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Characterization of Vertical Transport of Wildfire Emissions over North America: Merging MISR Observations and a 1-D Plu

This research aims to understand the injection and plume heights of fire emissions over North America by combining MISR observations with a 1-D plume-resolving model. It provides insight into the distribution of plumes, atmospheric conditions, and fire properties. The results show a relationship between fire intensity, size, and plume heights. The 1-D model successfully simulates observed plume heights.

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Characterization of Vertical Transport of Wildfire Emissions over North America: Merging MISR Observations and a 1-D Plu

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  1. Characterization of vertical transport of wildfire emissions over North America: Merging MISR observations and a 1-D plume-resolving model Maria Val Martin and J. Logan (Harvard Univ., USA) D. Nelson, C. Ichoku, R. Kahn and D. Diner (NASA, USA) S. Freitas (INPE, Brazil) F.-Y. Leung (Washington State Univ., USA) Research funded by NSF and EPA

  2. Hayman fire caused worst air quality ever in Denver The Hayman fire, Colorado • 56000 ha, June 8-22, 2002 • 30 miles from Denver and Colorado Springs June 8, 2002 June 9, 2002 PM10 = 40 μg/m3 PM2.5 = 10 μg/m3 PM10 = 372 μg/m3 PM2.5 = 200 μg/m3 Colorado Department of Public Health and Environment Vedal et al., Env Res, 2006

  3. Long-range transport of boreal wildfire emissions http://asl.umbc.edu/pub/mcmillan/www/index_INTEXA.html

  4. Scientific Objectives 1. To have a better understanding of injection heights of fire emissions over North America 2. To develop a parameterization of the injection heights of North American wildfire emissions

  5. Scientific Objectives 1. To have a better understanding of plume heights of fire emissions over North America 2. To develop a parameterization of the injection heights of North American wildfire emissions • Outline • Overview of MISR plume data • Results from the MISR observations • Plume distribution, atmospheric conditions and fire properties • The use of 1-D plume-resolving model

  6. Wind-corrected heights Histogram of heights retrieved by MINX Cross-section of heights as a function of distance from the source MISR Plumes: MISR INteractive eXplorer (MINX) Smoke Plume over central Alaska on June 2002 http://www.openchannelsoftware.org Courtesy of D. Nelson and D. Diner

  7. MISR Plumes: MISR INteractive eXplorer (MINX) Smoke cloud over Yukon territory Zero-wind heights Histogram of heights retrieved by MINX Cross-section of heights as a function of distance from the source

  8. 2002 2004 2005 2006 2007 About 3500 plumes digitalized over North America http://www-misr2.jpl.nasa.gov/EPA-Plumes/

  9. Plume Height? Stable Layer Max Boundary Layer (BL) Avg Median Each individual height Mode Plume Distribution, Atmospheric Conditions and Fire Properties Histogram of Plume Height Retrievals Atmospheric Stability Profile • Meteorological fields from GEOS-4 and GEOS-5 2x2.5 • Fire Properties from MODIS Fire Radiative Power

  10. 5-30% smoke emissions are injected above the boundary layer 2002 10–25% 2005 4–15% 2006 9–28% 2007 9–18% 2004 Kahn et al, [2008] Distribution of MISR heights-PBL for smoke plumes

  11. Cropland Non-Boreal Grassland Boreal Grassland Non-Boreal Shrub Boreal Shrub Boreal Forest Temperate Forest Tropical Forest Classification of plume distribution by vegetation type Vegetation type based on MODIS IGBP land cover map 1x1 km resolution (http://modis-land.gsfc.nasa.gov/landcover.htm)

  12. 2002 2004 2005 2006 Number of plumes 2007 Percentage of smoke above BL varies with vegetation type and fire season % Height retrievals with [Height-PBL] > 0.5 km

  13. A larger fraction of smoke may reach higher altitudes in the atmosphere in a later stage of the plume Smoke Plume Heights – BL 5-30% above BL Median Height: 970 m 2002-2007 Smoke Cloud Heights – BL 40-80% above BL Median Height: 1850 m

  14. Close relationship between fire intensity, fire size, plume distribution Max Height MODIS FRP (MW) Min Height Fire Area (ha) Distribution of Max and Min heights by MODIS FRP and Fire Size Histogram of retrieved heights

  15. 200 2002 2004 2005 2006 2007 Fire intensity drives the interannual variability of plume heights Distribution of MISR heights and MODIS FRP by year

  16. Also, fire intensity drives the seasonality of plume heights 200 Boreal Forest

  17. 200 Intensity of the fire drives also the seasonality of the plume heights NonBoreal Shrub

  18. 1-D Plume-resolving Model • Key input parameters: • Instant fire size: MODIS FRP (max FRP observed in each biome 1 km2 burned [Charles Ichoku, personal communication]) • Total heat flux: Max MODIS FRP observed over vegetation type x 10 [Wooster et al, 2005; Freeborn et al., 2008] • RH, T, P, wind speed and direction: from GEOS-4 meteo fields 2x2.5 • Fuel moisture content: from the Canadian Fire Weather Model Detailed information in Freitas et al, [2007]

  19. Simulation of a boreal fire plume in Alaska and a grassland fire plume in Mexico 1D Plume-rise Model MISR Retrieved Heights MISR Smoke Plume Boreal Forest Fire Fire Size= 300 Ha Heat Flux= 18 kW/m2 Grassland Fire Fire Size= 3.8 Ha Heat Flux= 9 kW/m2

  20. Simulation of a boreal fire plume in Alaska and a grassland fire plume in Mexico 1D Plume-rise Model MISR Retrieved Heights MISR Smoke Plume Boreal Forest Fire 5025 m 5425 m Fire Size= 300 Ha Heat Flux= 18 kW/m2 Grassland Fire 1200 m 900 m Fire Size= 3.3 Ha Heat Flux= 18 kW/m2

  21. The 1-D Plume-resolving Model simulates fairly well the observed MISR heights Correlation between simulated plume heights and MISR observed heights over North America All Plumes

  22. The 1-D Plume-resolving Model simulates fairly well the observed MISR heights Correlation between simulated plume heights and MISR observed heights over North America Boreal Forest Plumes

  23. The 1-D Plume-resolving Model simulates fairly well the observed MISR heights Correlation between simulated plume heights and MISR observed heights over North America Temperate Forest Plumes

  24. Concluding Remarks • 5-30% of smoke emissions are injected above the BL. • The percentage of smoke that reaches the FT depends on fire characteristics (e.g., vegetation type, fire intensity, etc) and year-to-year variations . • Fire intensity drives the seasonality and interannual variability of the plume heights. • 1-D plume-resolving model simulates fairly well the observed MISR plume heights. • In the future, we plan to embed the 1-D plume-resolving model with GEOS-Chem to simulate vertical transport of North American wildfire emissions.

  25. Thanks for your attention

  26. Extra Slides Model simulated heights versus MISR observed heights by year

  27. Model simulated heights versus MISR observed heights by vegetation

  28. Intensity of the fire drives the interannual variability of plume heights

  29. Also, fire intensity drives the seasonality of plume heights Trop Forest

  30. Also, fire intensity drives the seasonality of plume heights Temperate Forest

  31. Also, fire intensity drives the seasonality of plume heights Boreal Shrub

  32. Also, fire intensity drives the seasonality of plume heights Boreal Grassland

  33. Also, fire intensity drives the seasonality of plume heights NonBoreal Grassland

  34. Also, fire intensity drives the seasonality of plume heights Cropland

  35. Close relationship between fire intensity and plume distribution

  36. Distribution of all individual heights in the FT – Stable Layer 13% 11% 13% 24% 7% Smoke emissions tend to get confined within stable layers in the atmosphere, when they exist MISR Height – Stable Layer Height ≈ 0 km

  37. Smoke Plume Heights Median 970 m Smoke Cloud Heights Median 1850 m A larger fraction of smoke may reach higher altitudes in the atmosphere in a later stage of the plume

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