@article{glotfelty_alapaty_he_hawbecker_song_zhang_2020, title={Studying Scale Dependency of Aerosol-Cloud Interactions Using Multiscale Cloud Formulations}, volume={77}, ISSN={["1520-0469"]}, DOI={10.1175/JAS-D-19-0203.1}, abstractNote={AbstractThe Weather Research and Forecasting Model with Aerosol–Cloud Interactions (WRF-ACI) configuration is used to investigate the scale dependency of aerosol–cloud interactions (ACI) across the “gray zone” scales for grid-scale and subgrid-scale clouds. The impacts of ACI on weather are examined across regions in the eastern and western United States at 36, 12, 4, and 1 km grid spacing for short-term periods during the summer of 2006. ACI impacts are determined by comparing simulations with current climatological aerosol levels to simulations with aerosol levels reduced by 90%. The aerosol–cloud lifetime effect is found to be the dominant process leading to suppressed precipitation in regions of the eastern United States, while regions in the western United States experience offsetting impacts on precipitation from the cloud lifetime effect and other effects that enhance precipitation. Generally, the cloud lifetime effect weakens with decreasing grid spacing due to a decrease in relative importance of autoconversion compared to accretion. Subgrid-scale ACI are dominant at 36 km, while grid-scale ACI are dominant at 4 and 1 km. At 12 km grid spacing, grid-scale and subgrid-scale ACI processes are comparable in magnitude and spatial coverage, but random perturbations in grid-scale ACI impacts make the overall grid-scale ACI impact appear muted. This competing behavior of grid- and subgrid-scale clouds complicate the understanding of ACI at 12 km within the current WRF modeling framework. The work implies including subgrid-scale cloud microphysics and ice/mixed-phase-cloud ACI processes may be necessary in weather and climate models to study ACI effectively.}, number={11}, journal={JOURNAL OF THE ATMOSPHERIC SCIENCES}, author={Glotfelty, Timothy and Alapaty, Kiran and He, Jian and Hawbecker, Patrick and Song, Xiaoliang and Zhang, Guang}, year={2020}, month={Nov}, pages={3847–3868} }
 @article{glotfelty_alapaty_he_hawbecker_song_zhang_2019, title={The Weather Research and Forecasting Model with Aerosol-Cloud Interactions (WRF-ACI): Development, Evaluation, and Initial Application}, volume={147}, ISSN={["1520-0493"]}, DOI={10.1175/MWR-D-18-0267.1}, abstractNote={Abstract
               The Weather Research and Forecasting Model with Aerosol–Cloud Interactions (WRF-ACI) is developed for studying aerosol effects on gridscale and subgrid-scale clouds using common aerosol activation and ice nucleation formulations and double-moment cloud microphysics in a scale-aware subgrid-scale parameterization scheme. Comparisons of both the standard WRF and WRF-ACI models’ results for a summer season against satellite and reanalysis estimates show that the WRF-ACI system improves the simulation of cloud liquid and ice water paths. Correlation coefficients for nearly all evaluated parameters are improved, while other variables show slight degradation. Results indicate a strong cloud lifetime effect from current climatological aerosols increasing domain average cloud liquid water path and reducing domain average precipitation as compared to a simulation with aerosols reduced by 90%. Increased cloud-top heights indicate a thermodynamic invigoration effect, but the impact of thermodynamic invigoration on precipitation is overwhelmed by the cloud lifetime effect. A combination of cloud lifetime and cloud albedo effects increases domain average shortwave cloud forcing by ~3.0 W m−2. Subgrid-scale clouds experience a stronger response to aerosol levels, while gridscale clouds are subject to thermodynamic feedbacks because of the design of the WRF modeling framework. The magnitude of aerosol indirect effects is shown to be sensitive to the choice of autoconversion parameterization used in both the gridscale and subgrid-scale cloud microphysics, but spatial patterns remain qualitatively similar. These results indicate that the WRF-ACI model provides the community with a computationally efficient tool for exploring aerosol–cloud interactions.}, number={5}, journal={MONTHLY WEATHER REVIEW}, author={Glotfelty, Timothy and Alapaty, Kiran and He, Jian and Hawbecker, Patrick and Song, Xiaoliang and Zhang, Guang}, year={2019}, month={May}, pages={1491–1511} }
 @article{glotfelty_he_zhang_2017, title={Improving organic aerosol treatments in CESM/CAM5: Development, application, and evaluation}, volume={9}, ISSN={["1942-2466"]}, DOI={10.1002/2016ms000874}, abstractNote={AbstractNew treatments for organic aerosol (OA) formation have been added to a modified version of the CESM/CAM5 model (CESM‐NCSU). These treatments include a volatility basis set treatment for the simulation of primary and secondary organic aerosols (SOAs), a simplified treatment for organic aerosol (OA) formation from glyoxal, and a parameterization representing the impact of new particle formation (NPF) of organic gases and sulfuric acid. With the inclusion of these new treatments, the concentration of oxygenated organic aerosol increases by 0.33 µg m−3 and that of primary organic aerosol (POA) decreases by 0.22 µg m−3 on global average. The decrease in POA leads to a reduction in the OA direct effect, while the increased OOA increases the OA indirect effects. Simulations with the new OA treatments show considerable improvement in simulated SOA, oxygenated organic aerosol (OOA), organic carbon (OC), total carbon (TC), and total organic aerosol (TOA), but degradation in the performance of HOA. In simulations of the current climate period, despite some deviations from observations, CESM‐NCSU with the new OA treatments significantly improves the magnitude, spatial pattern, seasonal pattern of OC and TC, as well as, the speciation of TOA between POA and OOA. Sensitivity analysis reveals that the inclusion of the organic NPF treatment impacts the OA indirect effects by enhancing cloud properties. The simulated OA level and its impact on the climate system are most sensitive to choices in the enthalpy of vaporization and wet deposition of SVOCs, indicating that accurate representations of these parameters are critical for accurate OA‐climate simulations.}, number={2}, journal={JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS}, author={Glotfelty, Timothy and He, Jian and Zhang, Yang}, year={2017}, month={Jun}, pages={1506–1539} }
 @article{he_zhang_wang_chen_leung_fan_li_zheng_zhang_duan_et al._2017, title={Multi-year application of WRF-CAM5 over East Asia-Part I: Comprehensive evaluation and formation regimes of O-3 and PM2.5}, volume={165}, ISSN={["1873-2844"]}, DOI={10.1016/j.atmosenv.2017.06.015}, abstractNote={Accurate simulations of air quality and climate require robust model parameterizations on regional and global scales. The Weather Research and Forecasting model with Chemistry version 3.4.1 has been coupled with physics packages from the Community Atmosphere Model version 5 (CAM5) (WRF-CAM5) to assess the robustness of the CAM5 physics package for regional modeling at higher grid resolutions than typical grid resolutions used in global modeling. In this two-part study, Part I describes the application and evaluation of WRF-CAM5 over East Asia at a horizontal resolution of 36-km for six years: 2001, 2005, 2006, 2008, 2010, and 2011. The simulations are evaluated comprehensively with a variety of datasets from surface networks, satellites, and aircraft. The results show that meteorology is relatively well simulated by WRF-CAM5. However, cloud variables are largely or moderately underpredicted, indicating uncertainties in the model treatments of dynamics, thermodynamics, and microphysics of clouds/ices as well as aerosol-cloud interactions. For chemical predictions, the tropospheric column abundances of CO, NO2, and O3 are well simulated, but those of SO2 and HCHO are moderately overpredicted, and the column HCHO/NO2 indicator is underpredicted. Large biases exist in the surface concentrations of CO, NOx, and PM10 due to uncertainties in the emissions as well as vertical mixing. The underpredictions of NO lead to insufficient O3 titration, thus O3 overpredictions. The model can generally reproduce the observed O3 and PM indicators. These indicators suggest to control NOx emissions throughout the year, and VOCs emissions in summer in big cities and in winter over North China Plain, North/South Korea, and Japan to reduce surface O3, and to control SO2, NH3, and NOx throughout the year to reduce inorganic surface PM.}, journal={ATMOSPHERIC ENVIRONMENT}, author={He, Jian and Zhang, Yang and Wang, Kai and Chen, Ying and Leung, L. Ruby and Fan, Jiwen and Li, Meng and Zheng, Bo and Zhang, Qiang and Duan, Fengkui and et al.}, year={2017}, month={Sep}, pages={122–142} }
 @article{zhang_wang_he_2017, title={Multi-year application of WRF-CAM5 over East Asia-Part II: Interannual variability, trend analysis, and aerosol indirect effects}, volume={165}, ISSN={["1873-2844"]}, DOI={10.1016/j.atmosenv.2017.06.029}, abstractNote={Following a comprehensive evaluation of WRF-CAM5 in Part I, Part II describes analyses of interannual variability, multi-year variation trends, and the direct, indirect, and total effects of anthropogenic aerosols. The interannual variations of chemical column and surface concentrations, and ozone (O3)/particulate matter (PM) indicators are strongly correlated to anthropogenic emission changes. Despite model biases, the model captures well the observed interannual variations of temperature at 2-m, cloud fraction, shortwave cloud forcing, downwelling shortwave radiation, cloud droplet number concentration, column O3, and column formaldehyde (HCHO) for the whole domain. While the model reproduces the volatile organic compound (VOC)-limited regimes of O3 chemistry at sites in Hong Kong, Taiwan, Japan, South Korea, and from the Acid Deposition Monitoring Network in East Asia (EANET) and the degree of sulfate neutralization at the EANET sites, it has limited capability in capturing the interannual variations of the ratio of O3 and nitrogen dioxide (O3/NO2) and PM chemical regime indicators, due to uncertainties in the emissions of precursors for O3 and secondary PM, the model assumption for ammonium bisulfate (NH4HSO4) as well as lack of gas/particle partitioning of total ammonia and total nitrate. While the variation trends in multi-year periods in aerosol optical depth and column concentrations of carbon monoxide, sulfur dioxide, and NO2 are mainly caused by anthropogenic emissions, those of major meteorological and cloud variables partly reflect feedbacks of chemistry to meteorological variables. The impacts of anthropogenic aerosol indirect effects either dominate or play an important role in the aerosol total effects for most cloud and chemical predictions, whereas anthropogenic aerosol direct effects influence most meteorological and radiation variables. The direct, indirect, and total effects of anthropogenic aerosols exhibit a strong interannual variability in 2001, 2006, and 2011.}, journal={ATMOSPHERIC ENVIRONMENT}, author={Zhang, Yang and Wang, Kai and He, Jian}, year={2017}, month={Sep}, pages={222–239} }
 @article{yahya_wang_campbell_chen_glotfelty_he_pirhalla_zhang_2017, title={Decadal application of WRF/Chem for regional air quality and climate modeling over the US under the representative concentration pathways scenarios. Part 1: Model evaluation and impact of downscaling}, volume={152}, ISSN={["1873-2844"]}, DOI={10.1016/j.atmosenv.2016.12.029}, abstractNote={An advanced online-coupled meteorology-chemistry model, i.e., the Weather Research and Forecasting Model with Chemistry (WRF/Chem), is applied for current (2001–2010) and future (2046–2055) decades under the representative concentration pathways (RCP) 4.5 and 8.5 scenarios to examine changes in future climate, air quality, and their interactions. In this Part I paper, a comprehensive model evaluation is carried out for current decade to assess the performance of WRF/Chem and WRF under both scenarios and the benefits of downscaling the North Carolina State University's (NCSU) version of the Community Earth System Model (CESM_NCSU) using WRF/Chem. The evaluation of WRF/Chem shows an overall good performance for most meteorological and chemical variables on a decadal scale. Temperature at 2-m is overpredicted by WRF (by ∼0.2–0.3 °C) but underpredicted by WRF/Chem (by ∼0.3–0.4 °C), due to higher radiation from WRF. Both WRF and WRF/Chem show large overpredictions for precipitation, indicating limitations in their microphysics or convective parameterizations. WRF/Chem with prognostic chemical concentrations, however, performs much better than WRF with prescribed chemical concentrations for radiation variables, illustrating the benefit of predicting gases and aerosols and representing their feedbacks into meteorology in WRF/Chem. WRF/Chem performs much better than CESM_NCSU for most surface meteorological variables and O3 hourly mixing ratios. In addition, WRF/Chem better captures observed temporal and spatial variations than CESM_NCSU. CESM_NCSU performance for radiation variables is comparable to or better than WRF/Chem performance because of the model tuning in CESM_NCSU that is routinely made in global models.}, journal={ATMOSPHERIC ENVIRONMENT}, author={Yahya, Khairunnisa and Wang, Kai and Campbell, Patrick and Chen, Ying and Glotfelty, Timothy and He, Jian and Pirhalla, Michael and Zhang, Yang}, year={2017}, month={Mar}, pages={562–583} }
 @article{yahya_wang_campbell_glotfelty_he_zhang_2016, title={Decadal evaluation of regional climate, air quality, and their interactions over the continental US and their interactions using WRF/Chem version 3.6.1}, volume={9}, number={2}, journal={Geoscientific Model Development}, author={Yahya, K. and Wang, K. and Campbell, P. and Glotfelty, T. and He, J. and Zhang, Y.}, year={2016}, pages={671–695} }
 @article{glotfelty_he_zhang_2017, title={Impact of future climate policy scenarios on air quality and aerosol-cloud interactions using an advanced version of CESM/CAM5: Part I. model evaluation for the current decadal simulations}, volume={152}, ISSN={["1873-2844"]}, DOI={10.1016/j.atmosenv.2016.12.035}, abstractNote={A version of the Community Earth System Model modified at the North Carolina State University (CESM-NCSU) is used to simulate the current and future atmosphere following the representative concentration partway scenarios for stabilization of radiative forcing at 4.5 W m−2 (RCP4.5) and radiative forcing of 8.5 W m−2 (RCP8.5). Part I describes the results from a comprehensive evaluation of current decadal simulations. Radiation and most meteorological variables are well simulated in CESM-NCSU. Cloud parameters are not as well simulated due in part to the tuning of model radiation and general biases in cloud variables common to all global chemistry-climate models. The concentrations of most inorganic aerosol species (i.e., SO42-, NH4+, and NO3−) are well simulated with normalized mean biases (NMBs) typically less than 20%. However, some notable exceptions are European NH4+, which is overpredicted by 33.0–42.2% due to high NH3 emissions and irreversible coarse mode condensation, and Cl−, that is negatively impacted by errors in emissions driven by wind speed and overpredicted HNO3. Carbonaceous aerosols are largely underpredicted following the RCP scenarios due to low emissions of black carbon, organic carbon, and anthropogenic volatile compounds in the RCP inventory and efficient wet removal. This results in underpredictions of PM2.5 and PM10 by 6.4–55.7%. The column mass abundances are reasonably well simulated. Larger biases occur in surface mixing ratios of trace gases in CESM-NCSU, likely due to numerical diffusion from the coarse grid spacing of the CESM-NCSU simulations or errors in the magnitudes and vertical structure of emissions. This is especially true for SO2 and NO2. The mixing ratio of O3 is overpredicted by 38.9–76.0% due to the limitations in the O3 deposition scheme used in CESM and insufficient titration resulted from large underpredictions in NO2. Despite these limitations, CESM-NCSU reproduces reasonably well the current atmosphere in terms of radiation, clouds, meteorology, trace gases, aerosols, and aerosol-cloud interactions, making it suitable for future climate simulations.}, journal={ATMOSPHERIC ENVIRONMENT}, author={Glotfelty, Timothy and He, Jian and Zhang, Yang}, year={2017}, month={Mar}, pages={222–239} }
 @article{zhang_he_zhu_gantt_2016, title={Sensitivity of simulated chemical concentrations and aerosol-meteorology interactions to aerosol treatments and biogenic organic emissions in WRF/Chem}, volume={121}, ISSN={["2169-8996"]}, DOI={10.1002/2016jd024882}, abstractNote={AbstractCoupled air quality and climate models can predict aerosol concentrations and properties, as well as aerosol direct and indirect effects that depend on aerosol chemistry and microphysics treatments. In this study, Weather Research and Forecasting with Chemistry (WRF/Chem) simulations are conducted over continental U.S. (CONUS) for January and July 2001 with the same gas‐phase mechanism (CB05) but three aerosol modules (Modal Aerosol Dynamics Model for Europe/Secondary Organic Aerosol Model (MADE/SORGAM), Model for Simulating Aerosol Interactions and Chemistry (MOSAIC), and Model of Aerosol Dynamics, Reaction, Ionization and Dissolution (MADRID)) to examine the impacts of aerosol treatments on predictions of aerosols and their effects on cloud properties and radiation. The simulations with the three aerosol modules give similar domain mean predictions of surface PM2.5 concentrations but exhibit a strong spatial variation in magnitudes with large differences in eastern U.S. Large discrepancies are found in the predicted concentrations of sulfate and organic matter due to different treatments in secondary inorganic and secondary organic aerosol (SOA) formation. In particular, the nucleation calculation in MADE/SORGAM causes mass buildup of sulfate which results in much higher sulfate concentrations that those predicted by WRF/Chem with the other two aerosol modules. Different PM mass concentrations and size representations lead to differences in the predicted aerosol number concentrations. The above differences in PM concentrations lead to large differences in simulated condensation nuclei (CCN) and cloud properties in both months. The simulated ranges of domain mean are (1.9–14.3) × 109 m−3 and (1.4–5.4) × 109 m−3 for PM2.5 number concentration, (1.6–3.9) × 108 cm−2 and (1.9–3.9) × 108 cm−2 for CCN, 102.9–208.2 cm−3 and 143.7–202.2 cm−3 for column cloud droplet number concentration (CDNC), and 4.5–6.4 and 3.6–6.7 for cloud optical depths (COT) in January and July, respectively. The sensitivity simulation for July 2001 using online biogenic emissions increases isoprene concentrations but decreases terpene concentrations, leading to a domain mean increase in O3 (1.5 ppb) and a decrease in biogenic SOA (−0.07 µg m−3) and PM2.5 (−0.2 µg m−3). Anthropogenic emissions contribute to O3, biogenic SOA (BSOA), and PM2.5 concentrations by 38.0%, 44.2%, and 53.6% domain mean and by up to 78.5%, 89.7%, and 96.3%, respectively, indicating that a large fraction of BSOA is controllable through controlling atmospheric oxidant levels in CONUS. Anthropogenic emissions also contribute to a decrease in downward shortwave flux at ground surface (−5.8 W m−2), temperature at 2 m (−0.05°C), wind speed at 10 m (−0.02 m s−1), planetary boundary layer height (−6.6 m), and precipitation (−0.08 mm), as well as an increase in CCN (+5.7 × 10−7 cm−2), in‐cloud CDNC (+40.4 cm−3), and COT (+0.6). This work indicates the need for an accurate representation of several aerosol processes such as SOA formation and aerosol‐cloud interactions in simulating aerosol direct and indirect effects in the online‐coupled models.}, number={10}, journal={JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES}, author={Zhang, Yang and He, Jian and Zhu, Shuai and Gantt, Brett}, year={2016}, month={May}, pages={6014–6048} }
 @article{he_zhang_tilmes_emmons_lamarque_glotfelty_hodzic_vitt_2015, title={CESM/CAM5 improvement and application: comparison and evaluation of updated CB05_GE and MOZART-4 gas-phase mechanisms and associated impacts on global air quality and climate}, volume={8}, number={12}, journal={Geoscientific Model Development}, author={He, J. and Zhang, Y. and Tilmes, S. and Emmons, L. and Lamarque, J. F. and Glotfelty, T. and Hodzic, A. and Vitt, F.}, year={2015}, pages={3999–4025} }
 @article{he_zhang_glotfelty_he_bennartz_rausch_sartelet_2015, title={Decadal simulation and comprehensive evaluation of CESM/CAM5.1 with advanced chemistry, aerosol microphysics, and aerosol-cloud interactions}, volume={7}, ISSN={["1942-2466"]}, DOI={10.1002/2014ms000360}, abstractNote={AbstractEarth system models have been used for climate predictions in recent years due to their capabilities to include biogeochemical cycles, human impacts, as well as coupled and interactive representations of Earth system components (e.g., atmosphere, ocean, land, and sea ice). In this work, the Community Earth System Model (CESM) with advanced chemistry and aerosol treatments, referred to as CESM‐NCSU, is applied for decadal (2001–2010) global climate predictions. A comprehensive evaluation is performed focusing on the atmospheric component—the Community Atmosphere Model version 5.1 (CAM5.1) by comparing simulation results with observations/reanalysis data and CESM ensemble simulations from the Coupled Model Intercomparison Project phase 5 (CMIP5). The improved model can predict most meteorological and radiative variables relatively well with normalized mean biases (NMBs) of −14.1 to −9.7% and 0.7–10.8%, respectively, although temperature at 2 m (T2) is slightly underpredicted. Cloud variables such as cloud fraction (CF) and precipitating water vapor (PWV) are well predicted, with NMBs of −10.5 to 0.4%, whereas cloud condensation nuclei (CCN), cloud liquid water path (LWP), and cloud optical thickness (COT) are moderately‐to‐largely underpredicted, with NMBs of −82.2 to −31.2%, and cloud droplet number concentration (CDNC) is overpredictd by 26.7%. These biases indicate the limitations and uncertainties associated with cloud microphysics (e.g., resolved clouds and subgrid‐scale cumulus clouds). Chemical concentrations over the continental U.S. (CONUS) (e.g., 
, Cl−, OC, and PM2.5) are reasonably well predicted with NMBs of −12.8 to −1.18%. Concentrations of SO2, 
, and PM10 are also reasonably well predicted over Europe with NMBs of −20.8 to −5.2%, so are predictions of SO2 concentrations over the East Asia with an NMB of −18.2%, and the tropospheric ozone residual (TOR) over the globe with an NMB of −3.5%. Most meteorological and radiative variables predicted by CESM‐NCSU agree well overall with those predicted by CESM‐CMIP5. The performance of LWP and AOD predicted by CESM‐NCSU is better than that of CESM‐CMIP5 in terms of model bias and correlation coefficients. Large biases for some chemical predictions can be attributed to uncertainties in the emissions of precursor gases (e.g., SO2, NH3, and NOx) and primary aerosols (black carbon and primary organic matter) as well as uncertainties in formulations of some model components (e.g., online dust and sea‐salt emissions, secondary organic aerosol formation, and cloud microphysics). Comparisons of CESM simulation with baseline emissions and 20% of anthropogenic emissions from the baseline emissions indicate that anthropogenic gas and aerosol species can decrease downwelling shortwave radiation (FSDS) by 4.7 W m−2 (or by 2.9%) and increase SWCF by 3.2 W m−2 (or by 3.1%) in the global mean.}, number={1}, journal={JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS}, publisher={American Geophysical Union (AGU)}, author={He, Jian and Zhang, Yang and Glotfelty, Tim and He, Ruoying and Bennartz, Ralf and Rausch, John and Sartelet, Karine}, year={2015}, month={Mar}, pages={110–141} }
 @article{zhang_zhang_wang_he_leung_fan_nenes_2015, title={Incorporating an advanced aerosol activation parameterization into WRF-CAM5: Model evaluation and parameterization intercomparison}, volume={120}, ISSN={["2169-8996"]}, DOI={10.1002/2014jd023051}, abstractNote={AbstractAerosol activation into cloud droplets is an important process that governs aerosol indirect effects. The advanced treatment of aerosol activation by Fountoukis and Nenes (2005) and its recent updates, collectively called the FN series, have been incorporated into a newly developed regional coupled climate‐air quality model based on the Weather Research and Forecasting model with the physics package of the Community Atmosphere Model version 5 (WRF‐CAM5) to simulate aerosol‐cloud interactions in both resolved and convective clouds. The model is applied to East Asia for two full years of 2005 and 2010. A comprehensive model evaluation is performed for model predictions of meteorological, radiative, and cloud variables, chemical concentrations, and column mass abundances against satellite data and surface observations from air quality monitoring sites across East Asia. The model performs overall well for major meteorological variables including near‐surface temperature, specific humidity, wind speed, precipitation, cloud fraction, precipitable water, downward shortwave and longwave radiation, and column mass abundances of CO, SO2, NO2, HCHO, and O3 in terms of both magnitudes and spatial distributions. Larger biases exist in the predictions of surface concentrations of CO and NOx at all sites and SO2, O3, PM2.5, and PM10 concentrations at some sites, aerosol optical depth, cloud condensation nuclei over ocean, cloud droplet number concentration (CDNC), cloud liquid and ice water path, and cloud optical thickness. Compared with the default Abdul‐Razzack Ghan (2000) parameterization, simulations with the FN series produce ~107–113% higher CDNC, with half of the difference attributable to the higher aerosol activation fraction by the FN series and the remaining half due to feedbacks in subsequent cloud microphysical processes. With the higher CDNC, the FN series are more skillful in simulating cloud water path, cloud optical thickness, downward shortwave radiation, shortwave cloud forcing, and precipitation. The model evaluation identifies several areas of improvements including emissions and their vertical allocation as well as model formulations such as aerosol formation, cloud droplet nucleation, and ice nucleation.}, number={14}, journal={JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES}, author={Zhang, Yang and Zhang, Xin and Wang, Kai and He, Jian and Leung, L. Ruby and Fan, Jiwen and Nenes, Athanasios}, year={2015}, month={Jul}, pages={6952–6979} }
 @article{yahya_he_zhang_2015, title={Multiyear applications of WRF/Chem over continental US: Model evaluation, variation trend, and impacts of boundary conditions}, volume={120}, ISSN={["2169-8996"]}, DOI={10.1002/2015jd023819}, abstractNote={AbstractMultiyear applications of an online‐coupled meteorology‐chemistry model allow an assessment of the variation trends in simulated meteorology, air quality, and their interactions to changes in emissions and meteorology, as well as the impacts of initial and boundary conditions (ICONs/BCONs) on simulated aerosol‐cloud‐radiation interactions over a period of time. In this work, the Weather Research and Forecasting model with Chemistry version 3.4.1 (WRF/Chem v. 3.4.1) with the 2005 Carbon Bond mechanism coupled with the Volatility Basis Set module for secondary organic aerosol formation (WRF/Chem‐CB05‐VBS) is applied for multiple years (2001, 2006, and 2010) over continental U.S. This work also examines the changes in simulated air quality and meteorology due to changes in emissions and meteorology and the model's capability in reproducing the observed variation trends in species concentrations from 2001 to 2010. In addition, the impacts of the chemical ICONs/BCONs on model predictions are analyzed. ICONs/BCONs are downscaled from two global models, the modified Community Earth System Model/Community Atmosphere model version 5.1 (CESM/CAM v5.1) and the Monitoring Atmospheric Composition and Climate model (MACC). The evaluation of WRF/Chem‐CB05‐VBS simulations with the CESM ICONs/BCONs for 2001, 2006, and 2010 shows that temperature at 2 m (T2) is underpredicted for all three years likely due to inaccuracies in soil moisture and soil temperature, resulting in biases in surface relative humidity, wind speed, and precipitation. With the exception of cloud fraction, other aerosol‐cloud variables including aerosol optical depth, cloud droplet number concentration, and cloud optical thickness are underpredicted for all three years, resulting in overpredictions of radiation variables. The model performs well for O3 and particulate matter with diameter less than or equal to 2.5 (PM2.5) for all three years comparable to other studies from literature. The model is able to reproduce observed annual average trends in O3 and PM2.5 concentrations from 2001 to 2006 and from 2006 to 2010 but is less skillful in simulating their observed seasonal trends. The 2006 and 2010 results using CESM and MACC ICONs/BCONs are compared to analyze the impact of ICONs/BCONs on model performance and their feedbacks to aerosol, clouds, and radiation. Comparing to the simulations with MACC ICONs/BCONs, the simulations with the CESM ICONs/BCONs improve the performance of O3 mixing ratios (e.g., the normalized mean bias for maximum 8 h O3 is reduced from −17% to −1% in 2010), PM2.5 in 2010, and sulfate in 2006 (despite a slightly larger normalized mean bias for PM2.5 in 2006). The impacts of different ICONs/BCONs on simulated aerosol‐cloud‐radiation variables are not negligible, with larger impacts in 2006 compared to 2010.}, number={24}, journal={JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES}, author={Yahya, Khairunnisa and He, Jian and Zhang, Yang}, year={2015}, month={Dec}, pages={12748–12777} }
 @article{he_zhang_2014, title={Improvement and further development in CESM/CAM5: gas-phase chemistry and inorganic aerosol treatments}, volume={14}, number={17}, journal={Atmospheric Chemistry and Physics}, author={He, J. and Zhang, Y.}, year={2014}, pages={9171–9200} }
 @article{gantt_he_zhang_zhang_nenes_2014, title={Incorporation of advanced aerosol activation treatments into CESM/CAM5: model evaluation and impacts on aerosol indirect effects}, volume={14}, number={14}, journal={Atmospheric Chemistry and Physics}, author={Gantt, B. and He, J. and Zhang, X. and Zhang, Y. and Nenes, A.}, year={2014}, pages={7485–7497} }