Articles | Volume 15, issue 13
https://doi.org/10.5194/gmd-15-5337-2022
https://doi.org/10.5194/gmd-15-5337-2022
Model description paper
 | 
13 Jul 2022
Model description paper |  | 13 Jul 2022

Development and evaluation of the Aerosol Forecast Member in the National Center for Environment Prediction (NCEP)'s Global Ensemble Forecast System (GEFS-Aerosols v1)

Li Zhang, Raffaele Montuoro, Stuart A. McKeen, Barry Baker, Partha S. Bhattacharjee, Georg A. Grell, Judy Henderson, Li Pan, Gregory J. Frost, Jeff McQueen, Rick Saylor, Haiqin Li, Ravan Ahmadov, Jun Wang, Ivanka Stajner, Shobha Kondragunta, Xiaoyang Zhang, and Fangjun Li

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Cited articles

Ahmadov, R., Grell, G., James, E., Csiszar, I., Tsidulko, M., Pierce, B., McKeen, S., Benjamin, S., Alexander, C., Pereira, G., Freitas, S., and Goldberg, M.: Using VIIRS Fire Radiative Power data to simulate biomass burning emissions, plume rise and smoke transport in a real-time air quality modeling system, 2017 Ieee International Geoscience and Remote Sensing Symposium, IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2806–2808, https://doi.org/10.1109/IGARSS.2017.8127581, 2017. 
Bauer, S. E., Im, U., Mezuman, K., and Gao, C. Y.: Desert dust, industrialization, and agricultural fires: Health impacts of outdoor air pollution in Africa, J. Geophys. Res.-Atmos., 124, 4104–4120, https://doi.org/10.1029/2018JD029336, 2019. 
Benedetti, A., Morcrette, J.-J., Boucher, O., Dethof, A., Engelen, R. J., Fisher, M., Flentje, H., Huneeus, N., Jones, L., Kaiser, J. W., Kinne, S., Mangold, A., Razinger, M., Simmons, A. J., and Suttie, M.: Aerosol analysis and forecast in the European Centre for Medium-Range Weather Forecasts Integrated Forecast System: 2. Data assimilation, J. Geophys. Res., 114, D13205, https://doi.org/10.1029/2008JD011115, 2009. 
Benedetti, A., Reid, J. S., and Colarco, P. R.: International cooperative for aerosol prediction workshop on aerosol forecast verification, B. Am. Meteorol. Soc., 92, ES48–ES53, https://doi.org/10.1175/BAMS-D-11-00105.1, 2011. 
Bhattacharjee, P. S., Wang, J., Lu, C.-H., and Tallapragada, V.: The implementation of NEMS GFS Aerosol Component (NGAC) Version 2.0 for global multispecies forecasting at NOAA/NCEP – Part 2: Evaluation of aerosol optical thickness, Geosci. Model Dev., 11, 2333–2351, https://doi.org/10.5194/gmd-11-2333-2018, 2018. 
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Short summary
The NOAA’s air quality predictions contribute to protecting lives and health in the US, which requires sustainable development and improvement of forecast systems. GEFS-Aerosols v1 has been developed in a collaboration between the NOAA research laboratories for operational forecast since September 2020 in the NCEP. The predictions demonstrate substantial improvements for both composition and variability of aerosol distributions over those from the former operational system.
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