Abstract
The impact of clouds and precipitation on the climate is a strong function of their spatial distribution and microphysical properties, characteristics that depend, in turn, on the environments in which they form. Simulating feedbacks between clouds, precipitation, and their surroundings therefore places an enormous burden on the parameterized physics used in current climate models. This paper uses multisensor observations from the Tropical Rainfall Measuring Mission (TRMM) to assess the representation of the response of regional energy and water cycles in the tropical Pacific to the strong 1998 El Niño event in (Atmospheric Model Intercomparison Project) AMIP-style simulations from the climate models that participated in the Intergovernmental Panel on Climate Change’s (IPCC’s) most recent assessment report. The relationship between model errors and uncertainties in their representation of the impacts of clouds and precipitation on local energy budgets is also explored.
With the exception of cloud radiative impacts that are often overestimated in both regions, the responses of atmospheric composition and heating to El Niño are generally captured in the east Pacific where the SST forcing is locally direct. Many models fail, however, to correctly predict the magnitude of induced trends in the west Pacific where the response depends more critically on accurate representation of the zonal atmospheric circulation. As a result, a majority of the models examined do not reproduce the apparent westward transport of energy in the equatorial Pacific during the 1998 El Niño event. Furthermore, the intermodel variability in the responses of precipitation, total heating, and vertical motion is often larger than the intrinsic ENSO signal itself, implying an inherent lack of predictive capability in the ensemble with regard to the response of the mean zonal atmospheric circulation in the tropical Pacific to ENSO. While ENSO does not necessarily provide a proxy for anthropogenic climate change, the results suggest that deficiencies remain in the representation of relationships between radiation, clouds, and precipitation in current climate models that cannot be ignored when interpreting their predictions of future climate.
Corresponding author address: Dr. Tristan S. L’Ecuyer, Department of Atmospheric Science, Colorado State University, Fort Collins, CO 80523. Email: tristan@atmos.colostate.edu
