Antoine Mangin | Sorbonne University (original) (raw)

Papers by Antoine Mangin

Journal of Operational Oceanography, 2019

Disclaimer Informa UK Limited, trading as Taylor & Francis Group, make every effort to ensure the... more Disclaimer Informa UK Limited, trading as Taylor & Francis Group, make every effort to ensure the accuracy of all the information (the "Content") contained in our publications. However, Informa UK Limited, trading as Taylor & Francis Group, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Informa UK Limited, trading as Taylor & Francis Group. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Informa UK Limited, trading as Taylor & Francis Group, shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content.

Journal of Geophysical Research, 2005

Spaceborne ocean color sensors which are now operational or under preparation, have a large numbe... more Spaceborne ocean color sensors which are now operational or under preparation, have a large number of spectral band. NAOC, which is an EC supported programme, proposes to use advanced neural methodology which are well suited to deal with this multi-spectral information for retrieving ocean constituents. NAOC is divided into for major tasks : First NAOC intends to perform classification of

Karst aquifers are complex systems characterized by a high heterogeneity and non-linearities. Our... more Karst aquifers are complex systems characterized by a high heterogeneity and non-linearities. Our approach consists in analyzing rainfall-discharge time series to characterize the functioning of karst aquifer in order to develop a conceptual rainfall-discharge model to simulate spring discharge at the daily step. The proposed methodology follows a two step approach. First rainfall-discharge time series analyses are analyzed in order

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014

In this paper, one-dimensional (1-D) geophysical time series are regarded as series of significan... more In this paper, one-dimensional (1-D) geophysical time series are regarded as series of significant time-scale events. We combine a wavelet-based analysis with a Gaussian mixture model to extract characteristic time-scales of 486 144 detected events in the Sea Surface Temperature Anomaly (SSTA) observed from satellite at global scale from 1985 to 2009. We retrieve four low-frequency characteristic time-scales of Niño Southern Oscillation (ENSO) in the 1.5-to 7-year range and show their spatial distribution. High-frequency (HF) SSTA event spatial distribution shows a dependency to the ENSO regimes, pointing out that the ENSO signal also involves specific signatures at these time-scales. These fine-scale signatures can hardly be retrieved from global EOF approaches, which tend to exhibit uppermost the low-frequency influence of ENSO onto the SSTA. In particular, we observe at global scale a major increase by 11% of the number of SSTA HF events during Niño periods, with a local maximum of 80% in Europe. The methodology is also used to highlight an ENSOinduced frequency shift during the major 1997-2000 ENSO event in the intertropical Pacific. We observe a clear shift from the high frequencies toward the 3.36-year scale with a maximum shift occurring 2 months before the ENSO maximum of energy at 3.36-year scale.

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015

The spatial and temporal coverage of satellites provides data that are particularly well suited f... more The spatial and temporal coverage of satellites provides data that are particularly well suited for the analysis and characterization of space-time-varying geophysical relationships. The latent-class models aim here to identify time-varying regimes within a dataset. This is of particular interest for geophysical processes driven by the seasonal variability. As a case example, we study the daily concentration of mineral suspended particulate matters estimated from satellite-derived datasets, in coastal waters adjacent to the French Gironde river mouth. We forecast this high-resolution dataset using environmental data (wave height, wind strength and direction, tides, and river outflow) and four latent-regime models: homogeneous and nonhomogeneous Markov-switching models, with and without an autoregressive term (i.e., the mineral suspended matter concentration observed the day before). Using a validation dataset, significant improvements are observed with the multiregime models compared to a classical multiregression and a state-of-the-art nonlinear model [support vector regression (SVR) model]. The best results are reported for a mixture of three regimes for the autoregressive model using nonhomogeneous transitions. With the autoregressive models, we obtain at day+1 for the mixture model forecasting performances of 93% of the explained variance, compared to 83% for a standard linear model and 85% using an SVR. These improvements are more important for the nonautoregressive models. These results stress the potential of the identification of geophysical regimes to improve the forecasting. We also show that nonhomogeneous transition probabilities and estimated autoregressive terms improve forecasting performances when observation data is lacking for short-time period of 1-15 days.

Journal of Geophysical Research: Oceans, 2013

1] The detection of long-term trends in geophysical time series is a key issue in climate change ... more 1] The detection of long-term trends in geophysical time series is a key issue in climate change studies. This detection is affected by many factors: the size of the trend to be detected, the length of the available data sets, and the noise properties. Although the noise autocorrelation observed in geophysical time series does not bias the trend estimate, it affects the estimation of its uncertainty and consequently the ability to detect, or not, a significant trend. Ignoring the noise autocorrelation level typically leads to an overdetection of significant trends. Satellite time series have been providing remote observations of the sea surface for several decades. Due to satellite lifetime, usually between 5 and 10 years, these time series do not cover the same period and are acquired by different sensors with different characteristics. These differences lead to unknown level shifts (biases) between the data sets, which affect the trend detection. In this work, we develop a generic framework to detect and evaluate linear trends and level shifts in multisensor time series of satellite chlorophyll-a concentrations, as provided by the Medium Resolution Imaging Spectrometer Instrument (MERIS AQ4

At local level, tsunami hazard is usually described by inundations maps providing inundation dept... more At local level, tsunami hazard is usually described by inundations maps providing inundation depths and extension. However, many other parameters such as eddies, fast currents, erosion, receding seas, impact of breaking waves have effects on natural and human environment. Modern tsunami modelling tools can provide a part of these informations and allow producing hazard maps with multiple parameters. Nevertheless, a

2008 IEEE/OES US/EU-Baltic International Symposium, 2008

The Baltic Sea is subject to various European environmental regulations which aim at securing its... more The Baltic Sea is subject to various European environmental regulations which aim at securing its long-term protection. This will be achieved by the accompanying monitoring programmes associated with, for example, the HELCOM convention, the EC Water Framework Directive, the Natura 2000 Directives and the upcoming European Maritime Policy, to name the most important regulatory policies. These monitoring programmes demand large scale, frequent and accurate measurements of physical, biological and chemical parameters.

In order to provide to decision makers an operational tool to help define mitigation measures and... more In order to provide to decision makers an operational tool to help define mitigation measures and to anticipate their qualitative and quantitative effects on air quality. ACRI-ST has developed a user friendly integrated modeling system called SAMAA (System for Air Modeling And Analysis), including a GIS based emission module called AIREMIS. This system allows to simulate air pollution events at

In order to better understand the qualitative and quantitative evolution of air pollu- tion in ci... more In order to better understand the qualitative and quantitative evolution of air pollu- tion in cities and their surroundings, ACRI-st has designed and developed, jointly with two French air surveillance networks, an integrated application for air pollution modelling. This simulator, called Samaa, enables testing the impact on pollution of different emission scenarios under a number of meteorological conditions. Samaa is

Ocean colour is an "essential climate variable" needed to support carbon cycle monitori... more Ocean colour is an "essential climate variable" needed to support carbon cycle monitoring and is globally monitored using satellite observations. In order to cover the long time span necessary for climate monitoring purposes, the required ocean colour data set can only be built by merging together observations made with different satellite systems. To ensure that different periods of the time

The major part of the New Caledonia (NC) lagoon was classified as UNESCO Natural Site of Humanity... more The major part of the New Caledonia (NC) lagoon was classified as UNESCO Natural Site of Humanity Patrimony. Indeed, 22 175 km2 of tropical coral lagoon area exhibit high biodiversity. The NC lagoon is semi enclosed and connected to the Coral Sea through a barrier reef segmented by narrow passes. The environment is oligotrophic, due to important flush during trade winds events, and bathymetry is highly variable. In order to predict eutrophication events, we used an extension of a 3D coupled physical-biogeochemical model recently developed on NC south western lagoon. The model is based on the Nitrogen and Carbon cycles, relating the variable stoechiometry of the elements in each biological compartment. The ecological model was developed to include an explicit description of the microbial loop. The resulting coupled model, forced by tide, wind, light, temperature and freshwater inputs, was used to calculate phytoplankton biomass, bacterial production, dissolved organic matter concentr...

Remote Sensing of Environment, 2011

... Maéva Doron a , b , c , low asterisk , E-mail The Corresponding Author , Marcel Babin b , c ,... more ... Maéva Doron a , b , c , low asterisk , E-mail The Corresponding Author , Marcel Babin b , c , Odile Hembise a , Antoine Mangin a and ... Using ocean color data, Prasad et al.(1998) proposed a relationship between the Secchi depth and the ratio of two water-leaving radiances. ...

Remote Sensing of Environment, 2010

The characteristics and benefits of ocean color merged data sets created using a semi-analytical ... more The characteristics and benefits of ocean color merged data sets created using a semi-analytical model and the normalized water-leaving radiance observations from the SeaWiFS, MODIS-AQUA and MERIS ocean color missions are presented. Merged data products are coalesced from multiple mission observations into a single data product with better spatial and temporal coverage than the individual missions. Using the data from SeaWiFS, MODIS-AQUA and MERIS for the 2002-2009 time period, the average daily coverage of a merged product is ∼ 25% of the world ocean which is nearly twice that of any single mission's observations. The frequency at which a particular area is sampled from space is also greatly improved in merged data as some areas can be sampled as frequently as 64% of the time (in days). The merged data presented here are validated through matchup analyses and by comparing them to the data sets obtained from individual missions. Further, a complete error budget for the final merged data products was developed which accounts for uncertainty associated with input water-leaving radiances and provides uncertainty levels for the output products (i.e. the chlorophyll concentration, the combined dissolved and detrital absorption coefficient and the particulate backscattering coefficient). These merged products and their uncertainties at each pixel were developed within the NASA REASON/MEaSUREs and ESA GlobColour projects and are available to the scientific community. Our approach has many benefits for the creation of unified Climate Data Records from satellite ocean color observations.

Remote Sensing of Environment, 2013

The availability of light in the water column and at the seabed determines the euphotic zone and ... more The availability of light in the water column and at the seabed determines the euphotic zone and constrains the type and the vertical distribution of algae species. Light attenuation is traditionally quantified as the diffuse attenuation coefficient of the downwelling spectral irradiance at wavelength 490 nm (K d490 ) or the photosynthetically available radiation (K dPAR ). Satellite observations provide global coverage of these parameters at high spatial and temporal resolution and several empirical and semi-analytical models are commonly used to derive K d490 and K dPAR maps from ocean colour satellite sensors. Most of these existing empirical or semi-analytical models have been calibrated in open ocean waters and perform well in these regions, but tend to underestimate the attenuation of light in coastal waters, where the backscattering caused by the suspended matters and the absorption by the dissolved organic matters increase light attenuation in the water column. We investigate two relationships between K dPAR and K d490 for clear and turbid waters using MERIS reflectances and the spectral diffuse attenuation coefficient K d (λ) developed by . Satellite-derived fields of K d490 and modelled K dPAR are evaluated using coincident in-situ data collected over the world in both clear and turbid waters, and by using Ecolight simulations. Temporal means at 250 m resolution of K dPAR and euphotic depth were computed over the period 2005-2009 for European coastal waters. These mean data were cross-tabulated with in-situ data of kelp (Laminaria hyperborea) and seagrass (Posidonia oceanica), respectively observed at locations on Atlantic and Mediterranean shores where the light is taken as the limiting factor to the depth distribution for these species. The minima observed for P. oceanica, in percent of energy, are very close to 1% of surface irradiance, the historical threshold known as euphotic depth as defined by . Real estimates of the surface irradiance are used in conjunction with the estimated K dPAR to calculate the residual energy at the lower limit of P. oceanica and L. hyperborea in mol·photons·m −2 ·day −1 as a complement to the usual fraction of the surface energy. We show that the observed values, in terms of energy, for both species were equivalent to the values reported in the literature.

JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 106, NO. D23, PAGES 31,755-31,770, DECEMBER 16, 2001 Error ... more JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 106, NO. D23, PAGES 31,755-31,770, DECEMBER 16, 2001 Error analysis and characterization of atmospheric profiles retrieved from GNSS occultation data Markus J. Rieder and Gottfried Kirchengast Institute for Geophysics, Astrophysics, ...