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Inigo J Losada - One of the best experts on this subject based on the ideXlab platform.
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Exploring the interannual variability of Extreme Wave climate in the Northeast Atlantic Ocean
Ocean Modelling, 2012Co-Authors: Cristina Izaguirre, Melisa Menendez, Fernando J Mendez, Paula Camus, Roberto Mínguez, Inigo J LosadaAbstract:Abstract The Extreme Wave climate is of paramount importance for: (i) off-shore and coastal engineering design, (ii) ship design and maritime transportation, or (iii) analysis of coastal processes. Identifying the synoptic patterns that produce Extreme Waves is necessary to understand the Wave climate for a specific location. Thus, a characterization of these weather patterns may allow the study of the relationships between the magnitude and occurrence of Extreme Wave events and the climate system. The aim of this paper is to analyze the interannual variability of Extreme Wave heights. For this purpose, we present a methodological framework and its application to an area over the North East (NE) Atlantic Ocean. The climatology in the NE Atlantic is analyzed using the self-organizing maps (SOMs). The application of this clustering technique to monthly mean sea level pressure fields provides a continuum of synoptic categorizations compared with discrete realizations produced through most traditional methods. The Extreme Wave climate has been analyzed by means of monthly maxima of the significant Wave height (SWH) in several locations over the NE Atlantic. A statistical approach based on a time-dependent generalized Extreme value (GEV) distribution has been applied. The seasonal variation was characterized and, afterwards, the interannual variability was studied throughout regional pressure patterns. The anomalies of the 50-year return level estimates of SWH, due to interannual variability have been projected into the weather types of SOM. It provides a comprehensive visual representation, which relates the weather type with the positive or negative contribution to Extreme Waves over the selected locations.
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global Extreme Wave height variability based on satellite data
Geophysical Research Letters, 2011Co-Authors: Cristina Izaguirre, Melisa Menendez, Fernando J Mendez, Inigo J LosadaAbstract:[1] The spatial and temporal variability of the Extreme significant Wave height (SWH) in the ocean is presented. The study has been performed using a highly reliable dataset from several satellite altimeter missions, which provide a good worldwide coverage for the period 1992 onwards. A non-stationary Extreme value analysis, which models seasonality and interannual variations, has been applied to characterize the Extreme SWH. The interannual variability is explained through variations in the atmosphere and ocean systems, represented by different climate indices, allowing a quantitative contribution of the climate-related patterns. Results demonstrate the strong relationship between the interannual variability of Extreme SWH and different ocean and atmosphere variations. A contribution of the AO and NAO indices in the North Atlantic ocean (e.g., every positive unit of the AO explains up to 70 cm of Extreme Wave height south of Iceland), the NINO3 in the Pacific (every negative unit of NINO3 explains up to 60 cm of Extreme Wave height in the Drake Passage), the SAM in the Southern ocean and the DMI in the Indian ocean reveal these climate patterns as the most relevant in the interannual Extreme Wave climate.
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Extreme Wave climate variability in southern europe using satellite data
Journal of Geophysical Research, 2010Co-Authors: Cristina Izaguirre, Melisa Menendez, Fernando J Mendez, Alberto Luceno, Inigo J LosadaAbstract:[1] A time-dependent generalized Extreme value (GEV) model for monthly significant Wave height maxima from satellite databases is used to model the seasonal and interannual variability of the Extreme Wave climate throughout southern Europe. In order to avoid a misleading use of the maxima time series, the classical Extreme value model has been modified to cope with nonhomogeneous monthly observations. Seasonality is represented using intraannual harmonic functions in the model, while interannual variability is modeled including North Atlantic and Mediterranean regional scale sea level pressure predictors, such as the North Atlantic Oscillation (NAO), the east Atlantic (EA), or the east Atlantic/western Russian (EA/WR) patterns. The results quantify the strong spatial variability detected in the seasonal location and scale GEV parameters. In general, prominent zonal (west–east) and meridional (north–south) gradients of these location and scale parameters reveal the predominance of low-pressure centers located in the NAO region (e.g., a gradient of 4 m for the location parameter and 1.5 units for the scale parameter between north–south is shown in the month of September). The model also quantifies the influence of regional climate patterns on Extreme Wave climate. Results show a great influence of NAO and EA on the Atlantic basin (e.g., every unit of the monthly NAO index explains 25 cm of the Extreme Wave height in the Gulf of Biscay and the EA index explains 20 cm) while the negative phases of EA/WR contribute greatly to the western Mediterranean basin.
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Variability of Extreme Wave heights in the northeast Pacific Ocean based on buoy measurements
Geophysical Research Letters, 2008Co-Authors: Melisa Menendez, Fernando J Mendez, Inigo J Losada, Nicholas E GrahamAbstract:Recent studies reveal important trends in mean values and high percentiles of significant Wave height in the northeast Pacific. However, changes of the Extreme Wave heights through time have not received much attention. In this work, the long-term variability of Extreme significant Wave height along the northeast Pacific is modeled using a time-dependent Extreme value model. Application of the model to significant Wave height data sets from 26 buoys over the period 1985–2007 shows significant positive longterm trends in Extreme Wave height between 30–45N near the western coast of the US averaging 2.35 cm/yr. We also demonstrate an impact of El Nin˜o on Extreme Wave heights (about 25 cmper unit ofNINO3.4 index) in the northeast Pacific as well as important correlations with mid-latitudinal climate patterns (e.g., NP and PNA indices).
Fernando J Mendez - One of the best experts on this subject based on the ideXlab platform.
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Exploring the interannual variability of Extreme Wave climate in the Northeast Atlantic Ocean
Ocean Modelling, 2012Co-Authors: Cristina Izaguirre, Melisa Menendez, Fernando J Mendez, Paula Camus, Roberto Mínguez, Inigo J LosadaAbstract:Abstract The Extreme Wave climate is of paramount importance for: (i) off-shore and coastal engineering design, (ii) ship design and maritime transportation, or (iii) analysis of coastal processes. Identifying the synoptic patterns that produce Extreme Waves is necessary to understand the Wave climate for a specific location. Thus, a characterization of these weather patterns may allow the study of the relationships between the magnitude and occurrence of Extreme Wave events and the climate system. The aim of this paper is to analyze the interannual variability of Extreme Wave heights. For this purpose, we present a methodological framework and its application to an area over the North East (NE) Atlantic Ocean. The climatology in the NE Atlantic is analyzed using the self-organizing maps (SOMs). The application of this clustering technique to monthly mean sea level pressure fields provides a continuum of synoptic categorizations compared with discrete realizations produced through most traditional methods. The Extreme Wave climate has been analyzed by means of monthly maxima of the significant Wave height (SWH) in several locations over the NE Atlantic. A statistical approach based on a time-dependent generalized Extreme value (GEV) distribution has been applied. The seasonal variation was characterized and, afterwards, the interannual variability was studied throughout regional pressure patterns. The anomalies of the 50-year return level estimates of SWH, due to interannual variability have been projected into the weather types of SOM. It provides a comprehensive visual representation, which relates the weather type with the positive or negative contribution to Extreme Waves over the selected locations.
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global Extreme Wave height variability based on satellite data
Geophysical Research Letters, 2011Co-Authors: Cristina Izaguirre, Melisa Menendez, Fernando J Mendez, Inigo J LosadaAbstract:[1] The spatial and temporal variability of the Extreme significant Wave height (SWH) in the ocean is presented. The study has been performed using a highly reliable dataset from several satellite altimeter missions, which provide a good worldwide coverage for the period 1992 onwards. A non-stationary Extreme value analysis, which models seasonality and interannual variations, has been applied to characterize the Extreme SWH. The interannual variability is explained through variations in the atmosphere and ocean systems, represented by different climate indices, allowing a quantitative contribution of the climate-related patterns. Results demonstrate the strong relationship between the interannual variability of Extreme SWH and different ocean and atmosphere variations. A contribution of the AO and NAO indices in the North Atlantic ocean (e.g., every positive unit of the AO explains up to 70 cm of Extreme Wave height south of Iceland), the NINO3 in the Pacific (every negative unit of NINO3 explains up to 60 cm of Extreme Wave height in the Drake Passage), the SAM in the Southern ocean and the DMI in the Indian ocean reveal these climate patterns as the most relevant in the interannual Extreme Wave climate.
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Extreme Wave climate variability in southern europe using satellite data
Journal of Geophysical Research, 2010Co-Authors: Cristina Izaguirre, Melisa Menendez, Fernando J Mendez, Alberto Luceno, Inigo J LosadaAbstract:[1] A time-dependent generalized Extreme value (GEV) model for monthly significant Wave height maxima from satellite databases is used to model the seasonal and interannual variability of the Extreme Wave climate throughout southern Europe. In order to avoid a misleading use of the maxima time series, the classical Extreme value model has been modified to cope with nonhomogeneous monthly observations. Seasonality is represented using intraannual harmonic functions in the model, while interannual variability is modeled including North Atlantic and Mediterranean regional scale sea level pressure predictors, such as the North Atlantic Oscillation (NAO), the east Atlantic (EA), or the east Atlantic/western Russian (EA/WR) patterns. The results quantify the strong spatial variability detected in the seasonal location and scale GEV parameters. In general, prominent zonal (west–east) and meridional (north–south) gradients of these location and scale parameters reveal the predominance of low-pressure centers located in the NAO region (e.g., a gradient of 4 m for the location parameter and 1.5 units for the scale parameter between north–south is shown in the month of September). The model also quantifies the influence of regional climate patterns on Extreme Wave climate. Results show a great influence of NAO and EA on the Atlantic basin (e.g., every unit of the monthly NAO index explains 25 cm of the Extreme Wave height in the Gulf of Biscay and the EA index explains 20 cm) while the negative phases of EA/WR contribute greatly to the western Mediterranean basin.
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Variability of Extreme Wave heights in the northeast Pacific Ocean based on buoy measurements
Geophysical Research Letters, 2008Co-Authors: Melisa Menendez, Fernando J Mendez, Inigo J Losada, Nicholas E GrahamAbstract:Recent studies reveal important trends in mean values and high percentiles of significant Wave height in the northeast Pacific. However, changes of the Extreme Wave heights through time have not received much attention. In this work, the long-term variability of Extreme significant Wave height along the northeast Pacific is modeled using a time-dependent Extreme value model. Application of the model to significant Wave height data sets from 26 buoys over the period 1985–2007 shows significant positive longterm trends in Extreme Wave height between 30–45N near the western coast of the US averaging 2.35 cm/yr. We also demonstrate an impact of El Nin˜o on Extreme Wave heights (about 25 cmper unit ofNINO3.4 index) in the northeast Pacific as well as important correlations with mid-latitudinal climate patterns (e.g., NP and PNA indices).
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A probability distribution for depth-limited Extreme Wave heights in a sea state
Coastal Engineering, 2007Co-Authors: Fernando J Mendez, Sonia CastanedoAbstract:A model for the depth-limited distribution of the highest Wave in a sea state is presented. The distribution for the Extreme Wave height is based on a probability density function (pdf) for depth-limited Wave height distribution for individual Waves [Mendez, F.J., Losada, I.J., Medina, R. 2004. Transformation model of Wave height distribution. Coastal Eng, Vol. 50, 97:115.] and considers the correlation between consecutive Waves. The model is validated using field data showing a good representation of the Extreme Wave heights in the surf zone. Some important statistical Wave heights are parameterized obtaining useful expressions that can be used in further calculations.
Frédéric Dias - One of the best experts on this subject based on the ideXlab platform.
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Extreme Wave run-up on a vertical cliff
Geophysical Research Letters, 2013Co-Authors: Francesco Carbone, Denys Dutykh, John Michael Dudley, Frédéric DiasAbstract:Wave impact and run-up onto vertical obstacles are among the most important phenomena which must be taken into account in the design of coastal structures. From linear Wave theory, we know that the Wave amplitude on a vertical wall is twice the incident Wave amplitude with weakly nonlinear theories bringing small corrections to this result. In this present study, however, we show that certain simple Wave groups may produce much higher run-ups than previously predicted, with particular incident Wave frequencies resulting in run up heights exceeding the initial Wave amplitude by a factor of 5, suggesting that the notion of the design Wave used in coastal structure design may need to be revisited. The results presented in this study can be considered as a note of caution for practitioners, on one side, and as a challenging novel material for theoreticians who work in the field of Extreme Wave - coastal structure interaction.
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Extreme Wave run-up on a vertical cliff
2013Co-Authors: Francesco Carbone, Denys Dutykh, John Michael Dudley, Frédéric DiasAbstract:Wave impact and run-up onto vertical obstacles constitutes one of the main phenomena which have to be taken into account in the design of coastal structures. From the linear Wave theory we know that the Wave height on a vertical wall is twice the incident Wave amplitude. Weakly nonlinear theories bring some small corrections to this result. However, in the present study we show that certain simple Wave groups may produce much higher run-ups ever predicted by previous theoretical investigations. Consequently, the results presented in this study can be considered as a note of caution for practitioners, on one side, and as a challenging novel material for theoreticians who work in the field of the Wave/structure interaction.
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Extreme Wave runup on a vertical cliff
Geophysical Research Letters, 2013Co-Authors: Francesco Carbone, Denys Dutykh, John Michael Dudley, Frédéric DiasAbstract:Wave impact and runup onto vertical obstacles are among the most important phenomena which must be taken into account in the design of coastal structures. From linear Wave theory, we know that the Wave amplitude on a vertical wall is twice the incident Wave amplitude with weakly nonlinear theories bringing small corrections to this result. In this present study, however, we show that certain simple Wave groups may produce much higher runups than previously predicted, with particular incident Wave frequencies resulting in runup heights exceeding the initial Wave amplitude by a factor of 5, suggesting that the notion of the design Wave used in coastal structure design may need to be revisited. The results presented in this study can be considered as a note of caution for practitioners, on one side, and as a challenging novel material for theoreticians who work in the field of Extreme Wave-coastal structure interaction.
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Extreme Wave events in Ireland: 14 680 BP-2012
Natural Hazards and Earth System Sciences, 2013Co-Authors: L. O'brien, John Michael Dudley, Frédéric DiasAbstract:The island of Ireland is battered by Waves from all sides, most ferociously on the west coast as the first port of call for Waves travelling across the Atlantic Ocean. However, when discussing ocean events relevant to the nation of Ireland, one must actually consider its significantly larger designated continental shelf, which is one of the largest seabed territories in Europe. With this expanded definition, it is not surprising that Ireland has been subject to many oceanic events which could be designated as "Extreme"; in this paper we present what we believe to be the first catalogue of such events, dating as far back as the turn of the last ice age.
Melisa Menendez - One of the best experts on this subject based on the ideXlab platform.
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Exploring the interannual variability of Extreme Wave climate in the Northeast Atlantic Ocean
Ocean Modelling, 2012Co-Authors: Cristina Izaguirre, Melisa Menendez, Fernando J Mendez, Paula Camus, Roberto Mínguez, Inigo J LosadaAbstract:Abstract The Extreme Wave climate is of paramount importance for: (i) off-shore and coastal engineering design, (ii) ship design and maritime transportation, or (iii) analysis of coastal processes. Identifying the synoptic patterns that produce Extreme Waves is necessary to understand the Wave climate for a specific location. Thus, a characterization of these weather patterns may allow the study of the relationships between the magnitude and occurrence of Extreme Wave events and the climate system. The aim of this paper is to analyze the interannual variability of Extreme Wave heights. For this purpose, we present a methodological framework and its application to an area over the North East (NE) Atlantic Ocean. The climatology in the NE Atlantic is analyzed using the self-organizing maps (SOMs). The application of this clustering technique to monthly mean sea level pressure fields provides a continuum of synoptic categorizations compared with discrete realizations produced through most traditional methods. The Extreme Wave climate has been analyzed by means of monthly maxima of the significant Wave height (SWH) in several locations over the NE Atlantic. A statistical approach based on a time-dependent generalized Extreme value (GEV) distribution has been applied. The seasonal variation was characterized and, afterwards, the interannual variability was studied throughout regional pressure patterns. The anomalies of the 50-year return level estimates of SWH, due to interannual variability have been projected into the weather types of SOM. It provides a comprehensive visual representation, which relates the weather type with the positive or negative contribution to Extreme Waves over the selected locations.
-
global Extreme Wave height variability based on satellite data
Geophysical Research Letters, 2011Co-Authors: Cristina Izaguirre, Melisa Menendez, Fernando J Mendez, Inigo J LosadaAbstract:[1] The spatial and temporal variability of the Extreme significant Wave height (SWH) in the ocean is presented. The study has been performed using a highly reliable dataset from several satellite altimeter missions, which provide a good worldwide coverage for the period 1992 onwards. A non-stationary Extreme value analysis, which models seasonality and interannual variations, has been applied to characterize the Extreme SWH. The interannual variability is explained through variations in the atmosphere and ocean systems, represented by different climate indices, allowing a quantitative contribution of the climate-related patterns. Results demonstrate the strong relationship between the interannual variability of Extreme SWH and different ocean and atmosphere variations. A contribution of the AO and NAO indices in the North Atlantic ocean (e.g., every positive unit of the AO explains up to 70 cm of Extreme Wave height south of Iceland), the NINO3 in the Pacific (every negative unit of NINO3 explains up to 60 cm of Extreme Wave height in the Drake Passage), the SAM in the Southern ocean and the DMI in the Indian ocean reveal these climate patterns as the most relevant in the interannual Extreme Wave climate.
-
Extreme Wave climate variability in southern europe using satellite data
Journal of Geophysical Research, 2010Co-Authors: Cristina Izaguirre, Melisa Menendez, Fernando J Mendez, Alberto Luceno, Inigo J LosadaAbstract:[1] A time-dependent generalized Extreme value (GEV) model for monthly significant Wave height maxima from satellite databases is used to model the seasonal and interannual variability of the Extreme Wave climate throughout southern Europe. In order to avoid a misleading use of the maxima time series, the classical Extreme value model has been modified to cope with nonhomogeneous monthly observations. Seasonality is represented using intraannual harmonic functions in the model, while interannual variability is modeled including North Atlantic and Mediterranean regional scale sea level pressure predictors, such as the North Atlantic Oscillation (NAO), the east Atlantic (EA), or the east Atlantic/western Russian (EA/WR) patterns. The results quantify the strong spatial variability detected in the seasonal location and scale GEV parameters. In general, prominent zonal (west–east) and meridional (north–south) gradients of these location and scale parameters reveal the predominance of low-pressure centers located in the NAO region (e.g., a gradient of 4 m for the location parameter and 1.5 units for the scale parameter between north–south is shown in the month of September). The model also quantifies the influence of regional climate patterns on Extreme Wave climate. Results show a great influence of NAO and EA on the Atlantic basin (e.g., every unit of the monthly NAO index explains 25 cm of the Extreme Wave height in the Gulf of Biscay and the EA index explains 20 cm) while the negative phases of EA/WR contribute greatly to the western Mediterranean basin.
-
Variability of Extreme Wave heights in the northeast Pacific Ocean based on buoy measurements
Geophysical Research Letters, 2008Co-Authors: Melisa Menendez, Fernando J Mendez, Inigo J Losada, Nicholas E GrahamAbstract:Recent studies reveal important trends in mean values and high percentiles of significant Wave height in the northeast Pacific. However, changes of the Extreme Wave heights through time have not received much attention. In this work, the long-term variability of Extreme significant Wave height along the northeast Pacific is modeled using a time-dependent Extreme value model. Application of the model to significant Wave height data sets from 26 buoys over the period 1985–2007 shows significant positive longterm trends in Extreme Wave height between 30–45N near the western coast of the US averaging 2.35 cm/yr. We also demonstrate an impact of El Nin˜o on Extreme Wave heights (about 25 cmper unit ofNINO3.4 index) in the northeast Pacific as well as important correlations with mid-latitudinal climate patterns (e.g., NP and PNA indices).
Cristina Izaguirre - One of the best experts on this subject based on the ideXlab platform.
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Exploring the interannual variability of Extreme Wave climate in the Northeast Atlantic Ocean
Ocean Modelling, 2012Co-Authors: Cristina Izaguirre, Melisa Menendez, Fernando J Mendez, Paula Camus, Roberto Mínguez, Inigo J LosadaAbstract:Abstract The Extreme Wave climate is of paramount importance for: (i) off-shore and coastal engineering design, (ii) ship design and maritime transportation, or (iii) analysis of coastal processes. Identifying the synoptic patterns that produce Extreme Waves is necessary to understand the Wave climate for a specific location. Thus, a characterization of these weather patterns may allow the study of the relationships between the magnitude and occurrence of Extreme Wave events and the climate system. The aim of this paper is to analyze the interannual variability of Extreme Wave heights. For this purpose, we present a methodological framework and its application to an area over the North East (NE) Atlantic Ocean. The climatology in the NE Atlantic is analyzed using the self-organizing maps (SOMs). The application of this clustering technique to monthly mean sea level pressure fields provides a continuum of synoptic categorizations compared with discrete realizations produced through most traditional methods. The Extreme Wave climate has been analyzed by means of monthly maxima of the significant Wave height (SWH) in several locations over the NE Atlantic. A statistical approach based on a time-dependent generalized Extreme value (GEV) distribution has been applied. The seasonal variation was characterized and, afterwards, the interannual variability was studied throughout regional pressure patterns. The anomalies of the 50-year return level estimates of SWH, due to interannual variability have been projected into the weather types of SOM. It provides a comprehensive visual representation, which relates the weather type with the positive or negative contribution to Extreme Waves over the selected locations.
-
global Extreme Wave height variability based on satellite data
Geophysical Research Letters, 2011Co-Authors: Cristina Izaguirre, Melisa Menendez, Fernando J Mendez, Inigo J LosadaAbstract:[1] The spatial and temporal variability of the Extreme significant Wave height (SWH) in the ocean is presented. The study has been performed using a highly reliable dataset from several satellite altimeter missions, which provide a good worldwide coverage for the period 1992 onwards. A non-stationary Extreme value analysis, which models seasonality and interannual variations, has been applied to characterize the Extreme SWH. The interannual variability is explained through variations in the atmosphere and ocean systems, represented by different climate indices, allowing a quantitative contribution of the climate-related patterns. Results demonstrate the strong relationship between the interannual variability of Extreme SWH and different ocean and atmosphere variations. A contribution of the AO and NAO indices in the North Atlantic ocean (e.g., every positive unit of the AO explains up to 70 cm of Extreme Wave height south of Iceland), the NINO3 in the Pacific (every negative unit of NINO3 explains up to 60 cm of Extreme Wave height in the Drake Passage), the SAM in the Southern ocean and the DMI in the Indian ocean reveal these climate patterns as the most relevant in the interannual Extreme Wave climate.
-
Extreme Wave climate variability in southern europe using satellite data
Journal of Geophysical Research, 2010Co-Authors: Cristina Izaguirre, Melisa Menendez, Fernando J Mendez, Alberto Luceno, Inigo J LosadaAbstract:[1] A time-dependent generalized Extreme value (GEV) model for monthly significant Wave height maxima from satellite databases is used to model the seasonal and interannual variability of the Extreme Wave climate throughout southern Europe. In order to avoid a misleading use of the maxima time series, the classical Extreme value model has been modified to cope with nonhomogeneous monthly observations. Seasonality is represented using intraannual harmonic functions in the model, while interannual variability is modeled including North Atlantic and Mediterranean regional scale sea level pressure predictors, such as the North Atlantic Oscillation (NAO), the east Atlantic (EA), or the east Atlantic/western Russian (EA/WR) patterns. The results quantify the strong spatial variability detected in the seasonal location and scale GEV parameters. In general, prominent zonal (west–east) and meridional (north–south) gradients of these location and scale parameters reveal the predominance of low-pressure centers located in the NAO region (e.g., a gradient of 4 m for the location parameter and 1.5 units for the scale parameter between north–south is shown in the month of September). The model also quantifies the influence of regional climate patterns on Extreme Wave climate. Results show a great influence of NAO and EA on the Atlantic basin (e.g., every unit of the monthly NAO index explains 25 cm of the Extreme Wave height in the Gulf of Biscay and the EA index explains 20 cm) while the negative phases of EA/WR contribute greatly to the western Mediterranean basin.
