Publication Abstracts

Wang et al. 2014

Wang, H., L. Long, A. Kumar, W. Wang, J.-K.E. Schemm, M. Zhao, G.A. Vecchi, T.E. LaRow, Y.-K. Lim, S.D. Schubert, D.A. Shaevitz, S.J. Camargo, N. Henderson, D.Y. Kim, J.A. Jonas, and K.J.E. Walsh, 2014: How well do global climate models simulate the variability of Atlantic tropical cyclones associated with ENSO? J. Climate, 27, no. 15, 5673-5692, doi:10.1175/JCLI-D-13-00625.1.

The variability of Atlantic tropical cyclones (TCs) associated with El Niño-Southern Oscillation (ENSO) in model simulations is assessed and compared with observations. The model experiments are 28-yr simulations forced with the observed sea surface temperature from 1982 to 2009. The simulations were coordinated by the U.S. Climate Variability and Predictability Research Program (CLIVAR) Hurricane Working Group and conducted with five global climate models (GCMs) with a total of 16 ensemble members. The model performance is evaluated based on both individual model ensemble means and multimodel ensemble mean. The latter has the highest anomaly correlation (0.86) for the interannual variability of TCs. Previous observational studies show a strong association between ENSO and Atlantic TC activity, as well as distinctions during eastern Pacific (EP) and central Pacific (CP) El Niño events. The analysis of track density and TC origin indicates that each model has different mean biases. Overall, the GCMs simulate the variability of Atlantic TCs well with weaker activity during EP El Niño and stronger activity during La Niña. For CP El Niño, there is a slight increase in the number of TCs as compared with EP El Niño. However, the spatial distribution of track density and TC origin is less consistent among the models. Particularly, there is no indication of increasing TC activity over the U.S. southeast coastal region during CP El Niño as in observations. The difference between the models and observations is likely due to the bias of the models in response to the shift of tropical heating associated with CP El Niño, as well as the model bias in the mean circulation.