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Zheng, XT, Hui C, Xie SP, Cai WJ, Long SM.  2019.  Intensification of El Nino Rainfall Variability Over the Tropical Pacific in the Slow Oceanic Response to Global Warming. Geophysical Research Letters. 46:2253-2260.   10.1029/2018gl081414   AbstractWebsite

Changes in rainfall variability of El Nino-Southern Oscillation (ENSO) are investigated under scenarios where the greenhouse gases increase and then stabilize. During the period of increasing greenhouse forcing, the ocean mixed layer warms rapidly. After the forcing stabilizes, the deeper ocean continues to warm the surface (the slow response). We show that ENSO rainfall variability over the tropical Pacific intensifies in both periods but the rate of increase per degree global mean surface temperature (GMST) warming is larger for the slow response because of greater relative warming in the base state as the mean upwelling changes from a damping to a driver of the surface warming. Our results have important implications for climate extremes under GMST stabilization that the Paris Agreement calls for. To stabilize GMST, the fast surface cooling offsets the slow warming from the prior greenhouse gas increase, while ENSO rainfall variability would continue to increase. Plain Language Summary The Paris Agreement calls for limiting global mean surface temperature increase to well below 2 degrees at the end of the 21st century. This requires the greenhouse gas (GHG) concentration to peak and subsequently decline in the next few decades. After the GHG concentration peak, the heat accumulated in the ocean surface layer continues to penetrate to the deeper ocean. This deeper ocean warming leads to a slow response of surface warming, further influencing the climate system. This study examines scenarios where GHGs increase and then stabilize to isolate the fast and slow responses of El Nino-Southern Oscillation (ENSO) rainfall variability. We find intensification of ENSO rainfall variability both during the increase and after stabilization of GHG concentrations due to a persistent El Nino-like mean warming pattern in the tropical Pacific. Furthermore, for unit global mean surface temperature increase, the changes in the mean state temperature and ENSO rainfall variability in the eastern equatorial Pacific is larger during the slow response. These results imply that there is a need for GHG emission reduction in the near future to avoid more extreme tropical rainfall during El Nino.

Huang, P, Xie SP.  2015.  Mechanisms of change in ENSO-induced tropical Pacific rainfall variability in a warming climate. Nature Geoscience. 8:922-U48.   10.1038/ngeo2571   AbstractWebsite

El Nino/Southern Oscillation (ENSO) is a mode of natural variability that has considerable impacts on global climate and ecosystems(1-4), through rainfall variability in the tropical Pacific and atmospheric teleconnections(5). In response to global warming, ENSO-driven rainfall variability is projected to intensify over the central-eastern Pacific but weaken over the western Pacific, whereas ENSO-related sea surface temperature variability is projected to decrease(6-14). Here, we explore the mechanisms that lead to changes in ENSO-driven rainfall variability in the tropical Pacific in response to global warming, with the help of a moisture budget decomposition for simulations from eighteen state-of-the-art climate models(15). We identify two opposing mechanisms that approximately offset each other: the increase in mean-state moisture content associated with surface warming strengthens ENSO-related rainfall anomalies(7), whereas the projected reduction in ENSO-related variability of sea surface temperatures suppresses rainfall. Two additional effects-spatially non-uniform changes in background sea surface temperatures and structural changes in sea surface temperature related to ENSO-both enhance central-eastern Pacific rainfall variability while dampening variability in the western Pacific, in nearly equal amounts. Our decomposition method may be generalized to investigate how rainfall variability would change owing to nonlinear interactions between background sea surface temperatures and their variability.

Mei, W, Xie SP, Zhao M.  2014.  Variability of tropical cyclone track density in the North Atlantic: Observations and high-resolution simulations. Journal of Climate. 27:4797-4814.   10.1175/jcli-d-13-00587.1   AbstractWebsite

Interannual-decadal variability of tropical cyclone (TC) track density over the North Atlantic (NA) between 1979 and 2008 is studied using observations and simulations with a 25-km-resolution version of the High Resolution Atmospheric Model (HiRAM) forced by observed sea surface temperatures (SSTs). The variability on decadal and interannual time scales is examined separately. On both time scales, a basinwide mode dominates, with the time series being related to variations in seasonal TC counts. On decadal time scales, this mode relates to SST contrasts between the tropical NA and the tropical northeast Pacific as well as the tropical South Atlantic, whereas on interannual time scales it is controlled by SSTs over the central eastern equatorial Pacific and those over the tropical NA. The temporal evolution of the spatial distribution of track density is further investigated by normalizing the track density with seasonal TC counts. On decadal time scales, two modes emerge: one is an oscillation between track density over the U.S. East Coast and midlatitude ocean and that over the Gulf of Mexico and the Caribbean Sea and the other oscillates between low and middle latitudes. They might be driven by the preceding winter North Atlantic Oscillation and concurrent Atlantic meridional mode, respectively. On interannual time scales, two similar modes are present in observations but are not well separated in HiRAM simulations. Finally, the internal variability and predictability of TC track density are explored and discussed using HiRAM ensemble simulations. The results suggest that basinwide total TC counts/days are much more predictable than local TC occurrence, posing a serious challenge to the prediction and projection of regional TC threats, especially the U.S. landfall hurricanes.