Project Funding: 2005 - 2008

NRA: 2004 NASA: Carbon Cycle Science   

Funded by NASA

Abstract:
We are developing a generalized framework for flux estimation from multiple streams of carbon observations, including spectral vegetation and land cover imagery, eddy covariance flux observations, meteorological data, and both in-situ and remotely sensed observations of atmospheric carbon gases. This will be accomplished using Ensemble Data Assimilation (EnsDA) techniques applied to a fully coupled model of regional meteorology, ecosystem carbon fluxes, and biomass burning (SiB-CASA-RAMS). Terrestrial carbon fluxes over North America due to photosynthesis, autotrophic respiration, decomposition, and fires, and a “residual” time-mean source or sink will be simulated by the model. Unknown parameters related to light response, allocation, drought stress, phenological triggers, combustion efficiency, PBL entrainment, convective efficiency, and the time-mean sink will be estimated to obtain optimum consistency with a wide variety of ecological, meteorological, and trace gas observations. The EnsDA method does not require the development of an adjoint of the coupled model, but rather applies an optimization method that involves a large ensemble of forward simulations. Unlike previous high-resolution inversions using transport model adjoint methods, we will not assume surface fluxes remain constant on monthly time scales, and we will not treat the transport model as “perfect.” Parameters in the forward coupled model will be quantitatively estimated, as will transport model error. The model will be integrated on a 20-km grid over a domain including most of North America and adjacent oceans, with lateral boundary conditions specified from the output of a global model. In the first year of the proposed research, we continued development and local testing of the coupled SiB-CASA model, including new modules for allocation, autotrophic respiration, and decomposition. We have also built a prototype of the EnsDA system using a greatly simplified version of the transport based on a Lagrangian Particle Dispersion Model (LPDM). We are now testing the EnsDA system using synthetic data generated by the forward coupled model, holding the transport constant and known, and evaluating assumptions about the spatial and temporal covariance of forward model error. In year 3, we will test our prototype EnsDA system with real observations by the maturing NACP system, including meteorological data assimilation, transport error estimation, and model improvement. Finally, we will work with appropriate partners to transfer the EnsDA framework to an operational center for continued analysis and source/sink estimation from available data.

Publications:

Lokupitiya, R. S., Zupanski, D., Denning, A. S., Kawa, S. R., Gurney, K. R., Zupanski, M. 2008. Estimation of global CO2fluxes at regional scale using the maximum likelihood ensemble filter. Journal of Geophysical Research. 113(D20). DOI: 10.1029/2007JD009679

More details may be found in the following project profile(s):

• NASA Terrestrial Ecology (TE) Project Profile
• North American Carbon Program (NACP) Project Profile