Variabilidad climática en eventos extremos de nivel del mar y oleaje

El análisis de los valores extremos asociados a temporales de oleaje y niveles del mar elevados juegan un papel relevante en los impactos marinos y costeros. Este trabajo presenta diferentes aspectos relativos al análisis estadístico de extremos para obtener información sobre la variabilidad climática en estas variables, tanto en su frecuencia de presentación como magnitud. Para ello, se han aplicado modelos estadísticos basados en la distribución generalizada de extremos (GEV) a partir de máximos mensuales permitiendo al modelo su variación en el tiempo. Los modelos se han aplicado sobre distintas fuentes de datos (mareógrafos, boyas, altimetría de satélite), teniendo en cuenta las peculiaridades de cada base de datos y comparando los resultados. Al modelar la variabilidad de los datos se analizan los ciclos estacionales en los periodos de retorno del oleaje y la influencia de patrones climáticos dominantes en las variaciones interanuales/decadales del nivel del mar. En particular la relevancia de la oscilación ártica (AO) sobre el hemisferio norte y la afección global del fenómeno del Niño.Extreme value analysis of sea surface dynamics (waves and sea level) play an important role in marine and coastal impacts. This paper presents different aspects of the statistical analysis of extremes to provide information on their climate variability, both in frequency and magnitude. This goal is achieved by applying time-dependent statistical models based on GEV (generalized extreme value) distribution from monthly maxima values. The models were applied on different data sources (tide-gauges, buoys, satellite altimetry), taking into account the peculiarities of each database and comparing the results. By modeling the climate variability, seasonal cycles of extreme waves and interannual variability of extreme sea levels are investigated through return value periods. In particular, the relevance of the Arctic Oscillation (AO) on the northern hemisphere and the overall influence of the El Niño phenomenon

Variabilidad climática en eventos extremos de nivel del mar y oleaje

Ponencia presentada en: X Congreso de la Asociación Española de Climatología celebrado en Alicante entre el 5 y el 8 de octubre de 2016.[ES]El análisis de los valores extremos asociados a temporales de oleaje y niveles del mar elevados juegan un papel relevante en los impactos marinos y costeros. Este trabajo presenta diferentes aspectos relativos al análisis estadístico de extremos para obtener información sobre la variabilidad climática en estas variables, tanto en su frecuencia de presentación como magnitud. Para ello, se han aplicado modelos estadísticos basados en la distribución generalizada de extremos (GEV) a partir de máximos mensuales permitiendo al modelo su variación en el tiempo. Los modelos se han aplicado sobre distintas fuentes de datos (mareógrafos, boyas, altimetría de satélite), teniendo en cuenta las peculiaridades de cada base de datos y comparando los resultados. Al modelar la variabilidad de los datos se analizan los ciclos estacionales en los periodos de retorno del oleaje y la influencia de patrones climáticos dominantes en las variaciones interanuales/decadales del nivel del mar. En particular la relevancia de la oscilación ártica (AO) sobre el hemisferio norte y la afección global del fenómeno del Niño.[EN]Extreme value analysis of sea surface dynamics (waves and sea level) play an important role in marine and coastal impacts. This paper presents different aspects of the statistical analysis of extremes to provide information on their climate variability, both in frequency and magnitude. This goal is achieved by applying time-dependent statistical models based on GEV (generalized extreme value) distribution from monthly maxima values. The models were applied on different data sources (tide-gauges, buoys, satellite altimetry), taking into account the peculiarities of each database and comparing the results. By modeling the climate variability, seasonal cycles of extreme waves and interannual variability of extreme sea levels are investigated through return value periods. In particular, the relevance of the Arctic Oscillation (AO) on the northern hemisphere and the overall influence of the El Niño phenomenon

Future behavior of wind wave extremes due to climate change

ABSTRACT: Extreme waves will undergo changes in the future when exposed to different climate change scenarios. These changes are evaluated through the analysis of significant wave height (Hs) return values and are also compared with annual mean Hs projections. Hourly time series are analyzed through a seven-member ensemble of wave climate simulations and changes are estimated in Hs for return periods from 5 to 100 years by the end of the century under RCP4.5 and RCP8.5 scenarios. Despite the underlying uncertainty that characterizes extremes, we obtain robust changes in extreme Hs over more than approximately 25% of the ocean surface. The results obtained conclude that increases cover wider areas and are larger in magnitude than decreases for higher return periods. The Southern Ocean is the region where the most robust increase in extreme Hs is projected, showing local increases of over 2 m regardless the analyzed return period under RCP8.5 scenario. On the contrary, the tropical north Pacific shows the most robust decrease in extreme Hs, with local decreases of over 1.5 m. Relevant divergences are found in several ocean regions between the projected behavior of mean and extreme wave conditions. For example, an increase in Hs return values and a decrease in annual mean Hs is found in the SE Indian, NW Atlantic and NE Pacific. Therefore, an extrapolation of the expected change in mean wave conditions to extremes in regions presenting such divergences should be adopted with caution, since it may lead to misinterpretation when used for the design of marine structures or in the evaluation of coastal flooding and erosion

Evaluación global de las condiciones extremas del oleaje ante escenarios de cambio climático

Ponencia presentada en: XII Congreso de la Asociación Española de Climatología celebrado en Santiago de Compostela entre el 19 y el 21 de octubre de 2022.[ES]El clima del oleaje puede verse afectado por el cambio climático, ya que ciertas variables directamente vinculadas a la generación y propagación del mismo (cobertura de hielo marino, viento sobre el mar) se están viendo alteradas por el calentamiento global del planeta. En este sentido, el estudio de posibles cambios futuros en las condiciones del oleaje extremo (temporales marítimos) son de especial interés, ya que pueden causar impactos relevantes en la navegación, así como en la erosión e inundación costera. Este estudio analiza cambios que pueden ocurrir en el oleaje extremal ante escenarios de cambio climático para el fin del siglo XXI. Para ello se ha elaborado, en primer lugar, una base de datos global multi-modelo de proyecciones climáticas del oleaje. Posteriormente, se ha evaluado la calidad de las simulaciones climáticas mediante la comparativa con datos históricos y se ha aplicado una corrección del sesgo, con especial atención a la cola superior de la distribución. Las series horarias resultantes de la variable altura de ola significante han sido utilizadas para caracterizar los valores extremos asociados a ciertos periodos de retorno. Finalmente, se han analizado los cambios detectados en estos eventos extremos, así como las diferencias con respecto a las condiciones medias del oleaje. Aunque ciertos patrones de cambio del oleaje medio se mantienen para los extremos, se han localizado regiones donde las condiciones extremas serán más severas a pesar de que las proyecciones indican un descenso en el clima medio.[EN]The wave climate may be affected by climate change, as certain variables directly linked to the generation and propagation of waves (marine sea ice coverage and wind) may be altered by the global warming. In this sense, the study of possible future changes in extreme wave conditions (sea storms) are of special interest, as they can cause relevant impacts on navigation, as well as on coastal erosion and flooding. This study analyses changes that may occur in extreme waves under climate change scenarios for the end of the 21st century. To this end, a global multi-model database of climate projections of waves has been developed. The quality of the climate simulations has been then assessed, by comparison with historical data, and a bias correction has been applied, with special focus on the upper tail of the probability distribution. The resulting hourly time series of the significant wave height variable have been used to characterize the extreme values associated with return periods. Finally, the changes detected in these extreme events have been analyzed, as well as the differences with respect to the mean wave conditions. Although certain patterns of mean wave change are also observed for the extreme wave conditions, regions of more severe wave storms, even though projections indicate a decrease in mean climate, are detected.Ayuda RTI2018-096449-B-I00 del proyecto EXCEED, financiado por MCIN/AEI/ 10.13039/501100011033

Exploring the climatic potential of Somo's Surf Spot for tourist destination management

Surfing is one of the most popular activities in coastal tourism resorts. However, the sport depends strongly on the met-ocean weather conditions, particularly on the surface wind-generated waves that reach the coast. This study provides examples of how users? needs and user perspectives are considered by climate data specialists to develop needed, highly useful information addressing human and social needs. In this vein, the climate analysis of such data can provide input on the expected length of a surfing season, according to the surfer?s level of expertise. In addition, other water sports, such as SUP Wave and windsurfing, among others, might be indicated when surfing conditions are not optimal. Finally, the safety of surfers and other tourists who venture into the sea is also dependent on those conditions. We collaborated with the surfing community to define a series of indices for quantifying surfing days (SD), surfing days stratified by surfers? skills (SDS), alternate offers (AOs), and surfers? and swimmers? safety (SuS and SwS). These are of general applications but require wind and wave data at a very fine scale as the input. To illustrate the potential of our indices, we applied them to the Somo beach (Cantabria, Spain). We downscaled a global wave hindcast dataset covering a 30-year period to a spatial resolution of 100 m to obtain wave-surfing information at Somo?s surf spot. The results confirmed Somo?s status as a year-round surf spot, with SD values of 229.5 days/year and monthly values between 22 days/month and 16 days/month. SDS showed different seasonal peaks according to the surfers? skills. Beginners? conditions occurred more often in the summer (18.1 days/month in July), intermediate surfers? conditions appeared in the transitional seasons (14.1 days/month in April), and advanced and big-wave riders in the winter (15.1 days/month in January and 0.7 days/month, respectively). The AO index identified the SUP wave values of 216 days/year. Wind water sports presented values of 141.6 days/year; conversely, SUP sports were possible on only 7.4 days/year. SuS and SwS identified different seasonal hazard values, decreasing from the winter, autumn, and spring to minimum values in the summer.This research is within the INDECIS project (INDECIS is part of ERA4CS, an ERA-NET initiated by JPI Climate and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), and ANR (FR) with co-funding by the European Union Grant 690462). This article publication was possible with the support of the Secretaria d’Universitats i Recerca del Departament d’Empresa i Coneixement de la Generalitat de Catalunya, the European Union (UE), and the European Social Fund (ESF) (Doctoral Research Grant 2021FI_B2 00147—Formació personal investigador novell)

Global extreme wave height variability based on satellite data

ABSTRACT: 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.The work was partially funded by projects “GRACCIE” (CSD2007‐00067, CONSOLIDER‐INGENIO 2010) from the Spanish Ministry of Science and Technology, “MARUCA” (200800050084091) from the Spanish Ministry of Public Works and “C3E” (E17/08) from the Spanish Ministry of Environment, Rural and Marine Affairs

Stabilization at Santinho-Ingleses dunefield, Southern Brazil: What will be the future of sediment input to Ingleses Beach?

ABSTRACT: This paper describes the overpassing process using a case study from southern Brazil, that present a decadal pulse of sediment entering in the system. A transgressive dune field extends across a headland from Santinho beach to Ingleses beach. Analysis of precipitation data (1961-2014), wind direction and speed (1964-2014), aeolian drift potential (DP), aerial photographs/satellite images (between 1938 and 2016) and morphological data (2002, 2010 and 2014) make it possible to analyze the decadal-scale dune field evolution. The wind historical data showed southern wind as the stronger, moving the dune crests to north. The rainfall analysis presents an increasing trend leading to a decrease in drift potential and favors dune stabilization by vegetation growth. There is a decadal pulse of sediment inputs to the system, as well. The northern sector of Santinho beach has a positive budget and provides about 6,000m³/year of sediment to the foredune. Then, with southern winds, the sediment migrates into the dune field (about 3,000-5,000m³/year) reaches Ingleses by overpassing, ensuring a positive sediment budget for the system that occurs at east side of the Ingleses beach

Extreme wave climate variability in southern Europe using satellite data

ABSTRACT: 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.The work was partially funded by projects “GRACCIE” (CSD2007–00067, CONSOLIDER‐INGENIO 2010) from the Spanish Ministry of Ciencia e Innovación, “MARUCA” from the Spanish Ministry of Fomento and “C3E” from the Spanish Ministry of Environment, Rural and Marine Affairs. Alberto Luceño acknowledges the support of the Spanish Dirección General de Investigación under grant MTM2008– 00759. The authors wish to thank the two anonymous reviewers for their constructive comments that helped to improve the manuscript