R script: ensemble_rrf_sigma_vs_mean_play.R Data: ensemble_mean_sigma_rrf_allgrids_epismax_new_13runs.csv Plot: boxplot_ensemble_rrf_sigma_vs_mean_nowater_new_13runs_epimax.pdf. 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).

Fortran/NCARgraphics program to compute and plot RRF mean and variability:map_rrf_variability_13runs_epimax.f Ioapi files needed by Fortran/NCARGraphics code: CMAQ.CONC.SREF.June2011.New.13runs.o3_8hrdm CMAQ.CONC.SREF.June2011.N50V25.New.13runs.o3_8hrdm GRIDCRO2D_060607 Plotting routines map_rrf_mean_sigma_ne_13runs_epimax.ps map_rrf_mean_sigma_ne_13runs_epimax.ncgm. 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).

Fortran/NCARgraphics program to compute and plot RRF mean and variability:map_rrf_variability_13runs_epimax.f Ioapi files needed by Fortran/NCARGraphics code: CMAQ.CONC.SREF.June2011.New.13runs.o3_8hrdm CMAQ.CONC.SREF.June2011.N50V25.New.13runs.o3_8hrdm GRIDCRO2D_060607 Plotting routines map_rrf_mean_sigma_ne_13runs_epimax.ps map_rrf_mean_sigma_ne_13runs_epimax.ncgm. 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).

R script for the reproduction of Figure6. This script accesses archived CMAQ and WRF model output on US EPA's HPC sol computer system and plots forward trajectories and ozone concentrations from major cities in the US. 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).

Two files provided. The ENS.tar file contains text data files (*.csv) used to create Figure 7 and Figure 8. The Figure7.txt is an R script that reads these files and generates the plots for various cities including the four published in Figure 7 and Figure 8. 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).

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).

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).

ACONC files containing simulated ozone and PM2.5 fields that were used to create the model difference plots shown in the journal article. This dataset is associated with the following publication: Appel, W., S. Napelenok, K. Foley, H. Pye, C. Hogrefe, D. Luecken, J. Bash, S. Roselle, J. Pleim, H. Foroutan, B. Hutzell, G. Pouliot, G. Sarwar, K. Fahey, B. Gantt, D. Kang, R. Mathur, D. Schwede, T. Spero, D. Wong, J. Young, and N. Heath. Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1. Geoscientific Model Development. Copernicus Publications, Katlenburg-Lindau, GERMANY, 10: 1703-1732, (2017).

ACONC files containing simulated ozone and PM2.5 fields that were used to create the model difference plots shown in the journal article. This dataset is associated with the following publication: Appel, W., S. Napelenok, K. Foley, H. Pye, C. Hogrefe, D. Luecken, J. Bash, S. Roselle, J. Pleim, H. Foroutan, B. Hutzell, G. Pouliot, G. Sarwar, K. Fahey, B. Gantt, D. Kang, R. Mathur, D. Schwede, T. Spero, D. Wong, J. Young, and N. Heath. Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1. Geoscientific Model Development. Copernicus Publications, Katlenburg-Lindau, GERMANY, 10: 1703-1732, (2017).

Files containing daily maximum 8-hr ozone mixing ratio observations and WRF/CMAQ simulations used in the analysis presented in the manuscript “Dynamic Evaluation of Two Decades of WRF-CMAQ Ozone Simulations over the Contiguous United States”. This dataset is associated with the following publication: Astitha, M., H. Luo, S.T. Rao, C. Hogrefe, R. Mathur, and N. Kumar. Dynamic evaluation of two decades of WRF-CMAQ ozone simulations over the contiguous United States. ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 164: 102-116, (2017).