Time–Space Distribution of Long-Range Atmospheric Predictability

Abstract

The global three-dimensional structure of long-range (one month to one season) atmospheric predictability was investigated with a general circulation model. The main focus was to ascertain the role of atmospheric initial conditions for such predictability as a function of lead time and space. Four types of predictability experiments with different types of initial and boundary conditions were conducted to this end. The experiments were verified against reanalysis and model data to determine real forecast skill, as well as skill under the perfect model assumption. Spatial maps and vertical cross sections of predictability at different lead times and for the two contrasting seasons were analyzed to document the varying influence of initial and boundary conditions on predictability. It was found that the atmosphere was remarkably sensitive to initial conditions on the week 3?6 forecast range. Particularly, the troposphere over Antarctica, the region over the tropical Indian Ocean, and the lower stratosphere were affected. It was shown that most of the initial condition memory was related to the persistent nature of the atmosphere in these regions, which in turn was linked to the major modes of atmospheric variability.