1 / 13

J.-F. Müller, J. Stavrakou, S. Wallens Belgian Institute for Space Aeronomy, Brussels, Belgium

Interannual variability of biogenic VOC emissions estimated from the MEGAN model and ECMWF analyses. J.-F. Müller, J. Stavrakou, S. Wallens Belgian Institute for Space Aeronomy, Brussels, Belgium. A. Guenther National Center for Atmospheric Research, Boulder, Colo., USA.

crwys
Download Presentation

J.-F. Müller, J. Stavrakou, S. Wallens Belgian Institute for Space Aeronomy, Brussels, Belgium

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. Interannual variability of biogenic VOC emissions estimated from the MEGAN model and ECMWF analyses J.-F. Müller, J. Stavrakou, S. Wallens Belgian Institute for Space Aeronomy, Brussels, Belgium 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) IUGG Symposium, July 2007

  2. 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

  3. 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 ε • 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)

  4. Results : Emissions in 2003 Very similar to distribution obtained by Guenther et al. (ACP2006) using NCEP meteorological data, except over arid areas

  5. Results: Impact of soil moisture stress Large reduction over arid areas Global annual emissions reduced by > 20%

  6. Results: Impact of using leaf (instead of air) temperature in the algorithm Global annual emission increased by 18%

  7. Results: Zonally averaged emissions Global annual emission is ~30% than in Guenther et al. (1995, 2006) Large interannual variability (20% difference between extreme years)

  8. Isoprene emissions and El Niño

  9. Comparison with campaign data: Harvard forest, Mass., 1995 Diurnal cycle is OK Day-to-day variations very well reproduced Overestimation in spring/fall

  10. 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

  11. 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.nl, De Smedt et al., in preparation

  12. 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

  13. Conclusions • Isoprene emission inventory 1995-2006 at 0.5°x0.5° resolution available at http://www.oma.be/TROPO/inventory.html in NetCDF format • 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 Thank you for your attention

More Related