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SUMMARY:Quantifying the predictive uncertainty of numerical mass balance m
 odels - Cameron Rye (University of Oxford)
DTSTART:20110216T163000Z
DTEND:20110216T173000Z
UID:TALK29738@talks.cam.ac.uk
CONTACT:Poul Christoffersen
DESCRIPTION:Spatially distributed\, physically based mass balance models a
 re valuable tools for exploring the detailed spatial and temporal response
 s of glaciers and ice sheets to climate forcing. Indeed\, the last two dec
 ades have seen their application become increasingly widespread\, partly d
 ue to the increased availability of computational resources\, and partly b
 ecause scientists have a natural tendency to adopt realistic descriptions 
 of real-world processes. However\, while considerable progress has been ma
 de in the development of sophisticated numerical models\, very little atte
 ntion has been given to their predictive uncertainty. In particular\, mass
  balance models have traditionally been calibrated (or “tuned”) in ord
 er to identify a single set of model parameters (e.g. snow density\, surfa
 ce albedo\, temperature lapse rate) such that the model’s behaviour clos
 ely matches that of the real system it represents. But\, as will be demons
 trated for a case study in Svalbard\, it is often difficult (if not imposs
 ible) to find a single “best” set of parameter values that reproduce a
 ll the characteristics of real-world observations. Instead\, multiple equa
 lly plausible parameter sets will usually exist\, which undoubtedly introd
 uces a degree of uncertainty into model forecasts. Despite knowledge of th
 is problem within the environmental science community\, there has yet to b
 e a rigorous attempt to quantify the predictive uncertainty of glacier mas
 s balance models. The present work will address this limitation through th
 e novel application of a calibration technique previously not employed in 
 glacial modelling – multi-objective optimisation – designed to identif
 y multiple optimal parameter sets that fit different characteristics of th
 e real-world observations\, thereby enabling an assessment of the uncertai
 nty associated with predictions. This is a generic methodology that can be
  applied to any type of mass balance model and to both glaciers and ice sh
 eets. Overall it is argued that a new calibration paradigm is urgently req
 uired to provide more useful information on the uncertainty associated wit
 h ongoing and future projections of ice volume and sea level rise. 
LOCATION:Scott Polar Research Institute\, main lecture theatre
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