GLAC-GR2: a joint glaciological and earth rheology Bayesian calibration for the last glacial cycle of the Greenland ice sheet.

Paleo ice sheet reconstructions without confident uncertainty bounds have limited value. Forapproaches based on glaciological models, such bounds require a model that adequatelyprobes uncertainties in both climate and ice processes along with a rigorous methodology forusing paleo-observations to constrain this probe. To date, deglacial reconstructions of theGreenland ice sheet either do not specify uncertainty bounds or have low confidence in theirderived bounds. This is due in good part to limited probing of model uncertainties and solereliance on climate forcings based on glacial indices derived from GRIP or GISPII ice corerecords. To rectify these limitations, we use the 3D Glacial Systems Model (GSM) withasynchronously coupled glacial isostatic adjustment (including a first order gravitationalcorrection and accounting for ice load contributions from other ice sheets). Model gridresolution is about 25 km and model runs are over the last two glacial cycles. The climatecomponent is distinguished by a calibrated weighting of diverse climate representations,including a two-way coupled 2D Energy Balance Climate model that has no dependence onGreenland ice core records. Calibrated model parameters also account for uncertainties in icecalving and submarine melt, basal drag, deep geothermal heat flux, and earth viscositystructure. The calibration was against a large set of relative sea level observations, constraints on iceextent from cosmogenic dates, and borehole temperature records from the Greenland ice coresites. The inversion invokes Bayesian artificial neural network emulators of the GSM toenable effective multi-million point Markov Chain Monte Carlo sampling of chronologies.Calibration results will be presented for the whole last glacial cycle with a focus on max/minbounds, comparison against previous chronological inferences, and remaining data/modelmisfits. [ABSTRACT FROM AUTHOR]