References of "Alvera Azcarate, Aïda"
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See detailDINCAE 1.0: a convolutional neural network with error estimates to reconstruct sea surface temperature satellite observations
Barth, Alexander ULiege; Alvera Azcarate, Aida ULiege; Licer, Matjaz et al

in Geoscientific Model Development (2020), 13(3), 1609--1622

A method to reconstruct missing data in sea surface temperature data using a neural network is presented. Satellite observations working in the optical and infrared bands are affected by clouds, which ... [more ▼]

A method to reconstruct missing data in sea surface temperature data using a neural network is presented. Satellite observations working in the optical and infrared bands are affected by clouds, which obscure part of the ocean underneath. In this paper, a neural network with the structure of a convolutional auto-encoder is developed to reconstruct the missing data based on the available cloud-free pixels in satellite images. Contrary to standard image reconstruction with neural networks, this application requires a method to handle missing data (or data with variable accuracy) in the training phase. The present work shows a consistent approach which uses the satellite data and its expected error variance as input and provides the reconstructed field along with its expected error variance as output. The neural network is trained by maximizing the likelihood of the observed value. The approach, called DINCAE (Data INterpolating Convolutional Auto-Encoder), is applied to a 25-year time series of Advanced Very High Resolution Radiometer (AVHRR) sea surface temperature data and compared to DINEOF (Data INterpolating Empirical Orthogonal Functions), a commonly used method to reconstruct missing data based on an EOF (empirical orthogonal function) decomposition. The reconstruction error of both approaches is computed using cross-validation and in situ observations from the World Ocean Database. DINCAE results have lower error while showing higher variability than the DINEOF reconstruction. [less ▲]

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See detailHalf a century of satellite remote sensing of sea-surface temperature
Minnett, P.J.; Alvera Azcarate, Aida ULiege; Chin, T.M. et al

in Remote Sensing of Environment (2019), 233

Sea-surface temperature (SST) was one of the first ocean variables to be studied from earth observation satellites. Pioneering images from infrared scanning radiometers revealed the complexity of the ... [more ▼]

Sea-surface temperature (SST) was one of the first ocean variables to be studied from earth observation satellites. Pioneering images from infrared scanning radiometers revealed the complexity of the surface temperature fields, but these were derived from radiance measurements at orbital heights and included the effects of the intervening atmosphere. Corrections for the effects of the atmosphere to make quantitative estimates of the SST became possible when radiometers with multiple infrared channels were deployed in 1979. At the same time, imaging microwave radiometers with SST capabilities were also flown. Since then, SST has been derived from infrared and microwave radiometers on polar orbiting satellites and from infrared radiometers on geostationary spacecraft. As the performances of satellite radiometers and SST retrieval algorithms improved, accurate, global, high resolution, frequently sampled SST fields became fundamental to many research and operational activities. Here we provide an overview of the physics of the derivation of SST and the history of the development of satellite instruments over half a century. As demonstrated accuracies increased, they stimulated scientific research into the oceans, the coupled ocean-atmosphere system and the climate. We provide brief overviews of the development of some applications, including the feasibility of generating Climate Data Records. We summarize the important role of the Group for High Resolution SST (GHRSST) in providing a forum for scientists and operational practitioners to discuss problems and results, and to help coordinate activities world-wide, including alignment of data formatting and protocols and research. The challenges of burgeoning data volumes, data distribution and analysis have benefited from simultaneous progress in computing power, high capacity storage, and communications over the Internet, so we summarize the development and current capabilities of data archives. We conclude with an outlook of developments anticipated in the next decade or so. [less ▲]

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See detailAnticyclonic Eddy Anomaly: impact on the boundary current and circulation in the western Mediterranean Sea
Aguiar, Eva; Juza, Mélanie; Mourre, Baptiste et al

in Journal of Operational Oceanography (2019), 12

An intense anticyclonic eddy anomaly event was observed in fall-winter 2017 north of the island of Mallorca in the western Mediterranean Sea. Similar long-lived eddies were reported during 1998 and 2010 ... [more ▼]

An intense anticyclonic eddy anomaly event was observed in fall-winter 2017 north of the island of Mallorca in the western Mediterranean Sea. Similar long-lived eddies were reported during 1998 and 2010. The eddy alters the general cyclonic circulation of the Balearic Sea and the regional water mass properties. In particular, glider data in 2017 showed an anomalous strong inflow through the Ibiza Channel of recent Atlantic Water. These changes significantly affect the heat, salt and nutrient distributions in the area with implications for climate and primary production. The monitoring of these events is thus essential for both science and society in this area. [less ▲]

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See detailSynergies in operational oceanography: The intrinsic need for sustained ocean observations
Davidson, F. J.; Alvera Azcarate, Aida ULiege; Barth, Alexander ULiege et al

in Frontiers in Marine Science (2019), 6(JUL),

Operational oceanography can be described as the provision of routine oceanographic information needed for decision-making purposes. It is dependent upon sustained research and development through the end ... [more ▼]

Operational oceanography can be described as the provision of routine oceanographic information needed for decision-making purposes. It is dependent upon sustained research and development through the end-to-end framework of an operational service, from observation collection to delivery mechanisms. The core components of operational oceanographic systems are a multi-platform observation network, a data management system, a data assimilative prediction system, and a dissemination/accessibility system. These are interdependent, necessitating communication and exchange between them, and together provide the mechanism through which a clear picture of ocean conditions, in the past, present, and future, can be seen. Ocean observations play a critical role in all aspects of operational oceanography, not only for assimilation but as part of the research cycle, and for verification and validation of products. Data assimilative prediction systems are advancing at a fast pace, in tandem with improved science and the growth in computing power. To make best use of the system capability these advances would be matched by equivalent advances in operational observation coverage. This synergy between the prediction and observation systems underpins the quality of products available to stakeholders, and justifies the need for sustained ocean observations. In this white paper, the components of an operational oceanographic system are described, highlighting the critical role of ocean observations, and how the operational systems will evolve over the next decade to improve the characterization of ocean conditions, including at finer spatial and temporal scales. © 2019 Davidson, Chassignet, Vinayachandran, Lu, Smith, Zhu, Wang, Liu, De Mey-Frémaux, Kourafalou, Hernandez, Moore, Siddorn, Martin, Alvera Azcarate and Brassington. [less ▲]

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See detailSEASTAR: A mission to study ocean submesoscale dynamics and small-scale atmosphere-ocean processes in coastal, shelf and polar seas
Gommenginger, C.; Chapron, B.; Hogg, A. et al

in Frontiers in Marine Science (2019), 6(JUL),

High-resolution satellite images of ocean color and sea surface temperature reveal an abundance of ocean fronts, vortices and filaments at scales below 10 km but measurements of ocean surface dynamics at ... [more ▼]

High-resolution satellite images of ocean color and sea surface temperature reveal an abundance of ocean fronts, vortices and filaments at scales below 10 km but measurements of ocean surface dynamics at these scales are rare. There is increasing recognition of the role played by small scale ocean processes in ocean-atmosphere coupling, upper-ocean mixing and ocean vertical transports, with advanced numerical models and in situ observations highlighting fundamental changes in dynamics when scales reach 1 km. Numerous scientific publications highlight the global impact of small oceanic scales on marine ecosystems, operational forecasts and long-term climate projections through strong ageostrophic circulations, large vertical ocean velocities and mixed layer re-stratification. Small-scale processes particularly dominate in coastal, shelf and polar seas where they mediate important exchanges between land, ocean, atmosphere and the cryosphere, e.g., freshwater, pollutants. As numerical models continue to evolve toward finer spatial resolution and increasingly complex coupled atmosphere-wave-ice-ocean systems, modern observing capability lags behind, unable to deliver the high-resolution synoptic measurements of total currents, wind vectors and waves needed to advance understanding, develop better parameterizations and improve model validations, forecasts and projections. SEASTAR is a satellite mission concept that proposes to directly address this critical observational gap with synoptic two-dimensional imaging of total ocean surface current vectors and wind vectors at 1 km resolution and coincident directional wave spectra. Based on major recent advances in squinted along-track Synthetic Aperture Radar interferometry, SEASTAR is an innovative, mature concept with unique demonstrated capabilities, seeking to proceed toward spaceborne implementation within Europe and beyond. [less ▲]

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See detailOcean reanalyses: Recent advances and unsolved challenges
Storto, A.; Alvera Azcarate, Aida ULiege; Balmaseda, M. A. et al

in Frontiers in Marine Science (2019), 6(JUL),

Ocean reanalyses combine ocean models, atmospheric forcing fluxes, and observations using data assimilation to give a four-dimensional description of the ocean. Metrics assessing their reliability have ... [more ▼]

Ocean reanalyses combine ocean models, atmospheric forcing fluxes, and observations using data assimilation to give a four-dimensional description of the ocean. Metrics assessing their reliability have improved over time, allowing reanalyses to become an important tool in climate services that provide a more complete picture of the changing ocean to end users. Besides climate monitoring and research, ocean reanalyses are used to initialize sub-seasonal to multi-annual predictions, to support observational network monitoring, and to evaluate climate model simulations. These applications demand robust uncertainty estimates and fit-for-purpose assessments, achievable through sustained advances in data assimilation and coordinated inter-comparison activities. Ocean reanalyses face specific challenges: i) dealing with intermittent or discontinued observing networks, ii) reproducing inter-annual variability and trends of integrated diagnostics for climate monitoring, iii) accounting for drift and bias due e.g. to air-sea flux or ocean mixing errors, iv) optimizing initialization and improving performances during periods and in regions with sparse data. Other challenges such as multi-scale data assimilation to reconcile mesoscale and large-scale variability and flow-dependent error characterization for rapidly evolving processes, are amplified in long-term reanalyses. The demand to extend reanalyses backward in time requires tackling all these challenges, especially in the emerging context of earth system reanalyses and coupled data assimilation. This mini-review aims at documenting recent advances from the ocean reanalysis community, discussing unsolved challenges that require sustained activities for maximizing the utility of ocean observations, supporting data rescue and advancing specific research and development requirements for reanalyses. © 2019 Storto, Alvera Azcarate, Balmaseda, Barth, Chevallier, Counillon, Domingues, Drévillon, Drillet, Forget, Garric, Haines, Hernandez, Iovino, Jackson, Lellouche, Masina, Mayer, Oke, Penny, Peterson, Yang and Zuo. [less ▲]

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See detailAnalysis of surface chlorophyll a associated with sea surface temperature and surface wind in the South China Sea
Huynh, Thi Hong Ngu ULiege; Alvera Azcarate, Aida ULiege; Beckers, Jean-Marie ULiege

in Ocean Dynamics (2019)

In this study, the spatial and temporal variability in surface chlorophyll a (Chl-a) in the whole South China Sea (SCS) was investigated in detail by using 8-day, 4-km, gap-free MODIS-A data (2003–2016 ... [more ▼]

In this study, the spatial and temporal variability in surface chlorophyll a (Chl-a) in the whole South China Sea (SCS) was investigated in detail by using 8-day, 4-km, gap-free MODIS-A data (2003–2016). Monthly climatology and empirical-orthogonal-functions analysis of Chl-a were performed in association with sea surface temperature and surface wind to aid in better understanding the physical mechanisms responsible for the Chl-a variability. The results are as follows: (1) Chl-a has out-of-phase variability between the coastal and open-sea regions due to different major factors controlling phytoplankton growth in each region; (2) in particular, Chl-a increases in the northern SCS during winter and in the western and southwestern SCS during summer mainly due to the effects of monsoons and orography; and (3) wind-driven coastal upwelling is stronger in the western SCS than in the eastern SCS. A wind-induced coastal upwelling not reported in the literature was detected along Palawan Island (8–12°N, 117–120°E) during winter. In the SCS, the Chl-a variability is influenced by the El Niño–Southern Oscillation with a time lag of 4–9 months, depending on the variability scales. [less ▲]

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See detailGenerating ocean climatologies from in situ observations
Barth, Alexander ULiege; Troupin, Charles ULiege; Watelet, Sylvain ULiege et al

in IMDIS 2018 International Conference on Marine Data and Information Systems, Book of Abstracts (2018, November 07)

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See detailHistory of the participation to the Colloquium: spatial analysis and time series
Troupin, Charles ULiege; Peelen, Charlotte ULiege; Alvera Azcarate, Aida ULiege et al

Conference (2018, June 01)

Since 1969, the Liège Colloquium on Ocean (Hydro)Dynamics is organised on a yearly basis and has gathered more than 3300 scientists in editions articulated around specific topics covering a wide range of ... [more ▼]

Since 1969, the Liège Colloquium on Ocean (Hydro)Dynamics is organised on a yearly basis and has gathered more than 3300 scientists in editions articulated around specific topics covering a wide range of disciplines and many sub-regions of the global ocean. Following the 3rd Edition (1971), the organizing committee proposed to make the Colloquium an annual event: “It is a great joy for the Organizing Committee to realize that, in the same time, the continuation of the Colloquia was deeply desired by all the participants and that their gratifying determination was indeed answerable for making, from now on, the Liège Colloquium on Ocean Hydrodynamics an annual meeting.” The present work presents a first analysis of the data collected on 1. the number of participants, 2. the abstracts received and 3. the articles published in the special editions. The data were processed in order to produce choropleth maps and time series. For the most recent editions, the information was available from the colloquium websites and from the journals publishing the special issue, whereas for the first editions, the printed versions of the journals were the only source of information. As of January 2017, the information from the 1990’s could not be recovered due to the absence of participant lists in the journals and the probable loss of lists, either in paper and electronic formats. While the attendance was not the main target for the successive organising committees since the topics were often very specific, it is worth noting a general increase in the number of participants and the represented countries. For instance, the 2013 edition, dedicated to the “Primary production in the ocean: from the synoptic to the global scale”, was attended by 220 scientists from 35 countries. An EOF approach was used to estimate the missing values in the different times series. In particular, based on the past editions and the number of abstracts received before the deadline, we use the DINEOF tool to estimate the number of participant for this edition. The forecast value is 112 participants. All the data and source codes are made available through GitHub (https://github.com/gher-ulg/Liege-Colloquium-on-Ocean-Dynamics), while the interactive maps and times series are displayed at https://gher-ulg.github.io/Liege-Colloquium/, with the idea that these datasets and maps will be updated every year and that more sophisticated analysis will be performed. [less ▲]

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See detailImproving SMOS Sea Surface Salinity in the Western Mediterranean Sea through Multivariate and Multifractal Analysis
Olmedo, Estrella; Taupier-Letage, Isabelle; Turiel, Antonio et al

in Remote Sensing (2018), 10(3), 485

A new methodology using a combination of debiased non-Bayesian retrieval, DINEOF (Data Interpolating Empirical Orthogonal Functions) and multifractal fusion has been used to obtain Soil Moisture and Ocean ... [more ▼]

A new methodology using a combination of debiased non-Bayesian retrieval, DINEOF (Data Interpolating Empirical Orthogonal Functions) and multifractal fusion has been used to obtain Soil Moisture and Ocean Salinity (SMOS) Sea Surface Salinity (SSS) fields over the North Atlantic Ocean and the Mediterranean Sea. The debiased non-Bayesian retrieval mitigates the systematic errors produced by the contamination of the land over the sea. In addition, this retrieval improves the coverage by means of multiyear statistical filtering criteria. This methodology allows obtaining SMOS SSS fields in the Mediterranean Sea. However, the resulting SSS suffers from a seasonal (and other time-dependent) bias. This time-dependent bias has been characterized by means of specific Empirical Orthogonal Functions (EOFs). Finally, high resolution Sea Surface Temperature (OSTIA SST) maps have been used for improving the spatial and temporal resolution of the SMOS SSS maps. The presented methodology practically reduces the error of the SMOS SSS in the Mediterranean Sea by half. As a result, the SSS dynamics described by the new SMOS maps in the Algerian Basin and the Balearic Front agrees with the one described by in situ SSS, and the mesoscale structures described by SMOS in the Alboran Sea and in the Gulf of Lion coincide with the ones described by the high resolution remotely-sensed SST images (AVHRR). [less ▲]

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See detailSMOS satellite inference of alkalinity over Mediterranean basin
Sabia, R.; Olmedo, E.; Turiel, A. et al

in SMOS satellite inference of alkalinity over Mediterranean basin (2018)

Novel SMOS satellite estimates of Sea Surface salinity in the Mediterranean Sea will be used to infer the spatial and temporal distribution of Alkalinity in this basin, exploiting the direct relationship ... [more ▼]

Novel SMOS satellite estimates of Sea Surface salinity in the Mediterranean Sea will be used to infer the spatial and temporal distribution of Alkalinity in this basin, exploiting the direct relationship between salinity and alkalinity. A proper validation of the derived variable will be performed against in-situ data, climatologies and model outputs. The resulting estimates of alkalinity in the Mediterranean Sea will be linked to the overall carbonate system in the broader context of ocean acidification assessment. © 2018 IEEE. [less ▲]

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See detailInvestigating the variability of surface chlorophyll-a in association with sea surface temperature and surface wind in the South China Sea
Huynh, Thi Hong Ngu ULiege; Alvera Azcarate, Aida ULiege; Beckers, Jean-Marie ULiege

Poster (2018)

In this study, the variability of surface chlorophyll-a (Chl-a) in association with sea surface temperature (SST), and surface wind (SW) in the South China Sea (SCS) is investigated using the 8-day, 4-km ... [more ▼]

In this study, the variability of surface chlorophyll-a (Chl-a) in association with sea surface temperature (SST), and surface wind (SW) in the South China Sea (SCS) is investigated using the 8-day, 4-km, DINEOF-reconstructed MODISA Chl-a and SST, and the 8-day, 25-km Cross-Calibrated Multi-Platform SW from 2003 to 2016. Empirical Orthogonal Function analysis on the data sets presents: (1) The first Chl-a mode presents the variability of coastal Chl-a, reaching maximum values in November-December and minimum values in April-May. (2) The second Chl-a mode shows the seasonal variability of open-sea Chl-a, increasing in winter and decreasing in summer. The second Chl-a mode has a correlation with the seasonal upwelling favorable SW. (3) The third Chl-a mode in association with the third SST mode captures the upwelling phenomena in the SCS in winter and summer. [less ▲]

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See detailCharacteristics of surface chlorophyll-a concentrations in the South China Sea
Huynh, Thi Hong Ngu ULiege; Alvera Azcarate, Aida ULiege; Barth, Alexander ULiege et al

Poster (2017, April 25)

In this study, the spatial and temporal variability of surface chlorophyll-a (Chl-a) concentrations in the South China Sea (SCS) is investigated, using the cloud-free MODISA Chl-a data set (2003-2016 ... [more ▼]

In this study, the spatial and temporal variability of surface chlorophyll-a (Chl-a) concentrations in the South China Sea (SCS) is investigated, using the cloud-free MODISA Chl-a data set (2003-2016) reconstructed by the Data Interpolating Empirical Orthogonal Functions technique. EOF analysis on the reconstructed data set presents the characteristics of the surface Chl-a: (1) the first mode presents the high Chl-a concentrations in the coastal regions, except those of the Palawan and Philippines, generally with peaks in summer (June-July) and winter (November-December). (2) the second mode shows the seasonal variability of Chl-a in the whole basin, increasing in winter and decreasing in summer. (3) the third mode highlights the out-of-phase variability of the southern SCS Chl-a between the west and east coasts in winter and summer. The analysis also indicates that the variability of surface Chl-a is influenced by ENSO with a time lag of 5-9 months. [less ▲]

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See detailOceanBrowser
Barth, Alexander ULiege; Troupin, Charles ULiege; Watelet, Sylvain ULiege et al

Conference (2017, April 05)

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See detailAnalysis of Ocean In Situ Observations and Web-Based Visualization: From Individual Measurements to an Integrated View
Barth, Alexander ULiege; Watelet, Sylvain ULiege; Troupin, Charles ULiege et al

in Paolo, Diviacco; Leadbetter, Adam; Glaves, Helen (Eds.) Oceanographic and Marine Cross-Domain Data Management for Sustainable Development (2017)

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See detailRelationships between environmental parameters and the microbenthic loop of Posidonia oceanica meadows at small spatial scale
Pete, Dorothée ULiege; Alvera Azcarate, Aida ULiege; Gobert, Sylvie ULiege

in Zoology 2016: 23rd Congress of Zoology (2016, December)

In these times of global change, understanding how carbon flows through ecosystems is of primary importance. In coastal Mediterranean regions, Posidonia oceanica meadows produce and store a lot of carbon ... [more ▼]

In these times of global change, understanding how carbon flows through ecosystems is of primary importance. In coastal Mediterranean regions, Posidonia oceanica meadows produce and store a lot of carbon, but most of it is described as refractory. As a step in the understanding of how organic matter degradation/storage happens in this ecosystem, this study focus on small scale relationships between the microbenthic loop (organic matter, microphytobenthos, bacteria and meiofauna) and environmental parameters (grain size, P. oceanica density, vegetal fibre biomass, pore water nutrient content, sediment total carbon (TC), organic carbon (TOC), nitrogen (TN) and phosphorous (TP) contents, phaeopigments and bacterial production (FDC)). Thus, a 1.25 m x 1.25 m frame was put in a pristine P. oceanica meadow and twelve points were randomly sampled in May 2008 for all the studied parameters. At such a small scale, every component of the microbenthic loop presented a heterogeneity, which was the highest for the microphytobenthos biomass and the lowest for total meiofauna abundance (TMA). No relationship was found between the components of the microbenthic loop but the abundances of Turbellaria and Ciliophora were correlated with total organic matter in the sediment (TOM). None of the environmental parameter was linked with the microphytobenthos biomass, suggesting that the high spatial variability observed did not depend on the measured parameters. Relationships were found between TOM and ammonium, total bacteria abundance and biomass (TBA and TBB) and sediment phaeopigments, TMA and TC, TN and TP. TBB variability was however explained by a combination of FDC and nutrient contents in pore water and sediment. Taking the microbenthic loop as a whole, pore water ammonium and nitrites + nitrates, FDC and phaeopigments were able to explain the observed variability. So, at small scale the variability in the microbenthic loop of a P. oceanica meadow is related with parameters linked with degradation processes and bacteria activities (phaeopigments, FDC, ammonium, nitrites + nitrates), except for meiofauna, which is related with the nutrient content of the sediment, especially TC. Those results underline the importance of the relationship between the microbenthic loop and degradation processes, even at a small scale. [less ▲]

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See detailOceanBrowser: on-line visualization of gridded ocean data and in situ observations
Barth, Alexander ULiege; Watelet, Sylvain ULiege; Troupin, Charles et al

Conference (2016, October)

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See detailOperational forecasting of the Black sea: merging model simulations and satellite products
Vandenbulcke, Luc ULiege; Capet, Arthur ULiege; Ivanov, Evgeny ULiege et al

Scientific conference (2016, September 29)

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See detailDINEOF analyses of Sea Surface Temperature data in the Black Sea
Alvera Azcarate, Aida ULiege; Vandenbulcke, Luc ULiege; Barth, Alexander ULiege et al

Scientific conference (2016, September 29)

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