loading page

Subseasonal Predictability of Sea Level in the Hawaiian Islands
  • +2
  • Hyang Yoon,
  • Philip Thompson,
  • Mark Merrifield,
  • James Potemra,
  • Bo Qiu
Hyang Yoon
University of Hawaii at Manoa

Corresponding Author:[email protected]

Author Profile
Philip Thompson
University of Hawaii at Manoa
Author Profile
Mark Merrifield
University of California San Diego
Author Profile
James Potemra
University of Hawaii at Manoa
Author Profile
Bo Qiu
University of Hawaii at Manoa
Author Profile

Abstract

The Hawaiian Islands experienced record-high sea levels during 2017, which caused nuisance flooding in vulnerable coastal communities and exacerbate beach erosion, especially when positive sea level anomalies coincided with high tides. To build toward solutions for mitigating inundation risk, the predictability of daily-averaged sea level anomalies is investigated. Background sea level around the Hawaiian Islands was elevated during most of 2017 due to an oceanic Rossby-type planetary wave, which propagated slowly westward across the tropical North Pacific over the course of a year. The investigation focused on leveraging observed westward propagation that sea level anomalies exhibit over a range of timescales to make subseasonal predictions. Daily near-real-time gridded altimetry (CMEMS/AVISO) was used to specify upstream sea level at each site with propagation speeds based on mode-one baroclinic Rossby wave speeds. The skill of the predictions exceeds persistence at most locations around the archipelago out to a month or more lead time, but the skill is highly dependent on location even over the short distances spanned by the Hawaiian Ridge. Here, hindcast results are presented that establish where skillful subseasonal predictions can be made in Hawaii, as well as the barriers to predictability in locations where they cannot. These results inform the oceanographic and modelling communities about what processes need to be resolved in order to provide island communities with useful short-term sea level forecasts as the frequency of flooding events increases.