Predictability and Forecast Skill in NMME

Predictability and Ensemble-Forecast Skill Enhancement Based on the Probability Density Function Estimation

I wish to address development of theoretical framework by improving and combining currently existing methodologies and techniques. I also wish to adapt new approaches based on dynamical systems theories that have not been used to enhance predictability in the past. My overall approach will involve Eulerian and Lagrangian descriptions of the probablity density funtion evolution, identification a...

Enhanced seasonal forecast skill following

Forecast and analysis assessment through skill scores

The Forecast of Predictability and Instability in Physical Modelling

the last century, the numerical approach to solving physical problems has gained in relevance with the increase of computational facilities. Methods derived from chaos theory and nonlinear dynamics techniques are quite useful in solving real problems where chaos is present and a strong dependence on initial conditions is a key issue. Predictability refers to the assessment of the likely errors ...

Diagnosing CFS2 forecast skill using empirical models of climate prediction and predictability from sub-seasonal to multi-decadal scales

We propose to employ a seamless empirical dynamical modeling approach to construct a state-of-the-art benchmark probabilistic forecast system and to evaluate factors impacting predictability at forecast lead times ranging from weeks to decades in the CFS2 forecast system, including climate drift. The model used, a linear inverse model (LIM) derived from observed simultaneous and time-lag correl...