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SUMMARY:The statistical challenges in tackling persistent climate model un
 certainty through model-observation comparisons. - Dr Jill S Johnson\; Sch
 ool of Mathematical and Physical Sciences\, University of Sheffield\, UK
DTSTART:20250624T130000Z
DTEND:20250624T140000Z
UID:TALK232384@talks.cam.ac.uk
CONTACT:Yao Ge
DESCRIPTION:Abstract: \nThe effects of aerosols on the Earth’s energy ba
 lance since pre-industrial times (aerosol radiative forcing) has significa
 ntly and repeatedly dominated the uncertainty in reported estimates of glo
 bal temperature change from the IPCC. The magnitude of aerosol radiative f
 orcing of climate over the industrial period is estimated to lie between a
 bout -2 and -0.4 W m-2\, compared to a much better understood forcing of 1
 .6 to 2.0 W m-2 due to CO2.\nIn this seminar\, past efforts to quantify th
 e range of possible aerosol forcings predicted from an aerosol-climate mod
 el that are caused by parametric uncertainty\, and to constrain that forci
 ng uncertainty through model-observation comparison using extensive aeroso
 l and cloud-based measurements from ships\, flight campaigns\, satellites 
 and ground stations\, will be discussed. We find that despite a very large
  reduction in plausible parameter space and reasonable constraint on obser
 vable properties\, the observational constraint based on this comprehensiv
 e set of measurements only partially reduces the range of aerosol radiativ
 e forcings from our model.\nIn the NERC project ‘Towards Maximum Feasibl
 e Reduction in Aerosol Forcing Uncertainty’ (Aerosol-MFR)\, several key 
 statistical challenges highlighted from this work are being addressed in o
 rder to improve the model-observation comparison process for uncertainty c
 onstraint. This includes optimising the way observational constraints are 
 applied\, designing new approaches for reducing error compensation effects
  and using the PPE to identify and characterise model structural errors. P
 reliminary results from the project so far will be outlined\, along with f
 urther plans to tackle this important problem.\n\nBiography:  \nDr Jill Jo
 hnson is a Lecturer in Statistics in the School of Mathematical and Physic
 al Sciences at the University of Sheffield. Her research interests are in 
 the development and practical application of statistical methods to quanti
 fy\, assess and then reduce uncertainty in large-scale complex models of r
 eal-world systems\, with a focus on problems in environmental science. \nP
 rior to joining Sheffield in August 2021\, Jill worked as an applied stati
 stician / research associate for over 8 years in the aerosol research grou
 p at the Institute for Climate and Atmospheric Science\, University of Lee
 ds\, where her work focussed on the quantification and constraint of key u
 ncertainties in models of the atmosphere and climate. Her current research
  builds on this work\, including the NERC research project ‘Towards Maxi
 mum Feasible Reduction in Aerosol Forcing Uncertainty (Aerosol-MFR)’.\n
LOCATION:Chemistry Dept\, Unilever Lecture Theatre and Teams
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