Comparison of CAMS and CMAQ analyses of surface-level PM2.5 and O3 over the conterminous United States (CONUS)
d315001
<p>In this study, we compare the performance of the analysis time series over the period of August 2020 to December 2021 at EPA AirNow stations for both PM2.5 and O3 from raw Copernicus Atmosphere Monitoring Service (CAMS) reanalyses (CAMS RA Raw), raw CAMS near real-time forecasts (CAMS FC Raw), raw near real-time Community Multi-scale Air Quality (CMAQ) forecasts (CMAQ FC Raw), bias-corrected CAMS forecasts (CAMS FC BC), and bias-corrected CMAQ forecasts (CMAQ FC BC). This 17-month period spans two wildfire seasons, to assess model analysis performance in high-end AQ events. In addition to determining the best-performing gridded product, this process allows us to benchmark the performance of CMAQ forecasts against other global datasets (CAMS reanalysis and forecasts). For both PM2.5 and O3, the bias correction algorithm employed here greatly improved upon the raw model time series, and CMAQ FC BC was the best-performing model analysis time series, having the lowest RMSE, smallest bias error, and largest critical success index at multiple thresholds.</p>
dataset
https://gdex.ucar.edu/datasets/d315001/
protocol: https
name: Dataset Description
description: Related Link
function: information
https://gdex.ucar.edu/datasets/d315001/dataaccess/
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name: Data Access
description: Related Link
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climatologyMeteorologyAtmosphere
dataset
revision
2021-03-30
AirNow > EPA AirNow Program
OPERATIONAL MODELS
revision
2025-10-03
EARTH SCIENCE > ATMOSPHERE > AIR QUALITY > PARTICULATE MATTER (PM 2.5)
EARTH SCIENCE > ATMOSPHERE > AIR QUALITY > TROPOSPHERIC OZONE
revision
2025-10-03
2020-08
2021-12
publication
2024-08-26
notPlanned
Creative Commons Attribution 4.0 International License
None
pointOfContact
NSF NCAR Geoscience Data Exchange
name: NSF NCAR Geoscience Data Exchange
description: The Geoscience Data Exchange (GDEX), managed by the Computational and Information Systems Laboratory (CISL) at NSF NCAR, contains a large collection of meteorological, atmospheric composition, and oceanographic observations, and operational and reanalysis model outputs, integrated with NSF NCAR High Performance Compute services to support atmospheric and geosciences research.
function: download
pointOfContact
2025-10-09T01:31:12Z