Abstract

In recent decades, wave power (WP) energy from the ocean is one of the cleanest renewable energy sources associated with oceanic warming. In Indo-Pacific Ocean, the WP is significantly influenced by natural climate variabilities, such as El Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), and Pacific Decadal Oscillation (PDO). In this study, the impact of major climate variability modes on seasonal extreme WP is examined over the period 1979–2019 using ERA5 reanalysis data and the non-stationary generalized extreme value analysis is applied to estimate the climatic extremes. Independent ENSO influence after removing the IOD impact (ENSO|IOD) on WP are evident over the northeast and central Pacific during December–February, and March–May, respectively, which subsequently shifts towards the western Pacific in June–August (JJA) and September–November (SON). The ENSO|PDO impact on WP exhibits similar yet weaker intensity year round compared to ENSO. Extreme WP responses due to the IOD|ENSO include widespread decreases over the tropical and eastern Indian Ocean, with localized increases only over South China and Philippine seas and Bay of Bengal during JJA, and the Arabian Sea during SON. Lastly, for the PDO|ENSO, the significant increases in WP are mostly confined to the Pacific, and most prominent in the North Pacific. Composite analysis of different phase combinations of PDO (IOD) with El Niño (La Niña) reveals stronger (weaker) influences year-round. The response patterns in significant wave height, peak wave period, sea surface temperatures, and sea level pressure help to explain the seasonal variations in WP.

Highlights

  • This study investigates the seasonal influence of dominant modes of natural climate variability, such as El Niño–Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), and Pacific Decadal Oscillation (PDO) on extreme wave power (WP) in the Indo–Pacific Ocean using ERA5 reanalysis data for the 41 year period from 1979–2019

  • This study investigates the impact of natural climate variability modes such as ENSO, IOD, and 513 PDO on seasonal extreme WP in the Indo-Pacific Ocean using ERA5 reanalysis data over the period 1979–2019

  • A non-stationary Generalized Extreme Value (GEV) distribution is applied on the seasonal extremes to determine the regions with significant impact, where the natural climate variability modes are taken as the covariates

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Summary

Data and Methodology

The latest reanalysis product from the European Centre for Medium-Range Weather Forecasting (ECMWF), referred to as the ERA5 reanalysis (Hersbach and Dee 2016), is used in the present study to analyze the mean and extreme WP for the 41-year period from 1979 to 2019 over the Indo–Pacific region for the four boreal seasons (i.e., December–February (DJF, winter), March– May (MAM, spring), June–August (JJA, summer), and September–November (SON, autumn). The ERA5 reanalysis data have several advancements compared to its predecessor, ERA-Interim (Dee et al 2011). In contrast to ERA-Interim, ERA5 has higher spatial and temporal resolution along with an improved representation of the tropospheric processes, including better representation of tropical cyclones, global balance of precipitation and evaporation cycle etc. In order to measure the WP, the seasonal mean and maxima of SWH (of combined wind waves and swell) and PWP are obtained from the six-hourly SWH and PWP data taken from ERA5. The seasonal mean SLP and SST were derived from 6-hourly SLP and SST data of ERA-5, respectively. The ERA5 reanalysis data for all the variables were downloaded from the ECMWF website (https://www.ecmwf.int/en/forecasts/datasets/reanalysisdatasets/era5/) at a horizontal resolution of 0.5°×0.5° (i.e. SWH and PWP) or 0.25°×0.25° (i.e., 165 SST and SLP)

Climate Indices
Methodology
SST and SLP mean Teleconnection
ENSO Influence
IOD Influence
PDO Influence
Composite Analysis of ENSO and IOD
Composite Analysis of ENSO and PDO
Summary and Conclusions
Analysis Method
Full Text
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