Climate Variability Impacts on Global Extreme Wave Heights: Seasonal Assessment Using Satellite Data and ERA5 Reanalysis

Patra, Anindita; Min, Seung‐Ki; Seong, Min‐Gyu

doi:10.1029/2020jc016754

Cited by 30 publications

(28 citation statements)

References 72 publications

(161 reference statements)

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“…3 a). These findings are consistent with the previous studies that have examined the impact on wave parameters 62 , 77 . Further, this correlation over PO enhances in SON (0.39, p-value < 0.01) and JJA (0.37, p-value < 0.05), as in JJA, tropical cyclone activities over the PO (particularly in western North Pacific (WNP)) are amplified by El Niño events 39 , 54 .…”

Section: Resultssupporting

confidence: 93%

“…Further, this correlation over PO enhances in SON (0.39, p-value < 0.01) and JJA (0.37, p-value < 0.05), as in JJA, tropical cyclone activities over the PO (particularly in western North Pacific (WNP)) are amplified by El Niño events 39 , 54 . Whereas in SON (the El Niño development year), the deepening of East Asian trough, as well as the intensification and more frequent northward shift of the storm tracks across WNP, increases the wave climate over PO 77 , 78 . Likewise, in IO, La Niña (a pattern that is reversed during El Niño) increases the wave climate during DJF 62 , 68 , 77 , due to an increase in pressure gradient between the IO and eastern Pacific 62 , 77 , and consequently SST strongly correlates with WP (Fig.…”

Section: Resultsmentioning

confidence: 99%

“…Whereas in SON (the El Niño development year), the deepening of East Asian trough, as well as the intensification and more frequent northward shift of the storm tracks across WNP, increases the wave climate over PO 77 , 78 . Likewise, in IO, La Niña (a pattern that is reversed during El Niño) increases the wave climate during DJF 62 , 68 , 77 , due to an increase in pressure gradient between the IO and eastern Pacific 62 , 77 , and consequently SST strongly correlates with WP (Fig. 3 b,e).…”

Section: Resultsmentioning

confidence: 99%

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Positive relationship between seasonal Indo-Pacific Ocean wave power and SST

Kaur

Kumar

Weller

et al. 2021

Sci Rep

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The influence of increasing sea surface temperatures (SSTs), in response to greenhouse warming, on wave power (WP) remains uncertain. Here, seasonal relationships between SST anomalies and mean and extreme WP over the Indo-Pacific Ocean are examined. Overall, seasonal WP has significantly increased over much of the Pacific, Indian, and Southern Ocean by 1.21–3.10 kW/m dec−1 over 1979–2019. Contributions from wave characteristics, namely significant wave height (SWH) and peak wave period (PWP), to changes in WP show that SWH contributes most in extra-tropical regions, and PWP most in tropical regions. Further, seasonal relationships between SST anomalies and WP indicate that increases in WP are also seen during strong El Niño years in December–February, and in-phase combinations of El Niño and positive Indian Ocean Dipole (IOD) events during June–August and September–November. Results highlight both long-term increasing SSTs and climate variability roles for inducing large-scale seasonal WP changes throughout the Indo-Pacific.

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Section: Resultssupporting

confidence: 93%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Positive relationship between seasonal Indo-Pacific Ocean wave power and SST

Kaur

Kumar

Weller

et al. 2021

Sci Rep

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“…Reanalysis data combine model data with observations from across the world into a globally complete and consistent dataset using the laws of physics. The ERA5 reanalysis data used in this paper are commonly used in marine research [31,32]. This data set has also been used in the studies of typhoon prediction and impact [33][34][35].…”

Section: Data Feasibilitymentioning

confidence: 99%

The Influence of Typhoon “MITAG” on Waves and Currents in Zhoushan Sea Area, China

et al. 2021

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Typhoon “MITAG” was generated at the end of September 2019 and landed briefly in Zhoushan on October 1. Based on reanalysis data provided by ERA5 and NCEP, this paper analyzes the characteristics of wave and current during “MITAG”. The variation rule of waves and currents in different periods during the influence of “MITAG” was found. The results are as follows: The variation of significant wave height and mean wave period is related to its waveform. The single waveform has a long wave period and the correlation between wave height and wave period reaches 0.87 during the wind wave period. The wave period of the mixed waveform is shorter. The Ekman pumping of the ocean by “MITAG” is concentrated on the right side of the typhoon path when it is away from land; however, Ekman pumping is on the land side when the typhoon is close to the land. The sea surface height of the coastal sea area changes regularly with the distance of “MITAG”. The area which has a strong current is consistent with higher wave height.

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“…In MAM, ENSO reduces the PDO signals over the PO. In addition, seasonal SLP teleconnection patterns regressed against ENSO|IOD, IOD|ENSO, ENSO|IOD, and PDO|ENSO, exhibit a high and low pressure anomaly that in turn generates strong winds(Kumar et al 2016(Kumar et al , 2019Patra et al 2020;Remya et al, 2020;Yang and Oh 2018) and consequently enhances the wave parameters (i.e. Hs and Tp) in the respective localized regions.…”

mentioning

confidence: 99%

Influence of Natural Climate Variability on Extreme Wave Power over Indo-Pacific Ocean Assessed using ERA5

Kumar

Kaur

Weller

et al. 2021

Preprint

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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 trends (ENSO|IOD) on WP are evident over the eastern and central Pacific during December–February (DJF) and March–May (MAM), 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 (IO), with localized increases only over the South China and Philippine (SCP) seas and Bay of Bengal (BOB) 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 (SWH), peak wave period (PWP), sea surface temperatures (SST), and sea level pressure (SLP) helps to explain the seasonal variations in WP.

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Climate Variability Impacts on Global Extreme Wave Heights: Seasonal Assessment Using Satellite Data and ERA5 Reanalysis

Cited by 30 publications

References 72 publications

Positive relationship between seasonal Indo-Pacific Ocean wave power and SST

Positive relationship between seasonal Indo-Pacific Ocean wave power and SST

The Influence of Typhoon “MITAG” on Waves and Currents in Zhoushan Sea Area, China

Influence of Natural Climate Variability on Extreme Wave Power over Indo-Pacific Ocean Assessed using ERA5

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