Effect of El Niño on Summer Extreme Ocean Waves over East Asian Regions

doi:10.21203/rs.3.rs-3719112/v1

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Effect of El Niño on Summer Extreme Ocean Waves over East Asian Regions

https://doi.org/10.21203/rs.3.rs-3719112/v1

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Extreme wave events with devastating impacts on East Asian (EA) coastal regions have recently been more variable. However, despite being a prominent extreme spot due to the influence of anomalous seasonal atmospheric and remote climate variability, the investigation of EA extreme wave attributes, such as duration and intensity, and their relation to the climate events remains unclear. By applying the peaks-over-threshold (POT) method with a fixed threshold set at the 99th percentile, this study aimed to quantify the duration and intensity of EA extreme wave events in boreal summer from 1980–2021 and investigate the influence of El Niño and Pacific Decadal Oscillation (PDO) as the main climate mode in the Pacific Ocean. Spatially, the findings demonstrated that extreme waves have occurred with an intensity up to 1.5 m, persisting in a range from 8 to 35 hours over the study and revealing the prominent spot in the southern part of the study area, impacting the southern coast of Korea. Based on the area-averaged over the prominent spot, the appearance of El Niño induces longer (with an average of 85 h) and more intense summer extreme waves (with 2 m of max intensity). The results suggest that the eastward shifting of tropical storms (TS) due to the El Niño-induced anomalous westerlies at 5°N–10°N contributes to this condition. Furthermore, a positive PDO strengthens the El Niño effect, with the almost doubled in duration, through strong anomalous anticyclonic formation in the Philippine Sea. The study findings enhance our understanding of the link between ENSO and TS activity with respect to extreme wave duration and intensity; these factors can be relevant in formulating plans for mitigating the impact of extreme wave events on coastal environments.

El Niño

summer extreme waves

Pacific Decadal Oscillation

climate mode

climate variability

The severe impacts of extreme ocean waves, including flooding in coastal areas (Melet et al., 2020), loss of life and property damage (Hansom et al., 2015), and severe coastal erosion (Masselink and Gehrels, 2014) have been recorded worldwide. The increasing rate of extreme ocean waves in northern latitudes, which also cover East Asian (EA) waters such as the East Sea (ES), the Yellow Sea (YS) and the East China Sea (ECS), is higher than that of the mean condition (Young et al., 2011) and is predicted to become more extreme in the future (Meucci et al., 2020). While extreme ocean surface waves are generally induced by storms and are associated with increasing surface wind speeds (Chun and Ahn, 2017; Heo et al., 2020), the EA region is notably sensitive to seasonal atmospheric phenomena, such as monsoonal systems (Chen et al., 2019; Son et al., 2023). Several wave climate studies conducted on a seasonal basis have shown that extreme wave heights in the EA seas have been increasing during the summer season (Liang et al., 2016; Li et al., 2016).

Moreover, extreme ocean wave events in the Western North Pacific (WNP) have been linked to tropical storm (TS) activities (Sasaki and Hibiya, 2007; Sasaki et al., 2005; Woo and Park, 2021) and associated with large-scale natural climate variability such as the El Niño Southern Oscillation (ENSO) (Chien et al., 2014; Yang and Oh, 2018). This is because ENSO events, which are indicated by the anomalous ocean warming tongue structure in the Central-Eastern Pacific Ocean, could influence the global climate system, including wind patterns in the EA region (Wang et al., 2000). In addition, ENSO can modulate TS (Camargo et al., 2005; Iizuka and Matsuura, 2008) through atmospheric pressure changes, with a stronger relationship occurring during summer (Zhao and Wang, 2019).

Based on the decomposition signal (Figure S1), significant wave height (Hs) in EA shows a decadal signal. This condition implies that the leading mode of anomalous sea surface temperature (SST) in the North Pacific, namely the Pacific Decadal Oscillation (PDO; Mantua et al., 1997) could contribute to Hs variation in the WNP. Wang et al. (2008) reported that the PDO could also modulate ENSO. Consequently, numerous studies have assessed the effects of the ENSO–PDO on anomalous variables, including heavy precipitation (Chan and Zhou, 2005; Wu and Mao, 2016) and atmospheric circulation (Kim et al., 2014; Lee et al., 2019). Although information on extreme ocean waves under the effect of climate modes remain limited, previous studies have attempted to improve our understanding of extreme ocean wave variation with respect to climate variability. A global study by Kumar et al. (2016) showed that the phase (in or out) of ENSO and PDO occurrence could strengthen or weaken the maximum wave height during winter. Results consistent with this were obtained by Yang and Oh (2020), who investigated the response of extreme anomalous summer wave power density in the WNP during the in phase of ENSO–PDO. They argued that the PDO modulation of the ENSO effect on extreme wave power was linked to southeast trade wind variations.

However, the response of extreme event attributes, such as the duration and the intensity of events under the El Niño effect during summer, has not been addressed thus far. This information is essential because the extreme wave impact on coastal regions is determined by the duration and strength of extreme events. For example, extreme wave height that occurred for 14 h caused significant damage to the breakwaters of Seogwipo harbour on Jeju Island (Chae et al., 2013). The duration of extreme waves plays a crucial role in determining the breakwater stability. Therefore, investigating how the PDO modulates the El Niño effect on extreme wave duration is necessary. This study aimed to assess the extreme wave climate over 42 years and quantify the duration and intensity. The combined effects of ENSO and PDO during summer were determined. The influence of TS activity was also evaluated. The findings of this study contribute to improving the understanding of extreme wave variations in EA under the climate-mode effect.

This study used the boreal summer (JJA: June–August) for the analysis. Hourly significant wave height (Hs) data from the ERA5 reanalysis for the duration of 1980–2021 were used to detect extreme events. Similarly, the JJA mean wind speed at the 10-m level and the wave period and direction were calculated from the same reanalysis datasets to examine the oceanic conditions during the extreme period. Furthermore, the JJA mean of the optimum interpolation of sea surface temperature (OISST) (Reynolds et al., 2007) from the National Oceanic and Atmospheric Administration (NOAA) and sea-level pressure (SLP; ERA5) were also calculated from the daily and 6-h Hs data, respectively, to examine the possible drivers. The TS data at 6 h intervals were obtained from the Typhoon best track data of the Regional Specialized Meteorological Center (RSMC) – Tokyo Typhoon Center.

Following Weisse and Gunther (2007), extreme wave events were quantitatively observed when the hourly Hs exceeded the 99th percentile (threshold) of the study period (Fig. 1A), applying the POT method. The 99th percentile can be regarded as the highest 1% of Hs data. The attributes for describing the extreme wave characteristics consist of duration, i.e., the period in which Hs remains above the threshold and intensity i.e., the averaged of differences between the Hs values and the threshold during the extreme event). A set of summary statistics is provided for each annual attribute, such as the mean duration (calculated from the frequency-weighted average per year) and mean intensity (average intensity per year). As the main interest is in extreme intensity, the return values (RVs) from the observed events which correspond to the return period were estimated using the inverse cumulative distribution function of the General Pareto Distribution (GPD). The GPD method has been commonly applied to estimate the return values of extreme waves such as Takbash and Young (2020) and Wang et al. (2021). The confidence interval of RVs is calculated using a Monte-Carlo method. Furthermore, the Niño 3.4 and PDO indices were used to investigate the link between extreme waves and climate variability.

In this study, the ENSO and PDO were considered to interact with each other. Following Kumar et al. (2016), the dependency of the indices was elucidated using simple linear regression to investigate the impact of individual climate modes. For example, the ENSO-independent index is the deviation between the original ENSO time series and the regressed component (ENSO onto PDO regression). Figure 1B shows the detrended and normalized time series for ENSO during the summer, with the black line representing the original ENSO and the red line representing ENSO independent of the PDO. This indicates that the PDO influences the year-to-year variation in ENSO and vice versa (Fig. 1C). An independent ENSO was then used to examine the individual effects of ENSO on extreme events. The combined effect was assessed by conducting a composite analysis using the selected years (Table 1) based on the original time series. Further, to determine the extreme variation in Hs, a detailed investigation was conducted on the area-averaged Hs of the prominent spot which was observed in Fig. 2A and B.

Table 1

Categorization of selected years when El Niño and a positive or negative Pacific Decadal Oscillation (PDO) was greater than the threshold from 1980–2021 (see black line in Fig. 1).
El Nino (ENSO+)
PDO+	1987,1992,1993,1997,2015,2019
PDO-	1982,1991,1994

3.1 Characteristics of EA Extreme Wave Climate

Figure 2 shows the extreme wave attributes observed during the study period. Extreme waves were recorded widely over the study area and persisted for 8–35 h (Fig. 2A). Notably, the analysis revealed a distinct pattern between the southern and northern parts of the domain, where the region of 125–145°E with a latitude below 30°N exhibited durations exceeding 20 h. Similarly, the most significant intensities, reaching up to 1.5 m, also appeared in the southern domain and were concentrated in 130–138 °E (Fig. 2B). This indicates that the southern areas of Korea and Japan in the EA region are places for the prominent extreme wave events with the longest and greatest wave intensities. This finding is consistent with that of Jeong et al. (2016) who investigated observational data along the Korean coasts and revealed that the southern coast is the most pronounced owing to the southerly storms. Furthermore, extreme wave attributes were calculated from the domain-averaged Hs to better understand the spatiotemporal characteristics. In this study, the most prominent spot, indicated by a black box (BB; Fig. 2A and B), was chosen for analysis; the extreme waves in the prominent spots were found to be longer (Fig. 2C) and more intense (Fig. 2D) in summer and autumn (fall).

The spatial patterns of the wind and wave direction and period that correspond to extreme events are shown in Fig. 3. It can be inferred that the extreme waves in the southern domain, which encompasses the BB area, predominantly originate from the southeast (Fig. 3A) and are characterized by wave periods of more than 9 s (Fig. 3B). Given the higher intensity and longer periods of the waves, this region is the most energetic compared to the other EA marginal seas, such as the YS and ES. This behaviour could be associated with the summer monsoonal wind, with typical strong south-easterlies blowing to the EA region (Fig. 3C). Moreover, extreme waves in the ECS originate from the southeast and southwest, implying a swell influence from the southern part. This finding is consistent with that of Li et al. (2016) who suggested that a long wind fetch contributes to higher Hs in the ECS. However, the severe waves in the ES partly originate from the northwest (Fig. 3A), indicating different characteristics from those in the southern domain. In a separate analysis, the seasonal distribution of extreme wave attributes based on domain-averaged data shows that severe events in the ES had a longer duration and greater intensity in the winter season (Figure S2). This is consistent with the findings of Heo et al. (2020), who suggested that pressure changes during the winter season caused extreme wave in EA and induced high swell-like waves along the eastern part of the Korean coast.

3.2 Influence of El Nino on summer extreme waves

Once the prominent extreme spots and periods were determined, further examination focused on the influence of the climate mode (Fig. 4). The spatial pattern of the regression coefficients for the summer JJA Hs on the independent ENSO mostly showed statistically significant (95% confidence level) positive anomalies over the EA region (Fig. 4A). This indicates that the EA waves were higher than usual during El Niño events in the JJA months. Notably, the BB area experienced a significant impact with the most noticeable increase in wave height, as expected. In line with the aforementioned impact, the BB extreme events lasted longer, reaching an average of 85 h with a maximum intensity of approximately 2 m above the threshold during El Niño. A greater impact occurred when El Niño was in phase with the PDO: the extremes persisted for approximately double the duration on average (Fig. 4B) and mean intensity tended to increase by 0.5 m (Fig. 4C) with respect to the neutral condition. Consistent with previous studies (Kumar et al., 2016 among others), these findings suggest that the PDO strengthens the effect of El Niño, specifically the duration and intensity of summer extreme waves.

The spatial patterns of anomalous oceanic and atmospheric conditions during the El Niño and PDO phase combinations, which were based on composite analysis, are shown in Fig. 5. Stronger anomalous summer wind speeds appeared in southern part of study domain including the BB area (Fig. 5B). Consequently, more widespread, and higher positive anomalous Hs dominated the EA region (Fig. 5A)., compared with the independent El Niño. Furthermore, the strong winds in the southern domain coexisted with warmer SST (Fig. 5C). This behaviour was associated with a strong anomalous anticyclonic formation, as indicated by the high-pressure northeast of the Philippine Sea (Fig. 5D). Additionally, the observed horizontal anomalous pressure gradient at 5°N–10°N indicated strong westerlies which could intensify the Philippine Sea anticyclone (PSAC) through El Niño-induced Indonesian subsidence.

3.3 Implications

The most extreme wave spot, indicated by duration and intensity with the more severe period during summer, is found in southern part of the study area, and in the track to impact the southern Korean coast. The modulation of summer extreme waves under the influence of climate mode was determined, providing evidence of longer and more intense extreme wave events during the El Niño period. The stronger El Niño effect on the summer extreme wave was stronger when El Niño was in phase with the PDO. This condition is associated with a strong anomalous PSAC, which can possibly alter TS activity. The locations of TS genesis, which correspond to summer extreme wave events in the BB area, are more eastward (Fig. 6). As expected, this was a consequence of strong El Niño-induced westerlies (Fig. 5D). This allows the TS to survive longer before reaching the land, potentially leading to longer and more powerful storms during El Niño, as shown in previous studies (Wang and Chan, 2002; Yang and Oh, 2018). Additionally, Wang and Zhang (2002) suggested that there was a higher occurrence of a northward TS track during El Niño when the PSAC formed. This would be more impactful for extreme waves in the EA region. Furthermore, the increasing EA summer wind speed trend over the study period coexisted with the positive SST (Figure S3), indicating a higher TS influence in recent decades.

To consider the important aspect of risk assessment, the RV estimation based on summer extreme wave intensity and duration in the BB area is shown in Fig. 7. The qqplot (Fig. 7A) shows the model of the empirical quantile used to evaluate the fitting quality. This clearly shows that the GPD is sufficient for modelling the cumulative distribution function of a data series. The estimated RVs revealed the possibility of future extreme summer Hs duration and intensities (Fig. 7B). The increasing RV reaches nearly 100 hours with about 2 m by the 100-year return period and is more likely to be exposed to extreme wave height-induced disasters twice larger than the present ones. It means that the doubled coastal impact can occur over the long-term period, compared to the impacts caused by that of the 5-year or less return period. An important implication of these findings is the potential impact of longer and more intense future summer extreme waves on the southern coast of Korea, since the extremes in the ECS, which are directly bordered, are more likely to be associated with the wave conditions in the BB area.

This paper presented a retrospective study, analysing the wave heights to record the spatial temporal of extreme ocean wave events from 1980 to 2021 in the East Asian Regions. Based on the spatial distribution, the extreme ocean waves were found across the study domain, revealing the prolonged and high intensity events throughout the study period in the southern area of domain. This study also identified the seasonal response of the prominent spot where the extreme events tend to be more severe in summer season. Furthermore, in relation to the influence of dominant climate mode in the Pacific Ocean, the extreme wave events have been revealed to be more intense and of longer duration, associated with the El Niño-induced anomalous conditions. The El Niño effect on summer EA is stronger when it is in-phase with the PDO + extreme waves through strong anticyclonic formations in the Philippine Sea. Potentially longer and stronger tropical storms due to the eastward shifting of their genesis during El Niño events may be responsible for the more severe wave events in the East Asian region. These findings contribute to the understanding of the link between ENSO and TS activity with respect to extreme wave duration and intensity, which can be relevant factors in the mitigation plan for extreme wave impacts on coastal environments, especially for the potential affected area such as the southern coast of Korea. Further study on how their behaviors will change in the future due to climate change is crucial.

EA	: East Asian	JJA	: June-July-August
POT	: Peaks-over-threshold	OISST	: Optimum Interpolation of Sea Surface Temperature
PDO	: Pacific Decadal Oscillation	NOAA	: National Oceanic and Atmospheric Administration
TS	: Tropical Storm	SLP	: Sea-level Pressure
ES	: East Sea	RSMC	: Regional Specialized Meteorological Center
YS	: Yellow Sea	RV	: Return Value
ECS	: East China Sea	NCEI	: National Centers for Environmental Information
WNP	: Western North Pacific	BB	: Black Box
ENSO	: El Niño Southern Oscillation	PSAC	: Philippine Sea anticyclone
Hs	: Significant wave height

Availability of data and materials

The ERA5 data used in this study are downloaded from Copernicus Climate Data Store https://cds.climate.copernicus.eu/. Climate indices such as Nino3.4 and PDO are provided by NOAA Climate Prediction Center (https://origin.cpc.ncep.noaa.gov/) and National Centers for Environmental Information (https://www.ncei.noaa.gov/access/monitoring/pdo/). Typhon best track data were freely retrieved from Japan Meteorological Agency through https://www.jma.go.jp/jma/jma-eng/jma-center/rsmc-hp-pub-eg/besttrack.html.

Competing Interest

The authors declare that we have no competing interest.

Funding

This study was supported by UST Young Scientist+ Research Program 2022 through the University of Science and Technology (No. PN91470), KIOST(PEA0142), and Korea Institute of Marine Science & Technology Promotion (KIMST) funded by the Ministry of Oceans and Fisheries, Korea (20220431, Development of Simulation Technology for Maritime Spatial Policy).

Author contributions

Ahmad Bayhaqi: Conceptualization; Data curation; Visualization; Writing – original draft. Jeseon Yoo: Supervision; Project administration; Writing – review and editing.

Acknowledgements

The authors thank editors and anonymous reviewers for insightful comments that improve the manuscript.

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You are reading this latest preprint version

Effect of El Niño on Summer Extreme Ocean Waves over East Asian Regions

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Version 1

Abstract

Figures

1. Introduction

2. Data and Methods

3. Results and Discussions

3.1 Characteristics of EA Extreme Wave Climate

3.2 Influence of El Nino on summer extreme waves

3.3 Implications

4. Conclusion

Abbreviations

Declarations

References

Supplementary Files

Status:

Version 1