1. PEcAn UNCERTAINTY
ANALYSIS
LTER ASM
2018
@PEcAnProject
@mcdietze

2. Parameter
Uncertainty
Sensitivit
yOutput
Uncertainty
Trait meta-analysis (AUTOMATED)
Iterative Bayesian calibration
(WEB)
(AUTOMATED
)
(AUTOMATED
)

3. 3

4. Variance Decomposition
*can easily be extended to
driver and IC uncertainties
*
Prior
Posterior
Parameter
Uncertainty
Sensitivit
y
Output
Uncertainty

7. • 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-

8. Characterize
Propagate
Analyze
Reduce

9. 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