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contributor authorSparrow, Sarah
contributor authorMillar, Richard J.
contributor authorYamazaki, Kuniko
contributor authorMassey, Neil
contributor authorPovey, Adam C.
contributor authorBowery, Andy
contributor authorGrainger, Roy G.
contributor authorWallom, David
contributor authorAllen, Myles
date accessioned2019-09-19T10:09:37Z
date available2019-09-19T10:09:37Z
date copyright3/20/2018 12:00:00 AM
date issued2018
identifier otherjcli-d-17-0514.1.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4262207
description abstractAbstractA very large ensemble is used to identify subgrid-scale parameter settings for the HadCM3 model that are capable of best simulating the ocean state over the recent past (1980?2010). A simple particle filtering technique based upon the agreement of basin mean sea surface temperature (SST) and upper 700-m ocean heat content with EN3 observations is applied to an existing perturbed physics ensemble with initial conditions perturbations. A single set of subgrid-scale parameter values was identified from the wide range of initial parameter sets that gave the best agreement with ocean observations for the period studied. The parameter set, different from the standard model parameters, has a transient climate response of 1.68 K. The selected parameter set shows an improved agreement with EN3 decadal-mean SST patterns and the Atlantic meridional overturning circulation (AMOC) at 26°N as measured by the Rapid Climate Change (RAPID) array. Particle filtering techniques as demonstrated here could have a useful role in improving the starting point for traditional model-tuning exercises in coupled climate models.
publisherAmerican Meteorological Society
titleFinding Ocean States That Are Consistent with Observations from a Perturbed Physics Parameter Ensemble
typeJournal Paper
journal volume31
journal issue12
journal titleJournal of Climate
identifier doi10.1175/JCLI-D-17-0514.1
journal fristpage4639
journal lastpage4656
treeJournal of Climate:;2018:;volume 031:;issue 012
contenttypeFulltext


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