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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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El Niño and La Niña events, together referred to as the El Niño – Southern Oscillation (ENSO), drive large-scale changes in weather patterns, generating recognizable alternations in seasonal climate across the globe. As such, predicting ENSO events many months in advance is of particular interest.
Despite decades of scientific research on the dynamics of ENSO, our ability to predict the amplitude of ENSO events 10-12 months in advance remains limited. This long lead-time forecast challenge is often attributed to internal variability of the climate system that influences the triggering and subsequent evolution of events. An open question is, how much does this internal variability hinder our ability predict ENSO events?
This presentation introduces a state-of-the-art climate model methodology to model perturbation growth that hinders ENSO predictability. The goal is to quantify how much random disturbances, like weather, contribute to increasing the range of possible outcomes in ENSO forecasts.
The details of the initial condition are also investigated, particularly whether preconditioning (i.e., the buildup of heat content in the equatorial Pacific subsurface) increases the predictability of events by reducing the range of possible outcomes and/or enhancing the signal we hope to predict.