A global sensitivity analysis and Bayesian inference framework for improving the parameter estimation and prediction of a process-based Terrestrial Ecosystem Model

Journal of Geophysical Research Atmospheres

Volumn 114, Issue 15, 2009, Pages

  Tang, Jinyun ^a,b   Zhuang, Qianlai ^a,b  

^a PURDUE UNIVERSITY   (United States)

^b PURDUE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ANALYTICAL GEOCHEMISTRY; BAYESIAN NETWORKS; BIOCHEMISTRY; BIOGEOCHEMISTRY; ECOSYSTEMS; FORECASTING; FORESTRY; INFERENCE ENGINES; PARAMETER ESTIMATION; PHOTOSYNTHESIS; SIMULATORS; UNCERTAINTY ANALYSIS;

AUTOTROPHIC RESPIRATION; BAYESIAN FRAMEWORKS; BAYESIAN INFERENCE; BAYESIAN INFERENCE ANALYSIS; BLACK SPRUCE FORESTS; CARBON DYNAMICS; CARBON FLUXES; ECOSYSTEM RESPIRATION; EDDY FLUXES; EFFECT OF PARAMETERS; ENSEMBLE SIMULATION; ERROR STRUCTURES; GLOBAL SENSITIVITY ANALYSIS; GROSS PRIMARY PRODUCTION; HYPERCUBE; INTERACTION STRUCTURES; KEY MODELS; MODEL PREDICTION; MONTE CARLO ENSEMBLE; PHOTOSYNTHETICALLY ACTIVE RADIATION; SATELLITE DATA; SATURATION CONSTANT; TEM; TEMPERATURE INCREASE; TERRESTRIAL ECOSYSTEMS; TIME STEP; UNCERTAINTY BOUNDS;

SENSITIVITY ANALYSIS;

BAYESIAN ANALYSIS; BIOGEOCHEMISTRY; CARBON DIOXIDE; CARBON FLUX; EDDY; LATENT HEAT FLUX; PHOTOSYNTHETICALLY ACTIVE RADIATION; RESPIRATION; SENSITIVITY ANALYSIS; TERRESTRIAL ECOSYSTEM;

PICEA MARIANA;

EID: 70350066343     PISSN: 01480227     EISSN: None     Source Type: Journal    
DOI: 10.1029/2009JD011724     Document Type: Article

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