Evaluation of near surface ozone and particulate matter in air quality simulations driven by dynamically downscaled historical meteorological fields

Metadata Updated: February 13, 2019

This dataset supports the modeling study of Seltzer et al. (2016) published in Atmospheric Environment. In this study, techniques typically used for future air quality projections are applied to a historical 11-year period to assess the performance of the modeling system when the driving meteorological conditions are obtained using dynamical downscaling of coarse-scale fields without correcting toward higher resolution observations. The Weather Research and Forecasting model and the Community Multiscale Air Quality model are used to simulate regional climate and air quality over the contiguous United States for 2000-2010. The air quality simulations for that historical period are then compared to observations from four national networks. Comparisons are drawn between defined performance metrics and other published modeling results for predicted ozone, fine particulate matter, and speciated fine particulate matter. The results indicate that the historical air quality simulations driven by dynamically downscaled meteorology are typically within defined modeling performance benchmarks and are consistent with results from other published modeling studies using finer-resolution meteorology. This indicates that the regional climate and air quality modeling framework utilized here does not introduce substantial bias, which provides confidence in the method’s use for future air quality projections.

This dataset is associated with the following publication: Seltzer, K., C. Nolte, T. Spero, W. Appel, and J. Xing. Evaluation of near surface ozone and particulate matter in air quality simulations driven by dynamically downscaled historical meteorological fields. ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 138: 42-54, (2016).

Access & Use Information

Public: This dataset is intended for public access and use. License: See this page for license information.

Downloads & Resources

References

http://www.sciencedirect.com/science/journal/aip/13522310

Dates

Metadata Created Date August 24, 2016
Metadata Updated Date February 13, 2019

Metadata Source

Harvested from EPA ScienceHub

Additional Metadata

Resource Type Dataset
Metadata Created Date August 24, 2016
Metadata Updated Date February 13, 2019
Publisher U.S. EPA Office of Research and Development (ORD)
Unique Identifier A-37pz-84
Maintainer
Christopher Nolte
Maintainer Email
Public Access Level public
Bureau Code 020:00
Schema Version https://project-open-data.cio.gov/v1.1/schema
Harvest Object Id 1d5a0d2b-093f-4a3f-9f41-f91f1d8537a0
Harvest Source Id cf9b0004-f9fd-420e-bade-a86839e82acf
Harvest Source Title EPA ScienceHub
License https://pasteur.epa.gov/license/sciencehub-license.html
Data Last Modified 2016-05-26
Program Code 020:094
Publisher Hierarchy U.S. Government > U.S. Environmental Protection Agency > U.S. EPA Office of Research and Development (ORD)
Related Documents http://www.sciencedirect.com/science/journal/aip/13522310
Source Datajson Identifier True
Source Hash 9b2dd4dd08afe3b167cc462eec4b24ac5068c329
Source Schema Version 1.1

Didn't find what you're looking for? Suggest a dataset here.