caa a22 4500 605471800 CHVBK 20210128100335.0 cr unu---uuuuu 210128e20150901xx s 000 0 eng 10.1007/s00382-014-2378-z doi (NATIONALLICENCE)springer-10.1007/s00382-014-2378-z Identifying and removing structural biases in climate models with history matching [Elektronische Daten] [Daniel Williamson, Adam Blaker, Charlotte Hampton, James Salter] We describe the method of history matching, a method currently used to help quantify parametric uncertainty in climate models, and argue for its use in identifying and removing structural biases in climate models at the model development stage. We illustrate the method using an investigation of the potential to improve upon known ocean circulation biases in a coupled non-flux-adjusted climate model (the third Hadley Centre Climate Model; HadCM3). In particular, we use history matching to investigate whether or not the behaviour of the Antarctic Circumpolar Current (ACC), which is known to be too strong in HadCM3, represents a structural bias that could be corrected using the model parameters. We find that it is possible to improve the ACC strength using the parameters and observe that doing this leads to more realistic representations of the sub-polar and sub-tropical gyres, sea surface salinities (both globally and in the North Atlantic), sea surface temperatures in the sinking regions in the North Atlantic and in the Southern Ocean, North Atlantic Deep Water flows, global precipitation, wind fields and sea level pressure. We then use history matching to locate a region of parameter space predicted not to contain structural biases for ACC and SSTs that is around 1 % of the original parameter space. We explore qualitative features of this space and show that certain key ocean and atmosphere parameters must be tuned carefully together in order to locate climates that satisfy our chosen metrics. Our study shows that attempts to tune climate model parameters that vary only a handful of parameters relevant to a given process at a time will not be as successful or as efficient as history matching. Springer-Verlag Berlin Heidelberg, 2014 Tuning nationallicence Ensembles nationallicence Emulators nationallicence HadCM3 nationallicence Climate model nationallicence Williamson Daniel College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK aut Blaker Adam National Oceanography Centre, SO14 3ZH, Southampton, UK aut Hampton Charlotte College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK aut Salter James College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK aut Climate Dynamics Springer Berlin Heidelberg 45/5-6(2015-09-01), 1299-1324 0930-7575 45:5-6<1299 2015 45 382 https://doi.org/10.1007/s00382-014-2378-z text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00382-014-2378-z text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Williamson Daniel College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK aut NATIONALLICENCE 700 1- Blaker Adam National Oceanography Centre, SO14 3ZH, Southampton, UK aut NATIONALLICENCE 700 1- Hampton Charlotte College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK aut NATIONALLICENCE 700 1- Salter James College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK aut NATIONALLICENCE 773 0- Climate Dynamics Springer Berlin Heidelberg 45/5-6(2015-09-01), 1299-1324 0930-7575 45:5-6<1299 2015 45 382