Visualising the Uncertainty Cascade in Multi-Ensemble Probabilistic Coastal Erosion Projections

ABSTRACT:Future projections of coastal erosion, which are one of the most demanded climate services in coastal areas, are mainly developed using top-down approaches. These approaches consist of undertaking a sequence of steps that include selecting emission or concentration scenarios and climate models, correcting models bias, applying downscaling methods, and implementing coastal erosion models. The information involved in this modelling chain cascades across steps, and so does related uncertainty, which accumulates in the results. Here, we develop long-term multi-ensemble probabilistic coastal erosion projections following the steps of the top-down approach, factorise, decompose and visualise the uncertainty cascade using real data and analyse the contribution of the uncertainty sources (knowledge-based and intrinsic) to the total uncertainty. We find a multi-modal response in long-term erosion estimates and demonstrate that not sampling internal climate variability?s uncertainty sufficiently could lead to a truncated outcomes range, affecting decision-making. Additionally, the noise arising from internal variability (rare outcomes) appears to be an important part of the full range of results, as it turns out that the most extreme shoreline retreat events occur for the simulated chronologies of climate forcing conditions. We conclude that, to capture the full uncertainty, all sources need to be properly sampled considering the climate-related forcing variables involved, the degree of anthropogenic impact and time horizon targeted.AT acknowledges the financial support from the FENIX Project by the Government of Cantabria. This research was also funded by the Spanish Government via the grant RISKCOADAPT (BIA2017-89401-R)

Multivariate wave climate using self-organizing maps

ABSTRACT: The visual description of wave climate is usually limited to two-dimensional conditional histograms. In this work, self-organizing maps (SOMs), because of their visualization properties, are used to characterize multivariate wave climate. The SOMs are applied to time series of sea-state parameters at a particular location provided by ocean reanalysis databases. Trivariate (significant wave height, mean period, and mean direction), pentavariate (the previous wave parameters and wind velocity and direction), and hexavariate (three wave parameters of the sea and swell components; or the wave, wind, and storm surge) classifications are explored. This clustering technique is also applied to wave and wind data at several locations to analyze their spatial relationship. Several processes are established in order to improve the results, the most relevant being a preselection of data by means a maximum dissimilarity algorithm (MDA). Results show that the SOM identifies the relevant multivariate sea-state types at a particular location spanning the historical variability, and provides an outstanding analysis of the dependency between the different parameters by visual inspection. In the case of wave climate characterizations for several locations the SOM is able to extract the qualitative spatial sea-state patterns, allowing the analysis of the spatial variability and the relationship between different locations. Moreover, the distribution of sea states over the reanalysis period defines a probability density function on the lattice, providing a visual interpretation of the seasonality and interannuality of the multivariate wave climate.The work was partially funded by projects GRACCIE (CSD2007-00067, CONSOLIDERINGENIO 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 Environs. The authors thank Puertos del Estado (Spanish Ministry of Public Works) for providing the reanalysis database

On the feasibility of the use of wind SAR to downscale waves on shallow water

n recent years, wave reanalyses have become popular as a powerful source of information for wave climate research and engineering applications. These wave reanalyses provide continuous time series of offshore wave parameters; nevertheless, in coastal areas or shallow water, waves are poorly described because spatial resolution is not detailed. By means of wave downscaling, it is possible to increase spatial resolution in high temporal coverage simulations, using forcing from wind and offshore wave databases. Meanwhile, the reanalysis wave databases are enough to describe the wave climate at the limit of simulations; wind reanalyses at an adequate spatial resolution to describe the wind structure near the coast are not frequently available. Remote sensing synthetic aperture radar (SAR) has the ability to detect sea surface signatures and estimate wind fields at high resolution (up to 300?m) and high frequency. In this work a wave downscaling is done on the northern Adriatic Sea, using a hybrid methodology and global wave and wind reanalysis as forcing. The wave fields produced were compared to wave fields produced with SAR winds that represent the two dominant wind regimes in the area: the bora (ENE direction) and sirocco (SE direction). Results show a good correlation between the waves forced with reanalysis wind and SAR wind. In addition, a validation of reanalysis is shown. This research demonstrates how Earth observation products, such as SAR wind fields, can be successfully up-taken into oceanographic modeling, producing similar downscaled wave fields when compared to waves forced with reanalysis wind

Spectral Ocean Wave Climate Variability Based on Atmospheric Circulation Patterns

Traditional approaches for assessing wave climate variability have been broadly focused on aggregated or statistical parameters such as significant wave height, wave energy flux, or mean wave direction. These studies, although revealing the major general modes of wave climate variability and trends, do not take into consideration the complexity of the wind-wave fields. Because ocean waves are the response to both local and remote winds, analyzing the directional full spectra can shed light on atmospheric circulation not only over the immediate ocean region, but also over a broad basin scale. In this work, the authors use a pattern classification approach to explore wave climate variability in the frequency–direction domain. This approach identifies atmospheric circulation patterns of the sea level pressure from the 31-yr long Climate Forecast System Reanalysis (CFSR) and wave spectral patterns of two selected buoys in the North Atlantic, finding one-to-one relations between each synoptic pattern (circulation type) and each spectral wave energy distribution (spectral type). Even in the absence of long-wave records, this method allows for the reconstruction of longterm wave spectra to cover variability at several temporal scales: daily, monthly, seasonal, interannual, decadal, long-term trends, and future climate change projections.The authors are grateful to Puertos del Estado (Spanish Ministry of Public Works and Infrastructures) for providing us the instrumental buoy data. This work was partially funded by the project IMAR21 (CT M2010-15009) from the Spanish Government

Discurso narrativo en población infantil con Trastorno del Desarrollo del Lenguaje: perfil y estimulación

El desenvolupament del discurs narratiu constitueix un bon indicador de la competència lingüística i mostra una forta relació amb el desenvolupament lingüístic i acadèmic en la població infantil. Els nens i les nenes amb Trastorn del Desenvolupament del Llenguatge (TDL) presenten múltiples dificultats en la producció i la comprensió narrativa, aspecte que afecta les seves habilitats de comunicació i possiblement afectarà el seu aprenentatge escolar. La implementació de programes d’intervenció enfocats a potenciar les habilitats narratives mostra canvis significatius en l’alumnat amb TDL, per la qual cosa implementar aquests programes resulta útil no només per desenvolupar la competència lingüística sinó també per impulsar el rendiment acadèmic.     The development of narrative discourse is a good indicator of children’s linguistic competence and shows a strong correlation with linguistic and academic performance. Children with Developmental Language Disorder (DLD) show multiple difficulties in various aspects of narrative production and comprehension, which affect their communicative skills and may affect their learning in school. The implementation of interventional programs focused on enhancing narrative skills results in significant changes in students with narrative difficulties, in such a way that implementing these programs would be useful not only for developing linguistic proficiency but also for boosting academic performance.El desarrollo del discurso narrativo constituye un buen indicador de la competencia lingüística y muestra una fuerte relación con el desempeño lingüístico y académico en la población infantil. Los niños y niñas con Trastorno del Desarrollo del Lenguaje (TDL) presentan múltiples dificultades en la producción y la comprensión narrativa, lo que afecta a sus habilidades comunicativas y probablemente repercutirá en su aprendizaje escolar. La implementación de programas de intervención centrados en potenciar las habilidades narrativas arroja cambios significativos en alumnado con TDL, por lo que implementar este tipo de programas resultaría útil no solo para desarrollar la competencia lingüística sino también para impulsar el rendimiento académico

A multiscale climate emulator for long-term morphodynamics (MUSCLE-morpho)

Interest in understanding long-term coastal morphodynamics has recently increased as climate change impacts become perceptible and accelerated. Multiscale, behavior-oriented and process-based models, or hybrids of the two, are typically applied with deterministic approaches which require considerable computational effort. In order to reduce the computational cost of modeling large spatial and temporal scales, input reduction and morphological acceleration techniques have been developed. Here we introduce a general framework for reducing dimensionality of wave-driver inputs to morphodynamic models. The proposed framework seeks to account for dependencies with global atmospheric circulation fields and deals simultaneously with seasonality, interannual variability, long-term trends, and autocorrelation of wave height, wave period, and wave direction. The model is also able to reproduce future wave climate time series accounting for possible changes in the global climate system. An application of long-term shoreline evolution is presented by comparing the performance of the real and the simulated wave climate using a one-line model

Evaluación del riesgo de erosión costera frente al cambio climático: aplicación al Principado de Asturias

El trabajo ha sido financiado por el Ministerio de Agricultura y Pesca, Alimentación y Medio Ambiente

Monitoring the stability of aerobic granular sludge using fractal dimension analysis

Cyclic episodes of granules formation and disintegration took place in two lab-scale aerobic granular sludge sequencing batch reactors, one fed with synthetic wastewater (COD: 0.6 g L−1 and NH4+–N:0.06 g L−1) and operated at a constant organic loading rate (2.5 g COD per L d), and the other fed with real wastewater (soluble COD: 0.27–1.37 and NH4+–N:0.02–0.16 g L−1) and with a variable loading rate (between 1.1 and 5.5 g CODsoluble per L d). The sludge volume index, density and diameter (mean value and relative standard deviation) of the granular biomass showed great fluctuations, without any clear tendency during the operational period. However, changes in granules fractal dimension values (both mean and relative standard deviation) matched with the formation and disintegration dynamics of the granular biomass. Statistical data analysis showed that the relative standard deviation of the granules fractal dimension could be a useful parameter for monitoring the granules status. Indeed, an increase of its value during the maturation or steady-state granulation stages is an early warning of disintegration episodes. A control strategy to maintain granules integrity based on this parameter is proposedThis work was funded by the Chilean Government through projects FONDECYT 1180650, FONDECYT 11181107, ANID/ FONDAP/15130015 and ANID PIA/BASAL FB0002, and by the Spanish Government through TREASURE [CTQ2017-83225-C2-1-R] and GRANDSEA [CTM2014-55397-JIN] projects. The authors from Universidade de Santiago de Compostela belong to CRETUS Strategic Partnership [ED431E 2018/01] and to the Galician Competitive Research Group [GRC ED431C 2017/29]. All the Spanish programs are co-funded by FEDER (EU)S