Articles | Volume 15, issue 21
https://doi.org/10.5194/gmd-15-7977-2022
https://doi.org/10.5194/gmd-15-7977-2022
Model evaluation paper
 | 
07 Nov 2022
Model evaluation paper |  | 07 Nov 2022

Evaluation of the NAQFC driven by the NOAA Global Forecast System (version 16): comparison with the WRF-CMAQ during the summer 2019 FIREX-AQ campaign

Youhua Tang, Patrick C. Campbell, Pius Lee, Rick Saylor, Fanglin Yang, Barry Baker, Daniel Tong, Ariel Stein, Jianping Huang, Ho-Chun Huang, Li Pan, Jeff McQueen, Ivanka Stajner, Jose Tirado-Delgado, Youngsun Jung, Melissa Yang, Ilann Bourgeois, Jeff Peischl, Tom Ryerson, Donald Blake, Joshua Schwarz, Jose-Luis Jimenez, James Crawford, Glenn Diskin, Richard Moore, Johnathan Hair, Greg Huey, Andrew Rollins, Jack Dibb, and Xiaoyang Zhang

Related authors

Updates and evaluation of NOAA’s online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, Raffaele Montuoro, and Robert C. Gilliam
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-107,https://doi.org/10.5194/gmd-2024-107, 2024
Revised manuscript accepted for GMD
Short summary
Impacts of estimated plume rise on PM2.5 exceedance prediction during extreme wildfire events: a comparison of three schemes (Briggs, Freitas, and Sofiev)
Yunyao Li, Daniel Tong, Siqi Ma, Saulo R. Freitas, Ravan Ahmadov, Mikhail Sofiev, Xiaoyang Zhang, Shobha Kondragunta, Ralph Kahn, Youhua Tang, Barry Baker, Patrick Campbell, Rick Saylor, Georg Grell, and Fangjun Li
Atmos. Chem. Phys., 23, 3083–3101, https://doi.org/10.5194/acp-23-3083-2023,https://doi.org/10.5194/acp-23-3083-2023, 2023
Short summary
Development and evaluation of an advanced National Air Quality Forecasting Capability using the NOAA Global Forecast System version 16
Patrick C. Campbell, Youhua Tang, Pius Lee, Barry Baker, Daniel Tong, Rick Saylor, Ariel Stein, Jianping Huang, Ho-Chun Huang, Edward Strobach, Jeff McQueen, Li Pan, Ivanka Stajner, Jamese Sims, Jose Tirado-Delgado, Youngsun Jung, Fanglin Yang, Tanya L. Spero, and Robert C. Gilliam
Geosci. Model Dev., 15, 3281–3313, https://doi.org/10.5194/gmd-15-3281-2022,https://doi.org/10.5194/gmd-15-3281-2022, 2022
Short summary
Improving predictability of high-ozone episodes through dynamic boundary conditions, emission refresh and chemical data assimilation during the Long Island Sound Tropospheric Ozone Study (LISTOS) field campaign
Siqi Ma, Daniel Tong, Lok Lamsal, Julian Wang, Xuelei Zhang, Youhua Tang, Rick Saylor, Tianfeng Chai, Pius Lee, Patrick Campbell, Barry Baker, Shobha Kondragunta, Laura Judd, Timothy A. Berkoff, Scott J. Janz, and Ivanka Stajner
Atmos. Chem. Phys., 21, 16531–16553, https://doi.org/10.5194/acp-21-16531-2021,https://doi.org/10.5194/acp-21-16531-2021, 2021
Short summary
Evaluation of the offline-coupled GFSv15–FV3–CMAQv5.0.2 in support of the next-generation National Air Quality Forecast Capability over the contiguous United States
Xiaoyang Chen, Yang Zhang, Kai Wang, Daniel Tong, Pius Lee, Youhua Tang, Jianping Huang, Patrick C. Campbell, Jeff Mcqueen, Havala O. T. Pye, Benjamin N. Murphy, and Daiwen Kang
Geosci. Model Dev., 14, 3969–3993, https://doi.org/10.5194/gmd-14-3969-2021,https://doi.org/10.5194/gmd-14-3969-2021, 2021
Short summary

Related subject area

Atmospheric sciences
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025,https://doi.org/10.5194/gmd-18-621-2025, 2025
Short summary
Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025,https://doi.org/10.5194/gmd-18-529-2025, 2025
Short summary
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025,https://doi.org/10.5194/gmd-18-483-2025, 2025
Short summary
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025,https://doi.org/10.5194/gmd-18-433-2025, 2025
Short summary
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025,https://doi.org/10.5194/gmd-18-405-2025, 2025
Short summary

Cited articles

Arakawa, A. and Lamb, V.: Computational design of the basic dynamical processes of the UCLA general circulation model, Meth. Comput. Phys., 17, 173–265, 1977. 
Baker, K. R., Woody, M. C., Tonnesen, G. S., Hutzell, W., Pye, H. O. T., Beaver, M. R., Pouliot, G., and Pierce, T.: Contribution of regional-scale fire events to ozone and PM2.5 air quality estimated by photochemical modeling approaches, Atmos. Environ., 140, 539–554, https://doi.org/10.1016/j.atmosenv.2016.06.032, 2016. 
Briggs, G. A.: A Plume Rise Model Compared with Observations, Journal of the Air Pollution Control Association, 15, 433–438, https://doi.org/10.1080/00022470.1965.10468404, 1965. 
Byun, D. and Schere, K. L.: Review of the governing equations, computational algorithms, and other components of the Models-3 Community Multiscale Air Quality (CMAQ) modeling system, Appl. Mech. Rev., 59, 51–77, https://doi.org/10.1115/1.2128636, 2006. 
Download
Short summary
This paper compares two meteorological datasets for driving a regional air quality model: a regional meteorological model using WRF (WRF-CMAQ) and direct interpolation from an operational global model (GFS-CMAQ). In the comparison with surface measurements and aircraft data in summer 2019, these two methods show mixed performance depending on the corresponding meteorological settings. Direct interpolation is found to be a viable method to drive air quality models.
Share