Upgrade of the HadGEM3-A based attribution system to high resolution and a new validation framework for probabilistic event attribution

After discussing the framing issues surrounding questions that can be asked with our system we construct a novel approach to the evaluation of atmosphere-only ensembles intended for event attribution, in the process highlighting and clarifying the distinction between hindcast skill and model performance. A framework based around assessing model representation of predictable components and ensuring exchangeability of model and real world statistics leads to a form of detection and attribution to boundary condition forcing as a means of quantifying one degree of freedom of potential model error and allowing for the bias correction of event probabilities and resulting probability ratios. This method is then applied systematically across the globe to assess contributions from anthropogenic influence and specific boundary conditions to the changing probability of observed and record seasonal mean temperatures of four recent 3-month seasons from March 2016-February 2017.