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Outline

Title
Abstract
Chapter 1. Introduction
The Results of On-Line Plume-Rise Implementation
The Improve Data and Oc/Ec Ratio
The Aod Data
The CAM5 Simulation Results
Data
Data and Methods
Land Cover Data
Results
The Model Results
Conclusion
References
All Topics
Environmental Science
Forest Sciences

Wildfires in earth system: Driver, transport and feedback

Profile image of Alex KeAlex Ke

2019

Abstract

Wildfires release large amounts of greenhouse gases, carbonaceous aerosols, and other pollutants, therefore having complex impacts on the earth climate, local weather, and air quality. To study the transport of the wildfire emissions, a plume height dataset has been developed. The resulting dataset from 2002 to 2010 captured well the observed MISR plume height distribution. By adding the plume height dataset in the climate model, the plume-rise enhanced AOD downstream of the wildfire spots by 20 to 50%. Moreover, an online plume rise module for CAM5 has been developed, allowing for the feedbacks of climate/weather on fire plume rise. As an application of this developed plume height dataset, the impact of West Canada wildfires (WCWs) on Northeast United States (NEUS) have been investigated. The observed OC/EC ratios over the NEUS show significant correlations with WCWs burned area since 2001. Detailed analysis and modeling simulations show that the strength of wildfire explains 48% v...

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References (89)

  1. PFTs REFERENCES
  2. Adam, M., Pahlow, M., Kovalev, V. A., Ondov, J. M., Parlange, M. B. and Nair, N.: Aerosol optical characterization by nephelometer and lidar: The Baltimore Supersite experiment during the Canadian forest fire smoke intrusion, J. Geophys. Res. D Atmos., 109(16), 1-15, doi:10.1029/2003JD004047, 2004.
  3. Aleman, J. C., Blarquez, O., Gourlet-Fleury, S., Bremond, L. and Favier, C.: Tree cover in Central Africa: Determinants and sensitivity under contrasted scenarios of global change, Sci. Rep., 7(December 2016), 1-12, doi:10.1038/srep41393, 2017.
  4. Aleman, J. C., Jarzyna, M. A. and Staver, A. C.: Forest extent and deforestation in tropical Africa since 1900, Nat. Ecol. Evol., 2(1), 26-33, doi:10.1038/s41559-017-0406-1, 2018. Allen, R. J., Sherwood, S. C., Norris, J. R. and Zender, C. S.: Recent Northern Hemisphere tropical expansion primarily driven by black carbon and tropospheric ozone, Nature, 485(7398), 350-354, doi:10.1038/nature11097, 2012.
  5. Andela, N. and van der Werf, G. R.: Recent trends in African fires driven by cropland expansion and El Niño to La Niña transition, Nat. Clim. Chang., 4(September), 791-795, doi:10.1038/nclimate2313, 2014a.
  6. Andela, N. and van der Werf, G. R.: Recent trends in African fires driven by cropland expansion and El Niño to La Niña transition, Nat. Clim. Chang., advance on(September), 791-795, doi:10.1038/nclimate2313, 2014b.
  7. Andela, N., Morton, D. C., Giglio, L., Chen, Y., van der Werf, G. R., Kasibhatla, P. S., Defries, R. S., Collatz, G. J., Hantson, S., Kloster, S., Bachelet, D., Forrest, M., Lasslop, G., Li, F., Mangeon, S., Melton, J., Yue, C. and Randerson, J. T.: A human-driven decline in global burned area, Science (80-. )., 356(6345), 1356-1362, doi:10.1126/science.aal4108, 2017.
  8. Andreae, M. O. and Merlet, P.: Emission of trace gases and aerosols from biomass burning, Global Biogeochem. Cycles, 15(4), 955-966, doi:10.1029/2000GB001382, 2001. Arden Pope III, C., Majid, E. and W., D. D.: Fine-Particulate Air Pollution and Life Expectancy in the United States, N. Engl. J. Med., 360(4), 376-386, doi:10.1056/NEJMsa0805646, 2009.
  9. Bates, J. T., Weber, R. J., Abrams, J., Verma, V., Fang, T., Klein, M., Strickland, M. J., Sarnat, S. E., Chang, H. H., Mulholland, J. A., Tolbert, P. E. and Russell, A. G.: Reactive Oxygen Species Generation Linked to Sources of Atmospheric Particulate Matter and Cardiorespiratory Effects, Environ. Sci. Technol., 49(22), 13605-13612, doi:10.1021/acs.est.5b02967, 2015.
  10. Bauer, S. E. and Menon, S.: Aerosol direct, indirect, semidirect, and surface albedo effects from sector contributions based on the IPCC AR5 emissions for preindustrial and present-day conditions, J. Geophys. Res. Atmos., 117(1), 1-15, doi:10.1029/2011JD016816, 2012.
  11. Boucher, O., Randall, D., Artaxo, P., Bretherton, C., Feingold, G., Forster, P., Kerminen, V.-M. V.-M., Kondo, Y., Liao, H., Lohmann, U., Rasch, P., Satheesh, S. K., Sherwood, S., Stevens, B., Zhang, X. Y. and Zhan, X. Y.: IPCC AR5 Clouds and Aerosols., 2013. Browman, D. M. J. S., Balch, J. K., Artaxo, P., Bond, W. J., Carlson, J. M., Cochrane, M. A., D'Antonio, C. M. A., DeFries, R. S., Doyle, J. C., Harrison, S. P., Johnston, F. H., Keeley, J. E., Krawchuk, M. A., Kull, C. a, Marston, J. B., Moritz, M. a, Prentice, I. C., Roos, C. I., Scott, A. C., Swetnam, T. W., van der Werf, G. R., Bowman, D. M. J. S., S.J., P., D'Antonio, C. M. and Pyne, S. J.: Fire in the Earth System, Science (80-. )., 324(5926), 481-484, doi:10.1126/science.1163886, 2009.
  12. Channan, S., Collins, K. and Emanuel, W. R.: Global mosaics of the standard MODIS land cover type data, Univ. Maryl. Pacific Northwest Natl. Lab. Coll. Park. Maryland, USA, 30, 2014.
  13. Chen, Y., Morton, D. C., Andela, N., Giglio, L. and Randerson, J. T.: How much global burned area can be forecast on seasonal time scales using sea surface temperatures?, Environ. Res. Lett., 11(4), 45001, doi:10.1088/1748-9326/11/4/045001, 2016a. Chen, Y., Morton, D. C., Andela, N., Giglio, L. and Randerson, J. T.: How much global burned area can be forecast on seasonal time scales using sea surface temperatures?, Environ. Res. Lett., 11(4), 45001, doi:10.1088/1748-9326/11/4/045001, 2016b. Chen, Y., Morton, D. C., Andela, N., Giglio, L. and Randerson, J. T.: How much global burned area can be forecast on seasonal time scales using sea surface temperatures?, Environ. Res. Lett., 11, 45001, doi:10.1088/1748-9326/11/4/045001, 2016c. Christoudias, T., Pozzer, A. and Lelieveld, J.: Influence of the North Atlantic Oscillation on air pollution transport, Atmos. Chem. Phys., 12(2), 869-877, doi:10.5194/acp-12-869-2012, 2012.
  14. Colarco, P. R.: Transport of smoke from Canadian forest fires to the surface near
  15. Washington, D.C.: Injection height, entrainment, and optical properties, J. Geophys. Res., 109(D6), 1-12, doi:10.1029/2003JD004248, 2004.
  16. DeBell, L. J., Talbot, R. W., Dibb, J. E., Munger, J. W., Fischer, E. V. and Frolking, S. E.: A major regional air pollution event in the northeastern United States caused by extensive forest fires in Quebec, Canada, J. Geophys. Res. D Atmos., 109(19), 1-16, doi:10.1029/2004JD004840, 2004.
  17. Delfino, R. J., Sioutas, C. and Malik, S.: Potential role of ultrafine particles in associations between airborne particle mass and cardiovascular health, Environ. Health Perspect., 113(8), 934-946, doi:10.1289/ehp.7938, 2005.
  18. Dempsey, F.: Forest fire effects on air quality in Ontario: Evaluation of several recent examples, Bull. Am. Meteorol. Soc., 94(7), 1059-1064, doi:10.1175/BAMS-D-11- 00202.1, 2013.
  19. Dirksen, R. J., Folkert Boersma, K., De Laat, J., Stammes, P., Van Der Werf, G.
  20. R., Martin, M. V. and Kelder, H. M.: An aerosol boomerang: Rapid around-the-world transport of smoke from the December 2006 Australian forest fires observed from space, J. Geophys. Res. Atmos., 114(21), 1-15, doi:10.1029/2009JD012360, 2009.
  21. Doherty, S. J., Dang, C., Hegg, D. A., Zhang, R. R., Warren, S. G., Ames, R. B., Fox, D. G., Malm, W. C., Schichtel, B. A., Bowman, D. M. J. S., Williamson, G. J., Abatzoglou, J. T., Kolden, C. A., Cochrane, M. A., Smith, A. M. S., Liu, Y., Goodrick, S. L., Heilman, W. E., Liu, Y., Urbanski, S. P., Kovalev, V., Mickler, R., Yang, J., Tian, H., Tao, B., Ren, W., Kush, J., Liu, Y., Wang, Y., Rothermel, R. C., Veraverbeke, S., Hook, S. J., Fallis, A. ., Ratio, N. B., Bhattarai, K. P., Picotte, J., Howard, S. M., Boschetti, L., Roy, D. P., Hoffmann, A. A., Humber, M., Scott, J. H., Groot, W. J. De, Anderson, G. K., Sandberg, D. V., Norheim, R. A., EPA, Liu, Y., Dentener, F., Kinne, S., Bond, T. C., Boucher, O., Cofala, J., Generoso, S., Ginoux, P., Gong, S., Hoelzemann, J. J., Ito, A., Marelli, L., Penner, J. E., Putaud, J.-P., Textor, C., Schulz, M., van der Werf, G. R., Wilson, J., Devore, J., Tai, A. P. K., Martin, M. V., Heald, C. L., Wang, Y., Wang, M., Zhang, R. R., Ghan, S. J., Lin, Y., Hu, J., Pan, B., Levy, M., Jiang, J. H., Molina, M. J., Biasutti, M., Urbanski, S. P., Miller, C., Ager, A. A., Knorr, W., Lehsten, V., Arneth, A., Huber, S., Fensholt, R., Rasmussen, K., French, N. H. F., de Groot, W. J. W. J., Jenkins, L. K., Rogers, B. M., Alvarado, E., Amiro, B. B. D., De Jong, B., Goetz, S., Hoy, E., Hyer, E., et al.: Modeling of biomass smoke injection into the lower stratosphere by a large forest fire (Part II): sensitivity studies, Atmos. Chem. Phys., 6(4), 5261-5277, doi:10.5194/acpd-6-6081- 2006, 2013.
  22. Donaldson, K., Stone, V., Seaton, A. and MacNee, W.: Ambient particle inhalation and the cardiovascular system: Potential mechanisms, Environ. Health Perspect., 109(SUPPL. 4), 523-527, doi:10.2307/3454663, 2001.
  23. Dreessen, J., Sullivan, J. and Delgado, R.: Observations and impacts of transported Canadian wildfire smoke on ozone and aerosol air quality in the Maryland region on June 9-12, 2015, J. Air Waste Manage. Assoc., 66(9), 842-862, doi:10.1080/10962247.2016.1161674, 2016.
  24. Ellicott, E., Vermote, E., Giglio, L. and Roberts, G.: Estimating biomass consumed from fire using MODIS FRE, Geophys. Res. Lett., 36(13), 1-5, doi:10.1029/2009GL038581, 2009.
  25. Evangeliou, N., Balkanski, Y., Hao, W. M., Petkov, A., Silverstein, R. P., Corley, R., Nordgren, B. L., Urbanski, S. P., Eckhardt, S., Stohl, A., Tunved, P., Crepinsek, S., Jefferson, A., Sharma, S., Nøjgaard, J. K. and Skov, H.: Wildfires in Northern Eurasia affect the budget of black carbon in the Arctic. A 12-year retrospective synopsis (2002- 2013)., Atmos. Chem. Phys. Discuss., (February), 1-41, doi:10.5194/acp-2015-994, 2016. Fang, T., Verma, V., T Bates, J., Abrams, J., Klein, M., Strickland, J. M., Sarnat, E. S., Chang, H. H., Mulholland, A. J., Tolbert, E. P., Russell, G. A. and Weber, J. R.: Oxidative potential of ambient water-soluble PM2.5 in the southeastern United States: Contrasts in sources and health associations between ascorbic acid (AA) and dithiothreitol (DTT) assays, Atmos. Chem. Phys., 16(6), 3865-3879, doi:10.5194/acp-16-3865-2016, 2016. Fiore, A. and Jacob, D.: Application of empirical orthogonal functions to evaluate ozone simulations with regional and global models, J. Geophys. …, 108(D14), 4431, doi:10.1029/2002JD003151, 2003.
  26. Fiore, A. M., Pierce, R. B., Dickerson, R. R. and Lin, M.: Detecting and attributing episodic high background ozone events, EM Air Waste Manag. Assoc. Mag. Environ. Manag., (FEB), 22-28, 2014.
  27. Freeborn, P. H., Wooster, M. J., Hao, W. M., Ryan, C. A., Nordgren, B. L., Baker, S. P. and Ichoku, C.: Relationships between energy release, fuel mass loss, and trace gas an aerosol emissions during laboratory biomass fires, J. Geophys. Res. Atmos., 113(1), 1- 17, doi:10.1029/2007JD008679, 2008.
  28. Freitas, S. R., Longo, K. M., Chatfield, R., Latham, D., Silva Dias, M. a. F., Andreae, M. O., Prins, E., Santos, J. C., Gielow, R. and Carvalho, J. a.: Including the sub- grid scale plume rise of vegetation fires in low resolution atmospheric transport models, Atmos. Chem. Phys. Discuss., 6(6), 11521-11559, doi:10.5194/acpd-6-11521-2006, 2006. Freitas, S. R., Longo, K. M., Chatfield, R., Latham, D., Silva Dias, M. a. F., Andreae, M. O., Prins, E., Santos, J. C., Gielow, R. and Carvalho, J. a.: Including the sub- grid scale plume rise of vegetation fires in low resolution atmospheric transport models, Atmos. Chem. Phys. Discuss., 7(7), 3385-3398, doi:10.5194/acpd-6-11521-2006, 2007. Freitas, S. R., Longo, K. M., Trentmann, J. and Latham, D.: Technical Note: Sensitivity of 1-D smoke plume rise models to the inclusion of environmental wind drag, Atmos. Chem. Phys., 10(2), 585-594, doi:10.5194/acp-10-585-2010, 2010.
  29. Gégo, E., Porter, P. S., Gilliland, A. and Rao, S. T.: Observation-based assessment of the impact of nitrogen oxides emissions reductions on ozone air quality over the Eastern United States, J. Appl. Meteorol. Climatol., 46(7), 994-1008, doi:10.1175/JAM2523.1, 2007. Giglio, L.: MODIS collection 5 active fire product user's guide version 2.4. [online] Available from: http://198.118.255.205/sites/default/files/field/document/MODIS_Fire_users_Guide_2.4. pdf, 2013.
  30. Giglio, L., Csiszar, I. and Justice, C. O.: Global distribution and seasonality of active fires as observed with the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) sensors, J. Geophys. Res. Biogeosciences, 111(2), 1-12, doi:10.1029/2005JG000142, 2006.
  31. Giglio, L., Randerson, J. T. and Van Der Werf, G. R.: Analysis of daily, monthly, and annual burned area using the fourth-generation global fire emissions database (GFED4), J. Geophys. Res. Biogeosciences, 118(1), 317-328, doi:10.1002/jgrg.20042, 2013. de Gouw, J. A., Warneke, C., Stohl, A., Wollny, A. G., Brock, C. A., Cooper, O.
  32. R., Holloway, J. S., Trainer, M., Fehsenfeld, F. C., Atlas, E. L., Donnelly, S. G., Stroud, V. and Lueb, A.: Volatile organic compounds composition of merged and aged forest fire plumes from Alaska and western Canada, J. Geophys. Res. Atmos., 111(10), 1-20, doi:10.1029/2005JD006175, 2006.
  33. Grell, G., Freitas, S. R., Stuefer, M. and Fast, J.: Inclusion of biomass burning in WRF-Chem: Impact of wildfires on weather forecasts, Atmos. Chem. Phys., 11(11), 5289- 5303, doi:10.5194/acp-11-5289-2011, 2011.
  34. Hirota, M., Holmgren, M., Nes, E. H. Van and Scheffer, M.: Global Resilience of Tropical Forest and Savanna to Critical Transitions, Science (80-. )., 334(October), 232- 235, doi:10.1126/science.1210657, 2011.
  35. Hodnebrog, Ø., Myhre, G., Forster, P. M., Sillmann, J. and Samset, B. H.: Local biomass burning is a dominant cause of the observed precipitation reduction in southern Africa, Nat. Commun., 7, 11236, doi:10.1038/ncomms11236, 2016. Hu, Y., Odman, M. T., Chang, M. E., Jackson, W., Lee, S., Edgerton, E. S., Baumann, K. and Russell, A. G.: Simulation of Air Quality Impacts from Prescribed Fires on an Urban Area, Environ. Sci. Technol., 42(10), 3676-3682, doi:10.1021/es071703k, 2008. Ichoku, C., Ellison, L. T., Willmot, K. E., Matsui, T., Dezfuli, A. K., Gatebe, C. K., Wang, J., Wilcox, E. M., Lee, J., Adegoke, J., Okonkwo, C., Bolten, J., Policelli, F. S. and Habib, S.: Biomass burning, land-cover change, and the hydrological cycle in Northern sub-Saharan Africa, Environ. Res. Lett., 11(9), 95005, doi:10.1088/1748- 9326/11/9/095005, 2016.
  36. Jaffe, D., Hafner, W., Chand, D., Westerling, A. and Spracklen, D.: Interannual variations in PM2.5 due to wildfires in the Western United States, Environ. Sci. Technol., 42(8), 2812-2818, doi:10.1021/es702755v, 2008.
  37. Jaffe, D. A. and Wigder, N. L.: Ozone production from wildfires: A critical review, Atmos. Environ., 51, 1-10, doi:10.1016/j.atmosenv.2011.11.063, 2012. Jiang, Y., Lu, Z., Liu, X., Qian, Y., Zhang, K., Wang, Y. and Yang, X. Q.: Impacts of global open-fire aerosols on direct radiative, cloud and surface-albedo effects simulated with CAM5, Atmos. Chem. Phys., 16(23), 14805-14824, doi:10.5194/acp-16-14805- 2016, 2016.
  38. Kahn, R. A., Li, W. H., Moroney, C., Diner, D. J., Martonchik, J. V. and Fishbein, E.: Aerosol source plume physical characteristics from space-based multiangle imaging, J. Geophys. Res. Atmos., 112(11), 1-20, doi:10.1029/2006JD007647, 2007.
  39. Kahn, R. A., Chen, Y., Nelson, D. L., Leung, F. Y., Li, Q., Diner, D. J. and Logan, J. A.: Wildfire smoke injection heights: Two perspectives from space, Geophys. Res. Lett., 35(4), 18-21, doi:10.1029/2007GL032165, 2008.
  40. Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L., Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Chelliah, M., Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K. C., Ropelewski, C., Wang, J., Leetmaa, A., Reynolds, R., Jenne, R. and Joseph, D.: The NCEP/NCAR 40-year reanalysis project, Bull. Am. Meteorol. Soc., 77(3), 437-471, doi:10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2, 1996.
  41. Kang, C. M., Gold, D. and Koutrakis, P.: Downwind O3 and PM2.5 speciation during the wildfires in 2002 and 2010, Atmos. Environ., 95, 511-519, doi:10.1016/j.atmosenv.2014.07.008, 2014.
  42. Keegan, K. M., Albert, M. R., McConnell, J. R. and Baker, I.: Climate change and forest fires synergistically drive widespread melt events of the Greenland Ice Sheet., Proc. Natl. Acad. Sci. U. S. A., 111(22), 7964-7, doi:10.1073/pnas.1405397111, 2014. Künzli, N., Avol, E., Wu, J., Gauderman, W. J., Rappaport, E., Millstein, J., Bennion, J., McConnell, R., Gilliland, F. D., Berhane, K., Lurmann, F., Winer, A. and Peters, J. M.: Health effects of the 2003 Southern California wildfires on children, Am. J. Respir. Crit. Care Med., 174(11), 1221-1228, doi:10.1164/rccm.200604-519OC, 2006. Lamarque, J. F., Bond, T. C., Eyring, V., Granier, C., Heil, A., Klimont, Z., Lee, D., Liousse, C., Mieville, A., Owen, B., Schultz, M. G., Shindell, D., Smith, S. J., Stehfest, E., Van Aardenne, J., Cooper, O. R., Kainuma, M., Mahowald, N., McConnell, J. R., Naik, V., Riahi, K. and Van Vuuren, D. P.: Historical (1850-2000) gridded anthropogenic and biomass burning emissions of reactive gases and aerosols: Methodology and application, Atmos. Chem. Phys., 10(15), 7017-7039, doi:10.5194/acp-10-7017-2010, 2010. Lamb, R. G. and Durran, D. R.: Eddy Diffusivities Derived from a Numerical Model of the Convective Planetary Boundary Layer (')., NUOVO Cim., 1C, 1-17, 1978. Latham, D.: PLUMP: A one-dimensional plume predictor and cloud model for fire and smoke managers, Gen. Tech. Rep. INT-GTR-314, Intermt. Res. Station. USDA For. Serv., 11526, 11528-11529, 1994.
  43. LAWRENCE, P. J., FEDDEMA, J. J., BONAN, G. B., A.MEEHL, G., O'NEILL, B. C., OLESON, K. W., LEVIS, S., LAWRENCE, D. M., KLUZEK, E., LINDSAY, K. and THORNTON, P. E.: Simulating the Biogeochemical and Biogeophysical Impacts of Transient Land Cover Change and Wood Harvest in the Community Climate System Model ( CCSM4 ) from 1850 to 2100, J. Clim., 25(9), 3071-3095, doi:10.1175/JCLI-D- 11-00256.1, 2012.
  44. Levy, R. C., Remer, L. A., Mattoo, S., Vermote, E. F. and Kaufman, Y. J.: Second- generation operational algorithm: Retrieval of aerosol properties over land from inversion of Moderate Resolution Imaging Spectroradiometer spectral reflectance, J. Geophys. Res. Atmos., 112(13), 1-21, doi:10.1029/2006JD007811, 2007.
  45. Li, Y., Sulla-Menashe, D., Motesharrei, S., Song, X. P., Kalnay, E., Ying, Q., Li, S. and Ma, Z.: Inconsistent estimates of forest cover change in China between 2000 and 2013 from multiple datasets: Differences in parameters, spatial resolution, and definitions, Sci. Rep., 7(1), 1-12, doi:10.1038/s41598-017-07732-5, 2017.
  46. Liu, X., Easter, R. C., Ghan, S. J., Zaveri, R., Rasch, P., Shi, X., Lamarque, J. F., Gettelman, A., Morrison, H., Vitt, F., Conley, A., Park, S., Neale, R., Hannay, C., Ekman, A. M. L., Hess, P., Mahowald, N., Collins, W., Iacono, M. J., Bretherton, C. S., Flanner, M. G. and Mitchell, D.: Toward a minimal representation of aerosols in climate models: Description and evaluation in the Community Atmosphere Model CAM5, Geosci. Model Dev., 5(3), 709-739, doi:10.5194/gmd-5-709-2012, 2012.
  47. Liu, Y.: Variability of wildland fire emissions across the contiguous United States, Atmos. Environ., 38(21), 3489-3499, doi:10.1016/j.atmosenv.2004.02.004, 2004. Liu, Y., Stanturf, J. and Goodrick, S.: Trends in global wildfire potential in a changing climate, For. Ecol. Manage., 259(4), 685-697, doi:10.1016/j.foreco.2009.09.002, 2010. Liu, Y., Goodrick, S. and Heilman, W.: Wildland fire emissions, carbon, and climate: Wildfire-climate interactions, For. Ecol. Manage., 317, 80-96, doi:10.1016/j.foreco.2013.02.020, 2014.
  48. Lutsch, E., Dammers, E., Conway, S. and Strong, K.: Long-range Transport of NH 3 , CO, HCN and C 2 H 6 from the 2014 Canadian Wildfires, Geophys. Res. Lett., 1-12, doi:10.1002/2016GL070114, 2016.
  49. Ma, X., Bartlett, K., Harmon, K. and Yu, F.: Comparison of AOD between CALIPSO and MODIS: Significant differences over major dust and biomass burning regions, Atmos. Meas. Tech., 6(9), 2391-2401, doi:10.5194/amt-6-2391-2013, 2013. Madden, J. M., Mölders, N. and Sassen, K.: 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 J. Air Pollut., 4(September), 119-138 [online] Available from: http://www.scirp.org/journal/ojap http://dx.doi.org/10.4236/ojap.2015.43012%5CnAssessment, 2015. Maidment, R. I., Allan, R. P. and Black, E.: Recent observed and simulated changes in precipitation over Africa, Geophys. Res. Lett., 42(19), 1-10, doi:10.1002/2015GL065765.Received, 2015.
  50. Malm, W. C., Schichtel, B. A., Pitchford, M. L., Ashbaugh, L. L. and Eldred, R. A.: Spatial and monthly trends in speciated fine particle concentration in the United States, J. Geophys. Res. Atmos., 109(D3), n/a-n/a, doi:10.1029/2003JD003739, 2004.
  51. Mayer, A. L. and Khalyani, A. H.: Grass Trumps Trees with Fire, Science (80-. )., 334(6053), 188-189, doi:10.1126/science.1213908, 2011.
  52. McKeen, S. A., Wotawa, G., Parrish, D. D., Holloway, J. S., Buhr, M. P., Hübler, G., Fehsenfeld, F. C. and Meagher, J. F.: Ozone production from Canadian wildfires during June and July of 1995, J. Geophys. Res. Atmos., 107(14), 1-25, doi:10.1029/2001JD000697, 2002.
  53. Monks, S. A., Arnold, S. R. and Chipperfield, M. P.: Evidence for El Niño-Southern Oscillation (ENSO) influence on Arctic CO interannual variability through biomass burning emissions, Geophys. Res. Lett., 39(14), 1-6, doi:10.1029/2012GL052512, 2012. Mu, M., Randerson, J. T., Van Der Werf, G. R., Giglio, L., Kasibhatla, P., Morton, D., Collatz, G. J., Defries, R. S., Hyer, E. J., Prins, E. M., Griffith, D. W. T., Wunch, D., Toon, G. C., Sherlock, V. and Wennberg, P. O.: Daily and 3-hourly variability in global fire emissions and consequences for atmospheric model predictions of carbon monoxide, J. Geophys. Res. Atmos., 116(24), 1-19, doi:10.1029/2011JD016245, 2011.
  54. Myneni, R. B., Yang, W., Nemani, R. R., Huete, A. R., Dickinson, R. E., Knyazikhin, Y., Didan, K., Fu, R., Negrón Juárez, R. I., Saatchi, S. S., Hashimoto, H., Ichii, K., Shabanov, N. V, Tan, B., Ratana, P., Privette, J. L., Morisette, J. T., Vermote, E. F., Roy, D. P., Wolfe, R. E., Friedl, M. a, Running, S. W., Votava, P., El-Saleous, N., Devadiga, S., Su, Y. and Salomonson, V. V: Large seasonal swings in leaf area of Amazon rainforests., Proc. Natl. Acad. Sci. U. S. A., 104(12), 4820-4823, doi:10.1073/pnas.0611338104, 2007.
  55. Neale, R. B., Gettelman, A., Park, S., Chen, C., Lauritzen, P. H., Williamson, D. L., Conley, A. J., Kinnison, D., Marsh, D., Smith, A. K., Vitt, F., Garcia, R., Lamarque, J., Mills, M., Tilmes, S., Morrison, H., Cameron-smith, P., Collins, W. D., Iacono, M. J., Easter, R. C., Liu, X., Ghan, S. J., Rasch, P. J. and Taylor, M. a: Description of the NCAR Community Atmosphere Model (CAM 5.0). NCAR Technical Notes., Natl. Cent. Atmos. Res., 214, doi:10.5065/D6N877R0., 2012.
  56. Neami, R. R. ., Keeling, C. D. . and Hashimoto, H. . E. Al: Climate-Driven Increases in Global Terrestrial Net Primary Production From 192 To 1999, Science, 300(5625), 1560-3, doi:10.1126/science.1082750, 2003.
  57. Oleson, K. W., Lawrence, D. M., Gordon, B., Flanner, M. G., Kluzek, E., Peter, J., Levis, S., Swenson, S. C., Thornton, E., Dai, A., Decker, M., Dickinson, R., Feddema, J., Heald, C. L., Lamarque, J., Niu, G., Qian, T., Running, S., Sakaguchi, K., Slater, A., Stöckli, R., Wang, A., Yang, L., Zeng, X. and Zeng, X.: Technical Description of version 4 . 0 of the Community Land Model ( CLM )., 2010.
  58. Pablo E. Saide, Thompson, G., Eidhammer, T., Silva, A. M. da, Pierce, R. B. and Carmichael, G. R.: Assessment of biomass burning smoke influence on environmental conditions for multiyear tornado outbreaks by combining aerosol-aware microphysics and fire emission constraints, , (121), 10294-10311, doi:10.1002/2015JD024524.Received, 2016. Park, R. J., Jacob, D. J. and Logan, J. A.: Fire and biofuel contributions to annual mean aerosol mass concentrations in the United States, Atmos. Environ., 41(35), 7389- 7400, doi:10.1016/j.atmosenv.2007.05.061, 2007.
  59. Paugam, R., Wooster, M., Freitas, S. and Val Martin, M.: A review of approaches to estimate wildfire plume injection height within large-scale atmospheric chemical transport models, Atmos. Chem. Phys., 16(2), 907-925, doi:10.5194/acp-16-907-2016, 2016. Pechony, O. and Shindell, D. T.: Driving forces of global wildfires over the past millennium and the forthcoming century, Proc. Natl. Acad. Sci., 107(45), 19167-19170, doi:10.1073/pnas.1003669107, 2010.
  60. Pfister, G. G., Avise, J., Wiedinmyer, C., Edwards, D. P., Emmons, L. K., Diskin, G. D., Podolske, J. and Wisthaler, A.: CO source contribution analysis for California during ARCTAS-CARB, Atmos. Chem. Phys., 11(15), 7515-7532, doi:10.5194/acp-11-7515- 2011, 2011.
  61. Randerson, J. T., Chen, Y., Van Der Werf, G. R., Rogers, B. M. and Morton, D. C.: Global burned area and biomass burning emissions from small fires, J. Geophys. Res. Biogeosciences, 117(4), doi:10.1029/2012JG002128, 2012.
  62. Saha, S., Moorthi, S., Wu, X., Wang, J., Nadiga, S., Tripp, P., Behringer, D., Hou, Y. T., Chuang, H. Y., Iredell, M., Ek, M., Meng, J., Yang, R., Mendez, M. P., Van Den Dool, H., Zhang, Q., Wang, W., Chen, M. and Becker, E.: The NCEP climate forecast system version 2, J. Clim., 27(6), 2185-2208, doi:10.1175/JCLI-D-12-00823.1, 2014. Sankaran, M., Ratnam, J. and Hanan, N. P.: Tree-grass coexistence in savannas revisited -Insights from an examination of assumptions and mechanisms invoked in existing models, Ecol. Lett., 7(6), 480-490, doi:10.1111/j.1461-0248.2004.00596.x, 2004. Sankaran, M., Hanan, N. P., Scholes, R. J., Ratnam, J., Augustine, D. J., Cade, B.
  63. S., Gignoux, J., Higgins, S. I., Le Roux, X., Ludwig, F., Ardo, J., Banyikwa, F., Bronn, A., Bucini, G., Caylor, K. K., Coughenour, M. B., Diouf, A., Ekaya, W., Feral, C. J., February, E. C., Frost, P. G. H., Hiernaux, P., Hrabar, H., Metzger, K. L., Prins, H. H. T., Ringrose, S., Sea, W., Tews, J., Worden, J. and Zambatis, N.: Determinants of woody cover in African savannas., Nature, 438(7069), 846-849, doi:10.1038/nature04070, 2005. Sankaran, M., Ratnam, J. and Hanan, N.: Woody cover in African savannas: The role of resources, fire and herbivory, Glob. Ecol. Biogeogr., 17(2), 236-245, doi:10.1111/j.1466-8238.2007.00360.x, 2008.
  64. Sapkota, A., Symons, J. M., Kleissl, J., Wang, L., Parlange, M. B., Ondov, J., Breysse, P. N., Diette, G. B., Eggleston, P. a and Buckley, T. J.: Impact of the 2002 Canadian forest fires on particulate matter air quality in Baltimore city., Environ. Sci. Technol., 39(1), 24-32, doi:10.1021/es035311z, 2005.
  65. Saunders, R. O. and Waugh, D. W.: Variability and potential sources of summer PM2.5 in the Northeastern United States, Atmos. Environ., 117, 259-270, doi:10.1016/j.atmosenv.2015.07.007, 2015.
  66. Schuster, G. L., Vaughan, M., MacDonnell, D., Su, W., Winker, D., Dubovik, O., Lapyonok, T. and Trepte, C.: Comparison of CALIPSO aerosol optical depth retrievals to AERONET measurements, and a climatology for the lidar ratio of dust, Atmos. Chem. Phys., 12(16), 7431-7452, doi:10.5194/acp-12-7431-2012, 2012.
  67. Seddon, A. W. R., Macias-Fauria, M., Long, P. R., Benz, D. and Willis, K. J.: Sensitivity of global terrestrial ecosystems to climate variability, Nature, 531(7593), 229- 232, doi:10.1038/nature16986, 2016.
  68. Simpson, J. and Wiggert, V.: models of percipitating cumulus towers, Mon.
  69. Weather Rev., 97(7), 471-489, doi:10.1126/science.27.693.594, 1969.
  70. Sofiev, M., Ermakova, T. and Vankevich, R.: Evaluation of the smoke-injection height from wild-land fires using remote-sensing data, Atmos. Chem. Phys., 12(4), 1995- 2006, doi:10.5194/acp-12-1995-2012, 2012.
  71. Sofiev, M., Vankevich, R., Ermakova, T. and Hakkarainen, J.: Global mapping of maximum emission heights and resulting vertical profiles of wildfire emissions, Atmos. Chem. Phys., 13(14), 7039-7052, doi:10.5194/acp-13-7039-2013, 2013. Staal, A., Dekker, S. C., Xu, C. and van Nes, E. H.: Bistability, Spatial Interaction, and the Distribution of Tropical Forests and Savannas, Ecosystems, 19(6), 1080-1091, doi:10.1007/s10021-016-0011-1, 2016.
  72. Staver, A. C. and Levin, S. A.: Integrating Theoretical Climate and Fire Effects on Savanna and Forest Systems, Am. Nat., 180(2), 211-224, doi:10.1086/666648, 2012. Staver, A. C., Archibald, S. and Levin, S.: The Global Extent and Determinants of, Science (80-. )., 334(6053), 230-232, doi:10.1126/science.1210465, 2011a.
  73. Staver, A. C., Archibald, S. and Levin, S. A.: The Global Extent and Determinants of Savanna and Forest as Alternative Biome States, Science (80-. )., 334(6053), 230-232, doi:10.1126/science.1210465, 2011b.
  74. Staver, A. C., Archibald, S. and Levin, S.: Tree cover in sub-Saharan Africa: Rainfall and fire constrain forest and savanna as alternative stable states, Ecology, 92(5), 1063-1072, doi:10.1890/i0012-9658-92-5-1063, 2011c.
  75. Stein, A. F., Rolph, G. D., Draxler, R. R., Stunder, B. and Ruminski, M.: Verification of the NOAA Smoke Forecasting System: Model Sensitivity to the Injection Height, Weather Forecast., 24(2), 379-394, doi:10.1175/2008WAF2222166.1, 2009. Tosca, M. G., Randerson, J. T., Zender, C. S., Nelson, D. L., Diner, D. J. and Logan, J. A.: Dynamics of fire plumes and smoke clouds associated with peat and deforestation fires in Indonesia, J. Geophys. Res. Atmos., 116(8), 1-14, doi:10.1029/2010JD015148, 2011. Tosca, M. G., Randerson, J. T. and Zender, C. S.: Global impact of smoke aerosols from landscape fires on climate and the Hadley circulation, Atmos. Chem. Phys., 13(10), 5227-5241, doi:10.5194/acp-13-5227-2013, 2013a.
  76. Tosca, M. G., Randerson, J. T. and Zender, C. S.: Global impact of smoke aerosols from landscape fires on climate and the Hadley circulation, Atmos. Chem. Phys., 13(10), 5227-5241, doi:10.5194/acp-13-5227-2013, 2013b.
  77. Tosca, M. G., Diner, D. J., Garay, M. J. and Kalashnikova, O. V.: Human-caused fires limit convection in tropical Africa: First temporal observations and attribution, Geophys. Res. Lett., 42(15), 6492-6501, doi:10.1002/2015GL065063, 2015. Touboul, J. D., Carla, A. and Asher, S.: On the complex dynamics of savanna landscapes, Proc. Natl. Acad. Sci., doi:10.1073/pnas.1712356115, 2017.
  78. Trentmann, J., Andreae, M. O., Graf, H.-F., Hobbs, P. V. V, Ottmar, R. D. D. and Trautmann, T.: Simulation of a biomass-burning plume: Comparison of model results with observations, J. Geophys. Res., 107(D2), 4013, doi:10.1029/2001JD000410, 2002. Turner, J. S.: Buoyancy effects in fluids, Cambridge University Press., 1979. Val Martin, M., Logan, J. a., Kahn, D., Leung, F. Y., Nelson, D. and Diner, D.: Smoke injection heights from fires in North America: analysis of 5 years of satellite observations, Atmos. Chem. Phys. Discuss., 9(5), 20515-20566, doi:10.5194/acpd-9- 20515-2009, 2009.
  79. Val Martin, M., Kahn, R. A., Logan, J. A., Paugam, R., Wooster, M. and Ichoku, C.: Space-based observational constraints for 1-D fire smoke plume-rise models, J. Geophys. Res. Atmos., 117(22), 1-18, doi:10.1029/2012JD018370, 2012.
  80. Verbesselt, J., Umlauf, N., Hirota, M., Holmgren, M., Van Nes, E. H., Herold, M., Zeileis, A. and Scheffer, M.: Remotely sensed resilience of tropical forests, Nat. Clim. Chang., 6(11), 1028-1031, doi:10.1038/nclimate3108, 2016.
  81. Vermote, E., Ellicott, E., Dubovik, O., Lapyonok, T., Chin, M., Giglio, L. and Roberts, G. J.: An approach to estimate global biomass burning emissions of organic and black carbon from MODIS fire radiative power, J. Geophys. Res. Atmos., 114(18), 1-22, doi:10.1029/2008JD011188, 2009.
  82. van der Werf, G. R., Randerson, J. T., Giglio, L., Collatz, G. J., Kasibhatla, P. S. and Arellano, A. F., J.: Interannual variability in global biomass burning emissions from 1997 to 2004, Atmos. Chem. Phys., 6(11), 3423-3441, doi:10.5194/acpd-6-3175-2006, 2006. van der Werf, G. R., Randerson, J. T., Giglio, L., van Leeuwen, T. T., Chen, Y., Rogers, B. M., Mu, M., van Marle, M. J. E., Morton, D. C., Collatz, G. J., Yokelson, R. J. and Kasibhatla, P. S.: Global fire emissions estimates during 1997&amp;ndash;2015, Earth Syst. Sci. Data Discuss., 1-43, doi:10.5194/essd-2016-62, 2017.
  83. Van Der Werf, G. R., Randerson, J. T., Giglio, L., Gobron, N. and Dolman, A. J.: Climate controls on the variability of fires in the tropics and subtropics, Global Biogeochem. Cycles, 22(3), 1-13, doi:10.1029/2007GB003122, 2008. Van Der Werf, G. R., Randerson, J. T., Giglio, L., Collatz, G. J., Mu, M.,
  84. Kasibhatla, P. S., Morton, D. C., Defries, R. S., Jin, Y. and Van Leeuwen, T. T.: Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997-2009), Atmos. Chem. Phys., 10(23), 11707-11735, doi:10.5194/acp-10-11707- 2010, 2010.
  85. Westerling, a. L., Hidalgo, H. G., Cayan, D. R. and Swetnam, T. W.: Warming and earlier spring increase western U.S. forest wildfire activity, Science (80-. )., 313(5789), 940-3, doi:10.1126/science.1128834, 2006.
  86. Winiger, P., Andersson, A., Eckhardt, S., Stohl, A. and Gustafsson, Ö.: The sources of atmospheric black carbon at a European gateway to the Arctic, Nat. Commun., 7, 12776, doi:10.1038/ncomms12776, 2016.
  87. Winker, D. M., Pelon, J., Coakley, J. A., Ackerman, S. A., Charlson, R. J., Colarco, P. R., Flamant, P., Fu, Q., Hoff, R. M., Kittaka, C., Kubar, T. L., Le Treut, H., McCormick, M. P., Mégie, G., Poole, L., Powell, K., Trepte, K., Vaughan, M. A. and Wielicki, B. A.: The Calipso Mission: A Global 3D View of Aerosols and Clouds, Bull. Am. Meteorol. Soc., 91(9), 1211-1229, doi:10.1175/2010BAMS3009.1, 2010.
  88. Wooster, M. J., Roberts, G., Perry, G. L. W. and Kaufman, Y. J.: Retrieval of biomass combustion rates and totals from fire radiative power observations: FRP derivation and calibration relationships between biomass consumption and fire radiative energy release, J. Geophys. Res. Atmos., 110(24), 1-24, doi:10.1029/2005JD006318, 2005. Wuyts, B., Champneys, A. R. and House, J. I.: Amazonian forest-savanna bistability and human impact, Nat. Commun., 15519, 1-11, 2017a. Wuyts, B., Champneys, A. R. and House, J. I.: Amazonian forest-savanna bistability and human impact, Nat. Commun., 8(May), 1-11, doi:10.1038/ncomms15519, 2017b. Yuan Zhang, Wallace, J. M. and Battisti, D. S.: ENSO-like interdecadal variability: 1900-93, J. Clim., 10(5), 1004-1020, doi:10.1175/1520- 0442(1997)010<1004:ELIV>2.0.CO;2, 1997.
  89. Zeng, T. and Wang, Y.: Nationwide summer peaks of OC/EC ratios in the contiguous United States, Atmos. Environ., 45(3), 578-586, doi:10.1016/j.atmosenv.2010.10.038, 2011.

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