Assimilation of remote sensing data to monitor the terrestrial carbon cycle: The carbon observatory of geoland

The existing land data assimilation projects (NLDAS, GLDAS, ELDAS) do not include interactive vegetation land surface models, which limits the use of remote sensing data. The analysed variable in LDAS is soil moisture, only, and there is a need to account for vegetation biomass to monitor the biosphere vegetation-atmosphere CO/sub 2/ exchange. The geoland Integrated Project (2004-2007) co-funded by the European Commission, aims at addressing European and global environment issues, based on the use of remote sensing data. The carbon observatory of geoland, hereinafter referred to as "geoland/Carbon", provides a pre-operational global carbon accounting system, dealing with the impact of weather and climate variability on ecosystems fluxes and carbon stocks, on daily to seasonal and inter-annual time scales. The solution chosen in geoland/Carbon is to merge the LDAS approach and the interactive vegetation models, by making two communities work together: the meteorologists involved in ELDAS and the carbon modellers. In particular, we investigate the relationship between weather and climate variability and terrestrial CO/sub 2/ fluxes. The integration of in situ meteorological measurements and different satellite remote sensing sources of information are made by using assimilation techniques. In order to integrate the existing approaches and to deliver an assessment based on independent modelling results, two land surface models are used: 1) an operational scheme (ECMWF) used in numerical weather forecast models, modified to describe an interactive vegetation (based on ISBA-A-gs, Meteo-France); 2) a carbon-water-energy land surface scheme, fitted with carbon dynamics in biomass and soil pools, and with ecosystem dynamics (LSCE). The assimilation system can be run at the global scale with both carbon models. The assimilated output fields are checked against global observations of different nature, such as eddy covariance networks, long term ecological time series (e.g. IGBP transects), forest and soil carbon inventories, or satellite products that were not used at first in the assimilation procedure. At the end of this project, ECMWF is able to propose a single near-operational system based on components of the two approaches.