Assesment of Prediction Skill and Predictabilty of Tropical Intraseasonal Variability in Dynamic Models

The Intraseasonal variability (ISV) Hindcast Experiment (ISVHE), is a first of its kind initiative for assessing the prediction skill and predictability of tropical ISV in a multimodel frame work with a broad objective of developing optimal multi-model ensemble (MME) prediction strategies for the ISV. The prediction skill and predictability of winter time Madden Julian Oscillations (MJO) and summer time Eastern Pacific ISV are quantified using the dedicated set of extended-range hindcasts from eight coupled models participating in the ISVHE. In addition to the influence of MJO, the north American weather and climate also comes under the large-scale impacts of the EPAC ISV. An updated estimate of the predictability of the ISV in a suite of contemporary dynamical models, in conjunction with an estimate of prediction skill, is crucial for guiding future research and development priorities. While the prediction skill for the boreal winter MJO is around ~15-25 days in the ISVHE models, the skill for the EPAC ISV is considerably lower in most models with an average skill around 10 days. Two estimates of MJO predictability are made, based on single member and ensemble mean hindcasts, giving values of 20-30 days and 35-45 days, respectively. On the other hand, estimate of the predictability of the EPAC ISV shows a promising 20-30 day range. The dependence of MJO predictability on the phase of MJO during hindcast initiation and the influence of MJO forcing on EPAC ISV prediction skill are also explored. In addition, the performance of the different ensemble prediction systems are also evaluated with respect to the MJO.