Multiscale analysis of geometric planar deformations: application to wild animals electronic tracking and satellite ocean observation data

International audienceThe development of animal tracking technologies (including for instance GPS and ARGOS satellite systems) and the increasing resolution of remote sensing observations call for tools extracting and describing the geometric patterns along a track or within an image over a wide range of spatial scales. Whereas shape analysis has largely been addressed over the last decades, the multiscale analysis of the geometry of opened planar curves has received little attention. We here show that classical multiscale techniques cannot properly address this issue and propose an original wavelet-based scheme. To highlight the generic nature of our multiscale wavelet technique, we report applications to two different observation datasets, namely wild animal movement paths recorded by electronic tags and satellite observations of sea surface geophysical fields

Segmentation of mesoscale ocean surface dynamics using satellite SST and SSH observations

International audienceMulti-satellite measurements of altimeter-derived Sea Surface Height (SSH) and Sea Surface Temperature (SST) provide a wealth of information about ocean circulation, especially mesoscale ocean dynamics which may involve strong spatio-temporal relationships between SSH and SST fields. Within an observation-driven framework, we investigate the extent to which mesoscale ocean dynamics may be decomposed into a mixture of dynamical modes, characterized by different local regressions between SSH and SST fields. Formally, we develop a novel latent class regression model to identify dynamical modes from joint SSH and SST observation series. Applied to the highly dynamical Agulhas region, we demonstrate and discuss the geophysical relevance of the proposed mixture model to achieve a spatio-temporal segmentation of the upper ocean dynamics

Joint interpolation of multi-sensor sea surface geophysical fields using non-local and statistical priors

This work addresses the joint analysis of multi-source and multi-resolution remote sensing data for the interpolation of high-resolution geophysical fields. As case-study application, we consider the interpolation of sea surface temperature fields. We propose a novel statistical model, which combines two key features: an exemplar-based prior and second-order statistical priors. The exemplar-based prior, referred to as a non-local prior, exploits similarities between local patches (small field regions) to interpolate missing data areas from previously observed exemplars. This non-local prior also sets an explicit conditioning between the multi-sensor data. Two complementary statistical priors, namely a prior on the spatial covariance and a prior on the marginal distribution of the high-resolution details, are considered as sea surface geophysical fields are expected to depict specific spectral and marginal features in relation to the underlying turbulent ocean dynamics. We report experiments on both synthetic data and real SST data. These experiments demonstrate the contributions of the proposed combination of non-local and statistical priors to interpolate visually-consistent and geophysically-sound SST fields from multi-source satellite data. We further discuss the key features and parameterizations of this model as well as its relevance with respect to classical interpolation techniques

From data to knowledge: integrating observational data to trace phytoplankton dynamics in a changing world

Phytoplankton are a fundamental component of marine systems. They are involved in the global regulation and functioning of biogeochemical and trophic processes and are strictly connected to human health and well-being through the provision of essential ecosystem services. Despite their fundamental importance, there is still no broad consensus on the mechanisms underlying their seasonal and interannual variability, while even less is known about the ecology of individual species and their response to climate variability given the scarcity of comprehensive long-term observation sets. Here, by taking advantage of high- frequency oceanographic and biological data collected over more than 25 years in a coastal pelagic Mediterranean site, I applied a set of statistical methods in order to investigate different aspects of community and individual species’ ecology, with a particular emphasis on the environmental factors and the mechanisms underlying phytoplankton phenology. Further, I analyzed long-term meteorological variations in the area and their relationships to large-scale climatic oscillation in order to address their impact on the planktonic system during the different seasons of the year. Finally, I integrated the data from 10 worldwide- distributed coastal time-series and investigated the adaptive potential of ubiquitous phytoplankton species to local conditions using a niche-based approach. The results of these analyses highlighted an impressive regularity in the annual occurrence of phytoplankton community and individual taxa despite a highly variable environment. Light was the predominant factor regulating species turnover and replacement and seemed to regulate endogenous biological processes associated with species-specific phenological patterns. Over the time series, a considerable stability was shown by individual species and the whole community, while the effects of climate fluctuation on the abiotic and biotic components revealed a strong dependence on the season. The comparison of phytoplankton niches across diverse biogeographical regions supported the idea of evolutionary adaptation, further emphasizing the importance of long-term ecological observations in the context of climate change. Overall, the results of these studies highlight the considerable resilience and the active role that phytoplankton plays under different environmental constraints, which contrasts the view of these organisms as passively undergoing external changes that occur at different temporal scales in their habitat, and show how, under certain conditions, endogenous biological processes prevail over environmental forcing

Climate Change and Copepod Size Distribution: Comparison of Two Coastal Long-Term Series in the Western Mediterranean Sea

This thesis was aimed at investigating long-term dynamics of zooplankton communities in relation to climate change. It represents a pioneer study in comparing Mediterranean time series with a standardised methodology, i.e., the ZooScan, a digital imaging system for counting and sizing mesozooplankton from preserved samples. This study has proven that copepod size spectra (i.e., histogram of organisms arranged by size classes) obtained with the ZooScan is a powerful synthetic index to monitor changes in the pelagic system. Copepod abundance and size spectra were analyzed in the zooplankton time series conducted at stn MC (Gulf of Naples, Tyrrhenian Sea) and Point B (Villefranche Bay, Ligurian Sea) for the years 1986-2005 and 1974-2003, respectively. In both time series, the proportion of large individuals in the copepod community increased over the years, with a shift in the early 1990s at stn MC and in 1987 at Point B. In both cases, the 1990s copepod reproduction might have decreased due to earlier and stronger stratification driven by rising temperature. At stn MC, the shift to dominance of small phytoplankton cells in the 1990s seemed to be the direct cause. At Point B, in addition to the detrimental effect of earlier stratification in the 1990s, the 1980s seemed to be very productive due to strong winter convection driven by cool salty winters. High salinity was related to low winter atmospheric pressure linked to the North Atlantic Oscillation (+ winter NAO). In both locations, the frequency of occurrence of typical offshore species increased over the years, suggesting changes in coastal-offshore interactions. Mechanisms controlling the copepod communities in both sites seem to be different. Stn MC has a more coastal character than Point B and thus the former is more affected by local conditions as terrestrial nutrient inputs. At Point B, stratification-destratification dynamics seem to control production

Exploiting the multiscale synergy among ocean variables : application to the improvement of remote sensing salinity maps

Les imatges de teledetecció de la superfície oceànica proporcionen una vista sinòptica de la complexa geometria de la circulació oceànica, dominada per la variabilitat de mesoescala. Estructures com filaments i vòrtex són presents en els diferents escalars advectats pel flux oceànic. L’origen més probable d’aquestes estructures és el caràcter turbulent dels corrents, aquestes estructures són persistents amb el temps i compatibles amb la dinàmica mesoscalar oceànica. A escales espacials de quilòmetres o més, la turbulència és principalment 2D, i una complexa geometria, plena de filaments i remolins de mides diferents, emergeix en les imatges superficials de teledetecció de concentració de clorofil·la-a, salinitat superficial, així com en altres escalars més coneguts com són la temperatura superficial i la topografia dinàmica. L’objectiu d’aquesta tesi és explorar i aplicar metodologies de mapatge que permeten millorar la qualitat de mapes de teledetecció oceànica en general, i en particular de la salinitat superficial del mar (SSS). Les diferents metodologies emprades en aquesta tesi han estat aplicades amb l’objectiu específic de millorar els mapes de teledetecció de salinitat superficial del mar proveïts per la missió SMOS de l’Agència Espaial Europea. SMOS és el primer satèl·lit capaç de mesurar la humitat del sol i salinitat oceànica des de l’espai a escala global. La primera part d’aquesta tesi se centra a analitzar les característiques dels productes de nivell 2 (L2) de salinitat de SMOS i produir mapes de nivell 3 (L3) de salinitat utilitzant aproximacions clàssiques: millora del filtratge, mitjana ponderada i Interpolació Òptima. En el curs de la nostra recerca obtenim un conjunt de recomanacions de com processar les dades de SMOS començant des del nivell L2. Aquesta tesi també presenta una nova tècnica de fusió de dades que permet explotar les estructures turbulentes comunes entre diferents variables oceàniques, representant un pas endavant en la cadena de processat per generar mapes de nivell 4 (L4). Aquesta tècnica de fusió es basa teòricament en les propietats geomètriques dels traçadors advectats per la dinàmica oceànica (Turiel et al., 2005a). Degut a l’efecte de forta cissalla als fluits turbulents, l’estructura espacial d’un traçador oceànic hereta algunes propietats del flux subjacent, i en particular el seu arranjament geomètric. Com a conseqüència, les diferents variables oceàniques mostren propietats d’escala similars a la cascada d’energia turbulenta (Seuront and Schmitt, 2005; Nieves et al., 2007; Nieves and Turiel, 2009; Isern-Fontanet et al., 2007). El mètode de fusió agafa un senyal de menor qualitat (afectat per soroll, forats de dades i/o de resolució més baixa) i en millora la seva qualitat. A més d’això, el mètode de fusió és capaç d’extrapolar les dades de forma geofísicament coherent. Aquesta millora del senyal s’aconsegueix utilitzant una altra variable oceànica adquirida amb major qualitat, cobertura espacial més gran i/o millor resolució. Un punt clau d’aquesta aproximació és la suposició de l’existència d’una estructura multifractal de les imatges de teledetecció oceànica (Lovejoy et al., 2001b), i que les línies de singularitat de les diferents variables de l’oceà coincideixen. Sota aquestes premises, els gradients de les dues variables a fusionar estan relacionats per una matriu suau. Com a primera i simple aproximació, s’assumeix que aquesta matriu és proporcional a la identitat; això porta a un esquema de regressió lineal local. Aquesta tesi mostra que aquesta aproximació senzilla permet reduir l’error i millorar la cobertura del producte de nivell 4 resultant. D’altra banda, s’obté informació sobre la relació estadística entre les dues variables fusionades, ja que la dependència funcional entre elles es determina per cada punt de la imatge.Remote sensing imagery of the ocean surface provides a synoptic view of the complex geometry of ocean circulation, which is dominated by mesoscale variability. The signature of filaments and vortices is present in different ocean scalars advected by the oceanic flow. The most probable origin of the observed structures is the turbulent character of ocean currents, and those signatures are persistent over time scales compatible with ocean mesoscale dynamics. At spatial scales of kilometers or more, turbulence is mainly 2D, and a complex geometry, full of filaments and eddies of different sizes, emerges in remote sensing images of surface chlorophyll-a concentration and surface salinity, as well as in other scalars acquired with higher quality such as surface temperature and absolute dynamic topography. The aim of this thesis is to explore and apply mapping methodologies to improve the quality of remote sensing maps in general, but focusing in the case of remotely sensed sea surface salinity (SSS) data. The different methodologies studied in this thesis have been applied with the specific goal of improving surface salinity maps generated from data acquired by the European Space Agency's mission SMOS, the first satellite able to measure soil moisture and ocean salinity from space at a global scale. The first part of this thesis will introduce the characteristics of the operational SMOS Level 2 (L2) SSS products and the classical approaches to produce the best possible SSS maps at Level 3 (L3), namely data filtering, weighted average and Optimal Interpolation. In the course of our research we will obtain a set of recommendations about how to process SMOS data starting from L2 data. A fusion technique designed to exploit the common turbulent signatures between different ocean variables is also explored in this thesis, in what represents a step forward from L3 to Level 4 (L4). This fusion technique is theoretically based on the geometrical properties of advected tracers. Due to the effect of the strong shear in turbulent flows, the spatial structure of tracers inherit some properties of the underlying flow and, in particular, its geometrical arrangement. As a consequence, different ocean variables exhibit scaling properties, similar to the turbulent energy cascade. The fusion method takes a signal affected by noise, data gaps and/or low resolution, and improves it in a geophysically meaningful way. This signal improvement is achieved by using an appropriate data, which is another ocean variable acquired with higher quality, greater spatial coverage and/or finer resolution. A key point in this approach is the assumption of the existence of a multifractal structure in ocean images, and that singularity lines of the different ocean variables coincide. Under these assumptions, the horizontal gradients of both variables, signal and template, can be related by a smooth matrix. The first, simplest approach to exploit such an hypothesis assumes that the relating matrix is proportional to the identity, leading to a local regression scheme. As shown in the thesis, this simple approach allows reducing the error and improving the coverage of the resulting Level 4 product; Moreover, information about the statistical relationship between the two fields is obtained since the functional dependence between signal and template is determined at each point

Turbulent structure in environmental flows: effects of stratification and rotation

Several series of experiments in stratified and in rotating/stratified decaying flows after a grid is used to stir the two layer stable fluid brine and fresh water set up. We measure by comparing the gained potential energy with the available kinetic energy AKE, the relative efficiency of mixing. The experiments in stratified rotating flows with grid driven turbulence were both periodic (quasi stationary) and non-monotonic (decaying) forcing. This thesis compares experimental, numerical and field observations on the structure and Topology of the Stratified Rotating Flows as well as their decay, the horizontal spectra changes appreciable with slopes from 1.1 to 5, but vorticity and local circulation, and also the initial topology and forcing of the flow. A detailed study of the vorticity decay and vortex and energy structure has been performed, the new results show that neither stratified nor rotating flows exhibit pure 2D structures. The work parameterizes the role of the Richardson number and the Rossby number, both in the experiments and in the ocean visualizations is very important. The conditions of vortex decay show the effects of the internal waves in the decay turbulent conditions both for stratified and rotating flows. The parameter space (Re,Ri,Ro) has been used to interpret many previously disconnected explanations of the 2D-3D turbulent behaviour. The comparison of numerical simulations with experiments has allowed implementing new theoretical aspects of the interaction between waves and vortices finding the surprising and very interesting result that these interactions depend on the level of enstrophy. This also leads to new ways of using multifractal analysis ad intermittency in ocean environmental observations. A large collection of SAR images obtained from three European coastal areas were used for routine satellite analysis by SAR and other sensors, which seem very important to build seasonal databases of the dynamic conditions of ocean mixing. The topology of the basic flow is very important and in particular the topology of the vortices and their decay which depends on ambient factors such as wave activity, wind and currents. We find more realistic estimates of the spatial/temporal non-homogeneities (and intermittency obtained as spatial correlations of the turbulent dissipation); these values are used to parameterize the sea surface turbulence, as well as a laboratory experiments at a variety of scales. Using multi-fractal geometry as well, we can establish now a theoretical pattern for the turbulence behaviour that is reflected in the different descriptors. Vorticity evolution is smoother and different than that of scalar or tracer density. The correlation between the local Ri and the fractal dimension detected from energy or entropy is good. Using multi-fractal geometry we can also establish certain regions of higher local activity used to establish the geometry of the turbulence mixing that needs to be studied in detail when interpreting the complex balance between the direct 3D Kolmogorov type cascade and the Inverse 2D Kraichnan type cascade

Abstracts of manuscripts submitted in 1990 for publication

This volume contans the abstracts of manuscripts submitted for publication during calendar year 1990 by the staff and students of the Woods Hole Oceanographic Institution. We identify the journal of those manuscripts which are in press or have been published. The volume is intended to be informative, but not a bibliography. The abstracts are listed by title in the Table of Contents and are grouped into one of our five deparments, Marine Policy Center, Coastal Research Center, or the student category. An author index is presented in the back to facilitate locating specific papers

Book of Abstracts

ICES Annual Science Conference, 19 – 23 September 2011, Gdańsk Music and Congress Center, Gdańsk, Poland. IMR contributors: Benjamin Planque, Torild Johansen, Tuula Skarstein, Jon‐Ivar Westgaard, Halvor Knutsen, Kristin Helle, Michael Pennington, Marek Ostrowski, Nils Olav Handegard, Mette Skern‐Mauritzen, Edda Johannesen, Ulf Lindstrøm, Harald Gjøsæter, Ken Drinkwater, Trond Kristiansen, Geir Ottersen, Esben Moland Olse