This study investigates the relationship between decadal changes in solar activity and sea level extremes along the European coasts and derived from tide gauge data. Autumn sea level extremes vary ...with the 11 year solar cycle at Venice as suggested by previous studies, but a similar link is also found at Trieste. In addition, a solar signal in winter sea level extremes is also found at Venice, Trieste, Marseille, Ceuta, Brest, and Newlyn. The influence of the solar cycle is also evident in the sea level extremes derived from a barotropic model with spatial patterns that are consistent with the correlations obtained at the tide gauges. This agreement indicates that the link to the solar cycle is through modulation of the atmospheric forcing. The only atmospheric regional pattern that showed variability at the 11 year period was the East Atlantic pattern.
Key Points
Sea level extremes vary with the 11 year solar cycle at Venice, Trieste, Marseille, Ceuta, Brest, and Newlyn
The analysis of a model indicates that the solar influence on sea level extremes is through the modulation of the atmospheric forcing
The EA pattern is the only regional pattern related to sea level extremes that showed variability at the 11 year period
ABSTRACT
This study investigates the relationship between the wind wave climate and the main climate modes of atmospheric variability in the North Atlantic Ocean. The modes considered are the North ...Atlantic Oscillation (NAO), the East Atlantic (EA) pattern, the East Atlantic Western Russian (EA/WR) pattern and the Scandinavian (SCAN) pattern. The wave dataset consists of buoys records, remote sensing altimetry observations and a numerical hindcast providing significant wave height (SWH), mean wave period (MWP) and mean wave direction (MWD) for the period 1989–2009. After evaluating the reliability of the hindcast, we focus on the impact of each mode on seasonal wave parameters and on the relative importance of wind‐sea and swell components. Results demonstrate that the NAO and EA patterns are the most relevant, whereas EA/WR and SCAN patterns have a weaker impact on the North Atlantic wave climate variability. During their positive phases, both NAO and EA patterns are related to winter SWH at a rate that reaches 1 m per unit index along the Scottish coast (NAO) and Iberian coast (EA) patterns. In terms of winter MWD, the two modes induce a counterclockwise shift of up to 65° per negative NAO (positive EA) unit over west European coasts. They also increase the winter MWP in the North Sea and in the Bay of Biscay (up to 1 s per unit NAO) and along the western coasts of Europe and North Africa (1 s per unit EA). The impact of winter EA pattern on all wave parameters is mostly caused through the swell wave component.
The atmosphere plays a fundamental role in the transport of microbes across the planet but it is often neglected as a microbial habitat. Although the ocean represents two thirds of the Earth's ...surface, there is little information on the atmospheric microbial load over the open ocean. Here we provide a global estimate of microbial loads and air-sea exchanges over the tropical and subtropical oceans based on the data collected along the Malaspina 2010 Circumnavigation Expedition. Total loads of airborne prokaryotes and eukaryotes were estimated at 2.2 × 10
and 2.1 × 10
cells, respectively. Overall 33-68% of these microorganisms could be traced to a marine origin, being transported thousands of kilometres before re-entering the ocean. Moreover, our results show a substantial load of terrestrial microbes transported over the oceans, with abundances declining exponentially with distance from land and indicate that islands may act as stepping stones facilitating the transoceanic transport of terrestrial microbes.The extent to which the ocean acts as a sink and source of airborne particles to the atmosphere is unresolved. Here, the authors report high microbial loads over the tropical Atlantic, Pacific and Indian oceans and propose islands as stepping stones for the transoceanic transport of terrestrial microbes..
Liberibacter is a bacterial group causing different diseases and disorders in plants. Among liberibacters, Candidatus Liberibacter solanaceraum (CLso) produces disorders in several species mainly ...within Apiaceae and Solanaceae families. CLso isolates are usually grouped in defined haplotypes according to single nucleotide polymorphisms in genes associated with ribosomal elements. In order to characterize more precisely isolates of CLso identified in potato in Spain, a Multilocus Sequence Analysis (MLSA) was applied. This methodology was validated by a complete analysis of ten housekeeping genes that showed an absence of positive selection and a nearly neutral mechanism for their evolution. Most of the analysis performed with single housekeeping genes, as well as MLSA, grouped together isolates of CLso detected in potato crops in Spain within the haplotype E, undistinguishable from those infecting carrots, parsnips or celery. Moreover, the information from these housekeeping genes was used to estimate the evolutionary divergence among the different CLso by using the concatenated sequences of the genes assayed. Data obtained on the divergence among CLso haplotypes support the hypothesis of evolutionary events connected with different hosts, in different geographic areas, and possibly associated with different vectors. Our results demonstrate the absence in Spain of CLso isolates molecularly classified as haplotypes A and B, traditionally considered causal agents of zebra chip in potato, as well as the uncertain possibility of the present haplotype to produce major disease outbreaks in potato that may depend on many factors that should be further evaluated in future works.
The relationships of Mediterranean sea level, its atmospherically driven and thermosteric components with the large scale atmospheric modes over the North Atlantic and Europe are explored and ...quantified. The modes considered are the North Atlantic Oscillation (NAO), the East Atlantic pattern (EA), the Scandinavian pattern (SCAN) and the East Atlantic/Western Russian (EA/WR). The influence of each mode changes between winter and summer. During winter the NAO is the major mode impacting winter Mediterranean sea level (accounting for 83% of the variance) with SCAN being the second (56%) mode in importance. Both NAO and SCAN effects are partly due to direct atmospheric forcing of sea level through wind and pressure changes. However NAO and SCAN are correlated with each other during winter and they explain the same part of variability. The EA/WR also affects the atmospheric sea level component in winter (13%), acting through atmospheric pressure patterns. In winter, the thermosteric contribution is correlated with the SCAN in parts of the Eastern Mediterranean (9%). The rate of change of the thermosteric component in winter is correlated with the EA (24%). During the summer season, the sea level variance is much reduced and the impact of the large scale modes is in most parts of the Mediterranean Sea non-significant.
•The NAO is the primary contributor on winter Mediterranean sea level variability.•The EA/WR is the 2nd mode in importance on the atmospherically-induced sea level.•The EA pattern dominates the rate of change of winter thermosteric sea level.
Wave climate in the Western Mediterranean is presented through the calibration of an update wind wave hindcast spanning the period 1958–2008. The hindcast was obtained with the WAM model (spatial ...resolution of 1/6°) forced with wind fields from the atmospheric model ARPERA. Significant wave heights (SWH) provided by the hindcast were calibrated using buoy observations with the aim of improving the characterization of the wave climate over the region. The methodology is based on a spatial calibration of the statistical distribution of SWH performed through a non-linear transformation of the Empirical Orthogonal Functions of the modeled data that minimizes the differences with observations. This allows the calibration to be implemented not only at buoy locations, but also all over the model domain. The resulting fields were validated against satellite altimetry observations, showing an average reduction of about 76% in the bias and of about 10% in the root mean squared differences with respect to observations.
•Wave climate in the Western Mediterranean is presented through the calibration of an update wind wave hindcast (1958–2008).•Buoy observations from 22 stations are used for the calibration of SWH.•Calibrated SWH is validated with altimetry data. Bias and RMS are improved by 76% and 10% in average, respectively.
•The ability of statistical SWH future simulations over North Atlantic is assessed.•Comparisons with a dynamical simulation used as a reference are presented.•Wind speed-based models capture the ...dynamically simulated SWH variability and trends.•Atmospheric pressure-based models are limited in capturing SWH variability and trends•The combination of both wind-sea and swell models improve the wave field projections.
A dynamical wind-wave climate simulation covering the North Atlantic Ocean and spanning the whole 21st century under the A1B scenario has been compared with a set of statistical projections using atmospheric variables or large scale climate indices as predictors. As a first step, the performance of all statistical models has been evaluated for the present-day climate; namely they have been compared with a dynamical wind-wave hindcast in terms of winter Significant Wave Height (SWH) trends and variance as well as with altimetry data. For the projections, it has been found that statistical models that use wind speed as independent variable predictor are able to capture a larger fraction of the winter SWH inter-annual variability (68% on average) and of the long term changes projected by the dynamical simulation. Conversely, regression models using climate indices, sea level pressure and/or pressure gradient as predictors, account for a smaller SWH variance (from 2.8% to 33%) and do not reproduce the dynamically projected long term trends over the North Atlantic. Investigating the wind-sea and swell components separately, we have found that the combination of two regression models, one for wind-sea waves and another one for the swell component, can improve significantly the wave field projections obtained from single regression models over the North Atlantic.
We present an overview of the changes expected during the 21st century in key marine parameters (sea surface temperature, sea surface salinity, sea level and waves) in the sector of the NE Atlantic ...Ocean close to the Spanish shores. Under the A1B scenario, open-sea surface temperatures would increase by 1°C to 1.5°C by 2050 as a consequence of global ocean warming. Near the continental margin, however, the global temperature rise would be counteracted by an enhancement of the seasonal upwelling. Sea surface salinity is likely to decrease in the future, mainly due to the advection of high-latitude fresher waters from ice melting. Mean sea level rise has been quantified as 15-20 cm by 2050, but two contributions not accounted for by our models must be added: the mass redistribution derived from changes in the large-scale circulation (which in the NE Atlantic may be as large as 15 cm in 2050 or 35 cm by 2100) and the increase in the ocean mass content due to the melting of continental ice (for which estimates are still uncertain). The meteorological tide shows very small changes, and therefore extreme sea levels would be higher in the 21st century, but mostly due to the increase in mean sea level, not to an increase in the storminess. The wave projections point towards slightly smaller significant wave heights, but the changes projected are of the same order as the natural variability.
This study investigates the relative sea–level changes and the influence of vertical land movements at South Western Tropical Pacific Islands. The dataset consists of tide gauge records, remote ...satellite altimetry observations and GPS records. After evaluating the uncertainties and the nature of vertical land movements, we focus on the present and future relative sea–level changes. The main source of uncertainty comes from the types of vertical land motion estimates. Results revealed that the relative sea level has increased more than the global mean sea level (from 0.8 to 4.2 mm yr–1 higher) overall in the region during the last 4–6 decades, especially at the islands located over the most tectonically active areas where future changes cannot be reliably projected. For most of the islands located outside tectonically active areas, relative sea–level projected changes by the end of the 21st century are of similar magnitude to the projected global mean sea–level (0.6 ± 0.2 m in the RCP 8.5 scenario), with the exception of Tahiti where major changes are projected (0.8 ± 0.2 m).
•Estimates of vertical land movements are subject to considerably uncertainty•RSL increased more than the GMSL at SW Tropical Pacific during the past 4–6 decades•The most tectonically active subsiding islands experienced the highest RSL rise•Future RSL is projected to rise as the GMSL at tectonically stable islands•The highest RSL rise is projected to occur at Tahiti Island
This thesis aims at quantitatively characterizing the recent (last few decades) and future climate variability of marine climate in the Western Mediterranean Sea and the North Atlantic Ocean. Namely ...it focuses on sea level and wind-waves, as these are the variables with a larger potential impact on coastal ecosystems and infrastructures. We first use buoy and altimetry data to calibrate a 50-year wind-wave hindcast over the Western Mediterranean in order to obtain the best characterization of the wave climate over that region. The minimization of the differences with respect to observations through a non-linear transformation of the Empirical Orthogonal Functions of the modelled fields results in an improvement of the hindcast, according to a validation test carried out with independent observations. We then focus on the relationship between the large scale atmospheric forcing and our target variables. Namely we quantify and explore the cause-effect relations between the major modes of atmospheric variability over the North Atlantic and Europe, i.e. the North Atlantic Oscillation, the East Atlantic pattern, the East Atlantic Western Russian pattern and the Scandinavian pattern, and both the Mediterranean sea level and the North Atlantic wave climate. To do so, we use data from different sets of observations and numerical models, including tide gauges, wave buoys, altimetry, hydrography and numerical simulations. Our results point to the North Atlantic Oscillation as the mode with the largest impact on both, Mediterranean sea level (due to the local and remote influence on its atmospheric component) and the North Atlantic wave climate (due to its effect on both the wind-sea and swell components). Other climate indices have smaller but still meaningful contributions; e.g. the East Atlantic pattern plays a significant role in the wave climate variability through its impact on the swell component. Finally, we explore the performance of statistical models to project the future wave climate over the North Atlantic under global warming scenarios, including the large scale climate modes as predictors together with other variables such as atmospheric pressure and wind speed. Notably, we highlight that the use of wind speed as statistical predictor is essential to reproduce the dynamically projected long-term trends.
Esta tesis caracteriza cuantitativamente la variabilidad climática reciente (las últimas décadas) y futura del clima marino en el Mar Mediterráneo y en el Océano Atlántico Norte. Concretamente, se centra en el nivel del mar y en el oleaje, ya que éstas son las variables con un mayor impacto potencial en ecosistemas e infraestructuras costeras. En primer lugar, utilizamos datos de boyas y altimetría para calibrar un hindcast de oleaje de 50 años en el Mediterráneo Occidental, con el objetivo de obtener la mejor caracterización climática del oleaje sobre esta región. La minimización de las diferencias con respecto a las observaciones a través de una transformación no lineal de las Funciones Empíricas Ortogonales de los campos modelados se traduce en una mejora del hindcast, de acuerdo al test de validación llevado a cabo con observaciones independientes. Luego nos centramos en las relaciones entre el forzamiento atmosférico de gran escala y nuestras variables de interés. En concreto, cuantificamos y exploramos las relaciones causa-efecto entre los modos de variabilidad atmosférica más importantes del Atlántico Norte y Europa (la Oscilación del Atlántico Norte, el patrón del Atlántico Oriental, el patrón del Atlántico Oriental/Rusia Occidental y el patrón Escandinavo) y el nivel del mar del Mediterráneo y el oleaje del Atlántico Norte. Para ello, usamos datos de diferentes conjuntos de observaciones y modelos numéricos, incluyendo mareógrafos, boyas de oleaje, altimetría, hidrografía y simulaciones numéricas. Nuestros resultados señalan la Oscilación del Atlántico Norte como el modo de mayor impacto, tanto en el nivel del mar del Mediterráneo (debido a la influencia local y remota en su componente atmosférica) como en el oleaje del Atlántico Norte (debido a su efecto en las componentes de mar de viento y de mar de fondo). Otros índices climáticos tienen contribuciones más pequeñas pero todavía significativas; e.g. el patrón del Atlántico Oriental juega un papel importante en la variabilidad del oleaje a través de su impacto en la componente de mar de fondo. Finalmente, exploramos la capacidad de los modelos estadísticos de proyectar el clima futuro del oleaje sobre el Atlántico Norte bajo escenarios de calentamiento global, incluyendo los modos climáticos de gran escala como predictores junto con otras variables como la presión atmosférica y la velocidad del viento. En particular, destacamos que el uso de la velocidad del viento como predictor estadístico es esencial para reproducir las tendencias a largo plazo proyectadas de por los modelos dinámicos.
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