1. THE NEED FOR DATA/MODEL INTEGRATION
Retrodiction/prediction is meaningless without meaningful error bars or probability distribution of model results
Major challenge for climate change assessments
Are PMIP/observation discrepancies due to faulty boundary conditions or to problems in the models?
even dynamical process modelling needs constraints on boundary conditions
for under-constrained systems need data/physics integration -> calibrate model against observational data

2. Criteria for calibration methodology
Complicated under-constrained non-linear system with threshold behavior
effectively large number of poorly constrained model parameters
Large set of diverse noisy constraint data
Data and & model limitations -> need a fundamentally probabilistic approach
bumpy phase and likelihood spaces (shown below) further rule out gradient-based approaches such as adjoint (eg. 4D var) methods
-> stochastic methodology
accurate propagation of data uncertainties -> Bayesian approach
=> Markov Chain Monte Carlo

3. Bayesian calibration
Sample over posterior probability distribution for the ensemble parameters given fits to observational data using Markov Chain Monte Carlo (MCMC) methods
Other constraints:
Minimize margin forcing
LGM ice volume bounds
Hudson Bay glaciated at -25 kyr
Post MCMC scoring:
Marine Limits
Strandlines

4. Large ensemble Bayesian calibration
Bayesian neural network integrates over weight space
Self-regularized
Can handle local minima

5. It works

6. Bumpy likelihood space

7. Another data/model link: guide future data collection

8. North American Climate and meltwater phasing -> meltwater/iceberg discharge is a critical link between cryosphere and climate system

9. The meltwater link
Need more marine observations to corroborate/refute results
What happens to a meltwater plume in the Arctic Ocean?
Mixing dynamics in the GIN Seas?

10. A couple of other interim results
The calibration tends to favour an ice volume for North America that is too low to meet global LGM eustatic constraints
-> can be addressed by strong H2/H1/mwp1-a events
-> also starting to give consideration to larger marine components (especially given recent HOTRAX data)

11. Where to:
Completion of interim global calibrated deglacial ice/meltwater chronology
EMIC/GCM recursion to get climatological self-consistency
Calibration of glacial inception ice & climate with the glacial systems model coupled to a reduced AOGCM
Ditto for deglaciation
-> forward in time: P(future cryospheric evolution)
eventual calibration of full glacial cycle ice & climate