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

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

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

Large ensemble Bayesian calibration

Bayesian neural network integrates over weight space

Self-regularized Can handle local minima

It works

Bumpy likelihood space

Another data/model link: guide future data collection

North American Climate and meltwater phasing ->

meltwater/iceberg discharge

is a critical link between cryosphere and climate

system

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?

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)

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