Abstract
Abstract. Assimilation of in situ and satellite data in mechanistic terrestrial ecosystem models helps to constrain critical model parameters and reduce uncertainties in the simulated energy, water and carbon fluxes. So far the assimilation of eddy covariance measurements from flux-tower sites has been conducted mostly for individual sites ("single-site" optimization). Here we develop a variational data assimilation system to optimize 21 parameters of the ORCHIDEE biogeochemical model, using net CO2 flux (NEE) and latent heat flux (LE) measurements from 12 temperate deciduous broadleaf forest sites. We assess the potential of the model to simulate, with a single set of inverted parameters, the carbon and water fluxes at these 12 sites. We compare the fluxes obtained from this "multi-site" (MS) optimization to those of the prior model, and of the "single-site" (SS) optimizations. The model-data fit analysis shows that the MS approach decreases the daily root-mean-square difference (RMS) to observed data by 22%, which is close to the SS optimizations (25% on average). We also show that the MS approach distinctively improves the simulation of the ecosystem respiration (Reco), and to a lesser extent the gross primary productivity (GPP), although we only assimilated net CO2 flux. A process-oriented parameter analysis indicates that the MS inversion system finds a unique combination of parameters which is not the simple average of the different SS sets of parameters. Finally, in an attempt to validate the optimized model against independent data, we observe that global-scale simulations with MS optimized parameters show an enhanced phase agreement between modeled leaf area index (LAI) and satellite-based observations of normalized difference vegetation index (NDVI).
Highlights
Terrestrial ecosystem models have been a tool of growing importance in order to understand and simulate the behavior of land ecosystems and their response to various disturbances, be it natural or anthropogenic
The present study further investigates the potential of the simultaneous assimilation of carbon net ecosystem exchange (NEE) and latent heat (LE) flux measurements from an ensemble of flux towers situated in temperate deciduous broadleaf forests (DBF)
The error bars on the left part represent for both fluxes the total uncertainty averaged over all the periods: σtotal = σp2aram + σm2odel, (3)
Summary
Terrestrial ecosystem models have been a tool of growing importance in order to understand and simulate the behavior of land ecosystems and their response to various disturbances, be it natural or anthropogenic. Mechanistic terrestrial ecosystem models are widely used to assess the current land carbon balance (Sitch et al, 2008) and to predict its future evolution under climate change (Friedlingstein et al, 2006; Cox et al, 2000), as a major driver of the future climate itself In this context, there has been a growing effort to evaluate and validate the simulated carbon fluxes and stocks against in situ or remote sensing observations. We investigate the potential of eddy-covariance flux measurements from a dozen FLUXNET sites (http://fluxnet.ornl.gov/; Baldocchi et al, 2001, 2008) to improve a global process-based ecosystem model, ORCHIDEE (Krinner et al, 2005) These data provide near-continuous in situ measurements of carbon dioxide, water and energy fluxes; measurements are currently conducted at more than 500 sites, spanning a wide range of climate regimes and vegetation types worldwide. We focus on modeling deciduous broadleaf forests, which are well represented in the FLUXNET database
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
