edu.ucar.opensky::articles:43528 UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact 2025-12-24T17:49:42.502610 ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data ISO 19115-2:2009(E) https://n2t.net/ark:/85065/d7m90f23 https://doi.org/10.5065/cfya-4g50 https Related Dataset #1 CONUS air quality reanalysis dataset (2005-2018) https://doi.org/10.5065/D6RX99HX https Related Service #1 Cheyenne: SGI ICE XA Cluster A long-term high-resolution air quality reanalysis with a public-facing air quality dashboard over the Contiguous United States (CONUS) 2025-05-07T00:00:00Z publication https://n2t.net/ark:/85065/d7m90f23 https://doi.org/10.5194/essd-17-1807-2025 Kumar, Rajesh author Bhardwaj, P. author He, Cenlin author Boehnert, Jennifer M R author Lacey, Forrest author Alessandrini, Stefano author Sampson, K. author Casali, Matthew author Swerdlin, Scott P. author Wilhelmi, Olga author Pfister, Gabriele author Gaubert, Benjamin author Worden, Helen M. author UCAR/NCAR - Library publisher We present a 14-year, 12 km, hourly air quality dataset (https://doi.org/10.5065/cfya-4g50, Kumar and He, 2023) created by assimilating satellite observations of aerosol optical depth (AOD) and carbon monoxide (CO) in an air quality model to fill gaps in the contiguous United States (CONUS) air quality monitoring network and help air quality managers understand long-term changes in county-level air quality. Specifically, we assimilate the Moderate Resolution Imaging Spectroradiometer (MODIS) AOD and the Measurement of Pollution in the Troposphere (MOPITT) CO observations in the Community Multiscale Air Quality Model (CMAQ) every day from 1 January 2005 to 31 December 2018 to produce this dataset. Meteorological fields simulated with the Weather Research and Forecasting (WRF) model are used to drive CMAQ offline and to generate meteorology-dependent anthropogenic emissions. Both the weather and air quality (surface fine particulate matter (PM2.5) and ozone) simulations are subjected to a comprehensive evaluation against multi-platform observations to establish the credibility of our dataset and characterize its uncertainties. We show that our dataset captures regional hourly, seasonal, and interannual variability in meteorology very well across the CONUS. The correlation coefficient between the observed and simulated surface ozone and PM2.5 concentrations for different regions defined by the Environmental Protection Agency (EPA) across the CONUS are 0.77–0.91 and 0.49–0.79, respectively. The mean bias and root-mean-square error for modeled ozone are 3.7–6.8 and 7–9 ppbv, respectively, while the corresponding values for PM2.5 are −0.9–5.6 and 3.0–8.3 µg m−3, respectively. We estimate that the annual CONUS-averaged maximum daily 8 h average (MDA8) ozone and PM2.5 trends are −0.30 ppb yr−1 and −0.24 µg m−3 yr−1, respectively. Wintertime MDA8 ozone shows an increasing but statistically insignificant trend at several sites. We also found a decreasing trend in the 95th percentile of MDA8 ozone but an increasing trend in the 5th percentile. Most of the sites in the Pacific Northwest show an increasing but statistically insignificant trend during summer. An ArcGIS air quality dashboard has been developed to enable easy visualization and interpretation of county-level air quality measures and trends by stakeholders, and a Python-based Streamlit application has been developed to allow the download of the air quality data in simplified text and graphic formats. UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact PDF Text theme Resource Type 2016-01-01T00:00:00Z publication <style type="text/css"></style><span style="font-family:Arial;font-size:10pt;font-style:normal;" data-sheets-root="1">Copyright author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.</span> None eng geoscientificInformation