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OBJECTIVES

Study of Long-Range Transport and Stratosphere- Troposphere Exchange in Smoke Plumes From Forest Fires Caused by Aerosol Solar Heating Georgiy Stenchikov Department of Environmental Sciences, Rutgers University, New Brunswick, NJ Michael Fromm and Eric Shettle

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OBJECTIVES

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  1. Study of Long-Range Transport and Stratosphere-Troposphere Exchange in Smoke Plumes From Forest Fires Caused by Aerosol Solar Heating Georgiy Stenchikov Department of Environmental Sciences, Rutgers University, New Brunswick, NJ Michael Fromm and Eric Shettle NRL, Remote Sensing Division , Washington, DC

  2. OBJECTIVES Evaluate lofting of aerosols from large forest fires into the lower stratosphere driven by absorption of solar radiation in aerosol plume MODEL Regional Atmospheric Modeling System – RAMS Hybrid Particle and Concentration Transport model – HYPACT Simulations were initiated using NCEP reanalysis fields Assumptions POAM and SAGE/HALOE observations show Angstrom exponent ~2 in the plume that corresponds to small particles with sizes of 0.1µm In simulations we neglected particle dry and wet deposition Coagulation appears to be relatively slow for given concentrations and does not affect sedimentation velocities during the period of simulations

  3. Simulation Setup Regional domain in Polar Stereographic Projection 150W to 10W and 30N to 80N 60 vertical layers 300x300 grids horizontally with grid spacing of 25 km Time step 20s Aerosol initially distributed at 9.5 km in the area 106W to 114 W and from 63N to 66N With a constant mixing ratio of 10-3 g/kg. Total mass = 5kT Aerosol optical properties: Specific extinction coefficient = 4.5 m2/g (in visible) Single scattering albedo = 0.75 Asymmetry factor = 0.6 Simulations started at 18Z on May 29, 2001

  4. Chisholm Fire in Alberta, Canada on May 28-29, 2001 Duration – 7 hours Total area – 50x103 ha Energy release – 7x1016J (about 3x1012W) Assuming carbon content is 45% of dry forest fuel and smoke emission factor of 0.013 TOTAL SMOKE MASS= 10-20kT

  5. TOMS Level 2 AI. White pixels = no aerosol Deepest and/or thickest plume is west of MISR. Note: TOMS is ~45 min earlier than Terra. Wind is generally eastward. Shift TOMS east by ~1 pixel to match Terra. Approx. MISR “box”

  6. MISR StereoCloud Height tropopause 1840 UTC on May 29, 2001 Courtesy David Diner, NASA JPL

  7. TOMS Absorption Optical DepthOrbit 2 Courtesy Omar Torres, NASA-GSFC & UMBC-JCET

  8. TOMS aerosol index, May 30, 2001

  9. TOMS aerosol index, May 31, 2001

  10. TOMS aerosol index, June 1, 2001

  11. Assuming that radiative heating is equilibrated by adiabatic cooling associated with lofting we can get an estimate of lofting velocity The overshooting height for Chisholm Fire could be estimated as: Zmax=0.3xP1/4 ~ 10 km Zmax- height in km P – power in MW W * N2 = Q * R / H N2 = 5. 10-4 s-2 Weisel-Brent frequency R = 287 J/(K kg) - Gas constant for air H = 7 km – Characteristic height scale Q – heating rate in K/day Lofting velocity W = Q * 80 m/day W might be in the range from 200 m/day to 1 km/day The characteristic time of particle volume doubling by coagulation could be estimate as t = 2/(NxK) K= 2.10-10 cm3/sec–Coagulation kernel N – particle number density t = 1000 days for loadings of 100 μg/m3

  12. Conclusions The observed spatial-temporal evolution of the plume was reproduced in simulations fairly well when plume was initially placed below tropopause layer. The plume initially placed above tropopause develops significantly different than in observations. The plume with initial absorption optical depth of 0.24 as observed causes: Decrease of surface solar flux by 30W/m2 Heating rates in the aerosol layer of more than 2 K/day Vertical lofting velocity of ~400 m/day This shows that thermal lofting might be a possible mechanism that could lead to portion of the smoke plume to be mixed in the lower stratosphere Lofting effect depends significantly on plume homogeneity. Dilution tends to decrease local heating rates and lofting velocities. Eulerian transport schemes might exaggerate the dilution because of numerical diffusion. The lagrangian transport schemes show much less dilution and stronger spatial inhomogeneities

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