245 citations as recorded by crossref.

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2. Revealing Bias of Cloud Radiative Effect in WRF Simulation: Bias Quantification and Source Attribution Y. Shan et al. https://doi.org/10.1029/2021JD036319
3. Hybrid Deep Learning Framework for Forecasting Ground-Level Ozone in a North Texas Urban Region J. Kanayankottupoyil et al. https://doi.org/10.3390/app152211923
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5. Reflections on the Scientific Legacy of Sergej S. Zilitinkevich on PBL and Urban Parameterizations in NWP Models R. Bornstein & A. Baklanov https://doi.org/10.1007/s10546-023-00789-y
6. Investigation of aerosol direct effects on meteorology and air quality in East Asia by using an online coupled modeling system G. Nguyen et al. https://doi.org/10.1016/j.atmosenv.2019.03.017
7. Utilisation FINN data version 2.5 for forecasting PM2.5 during forest fire 2019 in Sumatra by using WRF–Chem P. Kombara et al. https://doi.org/10.1071/ES22030
8. MICS-Asia III: multi-model comparison and evaluation of aerosol over East Asia L. Chen et al. https://doi.org/10.5194/acp-19-11911-2019
9. CAPRAM reduction towards an operational multiphase halogen and dimethyl sulfide chemistry treatment in the chemistry transport model COSMO-MUSCAT(5.04e) E. Hoffmann et al. https://doi.org/10.5194/gmd-13-2587-2020
10. Use of CAMS near Real-Time Aerosols in the HARMONIE-AROME NWP Model D. Martín Pérez et al. https://doi.org/10.3390/meteorology3020008
11. Aerosol indirect effects on summer precipitation in a regional climate model for the Euro-Mediterranean region N. Da Silva et al. https://doi.org/10.5194/angeo-36-321-2018
12. Correspondence between tree pollen emissions sources and pollen content of the ambient air L. Kremenska et al. https://doi.org/10.1007/s10453-019-09579-x
13. An aerosol climatology for global models based on the tropospheric aerosol scheme in the Integrated Forecasting System of ECMWF A. Bozzo et al. https://doi.org/10.5194/gmd-13-1007-2020
14. April 2008 Saharan dust event: Its contribution to PM10 concentrations over the Anatolian Peninsula and relation with synoptic conditions B. Kabatas et al. https://doi.org/10.1016/j.scitotenv.2018.03.150
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16. An assessment of aerosol optical properties from remote-sensing observations and regional chemistry–climate coupled models over Europe L. Palacios-Peña et al. https://doi.org/10.5194/acp-18-5021-2018
17. A regional air quality forecasting system over Europe: the MACC-II daily ensemble production V. Marécal et al. https://doi.org/10.5194/gmd-8-2777-2015
18. Reviews and syntheses: influences of landscape structure and land uses on local to regional climate and air quality R. Massad et al. https://doi.org/10.5194/bg-16-2369-2019
19. THE OPTIMAL SETTINGS FOR THE ONLINE-INTEGRATED MODEL ENVIRO-HIRLAM IN ORDER TO SIMULATE THE ATMOSPHERE-CHEMISTRY INTERACTION FOR THE UKRAINIAN TERRITORY M. Savenets & L. Pysarenko https://doi.org/10.15407/Meteorology2022.02.035
20. Impact of air quality model settings for the evaluation of emission reduction strategies to curb air pollution B. Bessagnet et al. https://doi.org/10.1016/j.envres.2024.119112
21. Assessment of the MACC reanalysis and its influence as chemical boundary conditions for regional air quality modeling in AQMEII-2 L. Giordano et al. https://doi.org/10.1016/j.atmosenv.2015.02.034
22. Description and evaluation of the Multiscale Online Nonhydrostatic AtmospheRe CHemistry model (NMMB-MONARCH) version 1.0: gas-phase chemistry at global scale A. Badia et al. https://doi.org/10.5194/gmd-10-609-2017
23. Volcanic ash modeling with the online NMMB-MONARCH-ASH v1.0 model: model description, case simulation, and evaluation A. Marti et al. https://doi.org/10.5194/acp-17-4005-2017
24. The Role of the Atmospheric Aerosol in Weather Forecasts for the Iberian Peninsula: Investigating the Direct Effects Using the WRF-Chem Model C. Silveira et al. https://doi.org/10.3390/atmos12020288
25. A multi-model assessment for the 2006 and 2010 simulations under the Air Quality Model Evaluation International Initiative (AQMEII) Phase 2 over North America: Part II. Evaluation of column variable predictions using satellite data K. Wang et al. https://doi.org/10.1016/j.atmosenv.2014.07.044
26. Modeling study of aerosol-meteorology feedback during winter haze events over the north China plain J. Li et al. https://doi.org/10.1016/j.apr.2021.101311
27. Local versus external dust source contributions to northern China and selected downwind cities: Evidence from representative dust events in 2025 Y. Fan et al. https://doi.org/10.1016/j.envpol.2026.128369
28. Tropospheric chemistry in the Integrated Forecasting System of ECMWF J. Flemming et al. https://doi.org/10.5194/gmd-8-975-2015
29. Aerosol radiative effects and feedbacks on boundary layer meteorology and PM2.5 chemical components during winter haze events over the Beijing-Tianjin-Hebei region J. Li et al. https://doi.org/10.5194/acp-20-8659-2020
30. Development of the CMA-GFS-AERO 4D-Var assimilation system v1.0 – Part 1: System description and preliminary experimental results Y. Liu et al. https://doi.org/10.5194/gmd-18-4855-2025
31. Application of WRF/Chem over East Asia: Part I. Model evaluation and intercomparison with MM5/CMAQ Y. Zhang et al. https://doi.org/10.1016/j.atmosenv.2015.07.022
32. Impact of the 4 April 2014 Saharan dust outbreak on the photovoltaic power generation in Germany D. Rieger et al. https://doi.org/10.5194/acp-17-13391-2017
33. A description and evaluation of an air quality model nested within global and regional composition-climate models using MetUM L. Neal et al. https://doi.org/10.5194/gmd-10-3941-2017
34. Numerical assessment of PM2.5 and O3 air quality in continental Southeast Asia: Baseline simulation and aerosol direct effects investigation G. Nguyen et al. https://doi.org/10.1016/j.atmosenv.2019.117054
35. Composition and origin of PM2.5 aerosol particles in the upper Rhine valley in summer X. Shen et al. https://doi.org/10.5194/acp-19-13189-2019
36. Setting-up a Real-Time Air Quality Forecasting system for Serbia: a WRF-Chem feasibility study with different horizontal resolutions and emission inventories Z. Podrascanin https://doi.org/10.1007/s11356-019-05140-y
37. Extension of WRF-Chem for birch pollen modelling—a case study for Poland M. Werner et al. https://doi.org/10.1007/s00484-020-02045-1
38. Advancing air pollution forecasting: a review of physical, statistical, and machine learning methods A. Rawat et al. https://doi.org/10.1007/s11356-026-37789-7
39. ICON-ART 2.1: a flexible tracer framework and its application for composition studies in numerical weather forecasting and climate simulations J. Schröter et al. https://doi.org/10.5194/gmd-11-4043-2018
40. The atmospheric composition component of the ICON modeling framework: ICON-ART version 2025.10 G. Hoshyaripour et al. https://doi.org/10.5194/gmd-19-1645-2026
41. Methods for reducing biases and errors in regional photochemical model outputs for use in emission reduction and exposure assessments P. Porter et al. https://doi.org/10.1016/j.atmosenv.2015.04.039
42. Evaluation of Meso-NH and WRF/CHEM simulated gas and aerosol chemistry over Europe based on hourly observations A. Berger et al. https://doi.org/10.1016/j.atmosres.2016.02.006
43. Comprehensive evaluation of multi-year real-time air quality forecasting using an online-coupled meteorology-chemistry model over southeastern United States Y. Zhang et al. https://doi.org/10.1016/j.atmosenv.2016.05.006
44. Estimating Local Air Pollutant Contribution Ratio Based on Concentration Variability Among Monitoring Stations Y. Wang et al. https://doi.org/10.3390/atmos17050481
45. Integration of prognostic aerosol–cloud interactions in a chemistry transport model coupled offline to a regional climate model M. Thomas et al. https://doi.org/10.5194/gmd-8-1885-2015
46. A CNN-transformer framework for air quality forecasting to support aeolian dust management in river basins P. Kow et al. https://doi.org/10.1016/j.aei.2025.103758
47. Establishing a non-hydrostatic global atmospheric modeling system at 3-km horizontal resolution with aerosol feedbacks on the Sunway supercomputer of China J. Gu et al. https://doi.org/10.1016/j.scib.2022.03.009
48. Gas-phase evaluation of the online NMMB/BSC-CTM model over Europe for 2010 in the framework of the AQMEII-Phase2 project A. Badia & O. Jorba https://doi.org/10.1016/j.atmosenv.2014.05.055
49. Estimates of exceedances of critical loads for acidifying deposition in Alberta and Saskatchewan P. Makar et al. https://doi.org/10.5194/acp-18-9897-2018
50. The effects of simulating volcanic aerosol radiative feedbacks with WRF-Chem during the Eyjafjallajökull eruption, April and May 2010 M. Hirtl et al. https://doi.org/10.1016/j.atmosenv.2018.10.058
51. The influence of temperature on ozone production under varying NOx conditions – a modelling study J. Coates et al. https://doi.org/10.5194/acp-16-11601-2016
52. High resolution application of the EMEP MSC-W model over Eastern Europe – Analysis of the EMEP4PL results M. Werner et al. https://doi.org/10.1016/j.atmosres.2018.04.025
53. Air quality forecasting for winter‐time PM2.5 episodes occurring in multiple cities in central and southern Chile P. Saide et al. https://doi.org/10.1002/2015JD023949
54. NUMAC: Description of the Nested Unified Model With Aerosols and Chemistry, and Evaluation With KORUS‐AQ Data H. Gordon et al. https://doi.org/10.1029/2022MS003457
55. A complex aerosol transport event over Europe during the 2017 Storm Ophelia in CAMS forecast systems: analysis and evaluation D. Akritidis et al. https://doi.org/10.5194/acp-20-13557-2020
56. Modeling the Processing of Aerosol and Trace Gases in Clouds and Fogs B. Ervens https://doi.org/10.1021/cr5005887
57. Data assimilation in atmospheric chemistry models: current status and future prospects for coupled chemistry meteorology models M. Bocquet et al. https://doi.org/10.5194/acp-15-5325-2015
58. Regional effects of atmospheric aerosols on temperature: an evaluation of an ensemble of online coupled models R. Baró et al. https://doi.org/10.5194/acp-17-9677-2017
59. Impact of inherent meteorology uncertainty on air quality model predictions R. Gilliam et al. https://doi.org/10.1002/2015JD023674
60. Population dynamics based on mobile phone data to improve air pollution exposure assessments M. Picornell et al. https://doi.org/10.1038/s41370-018-0058-5
61. An automatic observation-based aerosol typing method for EARLINET N. Papagiannopoulos et al. https://doi.org/10.5194/acp-18-15879-2018
62. Air quality and climate change, Topic 3 of the Model Inter-Comparison Study for Asia Phase III (MICS-Asia III) – Part 1: Overview and model evaluation M. Gao et al. https://doi.org/10.5194/acp-18-4859-2018
63. Source attribution of particulate matter in Berlin J. Pültz et al. https://doi.org/10.1016/j.atmosenv.2022.119416
64. Annual application and evaluation of the online coupled WRF–CMAQ system over North America under AQMEII phase 2 C. Hogrefe et al. https://doi.org/10.1016/j.atmosenv.2014.12.034
65. Advances in air quality modeling and forecasting A. Baklanov & Y. Zhang https://doi.org/10.1016/j.glt.2020.11.001
66. Current State of Atmospheric Aerosol Thermodynamics and Mass Transfer Modeling: A Review K. Semeniuk & A. Dastoor https://doi.org/10.3390/atmos11020156
67. Multi-year downscaling application of two-way coupled WRF v3.4 and CMAQ v5.0.2 over east Asia for regional climate and air quality modeling: model evaluation and aerosol direct effects C. Hong et al. https://doi.org/10.5194/gmd-10-2447-2017
68. Modelling of airborne birch pollen over Central Europe – model evaluation and sensitivity analysis J. Boreczek et al. https://doi.org/10.1016/j.scitotenv.2025.179873
69. Impacts of aerosol–radiation interaction on meteorological forecasts over northern China by offline coupling of the WRF-Chem-simulated aerosol optical depth into WRF: a case study during a heavy pollution event Y. Yang et al. https://doi.org/10.5194/acp-20-12527-2020
70. Exploring the economy-wide effects of agriculture on air quality and health: Evidence from Europe E. Giannakis et al. https://doi.org/10.1016/j.scitotenv.2019.01.410
71. Evaluation of ECMWF IFS-AER (CAMS) operational forecasts during cycle 41r1–46r1 with calibrated ceilometer profiles over Germany H. Flentje et al. https://doi.org/10.5194/gmd-14-1721-2021
72. Modelling aerosol–cloud–meteorology interaction: A case study with a fully coupled air quality model (GEM-MACH) W. Gong et al. https://doi.org/10.1016/j.atmosenv.2015.05.062
73. Impacts of the direct radiative effect of aerosols in numerical weather prediction over Europe using the ALADIN-HIRLAM NWP system V. Toll et al. https://doi.org/10.1016/j.atmosres.2016.01.003
74. Novel Decomposition Scheme for Characterizing Urban Air Quality with MODIS P. Misra et al. https://doi.org/10.3390/rs9080812
75. Thermodynamics-guided machine learning model for predicting convective boundary layer height and its multi-site applicability Y. Chu et al. https://doi.org/10.5194/acp-26-1415-2026
76. Dynamical-statistical method for seasonal forecasting of wintertime PM10 concentration in South Korea using multi-model ensemble climate forecasts J. Choi et al. https://doi.org/10.1088/1748-9326/ad5030
77. On the limit to the accuracy of regional-scale air quality models S. Rao et al. https://doi.org/10.5194/acp-20-1627-2020
78. Utilisation of local emission inventory data for forecasting PM10 using the WRF-Chem model in the Bandung Basin P. Kombara et al. https://doi.org/10.1071/ES23026
79. The Weather Research and Forecasting Model: Overview, System Efforts, and Future Directions J. Powers et al. https://doi.org/10.1175/BAMS-D-15-00308.1
80. A simple and realistic aerosol emission approach for use in the Thompson–Eidhammer microphysics scheme in the NOAA UFS Weather Model (version GSL global-24Feb2022) H. Li et al. https://doi.org/10.5194/gmd-17-607-2024
81. Feedbacks between air pollution and weather, part 2: Effects on chemistry P. Makar et al. https://doi.org/10.1016/j.atmosenv.2014.10.021
82. Dispersion-box modeling investigation of the influences of gasoline, diesel, M85 and E85 vehicle exhaust emission on photochemistry M. Gabay & E. Tas https://doi.org/10.1016/j.envpol.2019.05.142
83. A modified gas-phase scheme for advanced regional climate modelling with RegCM4 J. Ciarlo` et al. https://doi.org/10.1007/s00382-021-05722-y
84. Added Value of Aerosol-Cloud Interactions for Representing Aerosol Optical Depth in an Online Coupled Climate-Chemistry Model over Europe L. Palacios-Peña et al. https://doi.org/10.3390/atmos11040360
85. Deep learning for air pollutant forecasting: opportunities, challenges, and future directions C. Tao et al. https://doi.org/10.1007/s11783-025-2092-6
86. GEM-MACH-PAH (rev2488): a new high-resolution chemical transport model for North American polycyclic aromatic hydrocarbons and benzene C. Whaley et al. https://doi.org/10.5194/gmd-11-2609-2018
87. Study of interaction between cloud microphysics and chemistry using coupled bin microphysics and bin aqueous chemistry scheme G. Schmeller & I. Geresdi https://doi.org/10.1016/j.atmosenv.2018.10.064
88. Decadal application of WRF/Chem over the continental U.S.: Simulation design, sensitivity simulations, and climatological model evaluation K. Wang et al. https://doi.org/10.1016/j.atmosenv.2021.118331
89. Sensitivity of feedback effects in CBMZ/MOSAIC chemical mechanism R. San José et al. https://doi.org/10.1016/j.atmosenv.2015.04.030
90. A perspective on the development of gas-phase chemical mechanisms for Eulerian air quality models W. Stockwell et al. https://doi.org/10.1080/10962247.2019.1694605
91. Improving air quality forecasting with the assimilation of GOCI aerosol optical depth (AOD) retrievals during the KORUS-AQ period S. Ha et al. https://doi.org/10.5194/acp-20-6015-2020
92. Modeling Surface Air Pollution with Reduced Emissions during the COVID-19 Pandemic Using CHIMERE and COSMO-ART Chemical Transport Models I. Kuznetsova et al. https://doi.org/10.3103/S1068373922030025
93. A comparative study of two-way and offline coupled WRF v3.4 and CMAQ v5.0.2 over the contiguous US: performance evaluation and impacts of chemistry–meteorology feedbacks on air quality K. Wang et al. https://doi.org/10.5194/gmd-14-7189-2021
94. Modeling of the chemical composition of fine particulate matter: Development and performance assessment of EASYWRF-Chem M. Mendez et al. https://doi.org/10.1016/j.atmosres.2015.11.006
95. Modelling chain for the effect of road traffic on air and water quality: Techniques, current status and future prospects M. Fallah Shorshani et al. https://doi.org/10.1016/j.envsoft.2014.11.020
96. Implementation of Aerosol-Cloud Interaction within WRF-CHIMERE Online Coupled Model: Evaluation and Investigation of the Indirect Radiative Effect from Anthropogenic Emission Reduction on the Benelux Union P. Tuccella et al. https://doi.org/10.3390/atmos10010020
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98. WRF-Chem model sensitivity to chemical mechanisms choice in reconstructing aerosol optical properties A. Balzarini et al. https://doi.org/10.1016/j.atmosenv.2014.12.033
99. MOPSMAP v1.0: a versatile tool for the modeling of aerosol optical properties J. Gasteiger & M. Wiegner https://doi.org/10.5194/gmd-11-2739-2018
100. Chemistry‐Weather Interacted Model System GRAPES_Meso5.1/CUACE CW V1.0: Development, Evaluation and Application in Better Haze/Fog Prediction in China H. Wang et al. https://doi.org/10.1029/2022MS003222
101. Ozone air quality simulations with WRF-Chem (v3.5.1) over Europe: model evaluation and chemical mechanism comparison K. Mar et al. https://doi.org/10.5194/gmd-9-3699-2016
102. Description and evaluation of the tropospheric aerosol scheme in the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS-AER, cycle 45R1) S. Rémy et al. https://doi.org/10.5194/gmd-12-4627-2019
103. Precipitation response to aerosol–radiation and aerosol–cloud interactions in regional climate simulations over Europe J. López-Romero et al. https://doi.org/10.5194/acp-21-415-2021
104. Current and Future Disease Burden From Ambient Ozone Exposure in India L. Conibear et al. https://doi.org/10.1029/2018GH000168
105. ICON–ART 1.0 – a new online-coupled model system from the global to regional scale D. Rieger et al. https://doi.org/10.5194/gmd-8-1659-2015
106. The role of emissions and meteorology in driving CO2 concentrations in urban areas G. Gualtieri et al. https://doi.org/10.1007/s11356-021-12754-8
107. Influence of the Grid Resolutions on the Computer-Simulated Surface Air Pollution Concentrations in Bulgaria G. Gadzhev et al. https://doi.org/10.3390/atmos13050774
108. Regional-scale modelling for the assessment of atmospheric particulate matter concentrations at rural background locations in Europe G. Gašparac et al. https://doi.org/10.5194/acp-20-6395-2020
109. Understanding air pollution dynamics of Antalya Manavgat forest fires: a WRF-Chem analysis Y. Kara et al. https://doi.org/10.1007/s10661-025-13833-w
110. Enviro-HIRLAM online integrated meteorology–chemistry modelling system: strategy, methodology, developments and applications (v7.2) A. Baklanov et al. https://doi.org/10.5194/gmd-10-2971-2017
111. Error apportionment for atmospheric chemistry-transport models – a new approach to model evaluation E. Solazzo & S. Galmarini https://doi.org/10.5194/acp-16-6263-2016
112. Prediction of ground-level ozone concentration in São Paulo, Brazil: Deterministic versus statistic models G. Hoshyaripour et al. https://doi.org/10.1016/j.atmosenv.2016.09.061
113. Short-Term Forecast of the Carbon Monoxide Concentration Over the Moscow Region by COSMO-ART A. Revokatova et al. https://doi.org/10.1007/s00024-018-2001-z
114. Validation of PM10 and PM2.5 early alert in Bogotá, Colombia, through the modeling software WRF-CHEM A. Casallas et al. https://doi.org/10.1007/s11356-019-06997-9
115. Aerosols, Clusters, Greenhouse Gases, Trace Gases and Boundary-Layer Dynamics: on Feedbacks and Interactions M. Kulmala et al. https://doi.org/10.1007/s10546-022-00769-8
116. Towards Real-Time, High-Spatial-Resolution Air Pollution Exposure Estimation in Microenvironments Supported by Physics-Informed Machine Learning Approaches J. Bartzis et al. https://doi.org/10.3390/environments13050256
117. Assessment of future solar energy potential changes under the shared socio-economic pathways scenario 2–4.5 with WRF-chem: The roles of meteorology and emission Y. Zhang et al. https://doi.org/10.1016/j.atmosenv.2023.120232
118. Numerical simulations of atmospheric dispersion of iodine-131 by different models Á. Leelőssy et al. https://doi.org/10.1371/journal.pone.0172312
119. Coupled Stratospheric Chemistry–Meteorology Data Assimilation. Part I: Physical Background and Coupled Modeling Aspects R. Ménard et al. https://doi.org/10.3390/atmos11020150
120. Pollution slightly enhances atmospheric cooling by low-level clouds in tropical West Africa V. Hahn et al. https://doi.org/10.5194/acp-23-8515-2023
121. Preface S. Galmarini et al. https://doi.org/10.1016/j.atmosenv.2015.06.009
122. A review of numerical models to predict the atmospheric dispersion of radionuclides Á. Leelőssy et al. https://doi.org/10.1016/j.jenvrad.2017.11.009
123. Earth system modeling of mercury using CESM2 – Part 1: Atmospheric model CAM6-Chem/Hg v1.0 P. Zhang & Y. Zhang https://doi.org/10.5194/gmd-15-3587-2022
124. Air quality modeling in the metropolitan area of São Paulo, Brazil: A review M. Gavidia-Calderón et al. https://doi.org/10.1016/j.atmosenv.2023.120301
125. Severe Wildfires Near Moscow, Russia in 2010: Modeling of Carbon Monoxide Pollution and Comparisons with Observations A. Safronov et al. https://doi.org/10.3390/rs70100395
126. An online emission module for atmospheric chemistry transport models: implementation in COSMO-GHG v5.6a and COSMO-ART v5.1-3.1 M. Jähn et al. https://doi.org/10.5194/gmd-13-2379-2020
127. Sensitivity of low-level clouds and precipitation to anthropogenic aerosol emission in southern West Africa: a DACCIWA case study A. Deroubaix et al. https://doi.org/10.5194/acp-22-3251-2022
128. Application of WRF/Chem over North America under the AQMEII Phase 2 – Part 2: Evaluation of 2010 application and responses of air quality and meteorology–chemistry interactions to changes in emissions and meteorology from 2006 to 2010 K. Yahya et al. https://doi.org/10.5194/gmd-8-2095-2015
129. A new chemistry option in WRF-Chem v. 3.4 for the simulation of direct and indirect aerosol effects using VBS: evaluation against IMPACT-EUCAARI data P. Tuccella et al. https://doi.org/10.5194/gmd-8-2749-2015
130. Air-stagnation episodes based on regional climate models part I: evaluation over Europe J. Van Nieuwenhuyse et al. https://doi.org/10.1007/s00382-023-06665-2
131. Evaluation of operational on-line-coupled regional air quality models over Europe and North America in the context of AQMEII phase 2. Part I: Ozone U. Im et al. https://doi.org/10.1016/j.atmosenv.2014.09.042
132. Extension of the WRF-Chem volcanic emission preprocessor to integrate complex source terms and evaluation for different emission scenarios of the Grimsvötn 2011 eruption M. Hirtl et al. https://doi.org/10.5194/nhess-20-3099-2020
133. RECTV: Enhancing Agile Decision-Making in Startups Through Value-Driven Requirements Prioritization F. Pattyn et al. https://doi.org/10.1109/ACCESS.2025.3589942
134. Application of an Online-Coupled Regional Climate Model, WRF-CAM5, over East Asia for Examination of Ice Nucleation Schemes: Part I. Comprehensive Model Evaluation and Trend Analysis for 2006 and 2011 Y. Chen et al. https://doi.org/10.3390/cli3030627
135. Aerosol Indirect Effects on the Predicted Precipitation in a Global Weather Forecasting Model J. Kang et al. https://doi.org/10.3390/atmos10070392
136. Impact of mixing states on aerosol radiative effects and feedback during winter haze episodes over the North China Plain J. Wang et al. https://doi.org/10.1039/D5EA00126A
137. Curriculum vitae of the LOTOS–EUROS (v2.0) chemistry transport model A. Manders et al. https://doi.org/10.5194/gmd-10-4145-2017
138. Overview of the Meso-NH model version 5.4 and its applications C. Lac et al. https://doi.org/10.5194/gmd-11-1929-2018
139. PALM-meteo 2.8: Processor of PALM meteorological input data P. Krč et al. https://doi.org/10.5194/gmd-19-4071-2026
140. Non-isothermal scavenging of highly soluble gaseous pollutants by rain in the atmosphere with non-uniform vertical concentration and temperature distributions T. Elperin et al. https://doi.org/10.1007/s00703-014-0330-8
141. An assessment of vapour pressure estimation methods S. O'Meara et al. https://doi.org/10.1039/C4CP00857J
142. Performance studies of planetary boundary layer schemes in WRF-Chem for the Andean region of Southern Ecuador R. Parra https://doi.org/10.1016/j.apr.2017.11.011
143. Modelled NO2 tropospheric columns at different resolutions versus OMI satellite data: analysis of a 1-year BOLCHEM simulation over Europe L. Aidaoui et al. https://doi.org/10.1007/s11869-015-0315-x
144. Sub-kilometer dispersion simulation of a CO tracer for an inter-Andean urban valley J. Henao et al. https://doi.org/10.1016/j.apr.2020.02.005
145. Recent progress, bottlenecks, and outlook of multiscale air quality modelling: a review Y. Dai et al. https://doi.org/10.1016/j.aeaoa.2026.100435
146. The influence of resolved convective motions on scalar dispersion in hectometric‐scale numerical weather prediction models L. Blunn et al. https://doi.org/10.1002/qj.4632
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151. Development of an atmospheric chemistry model coupled to the PALM model system 6.0: implementation and first applications B. Khan et al. https://doi.org/10.5194/gmd-14-1171-2021
152. IL-GLOBO (1.0) – integrated Lagrangian particle model and Eulerian general circulation model GLOBO: development of the vertical diffusion module D. Rossi & A. Maurizi https://doi.org/10.5194/gmd-7-2181-2014
153. SILAM and MACC reanalysis aerosol data used for simulating the aerosol direct radiative effect with the NWP model HARMONIE for summer 2010 wildfire case in Russia V. Toll et al. https://doi.org/10.1016/j.atmosenv.2015.06.007
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155. Aerosol characteristics and polarimetric signatures for a deep convective storm over the northwestern part of Europe – modeling and observations P. Shrestha et al. https://doi.org/10.5194/acp-22-14095-2022
156. Air quality and climate change, Topic 3 of the Model Inter-Comparison Study for Asia Phase III (MICS-Asia III) – Part 2: aerosol radiative effects and aerosol feedbacks M. Gao et al. https://doi.org/10.5194/acp-20-1147-2020
157. Simulating PM2.5 Concentrations during New Year in Cuenca, Ecuador: Effects of Advancing the Time of Burning Activities R. Parra et al. https://doi.org/10.3390/toxics10050264
158. Investigating Southeast Asian biomass burning by the WRF-CMAQ two-way coupled model: Emission and direct aerosol radiative effects Y. Huang et al. https://doi.org/10.1016/j.atmosenv.2022.119521
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164. Status and future of numerical atmospheric aerosol prediction with a focus on data requirements A. Benedetti et al. https://doi.org/10.5194/acp-18-10615-2018
165. Evaluation of NASA's high-resolution global composition simulations: Understanding a pollution event in the Chesapeake Bay during the summer 2017 OWLETS campaign N. Dacic et al. https://doi.org/10.1016/j.atmosenv.2019.117133
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174. Exploring the stratospheric source of ozone pollution over China during the 2016 Group of Twenty summit Z. Ni et al. https://doi.org/10.1016/j.apr.2019.02.010
175. The impact of data assimilation into the meteorological WRF model on birch pollen modelling M. Werner et al. https://doi.org/10.1016/j.scitotenv.2021.151028
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204. Aerosol as a critical factor causing forecast biases of air temperature in global numerical weather prediction models X. Huang & A. Ding https://doi.org/10.1016/j.scib.2021.05.009
205. Radiative forcing of dust aerosols during a severe dust event in southern Iran M. Rezazadeh et al. https://doi.org/10.1007/s12517-021-08366-8
206. Dome effect of black carbon and its key influencing factors: a one-dimensional modelling study Z. Wang et al. https://doi.org/10.5194/acp-18-2821-2018
207. Combining POLDER-3 satellite observations and WRF-Chem numerical simulations to derive biomass burning aerosol properties over the southeast Atlantic region A. Siméon et al. https://doi.org/10.5194/acp-21-17775-2021
208. Carbonaceous aerosol in the Brahmaputra plains: Sources, and influence from the hotspot Indo-Gangetic plains, India T. Paul et al. https://doi.org/10.1007/s10874-024-09464-z
209. Two-way coupled meteorology and air quality models in Asia: a systematic review and meta-analysis of impacts of aerosol feedbacks on meteorology and air quality C. Gao et al. https://doi.org/10.5194/acp-22-5265-2022
210. Assessment of the impact of atmospheric aerosols and meteorological data assimilation on simulation of the weather over India during summer 2015 S. Devaliya et al. https://doi.org/10.1016/j.atmosenv.2023.119586
211. The potential for geostationary remote sensing of NO2 to improve weather prediction X. Liu et al. https://doi.org/10.5194/acp-21-9573-2021
212. A standardized methodology for the validation of air quality forecast applications (F-MQO): lessons learnt from its application across Europe L. Vitali et al. https://doi.org/10.5194/gmd-16-6029-2023
213. Seeing and turbulence profile simulations over complex terrain at the Thai National Observatory using a chemistry-coupled regional forecasting model R. Macatangay et al. https://doi.org/10.1093/mnras/stae727
214. Insights for Air Quality Management from Modeling and Record Studies in Cuenca, Ecuador R. Parra & C. Espinoza https://doi.org/10.3390/atmos11090998
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216. Evaluation of the high resolution WRF-Chem (v3.4.1) air quality forecast and its comparison with statistical ozone predictions R. Žabkar et al. https://doi.org/10.5194/gmd-8-2119-2015
217. Investigation the soliton solutions of mussel and algae model leading to concentration W. Islam et al. https://doi.org/10.1016/j.aej.2023.01.025
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219. The role of aerosol–radiation–cloud interactions in linking anthropogenic pollution over southern west Africa and dust emission over the Sahara L. Menut et al. https://doi.org/10.5194/acp-19-14657-2019
220. Data Assimilation Algorithms for Atmospheric Chemistry Models A. Penenko et al. https://doi.org/10.1134/S0001433825700719
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223. Integrated models of nutrient dynamics in lake and reservoir watersheds: A systematic review and integrated modelling decision pathway F. Clopin et al. https://doi.org/10.1016/j.envsoft.2025.106321
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225. Time-Dependent Downscaling of PM2.5 Predictions from CAMS Air Quality Models to Urban Monitoring Sites in Budapest A. Varga-Balogh et al. https://doi.org/10.3390/atmos11060669
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230. Characterising Brazilian biomass burning emissions using WRF-Chem with MOSAIC sectional aerosol S. Archer-Nicholls et al. https://doi.org/10.5194/gmd-8-549-2015
231. Role of aerosol–cloud–radiation interactions in modulating summertime quasi-biweekly rainfall intensity over South China H. Chen et al. https://doi.org/10.5194/acp-25-15765-2025
232. Development and application of the WRFPLUS-Chem online chemistry adjoint and WRFDA-Chem assimilation system J. Guerrette & D. Henze https://doi.org/10.5194/gmd-8-1857-2015
233. Simulation the Spatial and Temporal Patterns of PM2.5 Over Iraq (Baghdad) Using the WRF/Chem Model M. Al-Jiboori et al. https://doi.org/10.1088/1755-1315/1531/1/012003
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235. Understanding emissions of ammonia from buildings and the application of fertilizers: an example from Poland M. Werner et al. https://doi.org/10.5194/bg-12-3623-2015
236. Evaluation of ECMWF-IFS (version 41R1) operational model forecasts of aerosol transport by using ceilometer network measurements K. Chan et al. https://doi.org/10.5194/gmd-11-3807-2018
237. Scenario Modelling and Impact Estimation of a Local Pollutant on the Environment V. Hura et al. https://doi.org/10.2478/acss-2025-0021
238. Unraveling Street-Level Air Pollution upon a Pivotal City of Yangtze River Delta, China R. Feng et al. https://doi.org/10.1007/s41810-021-00093-7
239. Solar “brightening” impact on summer surface ozone between 1990 and 2010 in Europe – a model sensitivity study of the influence of the aerosol–radiation interactions E. Oikonomakis et al. https://doi.org/10.5194/acp-18-9741-2018
240. Modelling Hourly Particulate Matter (PM10) Concentrations at High Spatial Resolution in Germany Using Land Use Regression and Open Data S. Wallek et al. https://doi.org/10.3390/atmos13081282
241. Introduction: The Pan-Eurasian Experiment (PEEX) – multidisciplinary, multiscale and multicomponent research and capacity-building initiative M. Kulmala et al. https://doi.org/10.5194/acp-15-13085-2015
242. High Resolution Urban Air Quality Modeling by Coupling CFD and Mesoscale Models: a Review R. Kadaverugu et al. https://doi.org/10.1007/s13143-019-00110-3
243. Passive versus Active Transport of Saharan Dust Aerosols by African Easterly Waves D. Grogan & T. Nathan https://doi.org/10.3390/atmos12111509
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