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J.-F. Müller, J. Stavrakou, S. Wallens Belgian Institute for Space Aeronomy, Brussels, Belgium IUGG Symposium, July 2007 Interannual variability of biogenic VOC emissions estimated from the MEGAN model and ECMWF analyses A. Guenther National Center for Atmospheric Research, Boulder, Colo., USA Thanks to: J. Rinne (Univ. Helsinki), M. Potosnak (Desert Res. Institute), B. Munger and S. Wofsy (Harvard Univ.), A. Goldstein (Univ. California), M. Van Roozendael and I. De Smedt (IASB, Brussels)
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Outline MEGAN model : emission algorithm MOHYCAN model: canopy environment model Results: Inventory for 1995-2006 Interannual variability Comparison with campaign data Evaluation using GOME HCHO data
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MEGAN model for estimating the emissions of isoprene from plant foliage = emission rate in standard conditions, = response functions to radiation and temperature at leaf level = dependence to leaf age = dependence to soil moisture stress LAI = Leaf Area Index LAI from MODIS 2000-2006 ECMWF analyses provide: canopy top values of downward solar radiation, temperature, wind, and humidity + cloudiness + soil moisture in 4 layers values inside the canopy require a multi-layer canopy model (MOHYCAN) (Wallens, 2004; Müller et al., 2007) ε
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Results : Emissions in 2003 Very similar to distribution obtained by Guenther et al. (ACP2006) using NCEP meteorological data, except over arid areas
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Results: Impact of soil moisture stress Large reduction over arid areas Global annual emissions reduced by > 20%
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Results: Impact of using leaf (instead of air) temperature in the algorithm Global annual emission increased by 18%
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Results: Zonally averaged emissions Global annual emission is ~30% than in Guenther et al. (1995, 2006) Large interannual variability (20% difference between extreme years)
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Isoprene emissions and El Niño
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Comparison with campaign data: Harvard forest, Mass., 1995 Diurnal cycle is OK Day-to-day variations very well reproduced Overestimation in spring/fall
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Comparison with campaign data: Tapajos, Amazonia, 2000, 2001, 2003 (Here model results scaled down by factor 1.7) Wet season fluxes (April-July) largely overestimated by model
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GOME HCHO data Slant columns retrieved at IASB-BIRA (I. De Smedt, M. Van Roozendael) from GOME spectra using the WinDOAS technique Fitting window chosen to avoid artefacts over desert areas and reduce noise Vertical HCHO profiles taken from IMAGES CTM http://www.temis.nlhttp://www.temis.nl, De Smedt et al., in preparation
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Vertical HCHO columns calculated by the IMAGES CTM (curves) and retrieved from GOME (diamonds) Using GEIA inventory Using MEGAN- based inventory Id., neglecting soil moisture stress
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Conclusions Isoprene emission inventory 1995-2006 at 0.5°x0.5° resolution available at http://www.oma.be/TROPO/inventory.html in NetCDF format http://www.oma.be/TROPO/inventory.html Müller et al., will be soon submitted to ACP Soil moisture stress might have a big impact, but the calculated effect depends on choice of meteorological data + wilting point database Global emission is ~410 Tg/year Large interannual variability, to a great extent related to El Niño Short-term variations of isoprene emissions well captured by model, not so much the seasonal variation Satellite HCHO : a promising tool for constraining the emission distribution and variability also in Tropical regions
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