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contributor authorLiu, Y.
contributor authorLiu, Z.
contributor authorZhang, S.
contributor authorJacob, R.
contributor authorLu, F.
contributor authorRong, X.
contributor authorWu, S.
date accessioned2017-06-09T17:08:59Z
date available2017-06-09T17:08:59Z
date copyright2014/09/01
date issued2014
identifier issn0894-8755
identifier otherams-80164.pdf
identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4223026
description abstractarameter estimation provides a potentially powerful approach to reduce model bias for complex climate models. Here, in a twin experiment framework, the authors perform the first parameter estimation in a fully coupled ocean?atmosphere general circulation model using an ensemble coupled data assimilation system facilitated with parameter estimation. The authors first perform single-parameter estimation and then multiple-parameter estimation. In the case of the single-parameter estimation, the error of the parameter [solar penetration depth (SPD)] is reduced by over 90% after ~40 years of assimilation of the conventional observations of monthly sea surface temperature (SST) and salinity (SSS). The results of multiple-parameter estimation are less reliable than those of single-parameter estimation when only the monthly SST and SSS are assimilated. Assimilating additional observations of atmospheric data of temperature and wind improves the reliability of multiple-parameter estimation. The errors of the parameters are reduced by 90% in ~8 years of assimilation. Finally, the improved parameters also improve the model climatology. With the optimized parameters, the bias of the climatology of SST is reduced by ~90%. Overall, this study suggests the feasibility of ensemble-based parameter estimation in a fully coupled general circulation model.
publisherAmerican Meteorological Society
titleEnsemble-Based Parameter Estimation in a Coupled General Circulation Model
typeJournal Paper
journal volume27
journal issue18
journal titleJournal of Climate
identifier doi10.1175/JCLI-D-13-00406.1
journal fristpage7151
journal lastpage7162
treeJournal of Climate:;2014:;volume( 027 ):;issue: 018
contenttypeFulltext


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