These data include three-dimensional meteorological (WRF) and air quality (CMAQ) model output for a 2-km domain covering the San Joaquin Valley (SJV) of California for January and February of 2013. The WRF and CMAQ parameters used in the analysis presented in the research effort are listed in the attached spreadsheet. The WRF/CMAQ data themselves are located on EPA's asm tape archive in the directories below. These data are available upon request from the authors, specifically K. Wyat Appel (appel.wyat@epa.gov). /asm/MOD3EVAL/DISCOVERAQ/SJV/2km_Meso/WRF /asm/MOD3EVAL/DISCOVERAQ/SJV/2km_Meso/CMAQ. This dataset is associated with the following publication: Friberg, M., R. Kahn, J. Limbacher, W. Appel, and J. Mulholland. Constraining chemical transport PM2.5 modeling outputs using surface monitor measurements and satellite retrievals: application over the San Joaquin Valley. Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau, GERMANY, 18: 12891-12913, (2018).

Hemispheric scale simulations with CMAQ and the Weather Research and Forecasting model are performed for multiple years. Model capabilities for a range of applications including episodic long-range pollutant transport, long-term trends in air pollution across the Northern Hemisphere, and air pollution-climate interactions are evaluated through detailed comparison with available surface, aloft, and remotely sensed observations. This dataset is associated with the following publication: Mathur, R., J. Xing, R. Gilliam, G. Sarwar, C. Hogrefe, J. Pleim, G. Pouliot, S. Roselle, T. Spero, D. Wong, and J. Young. Extending the Community Multiscale Air Quality (CMAQ) Modeling System to Hemispheric Scales: Overview of Process Considerations and Initial Applications. Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau, GERMANY, 17: 12449-12474, (2017).

Hemispheric scale simulations with CMAQ and the Weather Research and Forecasting model are performed for multiple years. Model capabilities for a range of applications including episodic long-range pollutant transport, long-term trends in air pollution across the Northern Hemisphere, and air pollution-climate interactions are evaluated through detailed comparison with available surface, aloft, and remotely sensed observations. This dataset is associated with the following publication: Mathur, R., J. Xing, R. Gilliam, G. Sarwar, C. Hogrefe, J. Pleim, G. Pouliot, S. Roselle, T. Spero, D. Wong, and J. Young. Extending the Community Multiscale Air Quality (CMAQ) Modeling System to Hemispheric Scales: Overview of Process Considerations and Initial Applications. Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau, GERMANY, 17: 12449-12474, (2017).

Software Model simulations were conducted using WRF version 3.8.1 (available at https://github.com/NCAR/WRFV3) and CMAQ version 5.2.1 (available at https://github.com/USEPA/CMAQ). The meteorological and concentration fields created using these models are too large to archive on ScienceHub, approximately 1 TB, and are archived on EPA’s high performance computing archival system (ASM) at /asm/MOD3APP/pcc/02.NOAH.v.CLM.v.PX/. Figures Figures 1 – 6 and Figure 8: Created using the NCAR Command Language (NCL) scripts (https://www.ncl.ucar.edu/get_started.shtml). NCLD code can be downloaded from the NCAR website (https://www.ncl.ucar.edu/Download/) at no cost. The data used for these figures are archived on EPA’s ASM system and are available upon request. Figures 7, 8b-c, 8e-f, 8h-i, and 9 were created using the AMET utility developed by U.S. EPA/ORD. AMET can be freely downloaded and used at https://github.com/USEPA/AMET. The modeled data paired in space and time provided in this archive can be used to recreate these figures. The data contained in the compressed zip files are organized in comma delimited files with descriptive headers or space delimited files that match tabular data in the manuscript. The data dictionary provides additional information about the files and their contents. This dataset is associated with the following publication: Campbell, P., J. Bash, and T. Spero. Updates to the Noah Land Surface Model in WRF‐CMAQ to Improve Simulated Meteorology, Air Quality, and Deposition. Journal of Advances in Modeling Earth Systems. John Wiley & Sons, Inc., Hoboken, NJ, USA, 11(1): 231-256, (2019).

These data include three-dimensional meteorological (WRF) and air quality (CMAQ) model output for 4-km and 2-km domains covering the San Joaquin Valley (SJV) of California for January and February of 2013. The WRF and CMAQ parameters used in the analysis presented in the research effort are listed in the attached spreadsheet. The WRF/CMAQ data themselves are located on EPA's asm tape archive in the directories below. These data are available upon request from the authors, specifically K. Wyat Appel (appel.wyat@epa.gov). /asm/MOD3EVAL/DISCOVERAQ/SJV/DISCOVERAQ_SJV_4km_CMAQv52_Jul19_CB6_NewEmis /asm/MOD3EVAL/DISCOVERAQ/SJV/output_sf_SJV_2km_CMAQv52_CB6_Jul192017rel_NewEmis. This dataset is associated with the following publication: Choi, S., L. Lok, J. Joiner, N. Krotkov, M. Follette-Cook, W. Swartz, K. Pickering, C. Loughner, K.W. Appel, G. Pfister, P. Saide, R. Cohen, A. Weinheimer, and J. Herman. Assessment of NO2 Observations during DISCOVER-AQ and KORUS-AQ Field Campaigns. Atmospheric Measurement Techniques. Copernicus Publications, Katlenburg-Lindau, GERMANY, 13(5): 2523–2546, (2020).

Input files for running the Community Multiscale Air Quality (CMAQ) modeling system. Input files include emissions, meteorology, boundary and initial conditions, and other ancillary data needed for running a simulation over the contiguous United States (12US2 domain) for December 22, 2015 - January 31, 2016. These input data can be used with two online tutorials described in Efstathiou et al. to set up and run a CMAQ simulation on Amazon Web Services and Microsoft Azure cloud computing resources. Data are netcdf formatted files using I/O API data structures (https://www.cmascenter.org/ioapi/). Information on variables within the files (variable names and units) and the model projection and grid structure is contained in the header information of each netcdf file.

This dataset documents the simulations demonstrating the capabilities of the new DESID module, a part of CMAQ that allows for adjustment of emissions and expanded diagnostic output. There are three figures, each with four subpanels, that are provided here. They are all present in the supporting information of the manuscript. There are no figures with data in the main manuscript. This dataset is not publicly accessible because: See explanation above. It can be accessed through the following means: See explanation above. Format: This research paper is somewhat unique in that there is no data presented in the main manuscript. There are three figures presented in the supporting information which are generated from input and output data from CMAQ. The figures are for tutorial purposes only and do not directly contribute to any analysis or conclusions of any scientific hypothesis or policy recommendation. The CMAQ code, data and figure scripts used to generate the supporting information figures may be found on ASM in the folder: /asm/MOD3DEV/bmurphy/ScienceHub/DESID. This dataset is associated with the following publication: Murphy, B., C. Nolte, F. Sidi, J. Bash, K.W. Appel, C. Jang, D. Kang, J. Kelly, R. Mathur, S. Napelenok, G. Pouliot, and H. Pye. The Detailed Emissions Scaling, Isolation, and Diagnostic (DESID) module in the Community Multiscale Air Quality (CMAQ) Modeling System version 5.3.2. Geoscientific Model Development. Copernicus Publications, Katlenburg-Lindau, GERMANY, 14(6): 3407-3420, (2021).

This dataset documents the simulations demonstrating the capabilities of the new DESID module, a part of CMAQ that allows for adjustment of emissions and expanded diagnostic output. There are three figures, each with four subpanels, that are provided here. They are all present in the supporting information of the manuscript. There are no figures with data in the main manuscript. This dataset is not publicly accessible because: See explanation above. It can be accessed through the following means: See explanation above. Format: This research paper is somewhat unique in that there is no data presented in the main manuscript. There are three figures presented in the supporting information which are generated from input and output data from CMAQ. The figures are for tutorial purposes only and do not directly contribute to any analysis or conclusions of any scientific hypothesis or policy recommendation. The CMAQ code, data and figure scripts used to generate the supporting information figures may be found on ASM in the folder: /asm/MOD3DEV/bmurphy/ScienceHub/DESID. This dataset is associated with the following publication: Murphy, B., C. Nolte, F. Sidi, J. Bash, K.W. Appel, C. Jang, D. Kang, J. Kelly, R. Mathur, S. Napelenok, G. Pouliot, and H. Pye. The Detailed Emissions Scaling, Isolation, and Diagnostic (DESID) module in the Community Multiscale Air Quality (CMAQ) Modeling System version 5.3.2. Geoscientific Model Development. Copernicus Publications, Katlenburg-Lindau, GERMANY, 14(6): 3407-3420, (2021).

CMAQ and WRF output files. This dataset is not publicly accessible because: Too Big. It can be accessed through the following means: The data can be accesses from the ASM data archive at the National Environmental Supercomputing Center at the USEPA. Format: WRF–CMAQ Model output data including SW radiation, PM2.5 , Sulfate aerosol, EC, and SO2 concentrations, Also aerosol optical depth (AOD). This dataset is associated with the following publication: Gan, C., J. Pleim , R. Mathur , C. Hogrefe , C.N. Long, J. Xing, D. Wong , R. Gilliam , and C. Wei. Assessment of long-term WRF–CMAQ simulations for understanding direct aerosol effects on radiation "brightening" in the United States. Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau, GERMANY, 15: 12193-12209, (2015).

The CMAQ Model Outputs data asset includes current and projected future levels of ambient concentrations and deposition to support regulatory impact analyses.