@article{oai:tsukuba.repo.nii.ac.jp:00040338, author = {松枝, 未遠 and Schiemann, Reinhard and Demory, Marie-Estelle and Shaffrey, Len C. and Strachan, Jane and Vidale, Pier Luigi and Mizielinski, Matthew S. and Roberts, Malcolm J. and Matsueda, Mio and Wehner, Michael F. and Jung, Thomas}, issue = {1}, journal = {Journal of climate}, month = {Jan}, note = {The aim of this study is to investigate if the representation of Northern Hemisphere blocking is sensitive to resolution in current-generation atmospheric global circulation models (AGCMs). An evaluation is conducted of how well atmospheric blocking is represented in four AGCMs whose horizontal resolution is increased from a grid spacing of more than 100 km to about 25 km. It is shown that Euro-Atlantic blocking is simulated overall more credibly at higher resolution (i.e., in better agreement with a 50-yr reference blocking climatology created from the reanalyses ERA-40 and ERA-Interim). The improvement seen with resolution depends on the season and to some extent on the model considered. Euro-Atlantic blocking is simulated more realistically at higher resolution in winter, spring, and autumn, and robustly so across the model ensemble. The improvement in spring is larger than that in winter and autumn. Summer blocking is found to be better simulated at higher resolution by one model only, with little change seen in the other three models. The representation of Pacific blocking is not found to systematically depend on resolution. Despite the improvements seen with resolution, the 25-km models still exhibit large biases in Euro-Atlantic blocking. For example, three of the four 25-km models underestimate winter northern European blocking frequency by about one-third. The resolution sensitivity and biases in the simulated blocking are shown to be in part associated with the mean-state biases in the models’ midlatitude circulation.}, pages = {337--358}, title = {The Resolution Sensitivity of Northern Hemisphere Blocking in Four 25-km Atmospheric Global Circulation Models}, volume = {30}, year = {2017} }