Research · Terrestrial Ecology
Development of the AmeriFlux Data Assimilation System (ADAS)
The objective of the project begun in late 2003 is to develop an AmeriFlux Data Assimilation System to integrate eddy covariance flux tower observations, site complementary information and mechanistic land surface models to generate synthetic, value-added products (reanalysis datasets and non-observable variables) that are spatially and temporally uniform and biophysically and biogeochemically consistent to support AmeriFlux network-wide synthesis activities and the North American Carbon Program's multi-scale initiatives in carbon budget studies. This project will produce solutions for the best use of available resources and greatly enhance the values of data products being collected by the AmeriFlux network and land surface models that have been developed. The synthetic products from the project will benefit researches in a wide range of areas including land atmosphere interactions, climate modeling, and terrestrial carbon and hydrological cycles.
To explore effective and efficient methodologies for integrated land surface flux data assimilation and develop an operational land surface flux data assimilation system. Our specific tasks include:
We use a variational framework for our flux data assimilation system. The forward model is the terrestrial Fluxes And Pools Integrated Simulator (FAPIS). The FAPIS model includes all processes that are known to affect land - atmosphere flux exchanges of CO2, water vapor, sensible heat, momentum, shortwave and longwave radiation. It separates diffuse and direct radiation and sunlit and shaded leaves for both carbon assimilation and energy balance calculations. It predicts vertical gradients in meteorological conditions within the canopy and flux exchanges in each layer are computed with local environmental conditions. It couples simulations of canopy and soil processes directly rather than explicitly. It has detailed treatments in both carbon and hydrological cycles. These rigorous representations of biophysical and ecophysiological processes are essential for successful flux data assimilation. The structure of the FAPIS model has been designed specifically for automatic generation of adjoint code for numerical optimization. Different optimization techniques are used in the assimilation.
The major observational variables assimilated into the system through a cost functional include flux exchanges of CO2, water vapor, sensible heat, momentum, reflected shortwave and outgoing longwave radiation. A nighttime flux filter is employed to detect the influence of low turbulence. The forward model is optimized for ecosystem state and critical parameters (e.g. LAI, Vcmax, Jmax, TPU, parameters describing their vertical distributions in the canopy, parameters in the soil respiration model, etc.). Because FAPIS predicts vertical profiles of CO2 concentration, water vapor concentration and temperature, these profiles can be assimilated to provide further model parameter constraints.
Results to Date
Data assimilation software development has been the main focus of the project so far. New codes consisting of tens of thousands of lines have been developed and tested for forward modeling and optimization. An objective and automatic nighttime flux filter (Moving Point Test, or MPT) has been developed and published. MPT have been adopted by several users in AmeriFlux as well as in CarboEurope and AsiaFlux and technical support has been provided to them. In collaboration with the Missouri Ozark AmeiFlux project, a new comprehensive optimization method has been developed for A/Ci curve analysis. This new method completely removes the need of a priori selection of critical internal CO2 partial pressure (Ci) values for estimating leaf biochemical parameters from A/Ci measurements in conventional A/Ci curve analysis methods, which can cause serious errors in estimated biochemical parameters and cause biases in ecosystem models that use these parameters. A software package (OptimalACi) has been developed for sharing with the community. Time series of soil respiration measurements have been used successfully to estimate soil carbon stocks through a multi-pool carbon model and its adjoint model. During our data assimilation effort, we have developed several novel approaches for analyzing flux data, particularly soil efflux data. These approaches have led to a few important findings regarding dynamics in soil respiration and its relationship to photosynthesis and soil carbon pool variations:
Liu, Q., N.T. Edwards, W.M. Post, L. Gu, J. Ledford, and S. Lenhart, 2005. Photosynthesis-driven signal in soil efflux observed from a deciduous forest FACE site, Global Change Biology (in review).
Gu, L., S. G. Pallardy, P. Hanson and S. D. Wullschleger, 2005. A comprehensive optimization method for objective estimation of parameters in biochemical models of leaf photosynthesis, Plant Cell and Environment (in review).
Gu, L., E.M. Falge, T. Boden, D. D. Baldocchi, T. A. Black, S. R. Saleska, T. Suni, S. B. Verma, T. Vesala, S. C. Wofsy, and L. Xu, 2005. Objective threshold determination for nighttime eddy flux filtering, Agricultural and Forest Meteorology, 128, 179-197.
Gu, L. W. M. Post, and A. W. King. Fast labile carbon turnover obscures sensitivity of heterotrophic respiration from soils to temperature: a model analysis, Global Biogeochemical Cycles. Global Biogeochemical Cycles, Vol. 18, Gb1022, Doi:10.1029/2003gb002119, 2004.
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