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Brown carbon (BrC) in China is of great interest to the regional and global climate due to its strong absorption of sunlight. However, the contribution of BrC to total carbonaceous aerosol light absorption and its direct radiative effects (DRE) in China remains largely uncertain. To better assess its climate impact in China, we develop an explicit BrC scheme and implement it in a global climate model, which includes optical parameters of primary BrC derived from local measurements, secondary BrC absorption, and a photobleaching parameterization of BrC. By comparing with multi‐type observational data, we find that with the implementation of this scheme, the model captures the seasonal variations of BrC light absorption well in China. The model estimates that BrC contributes 19% and 12% to the total light absorption of carbonaceous aerosol in China in winter and summer, resulting in 0.110 and 0.205 W m−2 of DRE, respectively. Plain Language Summary: While the existing research on the direct radiative effects (DRE) of brown carbon (BrC) predominantly focuses on biomass‐burning sources, little attention has been given to BrC originating from anthropogenic sources. Coal combustion and residential fuels used for cooking and heating release many brown carbon aerosols in China. Source of BrC in China is different from that in Europe and North America. Therefore, studying the light‐absorbing properties and climate effects of BrC in China is of great scientific significance. Here, we introduce local optical parameters of primary BrC based on observations in China, secondary BrC absorption, and chemical bleaching of BrC in a global climate model (GCM). We find that the model can simulate the strong seasonal variations of BrC absorption observed in China. With the help of the model and multi‐type measurement data, we estimate the contribution of BrC to the total carbonaceous aerosol absorption and the DRE of BrC in China in different seasons. This study is the first attempt to introduce an explicit BrC scheme in a GCM to estimate the DRE of BrC in China. Key Points: An explicit brown carbon (BrC) scheme is introduced in a climate model together with observations to constrain light absorption of BrCBrC contributes 19% and 12% of total carbonaceous aerosol absorption in China in winter and summer, respectivelySimulated direct radiative effects due to BrC absorption over China are 0.110 and 0.205 W m2 in the winter and summer seasons [ABSTRACT FROM AUTHOR]

In this study, a variable‐resolution version of the Community Earth System Model (VR‐CESM) with mesh refinement (∼0.125°) over East Asia is used to simulate the regional climate in this region. For the evaluation of model performance and sensitivity to model resolution, the simulated near‐surface temperature and precipitation are compared with observations and simulation results from a globally quasi‐uniform (∼1°) CESM (UN‐CESM). Results show that VR‐CESM better simulates the spatial patterns and seasonal variations of mean temperature and precipitation than UN‐CESM over China. For extreme events, VR‐CESM improves the simulation of the occurrence frequency of wintertime daily minimum temperature and heavy precipitation. In regions with complex terrains, VR‐CESM better resolves the topographic forcing and captures the observed fine‐scale spatial patterns of temperature and precipitation, although precipitation is still overestimated. For East Asian summer monsoon precipitation, both UN‐CESM and VR‐CESM tend to overestimate (underestimate) the precipitation over northern (southern) China, which is associated with too strong meridional water vapor transport in the models and biases in the large‐scale circulation in the middle and upper troposphere. Different from previous studies with different physics parameterizations and refined domains, as the model resolution increases, simulated monsoon precipitation evolution is not obviously improved, and convective precipitation intensity decreases over eastern China. Despite this, our results indicate that VR‐CESM simulates regional climate, topographical forcing, and large‐scale circulations over East Asia reasonably well, and thus it can be applied for the future climate projection in the region. Plain Language Summary: Horizontal resolution is one of the key factors that affect the climate model's fidelity. Current global climate models (GCMs) are usually run at a coarse resolution due to the limitation of computational resources. To compromise, variable‐resolution GCM with higher resolution over domains of interest is developed to reduce the computational costs of high‐resolution modeling. This study evaluates the impact of model horizontal resolution on simulating regional climate in terms of temperature and precipitation using the model with a regionally‐refined high resolution over East Asia. Compared to observational data sets and the coarse‐resolution model, the regionally‐refined model better simulates spatial distributions and seasonal variations of climatological mean temperature and precipitation over China, as well as the occurrence frequency of extreme cold events and heavy precipitation. The regionally‐refined model with high‐resolution terrain improves precipitation simulation in regions with complex terrains. Our results demonstrate the regionally‐refined model's capability in simulating the regional climate over East Asia. Key Points: Variable‐resolution CESM2 (VR‐CESM2) performs better in simulating seasonal variation of precipitation over China but overestimates its magnitude than the quasi‐uniform 1° CESM2VR‐CESM2 reasonably simulates frequency of cold temperature extremes and heavy precipitationPrecipitation improvements at higher resolution depend on model physics parameterizations and refined domain size [ABSTRACT FROM AUTHOR]

Representing subgrid variabilities of land surface processes and their upscaled effects is crucial for global climate modeling. Here, we implement a multiple atmosphere multiple land (MAML) framework in the superparamaterized version of E3SM (SP‐E3SM) to explicitly simulate the subgrid variabilities of land states and fluxes at cloud‐resolving scale and their interactions with atmosphere. Comparing to the standard SP‐E3SM in which all the atmospheric columns of the cloud resolving model embedded within the global atmospheric model grid interact with the same land surface (i.e., multiple atmosphere single land (MASL)), the impact of MAML on the strength of land‐atmosphere coupling is limited, partly because the current implementation mainly facilitates one‐way coupling between the cloud‐resolving model and the land surface model. Despite such limitation, MAML increases the surface latent heat flux at the expense of sensible heat flux, and increases precipitation in India, Amazon, and Central Africa, reducing the model dry bias compared to the standard SP‐E3SM. By employing a normalized gross moist stability (NGMS) diagnostic framework, we find that the increase in precipitation minus evaporation (P‐E) is primarily driven by the change in large‐scale moisture convergence, particularly by the increase of water vapor in the lower atmosphere, while the local effect of total surface energy flux plays a minor role in the P‐E change. More specifically, MAML changes the surface energy partitioning (evaporative fraction), increases the atmosphere water vapor, and further increases P‐E by decreasing the NGMS. Finally, future development in the MAML framework is discussed. Plain Language Summary: Land‐atmosphere interactions such as soil moisture‐precipitation feedback occur at a wide range of spatial scales. For example, spatial variability of surface fluxes such as radiation and precipitation can influence surface latent and sensible heat fluxes, which further influence turbulent mixing processes in the boundary layer and cloud and precipitation. Current global climate models (GCMs) have difficulties in representing land‐atmosphere interactions at scales smaller than the GCM grid (subgrid scales). To meet this challenge, we employ a novel framework, called multiple atmosphere multiple land (MAML), in a superparamaterized version of E3SM (SP‐E3SM) in which a cloud resolving model is embedded within each GCM grid to better resolve clouds and convection. MAML explicitly simulates the subgrid variabilities of land states and fluxes at scale of ∼1 km and provides feedback to the atmosphere. The use of MAML is shown to have a limited effect on the strength of land‐atmosphere coupling due to the current one‐way subgrid land‐atmosphere interaction setup. Despite the limited effect, MAML increases the rainfall in India, Amazon, and Central Africa, which reduces the dry bias in the model. Key Points: A multiple atmosphere multiple land (MAML) framework of land‐atmosphere coupling is implemented in the super‐parameterized E3SM (SP‐E3SM)MAML increases precipitation in India, Central Africa, and Amazon by increasing water vapor and hence large‐scale moisture convergenceMAML's impact on land‐atmosphere interactions is limited by the current setup of one‐way coupling on cloud‐resolving scales [ABSTRACT FROM AUTHOR]

Global climate models (GCMs) have been used widely to study radiative forcing and health risks of aerosols. A recent study using two GCMs found that light rain plays a dominant role in controlling aerosol loading. However, "too much light rain and too little heavy rain" is a longstanding bias in GCMs. It is unclear how much light rain affects aerosol‐cloud‐radiation interactions and health risks from air pollution. Here we show that, with the correction of the rainfall intensity spectrum in the National Center for Atmospheric Research Community Atmosphere Model version 5.3 by introducing a stochastic deep convection scheme, the reduced frequency of light rain (1–20 mm d−1) results in changes of aerosol direct radiative effects (DRE) of up to −0.5 ± 0.03 W/m2 and aerosol cloud radiative effects (CRE) of up to −0.9 ± 0.03 W/m2. The total (CRE + DRE) radiative effects of light rain‐mediated aerosol changes exceed the present‐day anthropogenic forcing of aerosols relative to preindustrial levels from the Coupled Model Intercomparison Project (CMIP5&6) models. However, the correction of the rainfall intensity spectrum has little effect on anthropogenic aerosol forcing (defined as the radiative perturbation due to changes in aerosol concentrations between the industrial era and preindustrial levels). Due to increased exposure to fine particulates (PM2.5), the estimated global total premature mortality is much higher than previously estimated, by 300,000 ± 60,000 deaths per year, and is more severe in populous regions such as India and China. The findings in this study highlight the need to understand uncertainties in radiative effects and health risks of aerosols due to simulation biases of precipitation in GCMs. Plain Language Summary: All global climate models have a problem of "too much light rain and too little heavy rain". Climatologically, light rain plays a disproportionate role in controlling the aerosol loading and thus can affect aerosol radiative effects and health risks. Here, we show that correcting this issue in a global climate model leads to substantial increases of the radiative effects and health risks of aerosols. The resulting change of the radiative effects is even larger than present‐day anthropogenic forcing of aerosols relative to preindustrial levels. The global total premature mortality due to elevated air pollution level is increased significantly. Key Points: Suppression of light rain increases the total radiative effect of aerosols by −1.4 W/m2, even larger than aerosol anthropogenic effectsElevated air pollution increases the health risks, with estimated global premature mortality increased by 300,000 deaths per yearReduced excessive light rain by suppressing too frequent convection has little effect on anthropogenic aerosol forcing [ABSTRACT FROM AUTHOR]

Accurately representing mesoscale convective systems (MCSs) is crucial to simulating the energy and water cycles in global climate models. Using a novel MCS identification and tracking algorithm applied to observations and model simulations, we evaluate how well the Energy Exascale Earth System Model (E3SM) simulates MCSs over the central US. Simulations performed by E3SM at 25 km grid spacing with and without superparameterization (SP) are compared and evaluated against observations using multiple metrics highlighting important MCS characteristics. Compared to E3SM, the superparameterized model (SP‐E3SM) better simulates MCS number and MCS precipitation amount, diurnal cycle, propagation, and the probability distribution of precipitation rate in both spring and summer. The improvement from SP is partly contributed by improvement in simulating the large‐scale environments, featuring enhanced atmospheric low‐level moisture and larger moisture transport to the central US relative to E3SM. However, SP‐E3SM still underestimates MCS precipitation amount, particularly in summer. This underestimation is closely related to the negative bias in MCS precipitation intensity, although the drier environments simulated during summer also contributes to underestimation of MCS frequency. Without SP, the larger bias in MCS precipitation amount is closely related to the negative bias in MCS frequency, while the substantial dry bias in the large‐scale environments also contributes to underestimation of MCS intensity. Our results suggest that SP improves MCS simulation by improving modeling of the large‐scale environments and convection initiation, which are both major limiting factors in E3SM even at 25 km grid spacing where deep convection is represented by a cumulus parameterization. Plain Language Summary: Large thunderstorms called mesoscale convective systems (MCSs) are an important source of flood‐producing rainfalls. In this paper, we examine how well the Energy Exascale Earth System Model (E3SM) simulate MCSs over the central US in spring and summer by comparing against observations. We run two versions of E3SM: one is the standard E3SM that uses a traditional parameterization to simulate deep convection, the other is E3SM with a superparameterization (SP‐E3SM) that uses a cloud resolving model within each E3SM grid column to explicitly simulate deep convection. By using a novel detection and tracking algorithm to characterize MCS features, we find that SP‐E3SM can better simulate the number, rainfall amount and intensity, and the diurnal cycle of MCSs compared to E3SM. SP improves MCS simulations by improving the representation of the large‐scale circulations and convection initiation. Despite the improvement, SP‐E3SM still underestimates the MCS rainfall amount, which is largely related to the underestimation of MCS rainfall intensity. In contrast, the larger underestimation of rainfall amount in E3SM is attributed in large parts to the lower MCS frequency. This study highlights the importance of large‐scale moisture transport and convection initiation in simulating MCSs. Key Points: Mesoscale convective systems (MCSs) in E3SM at 25 km with and without superparameterization (SP) are evaluated the central USIncluding SP significantly improves MCS simulations in both spring and summer, although large dry biases are still apparent in summerImprovements from SP are contributed by improved simulations of the large‐scale environments and MCS number and precipitation frequency [ABSTRACT FROM AUTHOR]

The dust emission parameterization in the Chinese Academy of Sciences Earth System Model version 2 (CAS‐ESM2) is described with emphasis on the implementation process and simulations of global dust cycle and East Asia dust event statistics. The parameterization is based on the scheme of Shao (2004; http://doi.org/10.1029/2003JD004372) which considers two major dust emission mechanisms, namely, saltation bombardment and aggregation disintegration. Shao (2004; http://doi.org/10.1029/2003JD004372) scheme was well tested against field observations and has been widely used in regional dust modeling. Here this scheme is implemented into a global climate model for the first time and thus provides an independent solution for simulating global dust emissions. With this scheme, CAS‐ESM2 reasonably simulates the main dust emission regions in the Earth and reproduces the observations of dust deposition flux and surface dust concentrations at most stations. Compared to the synoptic records of dust events, the model also captures the general patterns and seasonal variations of dust activities in East Asia. However, the model underestimates the frequency of strong dust events (instantaneous surface dust concentrations >1,000 μg m−3) due to the weaker surface winds simulated by the model. The model tends to simulate much weaker and longer‐lasting dust events in Eastern Sources (35–49°N, 94–126.5°E) of northern China, suggesting the weaker and slower‐moving synoptic weather systems associated with dust events in the model. Overall CAS‐ESM2 performs well in simulating the key aspects of global dust distribution and East Asian dust events, yet some biases remain to be improved. Plain Language Summary: Dust emitted from the bare soil is an important aerosol type, and dust cycle links the various components of Earth System including atmosphere, land, and oceans. Therefore, dust emission is an essential part of Earth system. In this study, we develop a dust emission module for Chinese Academy of Sciences Earth System Model version 2 (CAS‐ESM2) to simulate the global dust emission. The module incorporates advanced mechanisms of dust emission physics. The results show that with this module, CAS‐ESM2 reproduces well the global distribution of dust aerosol. We also evaluate the model's ability in simulating the individual dust events in terms of dust event frequency, intensity, and duration. We find that the model can reproduce the key regions of dust emission and the highest frequency of dust event in spring in East Asia. However, because the model underestimates surface wind speeds, it simulates weaker and longer‐lasting dust events. Overall CAS‐ESM2 provides a new and promising solution to simulate global dust emission, although there are still some biases for further improvements. Key Points: Chinese Academy of Sciences Earth System Model version 2 (CAS‐ESM2) with a physically based dust emission scheme provides a new and promising solution to simulate global dust emissionsCAS‐ESM2 captures the main global dust emission regions and reproduces observed dust depositions and surface dust concentrationsThe weaker dust events are compensated by overestimated dust event frequency and duration to produce reasonable means in East Asia [ABSTRACT FROM AUTHOR]

Predicting how regional precipitation will respond to future warming is among the most challenging undertaking in climate change projection. Despite sustained efforts to improve modeling and understanding of precipitation, the overall uncertainty in projecting regional precipitation has not been reduced substantially. Here, the potential for more robust precipitation projections is demonstrated through the use of discriminating metrics to subsample a multimodel ensemble. Using a two‐dimensional metric of precipitation and its relationship with large‐scale circulation indices in East Asia, 31 models in the Coupled Model Intercomparison Project Phase 5 (CMIP5) are classified into three groups. Models in the top performing group projected statistically significant increasing trends in precipitation and the regional precipitation patterns are more similar to each other than to the patterns in the bottom performing group. In contrast, models in the bottom performing group projected diverse responses, with overall small drying or no significant trends in precipitation. Plain Language Summary: Precipitation is a fundamental driver of land surface hydrology and water resources, but large biases in climate model simulations of precipitation and large uncertainties in the future projections hinder the use of climate models in climate impact studies. Metrics of precipitation used in climate model evaluation usually focus on different precipitation characteristics, while ignoring important physical mechanisms linking precipitation with its environments. In this study, a two‐dimensional metric is proposed to evaluate both the simulated precipitation and its relationship with large‐scale circulation patterns in East Asia. This metric is applied to the Coupled Model Intercomparison Project Phase 5 (CMIP5) models to classify 31 models into three groups based on model performances. The metric is able to discriminate model responses: models in the top performing group show more consistent and similar responses of precipitation to future warming, featuring larger increases of future precipitation than the CMIP5 ensemble mean over China. Key Points: A two‐dimensional metric is developed to evaluate precipitation and its relationships with the large‐scale circulation in climate modelsThe new metric identifies a subset of models skillful in simulating both precipitation and its relationship with the monsoon circulationThis subset of models projects a more robust and larger increase of future precipitation than the multimodel ensemble mean over China [ABSTRACT FROM AUTHOR]

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). [ABSTRACT FROM AUTHOR]

Efficient simulation strategies are crucial for the development and evaluation of high-resolution climate models. This paper evaluates simulations with constrained meteorology for the quantification of parametric sensitivities in the Community Atmosphere Model version 5 (CAM5). Two parameters are perturbed as illustrating examples: the convection relaxation time scale (TAU), and the threshold relative humidity for the formation of low-level stratiform clouds (rhminl). Results suggest that the fidelity of the constrained simulations depends on the detailed implementation of nudging and the mechanism through which the perturbed parameter affects precipitation and cloud. The relative computational costs of nudged and free-running simulations are determined by the magnitude of internal variability in the physical quantities of interest, as well as the magnitude of the parameter perturbation. In the case of a strong perturbation in convection, temperature, and/or wind nudging with a 6 h relaxation time scale leads to nonnegligible side effects due to the distorted interactions between resolved dynamics and parameterized convection, while 1 year free-running simulations can satisfactorily capture the annual mean precipitation and cloud forcing sensitivities. In the case of a relatively weak perturbation in the large-scale condensation scheme, results from 1 year free-running simulations are strongly affected by natural noise, while nudging winds effectively reduces the noise, and reasonably reproduces the sensitivities. These results indicate that caution is needed when using nudged simulations to assess precipitation and cloud forcing sensitivities to parameter changes in general circulation models. We also demonstrate that ensembles of short simulations are useful for understanding the evolution of model sensitivities. [ABSTRACT FROM AUTHOR]

Atmospheric deposition of reactive nitrogen (N) species from air pollutants is a significant source of exogenous nitrogen in marine ecosystems. Here we use an atmospheric chemical transport model to investigate the supply of soluble organic nitrogen (ON) from anthropogenic sources to the ocean. Comparisons of modeled deposition with observations at coastal and marine locations show good overall agreement for inorganic nitrogen and total soluble nitrogen. However, previous modeling approaches result in significant underestimates of the soluble ON deposition if the model only includes the primary soluble ON and the secondary oxidized ON in gases and aerosols. Our model results suggest that including the secondary reduced ON in aerosols as a source of soluble ON contributes to an improved prediction of the deposition rates (g N m−2 yr−1). The model results show a clear distinction in the vertical distribution of soluble ON in aerosols between different processes from the primary sources and the secondary formation. The model results (excluding the biomass burning and natural emission changes) suggest an increase in soluble ON outflow from atmospheric pollution, in particular from East Asia, to the oceans in the twentieth century. These results highlight the necessity of improving the process-based quantitative understanding of the chemical reactions of inorganic nitrogen species with organics in aerosol and cloud water. [ABSTRACT FROM AUTHOR]