On the Extraordinary Intensification of Hurricane Patricia (2015). Part I: Numerical Experiments

Abstract

Hurricane Patricia (2015) broke records in both peak intensity and rapid intensification (RI) rate over the eastern Pacific basin. All of the then-operational models predicted less than half of its extraordinary intensity and RI rate, leaving a challenge for numerical modeling studies. In this study, a successful 42-h simulation of Patricia is obtained using a quintuply nested-grid version of the Weather Research and Forecast (WRF) Model with the finest grid size of 333 m. Results show that the WRF Model, initialized with the Global Forecast System Final Analysis data only, could reproduce the track, peak intensity, and many inner-core features, as verified against various observations. In particular, its simulated maximum surface wind of 92 m s−1 is close to the observed 95 m s−1, capturing the unprecedented RI rate of 54 m s−1 (24 h)−1. In addition, the model reproduces an intense warm-cored eye, a small-sized eyewall with a radius of maximum wind of less than 10 km, and the distribution of narrow spiral rainbands. A series of sensitivity simulations is performed to help understand which model configurations are essential to reproducing the extraordinary intensity of the storm. Results reveal that Patricia’s extraordinary development and its many inner-core structures could be reasonably well simulated if ultrahigh horizontal resolution, appropriate model physics, and realistic initial vortex intensity are incorporated. It is concluded that the large-scale conditions (e.g., warm sea surface temperature, weak vertical wind shear, and the moist intertropical convergence zone) and convective organization play important roles in determining the predictability of Patricia’s extraordinary RI and peak intensity.

Practical Uncertainties in the Limited Predictability of the Record-Breaking Intensification of Hurricane Patricia (2015)

“…12f), indicating more of the kinetic energy might have been transported to the primary circulation versus the secondary circulation in the 1-km forecast, since tangential wind speeds are greater in 1 km than 3 km. Overall, the increased horizontal resolution appears important in order to capture Patricia's observed maximum wind speed and small and compact inner core with very tight radial gradients, in agreement with Fox and Judt (2018) and Qin and Zhang (2018). Additionally, the effect of the different horizontal resolutions appears here to be greater for the forecast initiated near the beginning of RI (2100 UTC 21 October) versus the forecast initialized in the middle of the RI (1800 UTC 22 October).…”

“…As in Fig. 11, but forecasts initialized from 1800 UTC 22 Oct. speed for wind speeds greater than hurricane force (33 m s 21 ; e.g., Powell et al 2003;Black et al 2007;Holthuijsen et al 2012;Bell et al 2012;Zhang 2013, 2014;Chen et al 2018) and we attempt here to examine two extremes of this current uncertainty range.…”

“…Based on this we may expect an increased predictability of Patricia's RI relative to other RI events and indeed this is speculated by Fox and Judt (2018), where they demonstrate small changes to RI forecasts of Patricia when very small perturbations are applied to a control simulation. Additionally, Qin and Zhang (2018) also hypothesized that favorable largescale environmental conditions may have made Patricia's intensification more predictable. However, the substantial gap between the expected high intrinsic predictability-given the favorable environmental conditions-and the actual low practical predictability of Patricia's intensity from operational real-time forecasts presents an apparent contradiction and will be explored within this study.…”

“…Given the large errors by all forecast models in Patricia's intensification and peak intensity, and given the large divergence among operational forecast guidance, the current study focuses on key uncertainties that may have limited the practical aspects of the predictability of Patricia-despite favorable environmental conditions that may potentially allow high intrinsic predictability. Key limiting factors potentially include but are not limited to: data assimilation methodology and the availability and quality of observations (e.g., Zhang et al 2004;Torn and Hakim 2009;Weng and Zhang 2012;Majumdar et al 2013;Zhang and Pu 2014;Poterjoy et al 2014;Aberson et al 2015;Zhang and Weng 2015;Poterjoy and Zhang 2016), model resolution and physics (e.g., Davis et al 2008;Jin et al 2014;Judt et al 2016;Torn 2016;Melhauser et al 2017;Qin and Zhang 2018), the underlying innercore TC dynamics (e.g., Van Sang et al 2008;Hakim 2013;Brown and Hakim 2013;Torn and Cook 2013;Judt et al 2016;Emanuel and Zhang 2016;Kieu and Moon 2016;Torn 2016;Finocchio and Majumdar 2017;Nystrom et al 2018), and the environmental conditions (e.g., Torn and Cook 2013;Judt et al 2016;Emanuel and Zhang 2016;Torn 2016;Nystrom et al 2018).…”

“…Second, given the observed small inner core of Patricia, we examine the implications of the model horizontal resolution, which is often limited by computational cost, on the accuracy and predictability of Patricia's intensification. Last, motivated by the large uncertainty in the physics related to the air-sea fluxes at high wind speeds (e.g., Powell et al 2003;Hsu et al 2017), we examine the impact of surface flux parameterization uncertainty on the prediction of Patricia's intensification.…”