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SUMMARY:Understanding uncertainty via statistical analysis of a global aer
 osol model - Lindsay Lee\, University of Leeds
DTSTART:20180613T130000Z
DTEND:20180613T140000Z
UID:TALK106366@talks.cam.ac.uk
CONTACT:Dr Gillian Young
DESCRIPTION:Huge investment in observations and more complex models of atm
 ospheric aerosol have improved understanding of aerosol-cloud processes bu
 t the uncertainty in aerosol radiative forcing has not been reduced.   We 
 have used a statistical analysis of a single global aerosol GLOMAP to bett
 er understand its sources of uncertainty.  We can use this uncertainty inf
 ormation to target research in the right places and to quantify the value 
 of observations with respect to reducing model uncertainty.  I will allow 
 some time to focus on what we learn about the polar regions and how we can
  use observations to help reduce model uncertainty.  This talk will show h
 ow statistical methods applied to this problem\, including expert elicitat
 ion\, Gaussian Process emulation and sensitivity analysis have helped to u
 nderstand why uncertainty in aerosol radiative is not being reduced.  
LOCATION:British Antarctic Survey\, Innovation Centre\, Seminar Room 2
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