A Multidecadal Assessment of Mean and Extreme Wave Climate Observed at Buoys off the U.S. East, Gulf, and West Coasts

Mohammad Jamous, Reza Marsooli

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

The current understanding of wind-generated wave climate from buoy-based measurements is mainly focused on a limited number of locations and has not been updated to include measurements in the past decade. This study quantifies wave climate variability and change during the historical period of 1980–2020 through a comprehensive analysis of wave height measurements at 43 buoys off the U.S. Pacific, Atlantic, and Gulf of Mexico Coasts. Variabilities and trends in the annual and monthly mean and 95th percentile significant wave heights (SWH) and the number of extreme wave events are quantified for the cold and warm seasons. We calculate the SWH long-term and decadal trends, and temporal variabilities using the ordinary least squares regression and coefficient of variation, respectively. Independent extreme wave events are identified using a method based on the peaks-over-threshold and the autocorrelation function, which accounts for the geographical variation in the timespan between independent extreme events. Results show that the warm season’s interannual variabilities in monthly and annual SWH are smaller in the Pacific while larger in the Atlantic and Gulf, with the largest variabilities observed at buoys in the Gulf and lower latitudes of the Atlantic. Strong significant alternating decadal trends in SWH are found in the Pacific and Atlantic regions. Buoys in the Atlantic and Gulf regions have experienced higher numbers of extreme wave events (anomalies) compared to the Pacific region. In general, the long-term trend in the number of extreme events during the cold season is positive at buoys located at higher latitudes but negative at lower latitudes.

Original languageEnglish
Article number916
JournalJournal of Marine Science and Engineering
Volume11
Issue number5
DOIs
StatePublished - May 2023

Keywords

  • autocorrelation
  • trend
  • variability
  • wave climate

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