Open AccessAn Assessment of Multimodel Simulations for the Variability of Western North Pacific Tropical Cyclones and Its Association with ENSO
Author(s) -
Ru Han,
Hui Wang,
Zeng Zhen Hu,
Arun Kumar,
Weijing Li,
Lindsey N. Long,
Jae Schemm,
Peitao Peng,
Wanqiu Wang,
Dong Si,
Xiaoyang Jia,
Ming Zhao,
Gabriel A. Vecchi,
Timothy E. LaRow,
Yin Cheng Lim,
Siegfried D. Schubert,
Suzana J. Camargo,
Naomi Henderson,
J. Jonas,
Kevin Walsh
Publication year - 2016
Publication title -
journal of climate
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.315
H-Index - 287
eISSN - 1520-0442
pISSN - 0894-8755
DOI - 10.1175/jcli-d-15-0720.1
Subject(s) - climatology , predictability , tropical cyclone , el niño southern oscillation , environmental science , sea surface temperature , climate model , la niña , pacific decadal oscillation , multivariate enso index , ensemble average , atmospheric sciences , climate change , geology , oceanography , mathematics , statistics
An assessment of simulations of the interannual variability of tropical cyclones (TCs) over the western North Pacific (WNP) and its association with El Niño–Southern Oscillation (ENSO), as well as a subsequent diagnosis for possible causes of model biases generated from simulated large-scale climate conditions, are documented in the paper. The model experiments are carried out by the Hurricane Work Group under the U.S. Climate Variability and Predictability Research Program (CLIVAR) using five global climate models (GCMs) with a total of 16 ensemble members forced by the observed sea surface temperature and spanning the 28-yr period from 1982 to 2009. The results show GISS and GFDL model ensemble means best simulate the interannual variability of TCs, and the multimodel ensemble mean (MME) follows. Also, the MME has the closest climate mean annual number of WNP TCs and the smallest root-mean-square error to the observation. Most GCMs can simulate the interannual variability of WNP TCs well, with stronger TC activities during two types of El Niño—namely, eastern Pacific (EP) and central Pacific (CP) El Niño—and weaker activity during La Niña. However, none of the models capture the differences in TC activity between EP and CP El Niño as are shown in observations. The inability of models to distinguish the differences in TC activities between the two types of El Niño events may be due to the bias of the models in response to the shift of tropical heating associated with CP El Niño.