Assessment of WRF/Chem Simulated Vertical Distributions of Particulate Matter from the 2009 Minto Flats South Wildfire in Interior Alaska by CALIPSO Total Backscatter and Depolarization Measurements


This feasibility study examined whether total backscatter and depolarization measurements from Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) in combination with sparse surface meteorological data and other information permitted qualitative assessment of simulated vertical and horizontal distributions of aerosols from wildfires over Interior Alaska. Comparisons between co-located WRF/Chem cross-sections and CALIPSO curtains showed temporal and spatial differences in smoke-plume height above ground, vertical and horizontal extension. Simple estimates of contributions of errors and processes elucidated that the different spatial and temporal resolution of model grid-cells and the lidar scan could provide offsets of the magnitude found in the comparison. The overestimation of 10 m wind speeds by on average 1.33 m·s-1 contributed to the offset. Energy estimates suggested that the energy needed for permafrost thawing may contribute to discrepancies between simulated and CALIPSO indicated plume height. A sensitivity study with lower emission rates showed similar features. The study demonstrated that use of CALIPSO data in combination with data from other sources than air-quality networks could serve for identification of potential model shortcomings by assessment of magnitudes of error and process impacts.

Share and Cite:

Madden, J. , Mölders, N. and Sassen, K. (2015) Assessment of WRF/Chem Simulated Vertical Distributions of Particulate Matter from the 2009 Minto Flats South Wildfire in Interior Alaska by CALIPSO Total Backscatter and Depolarization Measurements. Open Journal of Air Pollution, 4, 119-138. doi: 10.4236/ojap.2015.43012.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Moore, D., Copes, R., Fisk, R., Joy, R., Chan, K. and Brauer, M. (2006) Population Health Effects of Air Quality Changes Due to Forest Fires in British Columbia in 2003: Estimates from Physician-Visit Billing Data. Canadian Journal of Public Health, 97, 105-108.
[2] Dominici, F., Peng, R.D., Bell, M.L., Pham, L., McDermott, A., Zeger, S.L. and Samet, J.M. (2006) Fine Particulate Air Pollution and Hospital Admission for Cardiovascular and Respiratory Diseases. Journal of the American Medical Association, 295, 1127-1134.
[3] Mott, J.A., Meyer, P., Mannino, D., Redd, S.C., Smith, E.M., Gotway-Crawford, C. and Chase, E. (2002) Wildland Forest Fire Smoke: Health Effects and Intervention Evaluation, Hoopa, California, 1999. Western Journal of Medicine, 176, 157-162.
[4] Simpson, C.C., Pearce, H.G., Sturman, A.P. and Zawar-Reza, P. (2013) Verification of WRF Modelled Fire Weather in the 2009-10 New Zealand Fire Season. International Journal of Wildland Fire, 23, 34-45.
[5] Atmospheric Science Data Center (2006) CALIPSO Quality Statements Lidar Level 1B Profile Products. Version Release 3.00.
[6] Winker, D.M., Hunt, W.H. and McGill, M.J. (2007) Initial Performance Assessment of CALIOP. Geophysical Research Letters, 34.
[7] Mishchenko, M.I. and Sassen, K. (1998) Depolarization of Lidar Returns by Small Ice Crystals: An Application to Contrails. Geophysical Research Letters, 25, 309-312.
[8] Sassen, K. (2000) Lidar Backscatter Depolarization Technique for Cloud and Aerosol Research. In: Mishchenko, M.I., Hovenier, J.W. and Travis, L.D., Eds., Light Scattering by Nonspherical Particles, Academic Press, San Diego, 393-416.
[9] Chepfer, H., Bony, S., Winker, D., Chiriaco, M., Dufresne, J.-L. and Sèze, G. (2008) Use of CALIPSO Lidar Observations to Evaluate the Cloudiness Simulated by a Climate Model. Geophysical Research Letters, 35, Article ID: L15704.
[10] Yu, H.B., Chin, M., Winker, D.M., Omar, A.H., Liu, Z.Y., Kittaka, C. and Diehl, T. (2010) Global View of Aerosol Vertical Distributions from CALIPSO Lidar Measurements and Gocart Simulations: Regional and Seasonal Variations. Journal of Geophysical Research, 115, Article ID: D00H30.
[11] Sodemann, H., Pommier, M., Arnold, S.R., Monks, S.A., Stebel, K., Burkhart, J.F., et al. (2011) Episodes of Cross-Polar Transport in the Arctic Troposphere during July 2008 as Seen from Models, Satellite, and Aircraft Observations. Atmospheric Chemistry and Physics, 11, 3631-3651.
[12] Wang, J., Ge, C., Yang, Z.F., Hyer, E.J., Reid, J.S., Chew, B.-N., et al. (2013) Mesoscale Modeling of Smoke Transport over the Southeast Asian Maritime Continent: Interplay of Sea Breeze, Trade Wind, Typhoon, and Topography. Atmospheric Research, 122, 486-503.
[13] Skamarock, W.C., Klemp, J.B., Dudhia, J., Gill, D.O., Barker, D.M., Duda, M.G., et al. (2008) A Description of the Advanced Research WRF Version 3. NCAR/TN, 125 p.
[14] Peckham, S.E., Fast, J., Schmitz, R., Salzmann, M. and Freitas, S. (2011) WRF/Chem Version 3.3 User’s Guide, 96 p.
[15] Molders, N., Tran, H.N.Q., Quinn, P., Sassen, K., Shaw, G.E. and Kramm, G. (2011) Assessment of WRF/Chem to Capture Sub-Arctic Boundary Layer Characteristics during Low Solar Irradiation Using Radiosonde, Sodar, and Station Data. Atmospheric Pollution Research, 2, 283-299.
[16] Grell, G.A., Freitas, S.R., Stuefer, M. and Fast, J.D. (2011) Inclusion of Biomass Burning in WRF-Chem: Impact on Wildfires on Weather Forecasts. Atmospheric Chemistry and Physics, 11, 5289-5303.
[17] Barnard, J., Fast, J., Paredes-Miranda, G., Arnott, W. and Laskin, A. (2010) Technical Note: Evaluation of the WRF-Chem “Aerosol Chemical to Aerosol Optical Properties” Module Using Data from the MILAGRO Campaign. Atmospheric Chemistry and Physics, 10, 7325-7340.
[18] Grell, G.A., Peckham, S.E., Schmitz, R., McKeen, S.A., Frost, G., Skamarock, W.C. and Eder, B. (2005) Fully Coupled “Online” Chemistry within the WRF Model. Atmospheric Environment, 39, 6957-6975.
[19] Lin, Y.-L., Rarley, R.D. and Orville, H.D. (1983) Bulk Parameterization of the Snow Field in a Cloud Model. Journal of Applied Meteorology, 22, 1065-1092.<1065:BPOTSF>2.0.CO;2
[20] Grell, G.A. and Dévényi, D.A. (2002) Generalized Approach to Parameterizing Convection Combining Ensemble and Data Assimilation Techniques. Geophysical Research Letters, 29, 38-1-38-4.
[21] Chou, M.-D. and Suarez, M.J. (1994) An Efficient Thermal Infrared Radiation Parameterization for Use in General Circulation Models. Report, 85 p.
[22] Mlawer, E.J., Taubman, S.J., Brown, P.D., Iacono, M.J. and Clough, S.A. (1997) Radiative Transfer for Inhomogeneous Atmospheres: RRTM, a Validated Correlated-K Model for the Longwave. Journal of Geophysical Research, 102, 16663-16682.
[23] Mellor, G.L. and Yamada, T. (1982) Development of a Turbulence Closure Model for Geophysical Fluid Problems. Reviews of Geophysics Space Physics, 20, 851-875.
[24] Janjic, Z.I. (2002) Nonsingular Implementation of the Mellor-Yamada Level 2.5 Scheme in the NCEP Meso Model. NCEP Office Note, 61 p.
[25] Smirnova, T.G., Brown, J.M., Benjamin, S.G. and Kim, D. (2000) Parameterization of Cold Season Processes in the Maps Land-Surface Scheme. Journal Geophysical Research, 105, 4077-4086.
[26] Stockwell, W.R., Middleton, P., Chang, J.S. and Tang, X. (1990) The Second-Generation Regional Acid Deposition Model Chemical Mechanism for Regional Air Quality Modeling. Journal Geophysical Research, 95, 16343-16367.
[27] Madronich, S. (1987) Photodissociation in the Atmosphere, 1, Actinic Flux and the Effects of Ground Reflections and Clouds. Journal Geophysical Research, 92, 9740-9752.
[28] Ackermann, I.J., Hass, H., Memmesheimer, M., Ebel, A., Binkowski, F.S. and Shankar, U. (1998) Modal Aerosol Dynamics Model for Europe: Development and First Applications. Atmospheric Environment, 32, 2981-2299.
[29] Schell, B., Ackermann, I.J., Hass, H., Binkowski, F.S. and Ebel, A. (2001) Modeling the Formation of Secondary Organic Aerosol within a Comprehensive Air Quality Model System. Journal of Geophysical Research, 106, 28275-28293.
[30] Wesely, M.L. (1989) Parameterization of Surface Resistances to Gaseous Dry Deposition in Regional-Scale Numerical Models. Atmospheric Environment, 23, 1293-1304.
[31] European Commission (2010) Emission Database for Global Atmospheric Research (Edgar), Release Version 4.1.
[32] Tran, H.N.Q. (2012) Analysis of Model and Observation Data for the Development of a Public PM2.5 Air-Quality Advisories Tool (AQUAT). Dissertation, Department of Atmospheri Sciences, University of Alaska Fairbanks, Fairbanks, 309 p.
[33] Guenther, A. (1997) Seasonal and Spatial Variations in Natural Volatile Organic Compound Emissions. Ecological Applications, 7, 34-45.[0034:SASVIN]2.0.CO;2
[34] Simpson, D., Guenther, A., Hewitt, C.N. and Steinbrecher, R. (1995) Biogenic Emissions in Europe 1. Estimates and Uncertainties. Journal Geophysical Research, 100, 22875-22890.
[35] Freitas, S.R., Longo, K.M., Silva Dias, M.A.F., Silva Dias, P.L., Chatfield, R., Prins, E., et al. (2005) Monitoring the Transport of Biomass Burning Emissions in South America. Environmental Fluid Mechanics, 5, 135-167.
[36] Freitas, S.R., Longo, K.M., Chatfield, R., Latham, D., Silva Dias, M.A.F., Andreae, M.O., et al. (2007) Including the Sub-Grid Scale Plume Rise of Vegetation Fires in Low Resolution Atmospheric Transport Models. Atmospheric Chemistry and Physics, 7, 3385-3398.
[37] Longo, K.M., Freitas, S.R., Andreae, M.O., Setzer, A., Prins, E. and Artaxo, P. (2010) The Coupled Aerosol and Tracer Transport Model to the Brazilian Developments on the Regional Atmospheric Modeling System (CATT-BRAMS)—Part 2: Model Sensitivity to the Biomass Burning Inventories. Atmospheric Chemistry and Physics, 10, 5785-5795.
[38] Sestini, M., Reimer, E., Valeriano, D., et al. (2003) Mapa De Cobertura Da Terra Da Amazonia Legal Para Usa Em Modelos Meteorológicos. Anais XI Simpósio Brasileiro de Sensoriamento Remoto, 2901-2906.
[39] Olson, J., Watts, S. and Allison, L.J. (2000) Major World Ecosystem Complexes Ranked by Carbon in Live Vegetation: A Database (Revised November 2000). Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, Oak Ridge.
[40] Andreae, M.O. and Merlet, P. (2001) Emission of Trace Gases and Aerosols from Biomass Burning. Global Biogeochemical Cycles, 15, 955-966.
[41] Ward, D.E., Susott, R.A., Kaufman, J.B., Babbitt, R.E., Cummings, D.L., Dias, B., et al. (2002) Smoke and Fire Characteristics for Cerrado and Deforestation Burns in Brazil: Base-B Experiment. Journal of Geophysical Research, 97, 14601-14619.
[42] Freitas, S.R., Longo, K.M. and Andreae, M.O. (2006) Impact of Including the Plume Rise of Vegetation Fires in Numerical Simulations of Associated Atmospheric Pollutants. Geophysical Research Letters, 33, Article ID: L17808.
[43] Department of Commerce (2000) NCEP FNL Operational Model Global Tropospheric Analyses, Continuing from July 1999. Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory.
[44] Molders, N., Gende, S. and Pirhalla, M.A. (2013) Assessment of Cruise-Ship Activity Influences on Emissions, Air Quality, and Visibility in Glacier Bay National Park. Atmospheric Pollution Research, 4, 435-445.
[45] Leelasakultum, K., Molders, N., Tran, H.N.Q. and Grell, G.A. (2012) Potential Impacts of the Introduction of Low Sulfur Fuel on PM2.5-Concentrations at Breathing Level in a Subarctic City. Advances in Meteorology, 2012, Article ID: 427078.
[46] Sassen, K. (1991) The Polarization Lidar Technique for Cloud Research: A Review and Current Assessment. Bulletin of the American Meteorological Society, 72, 1848-1866.<1848:TPLTFC>2.0.CO;2
[47] Sassen, K. (2005) Dusty Ice Clouds over Alaska. Nature, 434, 7032, 456-456.
[48] Sassen, K. (2008) Boreal Tree Pollen Sensed by Polarization Lidar: Depolarizing Biogenic Chaff. Geophysical Research Letters, 35, Article ID: L18810.
[49] Martins, J.V., Hobbs, P.V., Weiss, R.E. and Artaxo, P. (1998) Sphericity and Morphology of Smoke Particles from Biomass Burning in Brazil. Journal of Geophysical Research, 103, 32051-32057.
[50] Murayama, T., Müller, D., Wada, K., Shimizu, A., Sekiguchi, M. and Tsukamoto, T. (2004) Characterization of Asian Dust and Siberian Smoke with Multi-Wavelength Raman Lidar over Tokyo, Japan in Spring 2003. Geophysical Research Letters, 31, Article ID: L23103.
[51] Sassen, K. (2008) Identifying Atmospheric Aerosols with Polarization Lidar. In: Kim, Y.J. and Platt, U., Eds., Advanced Environmental Modeling, Springer Science + Business Media Inc., New York, 136-142.
[52] Lee, C.H., Kim, J.H., Park, C.B., et al. (2004) Continuous Measurements of Smoke of Russian Forest Fire by 532/1064 nm Mie Scattering Lidar at Suwon, Korea. Proceedings of the 22nd International Laser Radar Conference, Matera, 12-16 July 2004, 535-538.
[53] Vautard, R.M.M., Solazzo, E., Gilliam, R.C., Matthias, V., Bianconi, R.C.C., Ferreira, J., Geyer, B., Hansen, A.B., Jericevic, A., Prank, M., et al. (2012) Evaluation of the Meteorological Forcing Used for the Air Quality Model Evaluation International Initiative (AQMEII) Air Quality Simulations. Atmospheric Environment, 53, 15-37.
[54] Menut, L., Tripathi, O.P., Colette, A., Vautard, R., Flaounas, E. and Bessagnet, B. (2013) Evaluation of Regional Climate Simulations for Air Quality Modelling Purposes. Climate Dynamics, 40, 2515-2533.
[55] PaiMazumder, D., Henderson, D. and Molders, N. (2012) Evaluation of WRF-Forecasts over Siberia: Air Mass Formation, Clouds and Precipitation. The Open Atmospheric Science Journal, 6, 93-110.
[56] Madden, J.M. (2014) Using WRF/Chem, In-Situ Observations, and CALIPSO Data to Simulate Smoke Plume Signatures on High-Latitude Pixels. Master’s Thesis, Department of Atmospheric Sciences, University of Alaska Fairbanks, Fairbanks, 106 p.
[57] Molders, N. (2008) Suitability of the Weather Research and Forecasting (WRF) Model to Predict the June 2005 Fire Weather for Interior Alaska. Weather and Forecasting, 23, 953-973.
[58] Hines, K.M., Bromwich, D.H., Bai, L.-S., Barlage, M. and Slater, A.G. (2011) Development and Testing of Polar WRF. Part III: Arctic Land. Journal of Climate, 24, 26-48.
[59] Hines, K.M. and Bromwich, D.H. (2008) Development and Testing of Polar Weather Research and Forecasting (WRF) Model. Part I: Greenland Ice Sheet Meteorology. Monthly Weather Review, 136, 1971-1989.
[60] Steeneveld, G.J., Ronda, R.J. and Holtslag, A.A.M. (2015) The Challenge of Forecasting the Onset and Development of Radiation Fog Using Mesoscale Atmospheric Models. Boundary-Layer Meteorology, 154, 265-289.
[61] Pirhalla, M.A., Gende, S. and Molders, N. (2014) Fate of Particulate Matter from Cruise-Ship Emissions in Glacier Bay during the 2008 Tourist Season. Journal of Environmental Protection, 4, 1235-1254.
[62] Molders, N. and Kramm, G. (2007) Influence of Wildfire Induced Land-Cover Changes on Clouds and Precipitation in Interior Alaska—A Case Study. Atmospheric Research, 84, 142-168.
[63] Hinzman, L.D., Fukuda, M., Sandberg, D.V., Chapin III, F.S. and Dash, D. (2003) FROSTFIRE: An Experimental Approach to Predicting the Climate Feedbacks from Changing Boreal Fire Regime. Journal of Geophysical Research, 108, 8153.
[64] Molders, N. (2011) Land-Use and Land-Cover Changes—Impact on Climate and Air Quality. Springer, Heidelberg, 193 p.
[65] Seinfeld, J.H. and Pandis, S.N. (1997) Atmospheric Chemistry and Physics, from Air Pollution to Climate Change. John Wiley & Sons, New York, 1326 p.
[66] Yarker, M.B., PaiMazumder, D., Cahill, C.F., Dehn, J., Prakash, A. and Molders, N. (2010) Theoretical Investigations on Potential Impacts of High-Latitude Volcanic Emissions of Heat, Aerosols and Water Vapor and Their Interactions on Clouds and Precipitation. The Open Atmospheric Science Journal, 4, 24-44.
[67] Ruiz, J.J., Saulo, C. and Nogués-Paegle, J. (2010) WRF Model Sensitivity to Choice of Parameterization over South America: Validation against Surface Variables. Monthly Weather Review, 138, 3342-3355.
[68] Zhang, J.L., Campbell, J.R., Reid, J.S., Westphal, D.L., Baker, N.L., Campbell, W.F. and Hyer, E.J. (2011) Evaluating the Impact of Assimilating CALIOP-Derived Aerosol Extinction Profiles on a Global Mass Transport Model. Geophysical Research Letters, 38, Article ID: L14801.

Copyright © 2023 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.