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CARBON-TESSEL |
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The model:
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Monthly ecosystem NEE fluxes for the month of January (upper panels) and July (lower panels) for three models: C-TESSEL, CASA, SiB.
The demo shows the evolution of 1-year land surface carbon fluxes produced by the C-TESSEL scheme developed at ECMWF under the GEOLAND2 project. These fluxes have been tested in a coupled GCM/CTM within the framework of the European project GEMS in order to evaluate their impact on modelling the variation of atmospheric CO2 concentrations.
The animations show the daily variation of the NEE (Net Ecosystem Exchange) CO2 fluxes and the daily distribution of the atmospheric CO2 concentrations in the free troposphere (averaged between 500 and 700 hPa).
Within the European project GEMS, the capability of adding tracers in the NWP forecast model has been coded based on the existing modelling framework for advection, convection and vertical diffusion (ECMWF, 2007).
Various climatologies were used to describe CO2 fluxes at the surface. The terrestrial natural biosphere fluxes are from CTESSEL. They are annually balanced and were used at their hourly resolution to resolve the diurnal cycle of the natural biosphere. A linear interpolation was used to provide the fluxes at the model time step.
The air-sea CO2 exchange is described by a monthly mean climatology and is based on the revised version of Takahashi et al 2002. This version uses wind speeds from 10-m height instead of 0.995 sigma-level. Anthropogenic emissions are based on the EDGAR.3.0 1x1 degree global Map for 1990 (Olivier and Berdowski, 2001) rescaled to the CDIAC (Carbon Dioxide Information Analysis Centre) country level estimates for 1998.
These emissions are kept constant throughout the years. Finally, wildfire emissions are from the Global Fire emissions Database version 2 (van der Werf et al., 2006) and are provided at an 8-day time resolution using MODIS Fire hot spots (Giglio et al., 2003). These emissions have been injected at the surface given the lack of information on the fire intensity time evolution. Apart from wildfire emissions none of the prescribed CO2 surface fluxes is year specific. All data sets were interpolated to the horizontal resolution of the model. Our runs are done at a resolution of approximately 1.125x1.125 degree and 60 sigma hybrid levels (T159L60).
ECMWF, 2007 IFS documentation, http://www.ecmwf.int/research/ifsdocs/CY31r1/index.html
GEMS, http://gems.ecmwf.int/
GEOLAND2, http://www.gmes-geoland.info/
Giglio, L., Descloitres, J., Justice, C.O., Kaufman, Y. 2003. An enhanced contextual fire detection algorithm for MODIS. Remote Sensing of Environment, 87:273-282.
Gibelin, A.-L., J.-C. Calvet, J.-L. Roujean, L. Jarlan, and S. O. Los (2006), Ability of the land surface model ISBA-A-gs to simulate leaf area index at the global scale: Comparison with satellites products, Journal of Geophysical Research, 111, D18102, doi:10.1029/2005JD006691.
Jarlan, L., G. Balsamo, S. Lafont, A. Beljaars, J.C. Calvet and E. Mougin, 2007: Analysis of Leaf Area Index in the ECMWF land surface scheme and impact on latent heat and carbon fluxes: Applications to West Africa, ECMWF Tech. memo. 544 [pdf].
Lafont S., A. Beljaars, M. Voogt, L. Jarlan, P. Viterbo, B. van den Hurk, J.-C. Calvet, 2006: Comparison of C-TESSEL CO2 fluxes with TransCom CO2 fluxes. Proc. Second Recent Advances in Quantitative Remote Sensing II, Torrent (Valencia), Spain, 26-29 September 2006.
Olivier, J. G. J., Berdowski, J. J. M. (2001). Global emissions sources and sinks. In The Climate SystemJ. Berdowski, R. Guicherit,B. J. Heij, Lisse, The Netherlands: A.A. Balkema Publishers/Swets and Zeitlinger Publishers, pp. 33-78
Takahashi, T., Sutherland, S. C., Sweeney, C., Poisson, A., Metzl, N., Tillbrook, B., Bates, N., Wanninkhof, R., Feely, R. A., Sabine, C., Olafsson, J. and Nojiri, Y. (2002). Global sea-air CO2 flux based on climatological surface ocean pCO2, and seasonal biological and temperature effects, Deep-Sea Res. II, 49, 1601-1622.
Van der Werf, G.R., J.T. Randerson, L. Giglio, G.J. Collatz, P.S. Kasibhatla, and A.F. Arellano, Jr. 2006. Interannual variability in global biomass burning emissions from 1997 to 2004. Atmospheric Chemistry and Physics. 6: 3423\x{2013}3441.
| 04.09.2008 |
| © ECMWF |