Abstract

AbstractThis paper explores changes in the principal components of observed energy budgets across the tropical Pacific in response to the strong 1998 El Niño event. Multisensor observations from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), Visible and Infrared Scanner (VIRS), and precipitation radar (PR) instruments aboard TRMM are used to quantify changes in radiative and latent heating in the east and west Pacific in response to the different phases of the El Niño–Southern Oscillation. In periods of normal east–west SST gradients there is substantial heating in the west Pacific and cooling in the east, implying strong eastward atmospheric energy transport. During the active phase of the El Niño, both the east and west Pacific tend toward local radiative–convective equilibrium resulting in their temporary energetic decoupling. It is further demonstrated that the response of these regions to ENSO-induced SST variability is directly related to changes in the characteristics of clouds and precipitation in each region. Through quantitative analysis of the radiative and latent heating properties of shallow, midlevel, and deep precipitation events and an equivalent set of nonprecipitating cloud systems, times of reduced atmospheric heating are found to be associated with a shift toward shallow and midlevel precipitation systems and associated low-level cloudiness. The precipitation from such systems is typically less intense, and they do not trap outgoing longwave radiation as efficiently as their deeper counterparts, resulting in reduced radiative and latent heating of the atmosphere. The results also suggest that the net effect of precipitating systems on top-of-the-atmosphere (TOA) fluxes and the efficiency with which they heat the atmosphere and cool the surface exhibit strong dependence on their surroundings. The sensitivity of cloud radiative impacts to the atmospheric and surface properties they act to modify implies the existence of strong feedbacks whose representation may pose a significant challenge to the climate modeling community.

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