Characterization of time-varying regimes in remote sensing time series: application to the forecasting of satellite-derived suspended matter concentrations

International audienceSatellite data, with their spatial and temporal coverage, are particularly well suited for the analysis and characterization of space-time-varying relationships between geophysical processes. We investigate here the forecasting of a geophysical variable using both satellite observations and model outputs. As 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 multi-latent-regime models: homogeneous and non-homogeneous Markov-switching models, with and without an autoregressive term, i.e. the suspended matter concentration observed the day before. We clearly show, using a validation dataset, significant improvements with multi-regime models compared to a classical multi-regression and a state-of-the-art non-linear model (Support Vector Regression (SVR) model). The best results are reported for a mixture of 3 regimes for autoregressive model using non-homogeneous transitions. With the autoregressive models, we obtain at day+1 forecasting performances of 93% of the explained variance for the mixture model compared to 83% for a standard linear model and 85% using a SVR. These improvements are even more important for the non-autoregressive models. These results stress the potential of the identification of geophysical regimes to improve the forecasting or the inversion. We also show that for short periods of lack of observations (typically lesser than 15 days), non-homogeneous transition probabilities and estimated autoregressive term, the observation of the previous day not being available, help to enhance forecasting performances

BRDF Estimations and Normalizations of Sentinel 2 Level 2 Data Using a Kalman-Filtering Approach and Comparisons with RadCalNet Measurements

BRDF estimation aims to characterize the anisotropic behaviour of the observed surface, which is directly related to the type of surface. BRDF theoretical models are then used in the normalization of the satellite-derived observations to virtually replace the sensor at the nadir. Such normalization reinforces the homogeneity within and between satellite-derived time series. Nevertheless, the inversion of the necessary BRDF parameters for the normalization requires the implementation of robust methods to account for the noise in the Level 2 surface reflectances caused by the atmospheric correction process. Here, we compare normalized reflectances obtained with a Kalman filtering approach with i/the classical weighted linear inversion and ii/a normalization performed using the coefficients of the NASA-MODIS BRDF MCD43A1 band 2 product. We show, using the RadCalNet nadir-view reflectances, that the Kalman filtering approach is a more suitable approach for the Sen2Cor level 2 and the selected sites. Using the proposed approach, daily global maps of land surface BRDF coefficients and the derived normalized Sentinel 2 reflectances would be extremely useful to the global and regional climate modelling communities and for the world’s cover monitoring

Analyse statistique de la variabilité spatio-temporelle des variables géophysiques, application à la couleur de l'eau et la température de surface observées depuis l'espace

In this manuscript-based thesis we propose statistical methods to analyse geophysical time-series. We particularly focus on ocean colour and sea surface temperature observed from space. The specific characteristics of the geophysical signal, i.e. noise autocorrelation, discontinuities in the observations, and the mixing of physical and biological processes showing distinct modes of variability, is integrated in the proposed methodologies. The first chapter includes details on the physical measurement principles of the variables of interest. Then we describe a methodology to estimate linear trends and associated uncertainties, using several time series, to optimise in-situ and satellite-based observation networks for the long term monitoring. We characterise after the significant time-scales of "El Niño Southern Oscillation" in the sea surface temperature using a normalised Gaussian mixture model to take into account the natural distribution of the scales of the events observed in the nature. The fourth chapter details the forecasting of a non-stationary process subject to seasonal forcing conditions, the sea surface turbidity, using four hidden Markov models. The hidden variables are used to estimate different relationships between the variable to estimate and its predictors. The last chapters details a Bayesian model, with dynamical updates of the a priori models, to inverse the sea surface reflectance in complex coastal areas for the OLCI sensor embedded onto the Sentinel 3 satellite. The perspectives are enhancements of satellite products provided by spatial agencies, operational forecasting using statistical models based on observations and learning, and the optimisation of observation networks.Dans cette thèse sur articles nous proposons des méthodes statistiques pour l¿analyse de séries temporelles géophysiques. Nous nous intéressons à la couleur de l¿eau et la température de surface de la mer observées depuis l¿espace. La nature du signal géophysique, i.e. l¿autocorrélation du bruit, la discontinuité des observations, et le mélange des processus physiques et biologiques pouvant comporter des modes distincts de variabilité, est partie intégrante des méthodes d¿analyses proposées. Le premier chapitre contient des informations sur la mesure physique des variables d¿intérêt. Nous décrivons ensuite une méthode d¿estimation de tendances linéaires et des incertitudes associées, à partir de plusieurs séries temporelles, dans le but d¿optimiser les réseaux d¿observations satellitaires et in-situ pour la surveillance à long terme de l¿environnement. Puis nous caractérisons les échelles temporelles du signal climatique "El Niño Southern Oscillation" dans la température de surface à partir d¿un mélange de Gaussiennes prenant en compte un facteur de normalisation pour corriger de la distribution naturelle des évènements. Le quatrième chapitre décrit la prévision temporelle d¿un processus non-stationnaire soumis à des forçages saisonniers, la turbidité de surface, en utilisant quatre différents modèles de Markov cachés. Les variables cachées sont utilisées pour identifier des relations distinctes entre la variable à estimer et ses prédicteurs. Le dernier chapitre décrit un modèle Bayésien avec mise à jour dynamique des modèles a priori pour l¿inversion de la réflectance marine en milieux côtiers complexes pour le capteur OLCI embarqué sur le satellite Sentinel 3. Les perspectives sont l¿amélioration des produits satellitaires fournis par les agences spatiales, la prévision opérationnelle avec des modèles statistiques basés sur des observations et de l¿apprentissage, et l¿optimisation des réseaux de surveillance

Alternative Vicarious Gain Estimates for Sentinel-4 OLCI: Investigation of Atmosphere-typed Spectral Optical Thickness Corrections for the Processor Vicarious Calibration, From the Open Ocean to the Shore

Vicarious calibration aims at fitting TOA observations to estimates. The historical formulation of the gain G*ρ_TOA= ρ_path+T*ρ_w allows centering the model with the observations. Nevertheless, this formulation doesn’t allow discretising errors made either in the transmittance T or in the atmosphere reflectance ρ_path,. i.e. identifying the error sources. We propose here a vicarious calibration, both in shape and amplitude, of the estimated spectral optical thicknesses. We show that, in open ocean waters, using the GlobColor dataset complemented by data collected by MOBY, that the direct model used to calculate ρ_TOA underestimates the total optical thicknesses for some 2% at 400nm to 0.02% at 681nm. The new formulation of the vicarious adjustment involves a non-linear correction which adjusts in a better way than the historical formulation both the atmospheric components (ρ_path, T) and the water reflectances ρ_w. Discrepancies are also assessed in coastal areas, and it is possible to correct them using a vicarious calibration scheme which involves probability-based transitions between clear maritime and continental aerosol-loaded coastal atmospheres. By introducing continuous transitions between multiple modes, we maximize the fitness of ρ_w in the two cases. It may initiate the use of conditional gains for the current level 2 processors of optical EOs. An example will be shown for OLCI, with the provision of gains values, including their uncertainty estimates, and the improvement of ρ_w in absolute and relative terms. Keywords: Alternative vicarious calibration for OLCI, MODIS, VIIRS; Spectral optical thickness corrections; Atmosphere-typed mixture of gains Acknowledgments: This research is a follow-up of the work for the E.U. Copernicus Marine Service Information http://marine.copernicus.eu/ , and the Sentinel-3 Mission Performance Centr

Interpolated fields of satellite-derived multi-algorithm chlorophyll-a estimates at global and European scales in the frame of the European Copernicus-Marine Environment Monitoring Service

The new level-4 daily chlorophyll-a interpolated products described in this paper and freely available in the Copernicus-Marine Environment Service, aim at providing daily continuous fields (cloud-free) of satellite-derived chlorophyll-a surface concentration at two different resolutions: 4*4 km over the world and 1*1 km resolution over Europe. The multi-sensor daily analyses, by filling the cloudy pixels, provide high-frequency retrievals of chlorophyll-a which can contribute to a better monitoring of the phytoplankton biomass. From a methodological point of view our approach is a combination of a water-typed merge of chlorophyll-a estimates and an optimal interpolation based on the kriging method with regional anisotropic covariance models. These analysed products have been designed to meet the expectations of the end users, by considering both the typical lack of observations during cloudy conditions and the historical multiplicity of available algorithms involved by case 1 (oligotrophic) and case 2 (turbid) water classifications. These products gather MODIS (Moderate Resolution Imaging Spectroradiometer), MERIS (MEdium Resolution Imaging Spectrometer), SeaWiFS (Sea-viewing Wide Field-of-view Sensor), VIIRS (Visible Infrared Imaging Radiometer Suite) and OLCI (Ocean and Land Colour Instrument) daily observations from 1997 to the present. A total product uncertainty, i.e. a combination of the interpolation and the product error, is provided for each pixel

MEETC2: Ocean color atmospheric corrections in coastal complex waters using a Bayesian latent class model and potential for the incoming sentinel 3 - OLCI mission

International audienceFrom top-of-atmosphere (TOA) observations, atmospheric correction for ocean color inversion aims at distinguishing atmosphere and water contributions. From a methodological point of view, our approach relies on a Bayesian inference using Gaussian Mixture Model prior distributions on reference spectra of aerosol and water reflectance. A reference spectrum for the aerosol characterizes the specific signature of the aerosols on the observed aerosol reflectance. A reference spectrum for the water characterizes the specific signature of chlorophyll-a, suspended particulate matters and colored dissolved organic matters on the observed sea surface reflectance.In our Bayesian inversion scheme, prior distributions of the marine and aerosol variables are set conditionally to the observed values of covariates, typically acquisition geometry acquisition conditions and pre-estimates of the aerosol and water reflectance in the near-infrared part of the spectrum. The numerical inversion exploits a gradient-based optimization from quasi-randomized initializations. We evaluate our estimates of the sea surface reflectance from the MERIS TOA observations. Using the MERMAID radiometric in-situ dataset, we obtain significant improvements in the estimation of the sea surface reflectance, especially for the 412, 442, 490 and 510 nm bands, compared with the standard ESA MEGS algorithm and the a state-of-the-art neural network approach (C2R). The mean gain value on the relative error for the 13 bands between 412 and 885 nm is of 57% compared with MEGS algorithm and 10% compared with the C2R. The water leaving reflectances are used in Ocean Color for the estimation of the chl-a concentration, the colored dissolved organic matters absorption and the suspended particulate matters concentration underlying the potential of such approach to improve the standard level 2 products in coastal areas. We further discuss the potential of MEETC2 for the incoming OLCI/Sentinel 3 mission that will be launched in December 2015

Meta-National Database of Buildings in France. Integration of heat-related indicators of French administrative areas.

International audienceThe innovation pathways for zero-carbon buildings by 2030 along with counterbalanced climate change impact are major transition challenges of the urban systems. The Urban Heat Island (UHI) effect, the most documented expression of climate change, reinforces the need for immediate action and puts under pressure local authorities. Moving the individual building to the building cluster or district level, involving simultaneous modification of local planning, can increase the current low rate of transition and reduce overall costs. However, the scarce availability of transparent and easily accessible data on building or city performance, which is necessary to cultivate the market for renovations and provide higher level energy efficiency design policies, is a major challenge to achieving the transition. To this end, we present an enhanced version of the French database on buildings with environmental and risk assessment indicators. The latest release includes the description of almost 27 million buildings across the country and the national energy efficiency label. The new proposed version is enhanced with various characteristics of the urban environment following the discretization scheme of administrative boundaries. The four new proposed indicators include UHI Intensity (UHIi), potential mitigation capacity (ΔUHIi), relative mitigation cost (€UHIi) and heat-stress-related vulnerability (HSi), for each administrative boundary of the entire country. The developed data source can help stakeholders for more targeted policy actions and provides high-resolution data for sustainability research studies in the field of urban building energy modeling (UBEM)

Meta-National Database of Buildings in France. Integration of heat-related indicators of French administrative areas.

International audienceThe innovation pathways for zero-carbon buildings by 2030 along with counterbalanced climate change impact are major transition challenges of the urban systems. The Urban Heat Island (UHI) effect, the most documented expression of climate change, reinforces the need for immediate action and puts under pressure local authorities. Moving the individual building to the building cluster or district level, involving simultaneous modification of local planning, can increase the current low rate of transition and reduce overall costs. However, the scarce availability of transparent and easily accessible data on building or city performance, which is necessary to cultivate the market for renovations and provide higher level energy efficiency design policies, is a major challenge to achieving the transition. To this end, we present an enhanced version of the French database on buildings with environmental and risk assessment indicators. The latest release includes the description of almost 27 million buildings across the country and the national energy efficiency label. The new proposed version is enhanced with various characteristics of the urban environment following the discretization scheme of administrative boundaries. The four new proposed indicators include UHI Intensity (UHIi), potential mitigation capacity (ΔUHIi), relative mitigation cost (€UHIi) and heat-stress-related vulnerability (HSi), for each administrative boundary of the entire country. The developed data source can help stakeholders for more targeted policy actions and provides high-resolution data for sustainability research studies in the field of urban building energy modeling (UBEM)

Bulletin d'information PREVIMER - Informations et analyses des eaux côtières. Mars Avril 2009- n°7

Sommaire * Météo, états de mer et débits des fleuves.....................2 * Caractéristiques des masses d’eau côtières..............6 * Production biologique............11 * Les faits marquants................12 * Rappel des objectifs du bulletin PREVIMER..................13 * Les moyens d’observations et de prévisions de l’état des mers côtières...........................13 * Glossaire..................................1