Among the biases in the tropical Pacific that are common in the climate models, two stand out. One is the excessive cold-tongue in the mean state—the pool of the cold water that is normally in the eastern tropical Pacific extends too far to the west. The other is the underestimate of the asymmetry of El Nino-Southern Oscillation—the fact that El Nino and La Nina are more or less a mirror image of each other in the models while they are not so in the observations. The importance of the tropical Pacific sea surface temperature in affecting climate variability on a range of time-scales over the continental U.S and the world at large demands our attention to the causes and removal of these two common biases in climate models.
The proposal attempts to delineate the relationship between these two common biases in the stateof- the-art climate models and isolate the root causes of them. Toward this objective, we will conduct focused data analysis as well as numerical experiments with climate models of varying complexity. The hypothesis the proposed project sets out to test is that these two tropical biases are linked. More specifically, we suspect that an excessive cold-tongue in the mean climatological state renders the two phases of ENSO more symmetric, possibly through its impact on the stability of the ENSO system, while a more symmetric ENSO results in less nonlinear heating to the cold-tongue which in turn contributes to the development of an excessive coldtongue. Moreover, we suspect that these two biases may be the symptoms of a single structural inadequacy in the models: a weak dynamical coupling between the atmosphere and ocean.
To test our hypothesis and pin down the physical processes responsible for the aforementioned biases, we will
(1) Capitalize on the greater range of variability among the CMIP5 models than CMIP3 models in their simulations of the tropical Pacific climate to examine the relationship between the zonal extent of the cold-tongue and ENSO asymmetry in the models.
(2) Conduct coupled experiments with two models of intermediate complexity to delineate the mechanisms by which an excessive cold-tongue affect the asymmetry of ENSO.
(3) Conduct forced ocean GCM experiments with surface forcing from models with different level of biases as well as from observations to quantify the feedback from ENSO events.
(4) Evaluate the precipitation-wind-SST relationship in the corresponding AMIP runs in conjunction with the coupled runs to fully evaluate the coupling strength as well as to diagnose causes for the initial error
(5) Conduct experiments with a fully coupled GCM (the NCAR Community Climate System Model-version 4) as well as experiments with its atmospheric and oceanic components.
The proposed project utilizes data analysis and models of varying complexity to achieve a deeper understanding of the causes of two prominent biases in the tropical Pacific and thereby helps to improve the simulations and predictions of the tropical Pacific climate—a key source for climate variability and predictability in the earth’s climate system– by our state-of-the-art climate models. Thus, the proposed project is highly relevant to the objectives and priorities of the Earth System Science Program of NOAA.