Interannual variability of wave climate in the Caribbean Sea

Vega, Marco J.; Álvarez-Silva, Óscar; Restrepo, Juan Camilo; Royero, Juan Carlos Ortíz; Díaz, Luis Jesús Otero

doi:10.1007/s10236-020-01377-1

Cited by 17 publications

(11 citation statements)

References 33 publications

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“…Figure 6 is consistent with several studies [54,55,58,73,75] that indicate an association between a tropical basin SST gradient and modification of the Caribbean trade wind regime and the CLLJ. Refs.…”

Section: Compositessupporting

confidence: 91%

“…The CLLJ has a July peak [72] and, as previously shown, sea levels on the south coast of Jamaica peak in August. The Pac-Atl gradient and ENSO, through its influence on the gradient, also impact the CLLJ summer strength [55,73], likely accounting for the significant correlations seen with the index in Table 4a. This suggests a significant role for the CLLJ in driving sea level change on seasonal and interannual timescales.…”

Section: Eof Analysis Of the Raw Versus Detrended Datamentioning

confidence: 99%

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Investigation of Multi-Timescale Sea Level Variability near Jamaica in the Caribbean Using Satellite Altimetry Records

Maitland,

Taylor,

Stephenson

2023

JMSE

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There is a dearth of studies characterizing historical sea level variability at the local scale for the islands in the Caribbean. This is due to the lack of reliable long term tide gauge data. There is, however, a significant need for such studies given that small islands are under increasing threat from rising sea levels, storm surges, and coastal flooding due to global warming. The growing length of satellite altimetry records provides a useful alternative to undertake sea level analyses. Altimetry data, spanning 1993–2019, are used herein to explore multi-timescale sea level variability near the south coast of Jamaica, in the northwest Caribbean. Caribbean basin dynamics and largescale forcing mechanisms, which could account for the variability, are also investigated. The results show that the average annual amplitude off the south coast of Jamaica is approximately 10 cm with a seasonal peak during the summer (July–August). The highest annual sea levels occur within the Caribbean storm season, adding to the annual risk. The annual trend over the 27 years is 3.3 ± 0.4 mm/yr when adjusted for Glacial Isostatic Adjustment (GIA), instrumental drift, and accounting for uncertainties. This is comparable to mean global sea level rise, but almost twice the prior estimates for the Caribbean which used altimetry data up to 2010. This suggests an accelerated rate of rise in the Caribbean over the last decade. Empirical Orthogonal Function (EOF) and correlation analyses show the long-term trend to be a basin-wide characteristic and linked to warming Caribbean sea surface temperatures (SSTs) over the period. When the altimetry data are detrended and deseasoned, the leading EOF mode has maximum loadings over the northwest Caribbean, including Jamaica, and exhibits interannual variability which correlates significantly with a tropical Pacific-tropical Atlantic SST gradient index, local wind strength, and the Caribbean Low Level Jet (CLLJ). Correlations with the El Niño Southern Oscillation (ENSO) in summer, seen in this and other studies, likely arise through the contribution of the ENSO to the SST gradient index and the ENSO’s modulation of the CLLJ peak strength in July. The results demonstrate the usefulness of altimetry data for characterizing sea level risk on various timescales for small islands. They also suggest the potential for developing predictive models geared towards reducing those risks.

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Section: Compositessupporting

confidence: 91%

Section: Eof Analysis Of the Raw Versus Detrended Datamentioning

confidence: 99%

Investigation of Multi-Timescale Sea Level Variability near Jamaica in the Caribbean Using Satellite Altimetry Records

Maitland,

Taylor,

Stephenson

2023

JMSE

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“…Thus, while the joint SWAN-LSTM model can help to overcome the lack of robust data due to faulty or absent observation platforms and sensors, extra attention should be placed on ensuring the robustness of SWAN itself to minimize the accumulation of errors. Additionally, although SWH data are only extracted from the model at two locations, other locations can be selected, and virtual buoys established to perform additional wave studies [47][48][49][50]. At these new locations, using the currently validated SWAN-LSTM model, high fidelity inversions of SWH to WSP can be performed to increase the coverage of 'observations' for wind research in general [51][52][53], but co-located wind and wave Additionally, although SWH data are only extracted from the model at two locations, other locations can be selected, and virtual buoys established to perform additional wave studies [47][48][49][50].…”

Section: Applications: Wind and Wave Reconstructionsmentioning

confidence: 99%

“…Additionally, although SWH data are only extracted from the model at two locations, other locations can be selected, and virtual buoys established to perform additional wave studies [47][48][49][50]. At these new locations, using the currently validated SWAN-LSTM model, high fidelity inversions of SWH to WSP can be performed to increase the coverage of 'observations' for wind research in general [51][52][53], but co-located wind and wave Additionally, although SWH data are only extracted from the model at two locations, other locations can be selected, and virtual buoys established to perform additional wave studies [47][48][49][50]. At these new locations, using the currently validated SWAN-LSTM model, high fidelity inversions of SWH to WSP can be performed to increase the coverage of 'observations' for wind research in general [51][52][53], but co-located wind and wave energy assessments in particular [54,55].…”

Section: Applications: Wind and Wave Reconstructionsmentioning

confidence: 99%

Bidirectional Modeling of Surface Winds and Significant Wave Heights in the Caribbean Sea

Bethel

Zhou

Cao

2021

JMSE

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Though the ocean is sparsely populated by buoys that feature co-located instruments to measure surface winds and waves, their data is of vital importance. However, due to either minor instrumentation failure or maintenance, intermittency can be a problem for either variable. This paper attempts to mitigate the loss of valuable data from two opposite but equivalent perspectives: the conventional reconstruction of significant wave height (SWH) from Caribbean Sea buoy-observed surface wind speeds (WSP) and the inverse modeling of WSP from SWH using the long short-term memory (LSTM) network. In either direction, LSTM is strongly able to recreate either variable from its counterpart with the lowest correlation coefficient (r2) measured at 0.95, the highest root mean square error (RMSE) is 0.26 m/s for WSP, and 0.16 m for SWH. The highest mean absolute percentage errors (MAPE) for WSP and SWH are 1.22% and 5%, respectively. Additionally, in the event of complete instrument failure or the absence of a buoy in a specific area, the Simulating WAves Nearshore (SWAN) wave model is first validated and used to simulate mean and extreme SWH before, during, and after the passage of Hurricane Matthew (2016). Synthetic SWH is then fed to LSTM in a joint SWAN—LSTM model, and the corresponding WSP is reconstructed and compared with observations. Although the reconstruction is highly accurate (r2 > 0.9, RMSE < 1.3 m/s, MAPE < 0.8%), there remains great room for improvement in minimizing error and capturing high-frequency events.

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“…Sea-level change is not spatially uniform, and hence different regions experience different rates of sea-level rise. Spatial sea-level trend variability in the Caribbean is related to changes in regional ocean circulation systems such as the Panama-Colombia Gyre 13 , 14 as well as with changes in the Caribbean Low-Level Jet (CLLJ) which may cause changes in wave height when it intensifies 15 . The signature of regional ocean circulation systems is also captured in the dynamic sea-level height, which is projected to change under different climate scenarios.…”

Section: Introductionmentioning

confidence: 99%

Determining sea-level rise in the Caribbean: A shift from temperature to mass control

Maitland,

Richter,

Raj

et al. 2024

Sci Rep

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Tropical Small Island Developing States (SIDS), such as those in the Caribbean, are among the most vulnerable to the impacts of climate change, most notably sea-level rise. The current sea-level rise in the Caribbean is 3.40 ± 0.3 mm/year (1993–2019), which is similar to the 3.25 ± 0.4 mm/year global mean sea-level (GMSL) rise (1993–2018). Throughout the year, Caribbean seasonal sea-level variability is found to respond to sea surface temperature variability. Over the past few decades, the trend in Caribbean Sea-level rise is also found to be variable. Satellite altimetry and steric sea-level records of the Caribbean region reveal a shift in the late 2003-early 2004, which separates two distinct periods of sea-level rise. Thermal expansion dominates the sea-level trend from 1993–2003. Following this period, there is an increased trend in sea-level rise, with a dominance of mass changes from 2004–2019, as confirmed by GRACE data. During this period, the sea-level trend is 6.15 ± 0.5 mm/year, which is 67% faster than the most recent estimates of global mean sea-level rise provided by the Intergovernmental Panel on Climate Change (3.69 ± 0.5 mm/year for the period 2006–2018). Despite its reduced importance, increasing temperatures contribute greatly to sea-level rise in the Caribbean region through thermal expansion of ocean water, hence there is a need to limit the current trend of global warming.

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Interannual variability of wave climate in the Caribbean Sea

Cited by 17 publications

References 33 publications

Investigation of Multi-Timescale Sea Level Variability near Jamaica in the Caribbean Using Satellite Altimetry Records

Investigation of Multi-Timescale Sea Level Variability near Jamaica in the Caribbean Using Satellite Altimetry Records

Bidirectional Modeling of Surface Winds and Significant Wave Heights in the Caribbean Sea

Determining sea-level rise in the Caribbean: A shift from temperature to mass control

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