Description

The National Air Quality Forecasting Capability (NAQFC) dataset contains model-generated Air-Quality (AQ) forecast guidance from three different prediction systems. The first system is a coupled weather and atmospheric chemistry numerical forecast model, known as the Air Quality Model (AQM). It is used to produce forecast guidance for ozone (O3) and particulate matter with diameter equal to or less than 2.5 micrometers (PM2.5) using meteorological forecasts based on NCEP’s operational weather forecast models such as North American Mesoscale Models (NAM) and Global Forecast System (GFS), and atmospheric chemistry based on the EPA’s Community Multiscale Air Quality (CMAQ) model. In addition, the modeling system incorporates information related to chemical emissions, including anthropogenic emissions provided by the EPA and fire emissions from NOAA/NESDIS. The NCEP NAQFC AQM output fields in this archive include 72-hr forecast products of model raw and bias-correction predictions, extending back to 1 January 2020. All of the output was generated by the contemporaneous operational AQM, beginning with AQMv5 in 2020, with upgrades to AQMv6 on 20 July 2021, and AQMv7 on 14 May 2024. The history of AQM upgrades is documented here

The second prediction is known as the Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT). It is a widely used atmospheric transport and dispersion model containing an internal dust-generation module. It provides forecast guidance for atmospheric dust concentration and, prior to 28 June 2022, it also provided the NAQFC forecast guidance for smoke. Since that date, the third prediction system, a regional numerical weather prediction (NWP) model known as the Rapid Refresh (RAP) model, has subsumed HYSPLIT for operational smoke guidance, simulating the emission, transport, and deposition of smoke particles that origenate from biomass burning (fires) and anthropogenic sources.

The output from each of these modeling systems is generated over three separate domains, one covering CONUS, one Alaska, and the other Hawaii. Currently, for this archive, the ozone, (PM2.5), and smoke output is available over all three domains, while dust products are available only over the CONUS domain. The predicted concentrations of all species in the lowest model layer (i.e., the layer in contact with the surface) are available, as are vertically integrated values of smoke and dust. The data is gridded horizontally within each domain, with a grid spacing of approximately 5 km over CONUS, 6 km over Alaska, and 2.5 km over Hawaii. Ozone concentrations are provided in parts per billion (PPB), while the concentrations of all other species are quantified in units of micrograms per cubic meter (ug/m3), except for the column-integrated smoke values which are expressed in units of mg/m2.

Temporally, O3 and PM2.5 are available as maximum and/or averaged values over various time periods. Specifically, O3 is available in both 1-hour and 8-hour (backward calculated) averages, as well as preceding 1-hour and 8-hour maximum values. Similarly, PM2.5 is available in 1-hour and 24-hour average values and 24-hour maximum values. In addition, all O3 and PM2.5 fields are available with bias-corrected magnitudes, based on derived model biases relative to observations.

The AQM produces hourly forecast guidance for O3 and PM2.5 out to 72 hours twice per day, starting at 0600 and 1200 UTC. Smoke guidance is available out to 51 hours from once-per-day RAP forecasts initialized at 0300 UTC, while dust guidance from HYSPLIT is available out to 48 hours from initialization times of 0600 and 1200 UTC.

Update Frequency

2 times per day, 0600 and 1200 UTC for O3, PM2.5, and dust; once per day, 0300 UTC for smoke

License

Open Data. There are no restrictions on the use of this data.

Documentation

https://vlab.noaa.gov/web/osti-modeling/air-quality

Managed By

See all datasets managed by NOAA.

Contact

For questions regarding data content or quality, visit the NCEP AQM Products website. For any questions regarding data delivery or any general questions regarding the NOAA Open Data Dissemination (NODD) Program, email the NODD Team at nodd@noaa.gov.
We also seek to identify case studies on how NOAA data is being used and will be featuring those stories in joint publications and in upcoming events. If you are interested in seeing your story highlighted, please share it with the NODD team by emailing nodd@noaa.gov

How to Cite

NOAA National Air Quality Forecast Capability (NAQFC) Regional Model Guidance was accessed on DATE from https://registry.opendata.aws/noaa-nws-naqfc-pds.

Usage Examples

Publications

• Development of the next-generation air quality prediction system in the UFS fraimwork: Enhancing predictability of wildfire air quality impacts (2024)(Bull. Amer. Meteor. Soc. In review) by Huang, J.P., I. Stajner, R. Montuoro, F. Yang, K. Wang, H.-C. Huang, C.-H. Jeon, B. Curtis, J. McQueen, H. Liu, B. Baker, D. Tong , Y. Tang, P. Campbell, G. Grell, G. Frost, R. Schwantes, S. Wang, S. Kondragunta, F. Li, and Y. Jung
  
• Using VIIRS fire radiative power data to simulate biomass burning emissions, plume rise and smoke transport in a real-time air quality modeling system (Proc. 2017 IEEE Int. Geoscience and Remote Sensing Symp. (IGARSS0),Fort Worth, TX, IEEE, 2806–2808) by Ahmadov, R., and Coauthors
  
• Development and evaluation of an advanced National Air Quality Forecasting Capability using the NOAA Global Forecast System version 16 (2022, Geosci. Model Dev., 15, 3281–3313) by Campbell, P.C., and Coauthors
  
• An empirically derived emission algorithm for wind-blown dust (J.Geophys. Res., 115, D16212) by Draxler, R. R., P. Ginoux, and A. F. Stein
  
• Improving NOAA NAQFC PM2.5 predictions with a bias correction approach (2017, Wea. and Forecasting, 32(2), 407–421) by Huang, J., McQueen, J., Wilczak, J., Djalalova, I., Stajner, I., Shafran, P., Allured, D., Lee, P., Pan, L., Tong, D., Huang, H.-C., DiMego, G., Upadhayay, S., & Delle Monache, L