Metrics for Quantifying Predictability Limits

Kathy
Pegion
University of Colorado/CIRES and NOAA/ESRL/PSD
As part of the joint PPAI and PSMI panel session on “Metrics for Quantifying Predictions and Predictability Limits”, I will present several methods that have been used for estimating the upper limit of prediction skill (i.e. predictability). These methods include: perfect model predictability, predictability determined from an empirical linear inverse model, cross-model predictability, and average predictability time. Examples from each of these methods are presented for the subseasonal timescale. In some cases, the predictability estimates from the different methods lead to different conclusions about the upper limit of skill, pointing to scientific limitations in our understanding of predictability limits.
Abstract file
Presentation file