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Datasets for figures and tables
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).
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WRF-CMAQ simulations of Aerosol Direct Effects
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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).
WRF and CMAQ Model Output
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WRF and CMAQ model output for July 2011. This dataset is not publicly accessible because: The files are too large. It can be accessed through the following means: The data can be accessed through NCC's tape archival storage system (ASM). Format: WRF and CMAQ model output for July 2011. This dataset is associated with the following publication: Foroutan, H., and J. Pleim. Improving the simulation of convective dust storms in regional-to-global models. Journal of Advances in Modeling Earth Systems. John Wiley & Sons, Inc., Hoboken, NJ, USA, 9(5): 2046–2060, (2017).
Three-dimensional WRF and CMAQ 2-km simulation output for California for January/February 2013
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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).
CMAQ v5.2 and WRF v3.8.1 model data, meta data and figures
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The data are described in detail in the uploaded file "Science hub metadata.docx". This dataset is associated with the following publication: Zhang, Y., J. Bash, S. Roselle, A. Shatas, A. Repinsky, R. Mathur, C. Hogrefe, J. Piziali, T. Jacobs, and A. Gilliland. Unexpected air quality impacts from implementation of green infrastructure in urban environments: a Kansas City Case Study. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 744(20): 140960, (2020).
Figure 3
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The Figure.tar.gz contains a directory for each WRF ensemble run. In these directories are *.csv files for each meteorology variable examined. These are comma delimited text files that contain statistics for each observation site. Also provided is an R script that reads these files (user would need to change directory pointers) and computes the variability of error and bias of the ensemble at each site and plots these for reproduction of figure 3. This dataset is not publicly accessible because: 30Mb tar, 15 Mb tar.gz. It can be accessed through the following means: On the EPA HPC system sol archive: /asm/grc/JGR_ENSEMBLE_ScienceHub/figure3.tar. Format: tar.gz file of text files that contain the surface meteorology statistics that were used to created Figure 3. Also included is a R script that will allow anyone interested to re-generate the figure. This dataset is associated with the following publication: Gilliam , R., C. Hogrefe , J. Godowitch, S. Napelenok , R. Mathur , and S.T. Rao. Impact of inherent meteorology uncertainty on air quality model predictions. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 120(23): 12,259–12,280, (2015).
Figure 3
공공데이터포털
The Figure.tar.gz contains a directory for each WRF ensemble run. In these directories are *.csv files for each meteorology variable examined. These are comma delimited text files that contain statistics for each observation site. Also provided is an R script that reads these files (user would need to change directory pointers) and computes the variability of error and bias of the ensemble at each site and plots these for reproduction of figure 3. This dataset is not publicly accessible because: 30Mb tar, 15 Mb tar.gz. It can be accessed through the following means: On the EPA HPC system sol archive: /asm/grc/JGR_ENSEMBLE_ScienceHub/figure3.tar. Format: tar.gz file of text files that contain the surface meteorology statistics that were used to created Figure 3. Also included is a R script that will allow anyone interested to re-generate the figure. This dataset is associated with the following publication: Gilliam , R., C. Hogrefe , J. Godowitch, S. Napelenok , R. Mathur , and S.T. Rao. Impact of inherent meteorology uncertainty on air quality model predictions. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 120(23): 12,259–12,280, (2015).
WRF Model Output
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This dataset contains WRF model output. There are three months of data: July 2012, July 2013, and January 2013. For each month, several simulations were made: A control and two lightning assimilation runs using different suppression techniques. For July 2012, and additional simulation was made with a third suppression technique. Please refer to the manuscript for a full description of each simulation. This dataset is not publicly accessible because: The files are too large. It can be accessed through the following means: The data can be accessed through NCC's tape archival storage system (ASM) or by contacting the author. Format: WRF model output for July 2012, July 2013, and January 2013. This dataset is associated with the following publication: Heath, N., J. Pleim, R. Gilliam, and D. Kang. A simple lightning assimilation technique for improving retrospective WRF simulations.. Journal of Advances in Modeling Earth Systems. John Wiley & Sons, Inc., Hoboken, NJ, USA, 8(4): 1806-1824, (2016).
Xing et al JGR2015
공공데이터포털
The data sets are outputs from the WRF-CMAQ modeling system. Typically these files contain a number of meteorological and atmospheric pollutant concentrations on a model grid which is either 2- or 3-dimensional and also in some instances vary with time. This dataset is associated with the following publication: Xing, J., R. Mathur , J. Pleim , C. Hogrefe , C. Gan, D. Wong , C. Wei, and J. Wang. Air pollution and climate response to aerosol direct radiative effects: A modeling study of decadal trends across the northern hemisphere. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 120(33): 12221-12236, (2015).
Xing et al JGR2015
공공데이터포털
The data sets are outputs from the WRF-CMAQ modeling system. Typically these files contain a number of meteorological and atmospheric pollutant concentrations on a model grid which is either 2- or 3-dimensional and also in some instances vary with time. This dataset is associated with the following publication: Xing, J., R. Mathur , J. Pleim , C. Hogrefe , C. Gan, D. Wong , C. Wei, and J. Wang. Air pollution and climate response to aerosol direct radiative effects: A modeling study of decadal trends across the northern hemisphere. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 120(33): 12221-12236, (2015).
WRF-ACI-Paper-1
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Data for all tables and figures are in netCDF format. This dataset is associated with the following publication: Glotfelty, T., K. Alapaty, J. He, P. Hawbecker, X. Song, and G. Zhang. The Weather Research and Forecasting Model with Aerosol–Cloud Interactions (WRF-ACI): Development, Evaluation, and Initial Application. Monthly Weather Review. American Meteorological Society, Boston, MA, USA, 147(5): 1491-1511, (2019).
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