The inter-annual variations of the significant wave height in the Western North Pacific and South China Sea region

Li, Shaotian; Li, Yineng; Peng, Shiqiu; Qi, Zhou

doi:10.1007/s00382-021-05636-9

Cited by 8 publications

(8 citation statements)

References 75 publications

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“…Such a WNPAC weakens the northeasterly winter monsoon, leading to weaker WS and smaller mixed-layer NIE in the study region. Consistent with previous studies (Li et al, 2021;Xu et al, 2019;Yuan & Yang, 2012), composite wind anomalies of strong El Niño events (not shown) exhibit an obvious anomalous cyclone to the northwest of the warming region and a WNPAC around the Philippine Sea.…”

Section: Interannual Variation Of Winter Niesupporting

confidence: 92%

“…For example, diapycnal mixing in the equatorial thermocline has been shown to be modulated by ENSO and is stronger during La Niña years (Richards et al., 2012). The northeast winter monsoon weakened by the El Niño‐related WNPAC leads to reduced surface wave height in the SCS (Li et al., 2021). Due to the change of stratification, vertical structures of internal tides near Xisha Island in the SCS are modulated by ENSO (Zhai et al., 2020).…”

Section: Introductionmentioning

confidence: 99%

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Interannual Variability of Near‐Inertial Energy in the South China Sea and Western North Pacific

Chen

Liu

et al. 2022

Geophysical Research Letters

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El Niño-Southern Oscillation (ENSO) is the most pronounced interannual climate variation on Earth. It has significant influences on human activities and many previous studies have focused on its modulation on the oceanic and atmospheric changes. Sea surface temperature (SST) anomalies (SSTA) in the tropical Pacific during El Niño could affect SSTA in the tropical Indian and Atlantic Oceans through Walker circulation (Chiang & Sobel, 2002;Latif & Barnett, 1995). El Niño could also affect the South China Sea (SCS) by inducing double-peak SSTA around February and August in the following El Niño year . During the El Niño developing summer, the number of intense and recurve-northward tropical cyclones (TCs) significantly increases (Camargo & Sobel, 2005;Wang & Chan, 2002). Initiation of the western North Pacific anomalous anticyclone (WNPAC) over the Philippine Sea is induced by SST cooling that results from the combined effects of the mean northeast trade wind and equatorward wind anomalies caused by El Niño (Wang et al., 2000). The weakened northeast monsoon affected by the wintertime WNPAC leads to weaker Kuroshio Loop Current and upper Luzon Strait transport in the northern SCS (

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Section: Interannual Variation Of Winter Niesupporting

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Interannual Variability of Near‐Inertial Energy in the South China Sea and Western North Pacific

Chen

Liu

et al. 2022

Geophysical Research Letters

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“…Similarly, significant Hmax responses to the ENSO are found over comparable regions but with limited spatial extent. Prior studies in this context use total SWH and obtain similar significant regions in response to ENSO (Izaguirre et al ., 2011; Patra et al ., 2020; Li et al ., 2021). However, the current study quantifies the individual responses of wind‐sea and swell SWH to various climate variability modes.…”

Section: Discussionmentioning

confidence: 99%

Influence of climate variability on wind‐sea and swell wave height extreme over the Indo‐Pacific Ocean

Kumar

Sardana

Kaur

et al. 2022

Intl Journal of Climatology

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In the Indo-Pacific Ocean (IPO), extreme significant wave heights (SWHs) can substantially induce coastal erosion, flooding, and devastating impacts on coastal livelihoods. This study examines the seasonal influence of the El Niño-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), Southern Annular Mode (SAM), and Pacific North American (PNA) pattern on extreme windwave parameters. The climatic extremes are calculated utilizing ERA5 reanalysis datasets from 1979 to 2019 and a nonstationary generalized extreme value distribution. Significant increases in extreme wind-sea (Hmax) and swell SWH (Hmax Sw ) response to ENSO occur over the northeast North Pacific (NP) during December-February (DJF) and western NP during June-August (JJA).The PNA influence exhibits a similar pattern to ENSO during DJF yet is inactive in JJA. Hmax and Hmax Sw responses to the IOD during September-November (SON) include significant increases over the western Pacific, southern Indian Ocean (IO), and southwest tropical IO, yet decreases over the central tropical IO. The Hmax Sw response to the SAM is larger than that for Hmax over the southern IPO during DJF, which extends toward the eastern Pacific in March-May (MAM). Overall, extreme wind-sea and swell parameter responses are found to be associated with sea level pressure (SLP) and SLP gradients. K E Y W O R D S climate variability, generalized extreme value (GEV) distribution, Indo-Pacific Ocean, wind-sea and swell SWH

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“…The model can provide hourly forecasts with a spatial resolution of 1/40°*1/40°. A more detailed description of the data is available here (Li et al, 2021). Due to the high accuracy of these data, they can be used as an approximation of the observed data in the case of insufficient actual measurement data.…”

Section: Datamentioning

confidence: 99%

A significant wave height prediction method based on deep learning combining the correlation between wind and wind waves

et al. 2022

Self Cite

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Accurate wave height prediction is significant in ports, energy, fisheries, and other offshore operations. In this study, a regional significant wave height prediction model with a high spatial and temporal resolution is proposed based on the ConvLSTM algorithm. The model learns the intrinsic correlations of the data generated by the numerical model, making it possible to combine the correlations between wind and wind waves to improve the predictions. In addition, this study also optimizes the long-term prediction ability of the model through the proposed Mask method and Replace mechanism. The experimental results show that the introduction of the wind field can significantly improve the significant wave height prediction results. The research on the prediction effect of the entire study area and two separate stations shows that the prediction performance of the proposed model is better than the existing methods. The model makes full use of the physical correlation between wind and wind waves, and the validity is up to 24 hours. The 24-hour forecast R² reached 0.69.

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The inter-annual variations of the significant wave height in the Western North Pacific and South China Sea region

Cited by 8 publications

References 75 publications

Interannual Variability of Near‐Inertial Energy in the South China Sea and Western North Pacific

Interannual Variability of Near‐Inertial Energy in the South China Sea and Western North Pacific

Influence of climate variability on wind‐sea and swell wave height extreme over the Indo‐Pacific Ocean

A significant wave height prediction method based on deep learning combining the correlation between wind and wind waves

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