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1. The impacts of oceanic deep temperature perturbations in the North Atlantic on decadal climate variability and predictability

Author

Florian Sévellec, Juliette Mignot, Agathe Germe, Alexey V. Fedorov, Sébastien Nguyen, Didier Swingedouw, Processus de la variabilité climatique tropicale et impacts (PARVATI), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), National Oceanography Centre [Southampton] (NOC), University of Southampton, Ocean and Earth Science [Southampton], University of Southampton-National Oceanography Centre (NOC), Océan et variabilité du climat (VARCLIM), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Yale University [New Haven], Environnements et Paléoenvironnements OCéaniques (EPOC), Observatoire aquitain des sciences de l'univers (OASU), Université Sciences et Technologies - Bordeaux 1 (UB)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Sciences et Technologies - Bordeaux 1 (UB)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), French national programme LEFE/INSU (DECLIC) Natural and Environmental Research Council UK (DYNAMOC) NE/M005097/1 Natural and Environmental Research Council UK (SMURPHS) NE/N005767/1 French national programme LEFE/INSU US DOE Office of Science DE-SC0016538 NSF AGS-1613318, European Project: 308378,EC:FP7:ENV,FP7-ENV-2012-two-stage,SPECS(2012), Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut de Recherche pour le Développement (IRD)-Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut de Recherche pour le Développement (IRD)-Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU), and Université Sciences et Technologies - Bordeaux 1-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Sciences et Technologies - Bordeaux 1-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-École pratique des hautes études (EPHE)

Subjects
Ocean observations, Atmospheric Science, 010504 meteorology & atmospheric sciences, North Atlantic variability, Atlantic meridional overturning circulation, Magnitude (mathematics), [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph], Linear, 010502 geochemistry & geophysics, 01 natural sciences, Physics::Geophysics, Linear optimal perturbations, 14. Life underwater, Precipitation, Predictability, Argo, Physics::Atmospheric and Oceanic Physics, IPSL-CM5A, 0105 earth and related environmental sciences, overturning circulation, optimal perturbations, Initial condition uncertainties, Decadal climate predictability, Ocean general circulation model, Sea surface temperature, 13. Climate action, Climatology, Common spatial pattern, Environmental science, Atlantic meridional
Abstract

International audience; Decadal climate predictability in the North Atlantic is largely related to ocean low frequency variability, whose sensitivity to initial conditions is not very well understood. Recently, three-dimensional oceanic temperature anomalies optimally perturbing the North Atlantic Mean Temperature (NAMT) have been computed via an optimization procedure using a linear adjoint to a realistic ocean general circulation model. The spatial pattern of the identified perturbations, localized in the North Atlantic, has the largest magnitude between 1000 and 4000 m depth. In the present study, the impacts of these perturbations on NAMT, on the Atlantic meridional overturning circulation (AMOC), and on climate in general are investigated in a global coupled model that uses the same ocean model as was used to compute the three-dimensional optimal perturbations. In the coupled model, these perturbations induce AMOC and NAMT anomalies peaking after 5 and 10 years, respectively, generally consistent with the ocean-only linear predictions. To further understand their impact, their magnitude was varied in a broad range. For initial perturbations with a magnitude comparable to the internal variability of the coupled model, the model response exhibits a strong signature in sea surface temperature and precipitation over North America and the Sahel region. The existence and impacts of these ocean perturbations have important implications for decadal prediction: they can be seen either as a source of predictability or uncertainty, depending on whether the current observing system can detect them or not. In fact, comparing the magnitude of the imposed perturbations with the uncertainty of available ocean observations such as Argo data or ocean state estimates suggests that only the largest perturbations used in this study could be detectable. This highlights the importance for decadal climate prediction of accurate ocean density initialisation in the North Atlantic at intermediate and greater depths.

Published
2017
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2. Multivariate peaks-over-threshold with latent variable representations of generalized Pareto vectors

Author

Bacro, Jean-Noel, Gaetan, Carlo, Opitz, Thomas, Toulemonde, Gwladys, Institut Montpelliérain Alexander Grothendieck (IMAG), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), University of Ca’ Foscari [Venice, Italy], Biostatistique et Processus Spatiaux (BioSP), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Littoral, Environment: MOdels and Numerics (LEMON), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut Montpelliérain Alexander Grothendieck (IMAG), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Hydrosciences Montpellier (HSM), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), and programme LEFE/INSU

Subjects
Pairwise likelihood, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], Multivariate censoring, Latent variable, Multivariate generalized Pareto distribution, Threshold exceedance, Multivariate extreme-value theory
Abstract

Generalized Pareto distributions with positive tail index arise from embedding a Gamma random variable for the rate of an exponential distribution. In this paper, we exploit this property to define a flexible and statistically tractable modeling framework for multivariate extremes based on componentwise ratios between any two random vectors with exponential and Gamma marginal distributions. To model multivariate threshold exceedances, we propose hierarchical constructions using a latent random vector with Gamma margins, whose Laplace transform is key to obtaining the multivariate distribution function. The extremal dependence properties of such constructions, covering asymptotic independence and asymptotic dependence, are studied. We detail two useful parametric model classes: the latent Gamma vectors are sums of independent Gamma components in the first construction (called the convolution model), whereas they correspond to chi-squared random vectors in the second construction. Both of these constructions exhibit asymptotic independence, and we further propose a parametric extension (called beta-scaling) to obtain asymptotic dependence. We demonstrate good performance of likelihood-based estimation of extremal dependence summaries for several scenarios through a simulation study for bivariate and trivariate Gamma convolution models, including a hybrid model mixing bivariate subvectors with asymptotic dependence and independence.

Published
2023

3. New particle formation from agricultural recycling of organic waste products

Author

Ciuraru, Raluca, Kammer, J., Decuq, Céline, Vojkovic, M., Haider, K., Carpentier, Y., Lafouge, Florence, Berger, C., Bourdat-Deschamps, Marjolaine, Ortega, I., Levavasseur, Florent, Houot, Sabine, Loubet, Benjamin, Petitprez, D., Focsa, Cristian, Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire de Physique des Lasers, Atomes et Molécules - UMR 8523 (PhLAM), Université de Lille-Centre National de la Recherche Scientifique (CNRS), Physicochimie des Processus de Combustion et de l’Atmosphère - UMR 8522 (PC2A), French national programme LEFE/INSU (ENGRAIS) 1762C0001, INRA EA department programme 'Pari Scientifique', ADEME (RAVISA), French National Research Agency (ANR), and ANR-10-LABX-0005,CheMISyst,CHEmistry of Molecular and Interfacial Systems(2010)

Subjects
Environmental sciences, Meteorology. Climatology, GE1-350, [SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology, QC851-999, agriculture, particle formation, organic waste products, recycling, secondary organic aerosols
Abstract

International audience; Secondary organic aerosols (SOA) are one of the main sources of uncertainty in the current understanding of the Earth's climate. Agriculture contributes to primary aerosol emissions, but there is no estimate of SOA formation from gaseous precursors. Organic waste products such as sewage sludge are applied to cropland as fertilizers. In this work, we show that sewage sludge is an unaccounted source of nucleation precursors, such as skatole (C9H9N). Skatole emission and nucleation rates up to 1.1 x 10(6) cm(-3) s(-1) owing to ozone reactivity were measured in the laboratory. Our results show that SO2 plays a key role in the oxidation of skatole and leads to intensive new particle formation. The products of ozone reactions with skatole and the possible ozonolysis reaction mechanism are discussed. This nucleation mechanism might aid our understanding of the organic waste agricultural recycling contribution to the aerosol balance in the atmosphere. Based on the measured particle emission flux, the surface area of sewage sludge spread in France and the time before sewage sludge incorporation into the soil, a rough estimate of the annual quantity of particles generated by this agricultural activity is in the range of one ton, which represents similar to 0.03% of the total PM1.0 emissions from the agricultural and forestry sectors in France. As spreading occurs over only a few days (mid-summer), these emissions may locally be of great concern for local and regional air quality during this period of the year.

Published
2021
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4. PDE-NetGen 1.0: from symbolic partial differential equation (PDE) representations of physical processes to trainable neural network representations

Author

Ronan Fablet, Olivier Pannekoucke, Centre Européen de Recherche et de Formation Avancée en Calcul Scientifique (CERFACS), CERFACS, Lab-STICC_IMTA_CID_TOMS, Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), Institut Mines-Télécom [Paris] (IMT)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-Institut Mines-Télécom [Paris] (IMT)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL), Département Signal et Communications (IMT Atlantique - SC), IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), French national programme LEFE/INSU (Etude du filtre de KAlman PArametrique, KAPA), Labex Cominlabs (grant SEACS), CNES (grant OSTST-MANATEE), ANR through the programme EUR IsblueFrench National Research Agency (ANR), ANR through the programme MelodyFrench National Research Agency (ANR), and ANR through the programme OceaniXFrench National Research Agency (ANR)

Subjects
Diffusion equation, 010504 meteorology & atmospheric sciences, Artificial neural network, business.industry, Deep learning, Physical science, lcsh:QE1-996.5, 02 engineering and technology, 01 natural sciences, Burgers' equation, lcsh:Geology, Workflow, [SDV.MP]Life Sciences [q-bio]/Microbiology and Parasitology, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Artificial intelligence, Uncertainty quantification, business, Implementation, 0105 earth and related environmental sciences
Abstract

Bridging physics and deep learning is a topical challenge. While deep learning frameworks open avenues in physical science, the design of physically consistent deep neural network architectures is an open issue. In the spirit of physics-informed neural networks (NNs), the PDE-NetGen package provides new means to automatically translate physical equations, given as partial differential equations (PDEs), into neural network architectures. PDE-NetGen combines symbolic calculus and a neural network generator. The latter exploits NN-based implementations of PDE solvers using Keras. With some knowledge of a problem, PDE-NetGen is a plug-and-play tool to generate physics-informed NN architectures. They provide computationally efficient yet compact representations to address a variety of issues, including, among others, adjoint derivation, model calibration, forecasting and data assimilation as well as uncertainty quantification. As an illustration, the workflow is first presented for the 2D diffusion equation, then applied to the data-driven and physics-informed identification of uncertainty dynamics for the Burgers equation.

Published
2020
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5. Hierarchical Space-Time Modeling of Asymptotically Independent Exceedances With an Application to Precipitation Data

Author

Gwladys Toulemonde, Carlo Gaetan, Jean-Noël Bacro, Thomas Opitz, Institut Montpelliérain Alexander Grothendieck (IMAG), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Dipartimento di Scienze Ambientali, Informatica e Statistica [Venezia] (DAIS), University of Ca’ Foscari [Venice, Italy], Biostatistique et Processus Spatiaux (BIOSP), Institut National de la Recherche Agronomique (INRA), Littoral, Environnement : Méthodes et Outils Numériques (LEMON), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Université de Montpellier (UM), Centre National de la Recherche Scientifique (CNRS), Biostatistique et Processus Spatiaux (BioSP), Littoral, Environment: MOdels and Numerics (LEMON), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut Montpelliérain Alexander Grothendieck (IMAG), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Hydrosciences Montpellier (HSM), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), French National Programme LEFE/INSU, LabEx NUMEV, financial support from Ca’ Foscari University, Italy, and Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)

Subjects
Statistics and Probability, Quasi-maximum likelihood, Computer science, 01 natural sciences, Composite likelihood, 010104 statistics & probability, Asymptotic independence, Gamma random fields, Hourly precipitation, Space-time convolution, Space-time extremes, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], 0502 economics and business, Precipitation, Statistical physics, 0101 mathematics, 050205 econometrics, [STAT.AP]Statistics [stat]/Applications [stat.AP], Symptotic independence, Space time, 05 social sciences, Statistical model, [STAT.TH]Statistics [stat]/Statistics Theory [stat.TH], [STAT]Statistics [stat], Event data, Key (cryptography), Statistics, Probability and Uncertainty, Settore SECS-S/01 - Statistica
Abstract

International audience; The statistical modeling of space-time extremes in environmental applications is key to understanding complex dependence structures in original event data and to generating realistic scenarios for impact models. In this context of high-dimensional data, we propose a novel hierarchical model for high threshold exceedances defined over continuous space and time by embedding a space-time Gamma process convolution for the rate of an exponential variable, leading to asymptotic independence inspace and time. Its physically motivated anisotropic dependence structure is based on geometric objects moving through space-time according to a velocity vector. We demonstrate that inference based on weighted pairwise likelihood is fast and accurate. The usefulness of our model is illustrated by an application to hourly precipitation data from a study region in Southern France, where it clearly improves on an alternative censored Gaussian space-time random field model. While classical limit models based on threshold-stability fail to appropriately capture relatively fast joint tail decay rates between asymptotic dependence and classical independence, strong empirical evidence from our application and other recent case studies motivates the use of more realistic asymptotic independence models such as ours.

Published
2019
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6. Exceedance-based nonlinear regression of tail dependence

Author

Valérie Chavez-Demoulin, Thomas Opitz, Linda Mhalla, Université de Genève (UNIGE), Biostatistique et Processus Spatiaux (BioSP), Institut National de la Recherche Agronomique (INRA), Université de Lausanne (UNIL), Centre de Recherches Mathématiques and the Canadian Statistical Sciences Institute, the French national programme LEFE/INSU, and Swiss National Science Foundation

Subjects
FOS: Computer and information sciences, Statistics and Probability, Multivariate statistics, Exponential distribution, extreme value theory, Multivariate random variable, tail dependence, Economics, Econometrics and Finance (miscellaneous), 01 natural sciences, generalized additive models, Methodology (stat.ME), 010104 statistics & probability, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], 0502 economics and business, Statistical physics, 050207 economics, 0101 mathematics, Extreme value theory, penalized likelihood, Engineering (miscellaneous), Statistics - Methodology, Mathematics, 05 social sciences, Univariate, Tail dependence, Estimator, Marginal distribution, asymptotic independence
Abstract

The probability and structure of co-occurrences of extreme values in multivariate data may critically depend on auxiliary information provided by covariates. In this contribution, we develop a flexible generalized additive modeling framework based on high threshold exceedances for estimating covariate-dependent joint tail characteristics for regimes of asymptotic dependence and asymptotic independence. The framework is based on suitably defined marginal pretransformations and projections of the random vector along the directions of the unit simplex, which lead to convenient univariate representations of multivariate exceedances based on the exponential distribution. Good performance of our estimators of a nonparametrically designed influence of covariates on extremal coefficients and tail dependence coefficients are shown through a simulation study. We illustrate the usefulness of our modeling framework on a large dataset of nitrogen dioxide measurements recorded in France between 1999 and 2012, where we use the generalized additive framework for modeling marginal distributions and tail dependence in monthly maxima. Our results imply asymptotic independence of data observed at different stations, and we find that the estimated coefficients of tail dependence decrease as a function of spatial distance and show distinct patterns for different years and for different types of stations (traffic vs. background)., 24 pages, 11 figures

Published
2019
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7. Focusing of internal tides by near-inertial waves

Author

Jérôme Vialard, Michael J. McPhaden, Pascale Bouruet-Aubertot, Yannis Cuypers, Interactions et Processus au sein de la couche de Surface Océanique (IPSO), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Processus de la variabilité climatique tropicale et impacts (PARVATI), NOAA Pacific Marine Environmental Laboratory [Seattle] (PMEL), National Oceanic and Atmospheric Administration (NOAA), French national programme LEFE/INSU, Institut National des Sciences de l'Univers (INSU), Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636))

Subjects
Inertial frame of reference, 010504 meteorology & atmospheric sciences, [SDU.STU.GP]Sciences of the Universe [physics]/Earth Sciences/Geophysics [physics.geo-ph], Baroclinity, 01 natural sciences, Physics::Geophysics, 14. Life underwater, Physics::Atmospheric and Oceanic Physics, 0105 earth and related environmental sciences, geography, geography.geographical_feature_category, 010505 oceanography, Internal tide, Geophysics, Internal wave, Inertial wave, Shear (geology), 13. Climate action, Ridge, Physics::Space Physics, General Earth and Planetary Sciences, Astrophysics::Earth and Planetary Astrophysics, Tropical cyclone, Seismology, Geology
Abstract

International audience; The refraction of internal waves by lower-frequency near-inertial waves has been predicted theoretically, but never observed before. Here, we report observations of semi-diurnal internal tides generated by the rough topography of the Central Indian Ridge, in the presence of a strong, lower-frequency near-inertial wave field generated by a tropical storm. The semi-diurnal internal tide energy is trapped within upward propagating bands with a periodicity close to the inertial period. A ray-tracing model suggests that this trapping results from the internal tide refraction by the shear associated with near-inertial waves. This yields a strong increase of the internal tide energy and shear in space-time regions where the background flow focuses the rays, leading to the formation of caustics. This mechanism may increase vertical mixing generated by baroclinic tides in the vicinity of mid-ocean ridges in tropical regions.

Published
2017
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8. Study and mitigation of calibration error sources in a water vapor Raman lidar

Author

Christian Thom, Pierre Bosser, Jacques Pelon, Olivier Bock, Leslie David, LAboratoire de REcherche en Géodésie [Paris] (LAREG), Laboratoire des Sciences et Technologies de l'Information Géographique (LaSTIG), École nationale des sciences géographiques (ENSG), Institut National de l'Information Géographique et Forestière [IGN] (IGN)-Institut National de l'Information Géographique et Forestière [IGN] (IGN)-École nationale des sciences géographiques (ENSG), Institut National de l'Information Géographique et Forestière [IGN] (IGN)-Institut National de l'Information Géographique et Forestière [IGN] (IGN), Laboratoire d'Opto-électronique et de Micro-Informatique (LOEMI), TROPO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Lab-STICC_ENSTAB_CID_SFIIS, OSM, Extraction et Exploitation de l'Information en Environnements Incertains (E3I2), École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Département STIC [Brest] (STIC), École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne), IUGG, Billon-Coat, Annick, Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Télécom Bretagne-Institut Brestois du Numérique et des Mathématiques (IBNM), Université de Brest (UBO)-Université européenne de Bretagne - European University of Brittany (UEB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Télécom Bretagne-Institut Brestois du Numérique et des Mathématiques (IBNM), Université de Brest (UBO)-Université européenne de Bretagne - European University of Brittany (UEB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS), Pôle STIC_OSM, and French national programme LEFE/INSU

Subjects
010504 meteorology & atmospheric sciences, [SPI.OPTI] Engineering Sciences [physics]/Optics / Photonic, [SDU.STU.GP]Sciences of the Universe [physics]/Earth Sciences/Geophysics [physics.geo-ph], Capacitive sensing, 01 natural sciences, Standard deviation, 010309 optics, LIDAR, Signal-to-noise ratio, Optics, 0103 physical sciences, Calibration, Zenith, 0105 earth and related environmental sciences, Remote sensing, [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, GNSS, business.industry, [SDU.OCEAN] Sciences of the Universe [physics]/Ocean, Atmosphere, Lidar, GNSS applications, [SPI.OPTI]Engineering Sciences [physics]/Optics / Photonic, Environmental science, [SDU.STU.GP] Sciences of the Universe [physics]/Earth Sciences/Geophysics [physics.geo-ph], business, Water vapor
Abstract

A detailed investigation of calibration variation sources in the instrumental part of the detection-fibered, water vapor Raman lidar, Rameau, is presented. This lidar has been developed by the Institut National de l'Information Géographique et Forestière (IGN) together with the Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS) and aims at calibrating GNSS wet delay signals and thus at improving vertical positioning. Several measurements campaigns enabled to validate the capacity of the instrument to retrieve high accuracy water vapor measurements. However, in order to insure a good stability, regular calibrations were necessary and led us to seek for instability sources in each sub-system of the instrument. The calibration variations are shown to be induced by fiber mode fluctuations and spatial non-uniformity of the photomultiplier photocathodes, and are responsible for significant calibration coefficient drifts. Such drifts are incompatible with both the long term stability required for applications such as climatology and the absolute accuracy needed for wet path delay correction of GNSS signals. We show by means of experimental tests that variation sources can be mitigated by means of an optimization and re-design of the optical detection system, a careful alignment procedure, and the operational monitoring of the system with dedicated measurements. In order to validate the modifications of the system and the new procedure, measurements were repeated over a period of 5 months. The detection subsystem stability was monitored from lidar profiles measured with a unique nitrogen filter used for detecting the signal in the two measurement channels. Compared to the previous campaign (Development of Methodologies for Water Vapor Measurement, Demevap), we observe an improvement in the stability of the system based on the nitrogen measurements which showed a drift of less than 3 % per month and a standard deviation of about 3 % during the campaign. The water vapor calibration coefficients were determined from capacitive humidity sensor measurements and from GPS zenith wet delays measurements. They show a similar small drift of 3 % per month and a standard deviation of ~ 6 %. Thanks to the N2 measurements, the drift can be completely removed. Lower standard deviation can be achieved by increasing the Signal to Noise Ratio and/or spatial and temporal integration window.

Published
2015
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