moment temperature changes can also counteract 25% of the ozone exceedance of 70 ppbv over SEUS, and may offset 48% of the mean warming induced increase of ozone exceedance in heat waves during 2046–2055 under A1B. The opposite changes in the higher-order moments over SEUS and WUS lead to opposite impacts on ozone exceedance in the two regions. Our results suggest that improving prediction of both the mean and higher-order temperature changes may be crucial to constraining the future changes in ozone concentration to better inform air quality policy.

Temperature and water vapor have been considered as important factors affecting ozone concentrations, however, their synergistic effect on ozone, as well as its response to a warming climate remains unclear. Here, numerical experiments with different combinations of climate and emissions highlighted opposite changes of annual ozone over the contiguous U.S. under scenarios with high vs. low ozone precursor emissions in the future with warming. Comparing the occurrence of heat waves on higher vs. lower ozone days, we found significant suppression of the heat wave exacerbation of ozone by anthropogenic emissions reductions. Variations of ozone with temperature ( T ) and water vapor ( Q ) over the western U.S. and southeastern U.S. in the simulations are clearly revealed through the construction of an O _3 - T-Q diagram. Based on the diagram, we further identified a T -dominant regime at higher temperatures where ozone increases with temperature increase, and a Q -dominant regime at lower temperatures where ozone decreases with temperature increase due to the negative effect of water vapor. With larger anthropogenic emission reductions, ozone may increase at a lower rate with temperature in the T -dominant regime, or even decrease with temperature in the Q -dominant regime. Our results show that with large emission reductions, substantial ozone pollution due to warming and increasing heat waves may be counteracted by water vapor, partly turning the ‘climate penalty’ on ozone into ‘climate benefit’. Hence controlling anthropogenic emissions may be an increasingly important strategy in a warmer and wetter climate to improve air quality and public health.

Abstract Modeling the aerosol lifecycle in traditional global climate models (GCM) is challenging for a variety of reasons, not the least of which is the coarse grid. The multiscale modeling framework (MMF), in which a cloud resolving model replaces conventional parameterizations of cloud processes within each GCM grid column, provides a promising framework to address this challenge. Here we develop a new version of MMF that for the first time treats aerosol processes at cloud scale to improve the aerosol‐cloud interaction representation in the model. We demonstrate that the model with the explicit aerosol treatments shows significant improvements of many aspects of the simulated aerosols compared to the previous version of MMF with aerosols parameterized at the GCM grid scale. The explicit aerosol treatments produce a significant increase of the column burdens of black carbon (BC), primary organic aerosol, and sulfate by up to 40% in many remote regions, a decrease of the sea‐salt aerosol burdens by 40% in remote regions. These differences are caused by the differences in aerosol convective transport and wet removal between these two models. The new model also shows reduced bias of BC surface concentration in North America and BC vertical profiles in the high latitudes. However, the biased‐high BC concentrations in the upper troposphere over the remote Pacific regions remain, requiring further improvements on other process representations (e.g., secondary activation neglected in the model).

A decline of surface biogenic secondary organic aerosols through the mediation of reduced anthropogenic aerosols has been recognized as an air quality co-benefit of anthropogenic emission control over the southeastern US. However, the climate impacts of this anthropogenic–biogenic interaction remain poorly understood. Here, we identified a substantial decline of summertime aerosol loading aloft over the southeastern US in recent decades through the interaction, which leads to a stronger decline in column-integrated aerosol optical depth and a greater increase in radiative fluxes over the southeastern than northeastern US, different from trends of anthropogenic emissions and near-surface aerosol loading. The anthropogenic–biogenic interaction is shown to explain more than 60% of the coherent increasing trend of 5.3 Wm ^−2 decade ^−1 in clear-sky surface downward radiative fluxes. We show that current climate models fail to represent this interaction. The interaction is further projected to amplify the positive radiative forcing from emission control by 42.3% regionally over the southeastern US and globally by 5.4% in 2050 under RCP4.5 compared to 2005. This amplification effect implies greater challenges to achieving the Paris Agreement temperature targets with continuous emission control in future.

The study was carried out to evaluate the influence of polysaccharides from Camellia oleifera cake (CCP) in Lingnan yellow broilers diet from 1 to 50 days. Growth performance, carcass traits, meat quality, blood profile, and caecum microorganisms were characterized by three different levels of 0, 200 and 800 mg/kg CCP supplementation. Dietary treatment did not affect the productive trait from 1 to 50 days of age, except that average daily feed intake decreased at 42 days of age (p < 0.05). Additionally, the effects of CCP on various organs were different. The weight (p < 0.01) and index (p < 0.05) of bursa of Fabricius gradually decreased with the higher CCP supplementation at 21 days of the broilers diet. The gizzard weights were all higher when the broilers were fed with higher CCP concentration at 21, 42, and 50 days, respectively (p < 0.05). The weight and index of the spleen increased most with low CCP concentration (200 mg/kg) at 42 and 50 days. Moreover, CCP addition had no significant effect on meat quality except cooking loss (P < 0.05) and yellowness of meat color (p < 0.05). In the study of blood metabolism at 50 days of broilers, the concentration of calcium (p < 0.01), total cholesterol (p < 0.05) and uric acid (p < 0.01) decreased with higher CCP supplementation. CCP increased the albumin concentration (p < 0.001) that was highest at 200 mg/kg CCP supplementation. The addition of CCP increased the number of Lactobacillus and Enterococcus faecalis (p < 0.01) in the caecum of broilers, and had the potential to inhibit the growth of Escherichia coli (p = 0.11). Results showed that CCP played a role in improving intestinal flora and the immunity of yellow broilers.

A fast and effective determination method of different species of vegetable seeds oil is vital in the plant oil industry. The near-infrared reflectance spectroscopy (NIRS) method was developed in this study to analyze the oil and moisture contents of Camellia gauchowensis Chang and C. semiserrata Chi seeds kernels. Calibration and validation models were established using principal component analysis (PCA) and partial least squares (PLS) regression methods. In the prediction models of NIRS, the levels of accuracy obtained were sufficient for C. gauchowensis Chang and C. semiserrata Chi, the correlation coefficients of which for oil were 0.98 and 0.95, respectively, and those for moisture were 0.92 and 0.89, respectively. The near infrared spectrum of crush seeds kernels was more precise compared to intact kernels. Based on the calibration models of the two Camellia species, the NIRS predictive oil contents of C. gauchowensis Chang and C. semiserrata Chi seeds kernels were 48.71 ± 8.94% and 58.37 ± 7.39%, and the NIRS predictive moisture contents were 4.39 ± 1.08% and 3.49 ± 0.71%, respectively. The NIRS technique could determine successfully the oil and moisture contents of C. gauchowensis Chang and C. semiserrata Chi seeds kernels.

The impacts of cloud radiative heating on the East Asian Summer Monsoon (EASM) over southeastern China (105°–125°E, 20°–35°N) are addressed by using the Community Atmosphere Model version 5 (CAM5). Sensitivity experiments demonstrate that the radiative heating of clouds leads to a positive effect on the local EASM circulation over southeastern China. Without the radiative heating of clouds, the EASM circulation and precipitation would be much weaker than that in normal conditions. The longwave heating of clouds dominates the changes of EASM circulation. The positive effect of clouds on EASM circulation is explained by the thermodynamic energy equation, i.e. the different heating rate between cloud base and cloud top enhances the convective instability over southeastern China, which consequently enhances updraft. The strong updraft would further result in a southward meridional wind above the center of the updraft through Sverdrup vorticity balance.

New particle formation (NPF) involving organic compounds has been identified as an important process affecting aerosol particle number concentrations in the global atmosphere. Laboratory studies have shown that highly oxygenated organic molecules (HOMs) can make a substantial contribution to NPF, but there is a lack of global model studies of NPF with detailed HOMs chemistry. Here, we add a state-of-art biogenic HOMs chemistry scheme with 96 chemical reactions to a global chemistry-climate model and quantify the contribution to global aerosols through HOMs-driven NPF. The updated model captures the frequency of NPF events observed at continental surface sites (normalized mean bias changes from -96 % to -15 %) and shows reasonable agreement with measured rates of NPF and sub-20 nm particle growth. Sensitivity simulations show that the effect of HOMs on particle growth is more important for particle number than the effect on particle formation. Globally, organics contribute around 45 % of the annual mean vertically-integrated nucleation rate (at 1 nm) and 25 % of the vertically-averaged growth rate. The inclusion of HOMs-related processes leads to a 39 % increase in the global annual mean aerosol number burden and a 33 % increase in cloud condensation nuclei (CCN) burden at 0.5 % supersaturation compared to a simulation with only inorganic nucleation. Our work predicts a greater contribution of organic nucleation to NPF than previous studies due to the explicit HOMs mechanism and an updated inorganic NPF scheme. The large contribution of biogenic HOMs to NPF on a global scale could make global aerosol sensitive to changes in biogenic emissions. [ABSTRACT FROM AUTHOR]

Fires have great ecological, social, and economic impacts. However, fire prediction and management remain a challenge due to a limited understanding of their role in the Earth system. Fires over southern Mexico and Central America (SMCA) are a good example, which greatly impact local air quality and regional climate. Here we report that the spring-peak (Apr-May) fire activities in this region have a distinct quasi-biennial signal based on multiple satellite datasets measuring different fire characteristics. The variability is initially driven by the quasi-biennial variations of precipitation. Composite analysis indicates that strong fire years correspond to suppressed ascending motions and weakened precipitation over the SMCA. The anomalous precipitation over the SMCA is further found to be mostly related to the East Pacific-North Pacific (EP-NP) pattern two months previous to the fire season. The positive phase of EP-NP leads to enhanced precipitation over the eastern US yet suppressed precipitation over SMCA, similar to the spatial pattern of precipitation difference between strong and weak fire years. Meanwhile, the quasi-biennial signals in precipitation and fires appear to be amplified by their interactions through a positive feedback loop on short timescales. Model simulations show that in strong fire years, more aerosol particles are released and transported downstream over the Gulf of Mexico and the eastern US, where suspended light-absorbing aerosols warm the atmosphere and cause ascending motions of the air aloft. Subsequently, a compensating downward motion is formed over the fire source region and ultimately suppresses precipitation and intensifies fires. Statistical analysis shows the different duration of the two-way interaction, where the fire suppression effect by precipitation lasts for more than 20 days, while fire leads to a decrease in precipitation at shorter time scales (3-5 days). This study demonstrates the importance of fire-climate interactions in shaping the fire activities on interannual scale and highlights how precipitation-fire interactions at short timescales contribute to the interannual variability of both fire and precipitation. [ABSTRACT FROM AUTHOR]