El Nino forecasting using Hierarchical Dynamic (HiDyn) Models: a web-based product

Authors

Noel A. Cressie, Ohio State UniversityFollow

RIS ID

108903

Publication Details

Cressie, N. (2003). El Nino forecasting using Hierarchical Dynamic (HiDyn) Models: a web-based product. TIES Newsletter, 9 (2), 15-16.

Abstract

The inter-annual variation of tropical Pacific sea surface temperature (SST) is an important factor in the variability of the global climate system. The dominant feature of this field is the episodic warming and cooling of ocean waters with periods of approximately 3-5 years, namely, the El Nino Southern Oscillation (ENSO) phenomenon. In recent years, long-lead predictions of tropical Pacific SSTs have improved greatly in light of better observational networks, analysis schemes, and understanding of the processes that govern the interaction of the atmosphere and ocean.

Link to publisher version (URL)

The International Environmetrics Society