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Asm2018 6 dietze

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Asm2018 6 dietze

  1. 1. PEcAn UNCERTAINTY ANALYSIS LTER ASM 2018 @PEcAnProject @mcdietze
  2. 2. Parameter Uncertainty Sensitivit yOutput Uncertainty Trait meta-analysis (AUTOMATED) Iterative Bayesian calibration (WEB) (AUTOMATED ) (AUTOMATED )
  3. 3. 3
  4. 4. Variance Decomposition *can easily be extended to driver and IC uncertainties * Prior Posterior Parameter Uncertainty Sensitivit y Output Uncertainty
  5. 5. • Growth Respiration: sensitivity • Root water uptake: data deficient • Stomatal conductance: • Conif: sensitivity increases North -> South • Hardwood: var in data • Quantum Efficiency: data deficient at high lat. Dietze et al 2014 JGR-
  6. 6. Characterize Propagate Analyze Reduce
  7. 7. http://pecanproject.org https://github.com/PecanProject NSF ABI #1458021, DIBBS #1261582, EF #1318164, EF #1241894, EF#1638577, EF #1702996, NASA 13-TE13-0060, 16-CMS16-0007, DOD SERDB, Amazon AWS, Google GSoC

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