@article{glotfelty_ramirez-mejia_bowden_ghilardi_west_2021, title={Limitations of WRF land surface models for simulating land use and land cover change in Sub-Saharan Africa and development of an improved model (CLM-AF v. 1.0)}, volume={14}, ISSN={["1991-9603"]}, url={https://doi.org/10.5194/gmd-14-3215-2021}, DOI={10.5194/gmd-14-3215-2021}, abstractNote={Abstract. Land use and land cover change (LULCC) impacts local and
regional climates through various biogeophysical processes. Accurate
representation of land surface parameters in land surface models (LSMs) is
essential to accurately predict these LULCC-induced climate signals. In this
work, we test the applicability of the default Noah, Noah-MP, and Community Land Model (CLM) LSMs
in the Weather Research and Forecasting (WRF) model over Sub-Saharan Africa.
We find that the default WRF LSMs do not accurately represent surface
albedo, leaf area index, and surface roughness in this region due to various
flawed assumptions, including the treatment of the MODIS woody savanna land use and land cover (LULC)
category as closed shrubland. Consequently, we developed a WRF CLM version
with more accurate African land surface parameters (CLM-AF), designed such
that it can be used to evaluate the influence of LULCC. We evaluate
meteorological performance for the default LSMs and CLM-AF against
observational datasets, gridded products, and satellite estimates. Further,
we conduct LULCC experiments with each LSM to determine if differences in
land surface parameters impact the LULCC-induced climate responses. Despite
clear deficiencies in surface parameters, all LSMs reasonably capture the
spatial pattern and magnitude of near-surface temperature and precipitation.
However, in the LULCC experiments, inaccuracies in the default LSMs result in
illogical localized temperature and precipitation changes. Differences in
thermal changes between Noah-MP and CLM-AF indicate that the temperature
impacts from LULCC are dependent on the sensitivity of evapotranspiration to
LULCC in Sub-Saharan Africa. Errors in land surface parameters indicate that
the default WRF LSMs considered are not suitable for LULCC experiments in
tropical or Southern Hemisphere regions and that proficient meteorological
model performance can mask these issues. We find CLM-AF to be suitable for
use in Sub-Saharan Africa LULCC studies, but more work is needed by the WRF
community to improve its applicability to other tropical and Southern
Hemisphere climates.
                    }, number={6}, journal={GEOSCIENTIFIC MODEL DEVELOPMENT}, author={Glotfelty, Timothy and Ramirez-Mejia, Diana and Bowden, Jared and Ghilardi, Adrian and West, J. Jason}, year={2021}, month={Jun}, pages={3215–3249} }
 @article{pedruzzi_andreao_baek_hudke_glotfelty_freitas_martins_bowden_pinto_alonso_et al._2022, title={Update of land use/land cover and soil texture for Brazil: Impact on WRF modeling results over Sao Paulo}, volume={268}, ISSN={["1873-2844"]}, DOI={10.1016/j.atmosenv.2021.118760}, abstractNote={Land Use/Land Cover (LULC) and soil texture play a key role in meteorological models because they determine the vegetation and soil proprieties that interfere in the exchange of energy, moisture, and momentum between the land surface and the atmosphere. Additionally, LULC and soil texture are relevant input datasets in meteorological models affecting their results and future applicability as in weather researches and air quality modeling. Brazil has a complex and heterogeneous LU, and it has faced significant LULC changes in the past years. Therefore, this paper aims to update the LULC, using the national product MapBiomas, and soil texture data, by SoilGrids, to replace the default input data in the Weather Research and Forecast (WRF) model for São Paulo, Brazil. Aiming to evaluate the impact of those input data on WRF simulations, five cases were simulated using WRF v4.1.3 with 1 km of grid resolution, and combinations of "Default" and "Updated" input data. Sixty-days simulations from March 15th to May 15th of 2015, covering the transition of wet to dry season, were performed and evaluated with observational data over São Paulo State. The results showed significant differences in the classifications of LULC and soil texture in the entire domain between the default and updated data. The updated data is more realistic and coherent with local characteristics, being more representative, as an example over Santos city area being correctly classified as urban and built-in updated LULC and not water, as in the default. The comparison between the modeled results with observations data has shown a similar behavior for temperature and humidity for the five cases at the monitoring stations grid cells because the LULC changes were between classes with similar land parameters, such as albedo, roughness length, and soils moisture, although the Default classes are not accurate. However, the latent and sensible heat fluxes were ways more sensitive to the LULC/soil texture changes in the WRF model. Additionally, reasonable differences were observed over the entire modeling domain for these two variables. The updated land surface data provoked low temperatures at 9h and 17h UTC, less humidity at 9h UTC, and more humidity at 17h UTC, especially in the north part of the modeling domain, the area which has faced more LULC and soil changes. The PBL height was also affected by the updated data, probably caused by the impact at heat flux over the domain, causing a variation from 30% to 70% over the modeled grid cell, which may have a higher impact on air quality modeling. Thus, it is recommended to update the land surface data for Brazil to avoid misclassification of LULC and soil texture, even if the comparison at monitoring stations has shown similar behavior between the default and updated land surface data. Additionally, updates in the land parameter inside the model are required to represent each LULC/soil class better.}, journal={ATMOSPHERIC ENVIRONMENT}, author={Pedruzzi, Rizzieri and Andreao, Willian Lemker and Baek, Bok Haeng and Hudke, Anderson Paulo and Glotfelty, Timothy William and Freitas, Edmilson Dias and Martins, Jorge Alberto and Bowden, Jared H. and Pinto, Janaina Antonino and Alonso, Marcelo Felix and et al.}, year={2022}, month={Jan} }
 @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{yahya_glotfelty_wang_zhang_nenes_2017, title={Modeling regional air quality and climate: Improving organic aerosol and aerosol activation processes in WRF/Chem version 3.7.1}, volume={10}, number={6}, journal={Geoscientific Model Development}, author={Yahya, K. and Glotfelty, T. and Wang, K. and Zhang, Y. and Nenes, A.}, year={2017}, pages={2333–2363} }
 @article{glotfelty_zhang_karamchandani_streets_2016, title={Changes in future air quality, deposition, and aerosol-cloud interactions under future climate and emission scenarios}, volume={139}, ISSN={["1873-2844"]}, DOI={10.1016/j.atmosenv.2016.05.008}, abstractNote={The prospect of global climate change will have wide scale impacts, such as ecological stress and human health hazards. One aspect of concern is future changes in air quality that will result from changes in both meteorological forcing and air pollutant emissions. In this study, the GU-WRF/Chem model is employed to simulate the impact of changing climate and emissions following the IPCC AR4 SRES A1B scenario. An average of 4 future years (2020, 2030, 2040, and 2050) is compared against an average of 2 current years (2001 and 2010). Under this scenario, by the Mid-21st century global air quality is projected to degrade with a global average increase of 2.5 ppb in the maximum 8-hr O3 level and of 0.3 μg m−3 in 24-hr average PM2.5. However, PM2.5 changes are more regional due to regional variations in primary aerosol emissions and emissions of gaseous precursor for secondary PM2.5. Increasing NOx emissions in this scenario combines with a wetter climate elevating levels of OH, HO2, H2O2, and the nitrate radical and increasing the atmosphere's near surface oxidation state. This differs from findings under the RCP scenarios that experience declines in OH from reduced NOx emissions, stratospheric recovery of O3, and increases in CH4 and VOCs. Increasing NOx and O3 levels enhances the nitrogen and O3 deposition, indicating potentially enhanced crop damage and ecosystem stress under this scenario. The enhanced global aerosol level results in enhancements in aerosol optical depth, cloud droplet number concentration, and cloud optical thickness. This leads to dimming at the Earth's surface with a global average reduction in shortwave radiation of 1.2 W m−2. This enhanced dimming leads to a more moderate warming trend and different trends in radiation than those found in NCAR's CCSM simulation, which does not include the advanced chemistry and aerosol treatment of GU-WRF/Chem and cannot simulate the impacts of changing climate and emissions with the same level of detailed treatments. This study indicates that effective climate mitigation and emission control strategies are needed to prevent future health impact and ecosystem stress. Further, studies that are used to develop these strategies should use fully coupled models with sophisticated chemical and aerosol-interaction treatments that can provide a more realistic representation of the atmosphere.}, journal={ATMOSPHERIC ENVIRONMENT}, author={Glotfelty, Timothy and Zhang, Yang and Karamchandani, Prakash and Streets, David G.}, year={2016}, month={Aug}, pages={176–191} }
 @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_zhang_2017, title={Impact of future climate policy scenarios on air quality and aerosol cloud interactions using an advanced version of CESM/CAM5: Part II. Future trend analysis and impacts of projected anthropogenic emissions}, volume={152}, ISSN={["1873-2844"]}, DOI={10.1016/j.atmosenv.2016.12.034}, abstractNote={Following a comprehensive evaluation of the Community Earth System Model modified at the North Carolina State University (CESM-NCSU), Part II describes the projected changes in the future state of the atmosphere under the representative concentration partway scenarios (RCP4.5 and 8.5) by 2100 for the 2050 time frame and examine the impact of climate change on future air quality under both scenarios, and the impact of projected emission changes under the RCP4.5 scenario on future climate through aerosol direct and indirect effects. Both the RCP4.5 and RCP8.5 simulations predict similar changes in air quality by the 2050 period due to declining emissions under both scenarios. The largest differences occur in O3, which decreases by global mean of 1.4 ppb under RCP4.5 but increases by global mean of 2.3 ppb under RCP8.5 due to differences in methane levels, and PM10, which decreases by global mean of 1.2 μg m−3 under RCP4.5 and increases by global mean of 0.2 μg m−3 under RCP8.5 due to differences in dust and sea-salt emissions under both scenarios. Enhancements in cloud formation in the Arctic and Southern Ocean and increases of aerosol optical depth (AOD) in central Africa and South Asia dominate the change in surface radiation in both scenarios, leading to global average dimming of 1.1 W m−2 and 2.0 W m−2 in the RCP4.5 and RCP8.5 scenarios, respectively. Declines in AOD, cloud formation, and cloud optical thickness from reductions of emissions of primary aerosols and aerosol precursors under RCP4.5 result in near surface warming of 0.2 °C from a global average increase of 0.7 W m−2 in surface downwelling solar radiation. This warming leads to a weakening of the Walker Circulation in the tropics, leading to significant changes in cloud and precipitation that mirror a shift in climate towards the negative phase of the El Nino Southern Oscillation.}, journal={ATMOSPHERIC ENVIRONMENT}, author={Glotfelty, Timothy and Zhang, Yang}, year={2017}, month={Mar}, pages={531–552} }
 @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{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{yahya_wang_gudoshava_glotfelty_zhang_2015, title={Application of WRF/Chem over North America under the AQMEII Phase 2: Part I. Comprehensive evaluation of 2006 simulation}, volume={115}, ISSN={["1873-2844"]}, DOI={10.1016/j.atmosenv.2014.08.063}, abstractNote={The Weather Research and Forecasting model with Chemistry (WRF/Chem) version 3.4.1 has been modified to include the Carbon Bond 2005 (CB05) gas-phase mechanism, the Modal for Aerosol Dynamics for Europe (MADE) and the Volatility Basis Set (VBS) approach for secondary organic aerosol (hereafter WRF/Chem-CB05-MADE/VBS), and aerosol-cloud-radiation feedbacks to improve predictions of secondary organic aerosols (SOA) and to study meteorology-chemistry feedbacks. In this Part I paper, a comprehensive evaluation is performed for WRF/Chem-CB05-MADE/VBS to simulate air quality over a large area in North America for the full year of 2006. Operational, diagnostic, and mechanistic evaluations have been carried out for major meteorological variables, gas and aerosol species, as well as aerosol-cloud-radiation variables against surface measurements, sounding data, and satellite data on a seasonal and annual basis. The model performs well for most meteorological variables with moderate to relatively high correlation and low mean biases (MBs), but with a cold bias of 0.8–0.9 °C in temperature, a moderate overprediction with normalized mean biases (NMBs) of 17–22% in wind speed, and large underpredictions with NMBs of −65% to −62% in cloud optical depths and cloud condensation nuclei over the ocean. Those biases are attributed to uncertainty in physical parameterizations, incomplete treatments of hydrometeors, and inaccurate aerosol predictions. The model shows moderate underpredictions in the mixing ratios of O3 with an annual NMB of −12.8% over rural and national park sites, which may be caused by biases in temperature and wind speed, underestimate in wildfire emissions, and underestimate in biogenic organic emissions (reflected by an NMB of −79.1% in simulated isoprene mixing ratio). The model performs well for PM2.5 concentrations with annual NMBs within ±10%; but with possible bias compensation for PM2.5 species concentrations. The model simulates well the domainwide organic carbon and SOA concentrations at two sites in the southeastern U.S. but it overpredicts SOA concentrations at two sites and underpredicts OC at one site in the same area. Those biases in site-specific SOA and OC predictions are attributed to underestimates in observed SOA, uncertainties in VOC emissions, inaccurate meteorology, and the inadequacies in the VBS treatment. Larger biases exist in predictions of dry and wet deposition fluxes of gas and PM species due mainly to overpredictions in their concentrations and precipitation, uncertainties in model treatments of deposition processes, and uncertainties in the CASTNET dry deposition data. Comparison of WRF and WRF/Chem simulations shows that the inclusion of chemical feedbacks to meteorology, clouds, and radiation results in improved predictions in most meteorological variables. Aerosol optical depth correlates strongly with aerosol concentration and cloud optical depth. The relationships between the aerosol and cloud variables are complex as the cloud variables are not only influenced by aerosol concentrations but by larger-scale dynamical processes.}, journal={ATMOSPHERIC ENVIRONMENT}, author={Yahya, Khairunnisa and Wang, Kai and Gudoshava, Masi Lin and Glotfelty, Timothy and Zhang, Yang}, year={2015}, month={Aug}, pages={733–755} }
 @article{glotfelty_zhang_karamchandani_streets_2014, title={Will the role of intercontinental transport change in a changing climate?}, volume={14}, number={17}, journal={Atmospheric Chemistry and Physics}, author={Glotfelty, T. and Zhang, Y. and Karamchandani, P. and Streets, D. G.}, year={2014}, pages={9379–9402} }
 @article{zhang_karamchandani_glotfelty_streets_grell_nenes_yu_bennartz_2012, title={Development and initial application of the global-through-urban weather research and forecasting model with chemistry (GU-WRF/Chem)}, volume={117}, journal={Journal of Geophysical Research-Atmospheres}, author={Zhang, Y. and Karamchandani, P. and Glotfelty, T. and Streets, D. G. and Grell, G. and Nenes, A. and Yu, F. Q. and Bennartz, R.}, year={2012} }