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SUMMARY:How can we ensemble geophysical models better? - Matt Amos | Unive
 rsity of Lancaster
DTSTART:20210518T100000Z
DTEND:20210518T113000Z
UID:TALK159058@talks.cam.ac.uk
CONTACT:87364
DESCRIPTION:Ensembles of geophysical models are typically used to increase
  the accuracy of projections and to allow for the quantification of projec
 tive uncertainties. However\, the landscape of these models is complicated
  with model components being shared between institutions (meaning they're 
 not independent)\, compounded by the fact that models are not equally good
 . When ensembling models together\, we need methods that can account for t
 he complicated interconnections between models and the variable model perf
 ormance.\n\nIn this talk\, I'll introduce the concept of ensembling models
  and how we might go about doing this better\, to consider variable model 
 skill and model dependence. I'll present two applications of model ensembl
 ing: a process-based weighting to project ozone hole recovery\, and Bayesi
 an neural network method to infill gaps in historic ozone records using an
  ensemble of models. Though the applications are specific these methods ar
 e widely applicable to any user of ensembles of environmental models.
LOCATION:https://zoom.us/j/6708259482?pwd=Qk03U3hxZWNJZUZpT2pVZnFtU2RRUT09
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