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SUMMARY:Understanding uncertainty via statistical analysis of a global aer
 osol model - Lindsey Lee\, University of Leeds
DTSTART:20191126T113000Z
DTEND:20191126T123000Z
UID:TALK130423@talks.cam.ac.uk
CONTACT:Jonathan Rosser
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 over s
 uccessive IPCC reports.   We have used a statistical analysis of a single 
 global aerosol GLOMAP to better understand its sources of uncertainty.  We
  can use this uncertainty information to target research in the right plac
 es and to quantify the value of observations with respect to reducing mode
 l uncertainty.  This talk will show how statistical methods applied to thi
 s problem\, including expert elicitation\, Gaussian Process emulation and 
 sensitivity analysis have helped to understand why uncertainty in aerosol 
 radiative is not being reduced using current techniques.  I will also show
  how the work has fed into further projects aiming to reduce the uncertain
 ty in aerosol forcing and into the first multi-model perturbed parameter e
 nsemble of global aerosol models. 
LOCATION:Bullard Lab\, Seminar Room
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