Impact du changement climatique sur la circulation océanique dans les systèmes d'upwelling de bord Est de l'hémisphère Sud

Parmi les océans du monde, les Systèmes d'Upwelling de Bord Est (EBUS, de l'anglais "Eastern Boundary Upwelling Systems") présentent un intérêt particulier car ils relient les bassins océaniques tropicaux aux latitudes moyennes et sont donc soumis à de fortes fluctuations associées à la fois à la variabilité naturelle du climat et au forçage anthropique. Comprendre comment le réchauffement climatique modifie la circulation océanique et les écosystèmes marins dans les EBUS reste un défi scientifique en raison de la complexité des processus en jeu. La génération actuelle de modèles couplés de circulation générale souffre encore des limitations associées à la non prise en compte de manière réaliste de certains aspects de la dynamique des upwellings côtiers et de la circulation à méso-échelle. Dans cette thèse, nous avons étudié les processus de formation du pattern de changement climatique et de la variabilité naturelle dans le Pacifique Sud-Est (SEP, de l'anglais "South East Pacific") sur la base de simulations numériques de dernière génération mises à disposition de la communauté pour étudier le changement climatique en présence de la variabilité climatique interne. Ces ressources incluent le CESM Large Ensemble (CESM-LENS) modèle réalisé par le NCAR aux Etats Unis et des simulations à long terme du climat mondial résolvant la méso-échelle réalisées au Centre IBS Center for Climate Physics (ICCP) en Corée du sud. En supposant un quasi-équilibre entre le forçage radiatif externe et les processus de couche de mélange de la circulation de l'océan de surface, il est possible d'identifier les processus océaniques et atmosphériques responsables de la tendance de la température de surface de la mer (SST, de l'anglais "Sea Surface température") sur la période 2006-2100. Nous montrons tout d'abord que la localisation latitudinale du réchauffement minimum de la SST dans le SEP s'écarte significativement de celle prédite par la théorie pour laquelle le refroidissement évaporatif maximum est contrôlé par le pattern de chaleur latente climatologique (précipitations moyennes). Le bilan de chaleur des simulations CESM-LENS révèle que l'advection océanique est responsable du pattern de réchauffement de type El Niño dans la région équatoriale et le long des côtes du Pérou et du Chili. Le centre de la zone de réchauffement minimum est principalement déterminé par le refroidissement relatif du flux de chaleur latente et le rayonnement solaire, partiellement compensé par l'advection méridienne de l'océan. Les détails de la tendance au réchauffement le long des côtes du Pérou et du Chili résultent également d'un équilibre entre l'advection induite à la fois par le changement des courants d'Ekman et la compensation géostrophique. Les résultats révèlent également que le pattern de changement climatique de la SST a une projection significative sur les modes de variabilité naturelle dans le SEP, ce qui suggère qu'il peut être compensé par la variabilité naturelle. Dans une suite de simulations de modèles à haute résolution, nous étudions la téléconnection océanique d'ENSO (de l'anglais "El Niño Southern Oscillation") le long des côtes du Pérou et du Chili sur le flux turbulent, considéré ici comme une source de variabilité naturelle dans le SEP. Nous avons montré en particulier que l'ENSO peut alimenter l'énergie de la circulation à des échelles de temps décennales le long des côtes du Pérou et du Chili en modulant les instabilités du système de courants côtiers. Globalement, la thèse illustre la complexité des processus associés à la téléconnection équatoriale dans le SEP à différentes échelles de temps, qui ne sont pas encore accessibles à partir du système d'observations actuel trop court.Among the world oceans, the Eastern Boundary Upwelling Systems (EBUS) are of particular interest because they connect the tropical ocean basins with the mid-latitudes and so are subject to large fluctuations associated with both the natural climate variability and the anthropogenic forcing. Understanding how global warming will modify the oceanic circulation and the marine ecosystems in the EBUS remains a scientific challenge due to the complex of processes at play. Current generation of Coupled General Circulation Models (CGCMs) still suffers limitations associated to not resolving realistically some aspects of the coastal upwelling dynamics and mesoscale circulation. Still they remain powerful tools to better understand the formation of climate change patterns in a key region of the world for the Earth's radiation budget. In this thesis, we have investigated processes of formation of the climate change pattern and of natural variability in the EBUS of the South Hemisphere, with particular emphasis in the South Eastern Pacific (SEP). We take advantage on latest generation resources to the community for studying climate change in the presence of internal climate variability, including the CESM Large Ensemble performed by NCAR and meso-scale-resolving global climate long-term simulations performed at the IBS Center for Climate Physics. Assuming quasi-equilibrium between the radiative external forcing and mixed layer and upper-ocean processes, oceanic and atmospheric processes responsible for the SST trend over the period 2006-2100 are derived. It is first shown that the latitudinal location of the minimum warming in the SEP deviates significantly from that predicted by theory for which maximum evaporative cooling is controlled by the pattern of mean climatological latent heat/precipitation. The explicit heat budget of the CESM-LE simulations reveals that advection forms the El Niño-like warming pattern in the equatorial region and along the coast of Peru and Chile, while the minimum warming center is mostly determined by the relative cooling of both latent heat and solar radiation, partly compensated by meridional advection. Details in the warming trend along the coast of Peru and Chile are also shown to result from a balance between advection induced by both change in Ekman currents and geostrophic compensation. The results also reveal that the SST climate change pattern has a significant projection on the patterns of natural variability in the SEP (i.e. El Niño and the South Pacific Meridional Mode), suggesting that it can be off-set by natural variability. In a suite of high-resolution model simulations we investigate the ENSO oceanic teleconnection along the coast of Peru and Chile on the turbulent flow, considered here as a source of natural variability in the SEP. It is shown in particular that ENSO can fuel energy in the circulation at decadal timescales along the coast of Peru and Chile through modulating instabilities in the coastal current system. Overall, the thesis illustrates the complex of processes associated to the equatorial teleconnection in the SEP at different timescales, which are not yet accessible from the current too-short observing system

Recovering discrete delayed fractional equations from trajectories

[EN] We show how machine learning methods can unveil the fractional and delayed nature of discrete dynamical systems. In particular, we study the case of the fractional delayed logistic map. We show that given a trajectory, we can detect if it has some delay effect or not and also to characterize the fractional component of the underlying generation model.Ministerio de Ciencia e Innovacion-Agencia Estatal de Investigacion, Grant/Award Number: PID2021-124618NB-C21; European UnionConejero, JA.; Garibo-I-Orts, Ó.; Lizama, C. (2023). Recovering discrete delayed fractional equations from trajectories. Mathematical Methods in the Applied Sciences. https://doi.org/10.1002/mma.922

Dynamics of the solutions of the water hammer equations

NOTICE: this is the author’s version of a work that was accepted for publication in Topology and its Applications. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Topology and its Applications, [Volume 203, 15 April 2016, Pages 67-83] DOI10.1016/j.topol.2015.12.076¨[EN] In this note we provide a representation of the solution using an operator theoretical approach based on the theory of C-0-semigroups and cosine operator functions, when considering this phenomenon on a compressible fluid along an infinite pipe. We provide an integro-differential equation that represents this phenomenon and it only involves the discharge. In addition, the representation of the solution in terms of a specific C-0-semigroup lets us show that hypercyclicity and the topologically mixing property can occur when considering this phenomenon on certain weighted spaces of integrable and continuous functions on the real line. (C) 2016 Elsevier B.V. All rights reserved.The first and third authors are supported by MEC Projects MTM2010-14909 and MTM2013-47093-P. The first author is also supported by Programa de Investigación y Desarrollo de la UPV, Ref. SP20120700. The second author is partially supported by CONICYT, under Fondecyt Grant number 1140258.Conejero, JA.; Lizama, C.; Ródenas Escribá, FDA. (2016). Dynamics of the solutions of the water hammer equations. Topology and its Applications. 203:67-83. https://doi.org/10.1016/j.topol.2015.12.076S678320

Linear dynamics of semigroups generated by differential operators

[EN] During the last years, several notions have been introduced for describing the dynamical behavior of linear operators on infinite-dimensional spaces, such as hypercyclicity, chaos in the sense of Devaney, chaos in the sense of Li-Yorke, subchaos, mixing and weakly mixing properties, and frequent hypercyclicity, among others. These notions have been extended, as far as possible, to the setting of C0-semigroups of linear and continuous operators. We will review some of these notions and we will discuss basic properties of the dynamics of C0-semigroups. We will also study in detail the dynamics of the translation C0-semigroup on weighted spaces of integrable functions and of continuous functions vanishing at infinity. Using the comparison lemma, these results can be transferred to the solution C0-semigroups of some partial differential equations. Additionally, we will also visit the chaos for infinite systems of ordinary differential equations, that can be of interest for representing birth-and-death process or car-following traffic models.The first, third and fourth authors were supported by MINECO and FEDER, grant MTM2016-75963-P. The second author has been partially supported by CONICYT under FONDECYT grant number 1140258 and CONICYT-PIA-Anillo ACT1416.Conejero, JA.; Lizama, C.; Murillo Arcila, M.; Peris Manguillot, A. (2017). Linear dynamics of semigroups generated by differential operators. Open Mathematics. 15(1):745-767. https://doi.org/10.1515/math-2017-0065S745767151Herzog, G. (1997). On a Universality of the Heat Equation. Mathematische Nachrichten, 188(1), 169-171. doi:10.1002/mana.19971880110Kalmes, T. (2010). Hypercyclicity and mixing for cosine operator functions generated by second order partial differential operators. 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Chaotic semigroups from second order partial differential equations

[EN] We give general conditions on given parameters to ensure Devaney and distributional chaos for the solution C-0-semigroup corresponding to a class of second-order partial differential equations. We also provide a critical parameter that led us to distinguish between stability and chaos for these semigroups. In the case of chaos, we prove that the Co-semigroup admits a strongly mixing measure with full support. We also give concrete examples of partial differential equations, such as the telegraph equation, whose solutions satisfy these properties. (C) 2017 Elsevier Inc. All rights reserved.The first and third authors are supported in part by MINECO and FEDER, grant MTM2016-75963-P. The second author is partially supported by CONICYT, under Fondecyt Grant number 1140258 and CONICYT-PIA, Anillo ACT1416.Conejero, JA.; Lizama, C.; Murillo Arcila, M. (2017). Chaotic semigroups from second order partial differential equations. Journal of Mathematical Analysis and Applications. 456(1):402-411. https://doi.org/10.1016/j.jmaa.2017.07.013S402411456

Learning 3D structure from 2D images using LBP features

An automatic machine learning strategy for computing the 3D structure of monocular images from a single image query using Local Binary Patterns is presented. The 3D structure is inferred through a training set composed by a repository of color and depth images, assuming that images with similar structure present similar depth maps. Local Binary Patterns are used to characterize the structure of the color images. The depth maps of those color images with a similar structure to the query image are adaptively combined and filtered to estimate the final depth map. Using public databases, promising results have been obtained outperforming other state-of-the-art algorithms and with a computational cost similar to the most efficient 2D-to-3D algorithms

Potential limitations in COVID-19 machine learning due to data source variability: A case study in the nCov2019 dataset

[EN] Objective: The lack of representative coronavirus disease 2019 (COVID-19) data is a bottleneck for reliable and generalizable machine learning. Data sharing is insufficient without data quality, in which source variability plays an important role. We showcase and discuss potential biases from data source variability for COVID-19 machine learning. Materials and Methods: We used the publicly available nCov2019 dataset, including patient-level data from several countries. We aimed to the discovery and classification of severity subgroups using symptoms and comorbidities. Results: Cases from the 2 countries with the highest prevalence were divided into separate subgroups with distinct severity manifestations. This variability can reduce the representativeness of training data with respect the model target populations and increase model complexity at risk of overfitting. Conclusions: Data source variability is a potential contributor to bias in distributed research networks. We call for systematic assessment and reporting of data source variability and data quality in COVID-19 data sharing, as key information for reliable and generalizable machine learning.This work was supported by Universitat Politecnica de Valencia contract no. UPV-SUB.2-1302 and FONDO SUPERA COVID-19 by CRUE-Santander Bank grant "Severity Subgroup Discovery and Classification on COVID-19 Real World Data through Machine Learning and Data Quality assessment (SUBCOVERWD-19)."Sáez Silvestre, C.; Romero, N.; Conejero, JA.; Garcia-Gomez, JM. (2021). Potential limitations in COVID-19 machine learning due to data source variability: A case study in the nCov2019 dataset. Journal of the American Medical Informatics Association. 28(2):360-364. https://doi.org/10.1093/jamia/ocaa25836036428

Fast 2D to 3D conversion using a clustering-based hierarchical search in a machine learning framework

Automatic 2D-to-3D conversion is an important application for filling the gap between the increasing number of 3D displays and the still scant 3D content. However, existing approaches have an excessive computational cost that complicates its practical application. In this paper, a fast automatic 2D-to-3D conversion technique is proposed, which uses a machine learning framework to infer the 3D structure of a query color image from a training database with color and depth images. Assuming that photometrically similar images have analogous 3D structures, a depth map is estimated by searching the most similar color images in the database, and fusing the corresponding depth maps. Large databases are desirable to achieve better results, but the computational cost also increases. A clustering-based hierarchical search using compact SURF descriptors to characterize images is proposed to drastically reduce search times. A significant computational time improvement has been obtained regarding other state-of-the-art approaches, maintaining the quality results

Improved 2D-to-3D video conversion by fusing optical flow analysis and scene depth learning

Abstract: Automatic 2D-to-3D conversion aims to reduce the existing gap between the scarce 3D content and the incremental amount of displays that can reproduce this 3D content. Here, we present an automatic 2D-to-3D conversion algorithm that extends the functionality of the most of the existing machine learning based conversion approaches to deal with moving objects in the scene, and not only with static backgrounds. Under the assumption that images with a high similarity in color have likely a similar 3D structure, the depth of a query video sequence is inferred from a color + depth training database. First, a depth estimation for the background of each image of the query video is computed adaptively by combining the depths of the most similar images to the query ones. Then, the use of optical flow enhances the depth estimation of the different moving objects in the foreground. Promising results have been obtained in a public and widely used database