The HYSPLIT-based Smoke Forecasting System

The NOAA Smoke Forecasting System integrates the NOAA National Environmental Satellite, Data and Information Service’s satellite information on the location of wildfires with NOAA National Weather Service inputs from the North American Mesoscale model and smoke dispersion simulations from the NOAA ARL HYSPLIT model to produce a daily 48-hour prediction of smoke transport and concentration. The model also incorporates U.S. Forest Service estimates for wildfire smoke emissions based on vegetation cover. This system is intended as guidance to air quality forecasters and the public for fine particulate matter emitted from large wildfires and agricultural burning which can elevate particulate concentrations to unhealthful levels.

ARL is developing the HYSPLIT-based Emissions Inverse Modeling System (HEIMS) to estimate wildfire emissions from the transport and dispersion of smoke plumes inferred from NOAA GOES satellite observations. HEIMS uses the smoke transport patterns captured by geostationary satellites with a high temporal resolution as a constraint under a general four-dimensional variational (4D-Var) data assimilation scheme. The model combines information from NOAA ARL, NOAA NESDIS and the US Forest Service to produce updated fire emissions. The ARL-developed HYSPLIT is the core engine for HEIMS, and products are intended for future use in the operational smoke forecast system.

Video published on YouTube Jun 29, 2012 by NOAA Visualizationsthis link opens in a new window




Papers, Posters, and Presentations

Inverse modeling of fire emissions constrained by smoke plume transport using HYSPLIT dispersion model and geostationary observations. Kim, H. C., Chai, T., Stein, A., and Kondragunta (2020), S. Atmos. Chem. Phys., 20, 10259–10277, https://doi.org/10.5194/acp-20-10259-2020

Ensemble PM2.5 Forecasting during the 2018 Camp Fire Event Using the HYSPLIT Transport and Dispersion Model. Li, Y., Tong, D. Q., Ngan, F., Cohen, M. D., Stein, A. F., Kondragunta, S., et al. (2020). Ensemble PM2.5 forecasting during the 2018 Camp Fire event using the HYSPLIT transport and dispersion model. Journal of Geophysical Research: Atmospheres, 125, e2020JD032768. https://doi.org/10.1029/2020JD032768

Evaluating a fire smoke simulation algorithm in the National Air Quality Forecast Capability (NAQFC) by using multiple observation data sets during the Southeast Nexus (SENEX) field campaign. Pan, L., Kim, H., Lee, P., Saylor, R., Tang, Y., Tong, D., Baker, B., Kondragunta, S., Xu, C., Ruminski, M. G., Chen, W., Mcqueen, J., and Stajner, I.: Geosci. Model Dev., 13, 2169–2184, https://doi.org/10.5194/gmd-13-2169-2020

Description and Verification of the NOAA Smoke Forecasting System: The 2007 Fire Season, Rolph, G.D; Draxler, R. R.; Stein, A.F.; Taylor, A; Ruminski, M.G.; Kondragunta, S.; Zeng, J,; Huang, H.; Manikin, G.; McQueen, J.T.; Davidson, P.M., Weather and Forecasting, *24, *361-378, 2009.  https://doi.org/10.1175/2008WAF2222165.1

Verification of the NOAA Smoke Forecasting System: Model Sensitivity to the Injection Height, Stein, A.F.; Rolph, G.D.; Draxler, R.R.; Stunder, B.; Ruminski, M.G., Weather and Forecasting, *24*, 379-394, 2009 https://doi.org/10.1175/2008WAF2222166.1

Regional real-time smoke prediction systems, Susan O.Neill, N. Larkin, J. Hoadley, G. Mills, J. Vaughn, R.Draxler, G.Rolph, M. Ruminski, and S. Ferguson, Wildland Fires and Air Pollution, A. Bytnerowicz et al., Eds., Developments in Environmental Science Series, Vol. 8, Elsevier, 499-534. https://www.fs.usda.gov/treesearch/pubs/34280

Use of Environmental Satellite Imagery for Smoke Depiction and Transport Model Initialization, Mark Ruminski, Shobha Kondragunta, Roland Draxler and Glenn Rolph, 16th International Emission Inventory Conference, Raleigh, North Carolina (5/07).

Recent Changes to the Hazard Mapping System, Mark Ruminski, Shobha Kondragunta, Roland Draxler and Jian Zeng, 15th International Emission Inventory Conference, New Orleans, Louisiana (5/06) Paper: ftp://satepsanone.nesdis.noaa.gov/Publications/EPA_msy-conf.pdf