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Biomass Burning in Southeast Asia: Science questions and proposed study approaches Bob Yokelson, University of Montana
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Biomass Burning in Southeast Asia: Science questions and proposed study approaches Bob Yokelson, University of Montana Thanks to: S. Akagi, P. Artaxo, D. Blake, I. Burling, P. Buseck, T. Campos, T. Christian, T. Clarke, H. Coe, J. Craven, J. Crounse, P. DeCarlo, J. de Gouw, A. Fried, J. Gilman, D. Griffith, A. Guenther, P. Hobbs, R. Holzinger, J. Jimenez, T. Karl, W. Kuster, S. Kreidenweis, A. Laskin, L. Mauldin, G. McMeeking, J. Reid, J. Roberts, J. Seinfeld, I. Simpson, C. Stockwell, J. Taylor, P. Veres, C. Warneke, A. Weinheimer, P. Wennberg, C. Wiedinmyer, and many others, plus NSF, DoD, JFSP, USFS, DOE, NASA, EPA,+ SEAC4RS Science Team Meeting Feb 23, 2012, Boulder, CO
Sources: Bond et al 2004, Forster et al 2007, Akagi et al., 2011.
Fires are a huge source and atmospheric chemistry is done by putting initial emissions in a chemical transport model. We have problems with SE Asia: There have never been any emissions measurements on real fires in SE Asia. In a recent lab experiment with organic soils (NOAA, Stockwell), ~28% of C emitted as NMOC, normally 1-2 % for other types of BB (DC8 package). Heritage: NASA/NSF Missions Have Produced Bulk of EF. SCAR-B/LBA-TROFFE Brazil SAFARI 2000 Africa MILAGRO Mexico-NH Tropics ARCTAS Boreal Forest SEAC4RS SE Asia?
2. There have never been any SE Asia plume aging measurements AND aging is extremely fast and variable. 3. Clouds and smoke are two of the largest and least understood climate forcers on Earth and they are intimately mixed in SE Asia. Smoke impacts on clouds are exceedingly complex. There are almost no data on the impact of clouds on smoke chemistry.
What we might see in SEAC4RS In addition to completing the “big three of biomass burning” we have an opportunity to learn how smoke plumes evolve. Based on limited available evidence, the evolution of aerosols and ozone in biomass burning plumes seems to differ in “warm-wet” vs “cool-dry” plumes and mixing may spur rapid evolution.
MILAGRO: Warm-wet plume (Yokelson et al., 2009) DeCarlo, Jimenez, Campos, data
Cool-dry plume (Akagi et al., 2012) Craven, Seinfeld, data
MILAGRO: Warm-wet plume (Yokelson et al., 2009) Clarke, Shinozuka, data
Warm-wet versus cool-dry: Ozone production Weinheimer, Campos, data
Cool-moist mixing with urban: Ozone production FF/BB mix also in: ARCTAS-CARB Lee et al.: 2008
How do we get more info on the substantial amount of rapid initial change? Fire are very variable within a fire AND fire to fire so be careful of this scenario…..
Emission Ratio (ER) DX/DCO = 10 ± 8 (2s) Lefer et al., 1994 JGR
Lifetime @ measured OH Benzene 9 d Toluene 2 d Ethane 47 d Propane 11 d
Quantitative plume evolution measurements. (Akagi et al., 2012)
Need an approach that’s practical for the DC8 and GV The single long-axis sample “time-machine” flight plan works sometime. DC8, GV alt. (DX/DY)I (DX/DY)F Windspeed 10 mph Aircraft speed 250 mph Check e.g. DBC/DCO
S3 END OR REPEAT S1 & S2 START F A E B Sample other targets or swap airspace with GV if small fire for time “X” C D A + X B + X • Pseudo-lagrangian can be as simple as breaking off to another target (ships, megacities, another fire, etc) and then coming back to projected downwind location later. C + X This could work for convective outflow too!
Finding fires Harder and easier then some may think. Case Study from SAFARI 2000: A prescribed fire seen from the flagship NASA aircraft was not seen by MAS on ER-2 or by TERRA as a thermal anomaly.
MILAGRO: Out of 56 fires found visually – only 10 were hotspots. Orbit gaps, clouds, and timing.
However a simple strategy works. If there were hotspots today & fair weather is forecast tomorrow go look. YES WE CAN FIND FIRES! THAT ALLOWS ACTUAL QUANTITATIVE AGES!
Back trajectories and hot-spots method. 48 38 36 31 28 26 22 18 11 2 HOURS UPWIND
http://geonetwork4.fao.org/firemap/ or http://firefly.geog.umd.edu/firemap/ or http://lance.nasa.gov/data-products/modis-products/ & Ed Hyer
FLAMBE for SEAC4RS Edward Hyer 20 February 2012
Characteristics of FLAMBE-SEAC4RS Basic Characteristics • Spatial resolution of satellite inputs (~5km) • Hourly temporal resolution • Latency: Incorporation of fire observations within 6 hours • Fuels description using new LC map from National University of Singapore • Based on 2010 observations • Includes tree plantations • Improved trace gas partitioning information • Yokelson Advanced Characteristics • Full coverage correction, and angular correction of MODIS • Diurnal cycle from geostationary observations • Tagging of fire regimes, vegetation types • Uncertainty estimates usable for ensemble generation • “probable fire under cloud” combining cloud data with persistence forecast • Forecast emissions fields based on empirical relations between weather and fire activity
Timeline of FLAMBE-SEAC4RS • 1 May: Generation of preliminary near-real-time product, and draft documentation available • 1 June: Reprocessing of 10/2010 to present complete (MTSAT-2 era) • 1 July: FLAMBE-SEAC4RS finalized with feedback from modelers, final documentation released • 21 July: October 2010-present processed with final version • 21 September: Reprocessing from 9/2008 to 10/2010 complete (MTSAT-1R era)
Idealized search cal/val procedure: will likely have to do one dipping and one off-shore.
All (rare) tropical O3 formation for testing model mechanism: 2005, O3 works ifNMOC increased ~3 or HONO added
Headlines Experts predict thousands to die as smog spreads Agence France-Presse (Paris) Sept 26, 1997 HONG KONG – Thousands of people will be killed by the smog blanketing Southeast Asia, experts in Hong Kong warned yesterday, adding some regions could face famine as crops are devastated and livestock chokes to death. “It will destroy the ecology of the region,” said Fang Ming, senior climatology programme manager at Hong Kong University of Science and Technology’s research centre. “Insects, animals, and vegetation alike will be largely destroyed,” he said.