1 / 19

Wildfire, aka Biomass Burning (BB), and Emissions

Wildfire, aka Biomass Burning (BB), and Emissions. Johannes Kaiser, Martin Schultz, Christiane Textor, Mikhail Sofiev, Tony Hollingsworth, Jean-Marie Gregoire. FIRE EMISSIONS: OUTLINE. Significance HALO Activities Requirements Observation System GFAS Proposal Correlations Study Summary.

lael
Télécharger la présentation

Wildfire, aka Biomass Burning (BB), and Emissions

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Wildfire, aka Biomass Burning (BB), and Emissions Johannes Kaiser, Martin Schultz, Christiane Textor, Mikhail Sofiev, Tony Hollingsworth, Jean-Marie Gregoire

  2. FIRE EMISSIONS: OUTLINE • Significance • HALO Activities • Requirements • Observation System • GFAS Proposal • Correlations Study • Summary

  3. SIGNIFICANCE for Atmosphere Monitoring: BB AIR QUALITY: • … can dominate regional air quality in “severe air pollution” events • … can elevate background of atmospheric pollutant after long range transport [Stohl et al. 2001, Forster et al. 2001, Andreae et al. 2001] POLLUTION CONTROL: • … significantly contributes to global budgets of several gases • Kyoto, CLRTAP, … WEATHER: (absorbing aerosols) • … influences the radiative energy budget [Konzelmann et al., JGR 1996] • … provides cloud condensation nuclei [Andreae et al., Science 2004] • Heat release accelerates deep convection. [Damoah et al., ACP 2006] REMOTE SENSING: • … affects essential a priori information for remote sensing (AOD, profiles) CHALLENGE: • … are highly variable on all time scales from hours to decades NOAA, 2005-12-11

  4. Interannual Variability

  5. SIGNIFICANCE for Land Monitoring • Wildfires represent a significant sink for the terrestrial carbon pools. • Wildfire behaviour characterises land cover types with repeated fire events. • typical fire repeat period • typical fire intensity • typical fire seasonality • … • Wildfires can change the land cover type reversibly • tropical deforestation • …

  6. HALO ACTIVITIES • compilation of EO fire product requirements for environmental monitoring • comparison to available products • development of a future strategy • quantitative refinement of requirements and strategy HALO Documents: • “Emissions for GEMS”, HALO report • “Global Assimilation of Wildfire Emissions for GEMS”, HALO report • “Observation Requirements for Global Biomass Burning Emission Monitoring”, Proceedings of the 2006 EUMETSAT Meteorological Satellite Conference • “Expression of Interest for Listing of a European Project on a Global Fire Assimilation System”, communicated to GAC

  7. REQUIREMENTS: Monitoring Objectives • Selected GEMS Deliverables: • global operational system for monitoring & forecasting atmospheric composition • global retrospective analyses 2000-2007 • several regional air-quality forecasting systems • Selected GEOLAND Objectives: • to model vegetation as part of the global carbon cycle quantitatively • to characterise behaviour of land cover types with repeated fire events • to monitor land cover change

  8. ATMOS. MONITOR.: BB Observation Requirements

  9. Two types of fire products accessible from Earth obs. systems • - Active fire • - Hot spot • Fire pixel • Fire count ACTIVE FIRE product Fire front BURNT AREA product - Burnt area - Burnt pixel - Burnt scar Area burnt OBSERVATIONSYSTEM • thermal emission, MIR • only during fire • spectrally flat • BRDF flat • dark • only after fire

  10. “pixels” burnt per vegetation type Area burnt per vegetation type: ha Fuel: T. ha-1 ???? M (…) = Area . Biomass . Burning efficiency. Emission factor Globe: ~ 400 millions hectaresburnt in 2000 Med. Basin: ~ 500000 hectares Woodland & forests ~ 1600 g CO2 / kg biomass Grasslands ~ 1700 g CO2 / kg biomass Dry tropical grass savanna: ~ 2 tons/hectare Moist tropical savanna: ~ 10 tons/hectare Boreal forest: ~ 20 tons/hectare Moist tropical forest: ~ 40 tons/hectare ~ 25% forest -- ~ 80% savanna OBSERVATION SYSTEM:Calculating Emission Amounts • traditional: • Fire Radiative Power (FRP): • M(…) = FRP * time * scaling factor * emission factor(…)

  11. OBSERVATION SYSTEM: Current Fire Products

  12. OBSERVATION SYSTEM: Some Conclusions • No current product satisfies all requirements. • The required information is being observed but not being made available in products. • LEO spatial coverage/resolution complements GEO temporal resolution. • Hot spots (tropical forest) complement burnt area Many existing products are inconsistent. [Boschetti et al. 2004] • Several new operational products are anticipated. • Fire Radiative Power from SEVIRI (M. Wooster) • WF_ABBA from global GEO system (E. Prins)

  13. PROPOSAL GFAS • A Global Fire Assimilation System (GFAS) is needed to combine • several fire observations • land cover products • meteorological conditions • a numerical model of fire activity. • Such a system can provide the required fire input for the GMES atmosphere and land monitoring systems.

  14. PROPOSAL GFAS, cont. • regionalised: e.g. events in mid-lats, statistics in tropics • single, consistent processing for all GMES systems • evolving with new scientific developments • supported by 37 European scientists / institutions • communicated to GEMS Advisory Commity meteorology fire climatology GEMS greenhouse gases land cover climatology Global Fire Assimilation System reactive gases satellite fire product global fire emissions satellite radiance aerosols geoland, … land cover product carbon regional air quality fire product

  15. CORRELATIONS STUDY: Goal • to quantify the correlation between the anticipated fire-related products of the GMES fast-track services for the land and atmosphere monitoring. • spatial correlation of changes in biomass and air pollution • impact on absolute values and variability of atm. constituents • constituents of primary interest: aerosols, CO2 [Wooster 2005] [Ichoku 2005]

  16. CORRELATION STUDY: Approach • use fire emission inventory GFEDv2 as dummy for future GFAS. It combines [van der Werf et al., ACP 2006] • MODIS hot spots • CASA vegetation model. • obtain custom version of GFEDv2 with 8-day time resolution • conversions to GRIB format • include fire emissions in IFS • compare forecasts with / without fire emissions • compare both to observed time series • compare the difference to fuel load changes in CASA

  17. SUMMARY • Fire, aka Biomass Burning (BB), emissions are needed globally in near-real time as well as in consistent multi-year time series. • No suitable BB emission product is available. Principal shortcomings are accuracy, delivery time, temporal resolution, geographical coverage. • Various fire observations complement each other. • The development of a Global Fire Assimilation System (GFAS) is needed to serve the GMES requirements. • Product generation needs to exploit existing observations more completely. • FRP is very promising due to accuracy of emitted amount calculation and temporal resolution. • A quantitative study by HALO is on the way.

  18. MORE INFORMATION • www.ecmwf.int/research/EU_projects/HALO • www.ecmwf.int/research/EU_projects/GEMS • www.gmes-geoland.info • j.kaiser@ecmwf.int This work has been funded by the European Commission through the FP6 projects HALO, GEMS, and GEOLAND. ACKNOWLEDGMENTS THANK YOU!

More Related