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Siler, N, Kosaka Y, Xie SP, Li XC.  2017.  Tropical ocean contributions to California's surprisingly dry El Nino of 2015/16. Journal of Climate. 30:10067-10079.   10.1175/jcli-d-17-0177.1   AbstractWebsite

The major El Nino of 2015/16 brought significantly less precipitation to California than previous events of comparable strength, much to the disappointment of residents suffering through the state's fourth consecutive year of severe drought. Here, California's weak precipitation in 2015/16 relative to previous major El Nino events is investigated within a 40-member ensemble of atmosphere-only simulations run with historical sea surface temperatures (SSTs) and constant radiative forcing. The simulations reveal significant differences in both California precipitation and the large-scale atmospheric circulation between 2015/16 and previous strong El Nino events, which are similar to (albeit weaker than) the differences found in observations. Principal component analysis indicates that these ensemble-mean differences were likely related to a pattern of tropical SST variability with a strong signal in the Indian Ocean and western Pacific and a weaker signal in the eastern equatorial Pacific and subtropical North Atlantic. This SST pattern was missed by the majority of forecast models, which could partly explain their erroneous predictions of above-average precipitation in California in 2015/16.

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.

Maloney, ED, Xie SP.  2013.  Sensitivity of tropical intraseasonal variability to the pattern of climate warming. Journal of Advances in Modeling Earth Systems. 5:32-47.   10.1029/2012ms000171   AbstractWebsite

An aquaplanet general circulation model is used to assess the sensitivity of intraseasonal variability to the pattern of sea surface temperature (SST) warming. Three warming patterns are used. Projected SST warming at the end of the 21st century from the Geophysical Fluid Dynamics Laboratory Climate Model 2.1 is one pattern, and zonally symmetric and globally uniform versions of this warming perturbation that have the same global mean SST change are the other two. Changes in intraseasonal variability are sensitive to the pattern of SST warming, with significant decreases in Madden-Julian oscillation (MJO)-timescale precipitation and wind variability for a zonally symmetric warming, and significant increases in MJO precipitation amplitude for a globally uniform warming. The amplitude of the wind variability change does not scale directly with precipitation, but is instead mediated by increased tropical dry static stability associated with SST warming. The patterned SST simulations have a zonal mean SST warming that maximizes on the equator, which fosters increased equatorial boundary layer convergence and also increases equatorial SST relative to the rest of the tropics. Both factors support increased convection, reflected in reduced gross moist stability (GMS). Mean precipitation is decreased and GMS is increased in the off-equatorial Eastern Hemisphere near 10 degrees S in the patterned warming simulations, where the strongest MJO-related intraseasonal precipitation variability is preferred in both the model and observations. It is argued that future changes in MJO activity may be sensitive to the pattern of SST warming, although these results should not be interpreted as a prediction of how MJO activity will change in future climate.