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Sea Surface Dynamics Reconstruction Using Neural Networks Based Kalman Filter

Said Ouala, Ronan Fablet, Cedric Herzet, Lucas Drumetz, Bertrand Chapron, Ananda Pascual, Fabrice Collard, Lucile Gaultier
2019 IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium  
From our numerical experiment, we prove the relevance of the proposed architecture in the reconstruction of geophysical fields with respect to the state-of-the-art schemes.  ...  In this work, we propose an alternative to the Ensemble Kalman filter through the implementation of a neural networks filtering scheme based on a parametric stochastic model.  ...  CONCLUSION In this work, propose an alternative to the ensemble Kalman filter for the spatio-temporal reconstruction of sea surface geophysical tracers.  ... 
doi:10.1109/igarss.2019.8898086 dblp:conf/igarss/OualaFHDCPCG19 fatcat:kbq6cwxcgfa3pa5vbl4nzpxngm

TSUNAMI LEAD WAVE RECONSTRUCTION BASED ON NOISY SEA SURFACE HEIGHT MEASUREMENTS

Kegen Yu
2016 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
This paper presents a Tsunami lead wave reconstruction method using noisy sea surface height (SSH) measurements such as observed by a satellite-carried GNSS reflectometry (GNSS-R) sensor.  ...  The results demonstrate that the proposed wave reconstruction approach has the potential for Tsunami detection and parameter estimation to assist in achieving reliable Tsunami warning.  ...  ACKNOWLEDGEMENTS This work was supported by the National Natural Science Foundation of China under Grant 41574031.  ... 
doi:10.5194/isprsarchives-xli-b1-525-2016 fatcat:i3cjblajejambhkircj7ysttyq

TSUNAMI LEAD WAVE RECONSTRUCTION BASED ON NOISY SEA SURFACE HEIGHT MEASUREMENTS

Kegen Yu
2016 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
This paper presents a Tsunami lead wave reconstruction method using noisy sea surface height (SSH) measurements such as observed by a satellite-carried GNSS reflectometry (GNSS-R) sensor.  ...  The results demonstrate that the proposed wave reconstruction approach has the potential for Tsunami detection and parameter estimation to assist in achieving reliable Tsunami warning.  ...  ACKNOWLEDGEMENTS This work was supported by the National Natural Science Foundation of China under Grant 41574031.  ... 
doi:10.5194/isprs-archives-xli-b1-525-2016 fatcat:hblinf4ejfbkplflctc7plhara

Multimodal 4DVarNets for the reconstruction of sea surface dynamics from SST-SSH synergies [article]

Ronan Fablet, Quentin Febvre, Bertrand Chapron
2022 arXiv   pre-print
We report an application to the reconstruction of the divergence-free component of sea surface dynamics from satellite-derived SSH and SST data.  ...  We introduce a trainable multimodal inversion scheme for the reconstruction of sea surface dynamics from multi-source satellite-derived observations.  ...  It benefited from HPC and GPU resources from Azure (Microsoft Azure grant) and from GENCI-IDRIS (Grant 2021-101030).  ... 
arXiv:2207.01372v1 fatcat:do5ecv2efbcgvfg5myfurrgpve

Neural Network Based Kalman Filters for the Spatio-Temporal Interpolation of Satellite-Derived Sea Surface Temperature

Said Ouala, Ronan Fablet, Cédric Herzet, Bertrand Chapron, Ananda Pascual, Fabrice Collard, Lucile Gaultier
2018 Remote Sensing  
In this work we adress this challenge and develop a novel Neural-Network-based (NN-based) Kalman filter for spatio-temporal interpolation of sea surface dynamics.  ...  , (ii) we derive the associated parametric Kalman-like filtering scheme for a computationally-efficient spatio-temporal interpolation of Sea Surface Temperature (SST) fields.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/rs10121864 fatcat:ytgmlxee5fejlerlhs3vb52iui

Data-Driven Interpolation of Sea Surface Suspended Concentrations Derived from Ocean Colour Remote Sensing Data

Jean-Marie Vient, Frederic Jourdin, Ronan Fablet, Baptiste Mengual, Ludivine Lafosse, Christophe Delacourt
2021 Remote Sensing  
Due to the large increase of both in situ and satellite measurements more and more available information is coming from in situ and satellite measurements, as well as from simulation models.  ...  Due to complex natural and anthropogenic interconnected forcings, the dynamics of suspended sediments within the ocean water column remains difficult to understand and monitor.  ...  This study addresses such issues, with a focus on satellite-derived data for the reconstruction of sea Surface Suspended Sediment Concentration (SSSC).  ... 
doi:10.3390/rs13173537 fatcat:gu6nsysnfzfnfjevgpozwzab6a

Real-time sea-level monitoring using Kalman filtering of GNSS-R data

Joakim Strandberg, Thomas Hobiger, Rüdiger Haas
2019 GPS Solutions  
Finally, based on SNR data from GTGU, it is also shown that the Kalman filter approach is able to detect the presence of sea ice with a higher temporal resolution than the previous methods and traditional  ...  Current GNSS-R (GNSS reflectometry) techniques for sea surface measurements require data collection over longer periods, limiting their usability for real-time applications.  ...  Measurements of sea surface height with Kalman filtering One feature of the combination of B-splines and the Kalman filter that is of particular interest is that the solution can be evaluated in both real  ... 
doi:10.1007/s10291-019-0851-1 fatcat:qskedecj3zdkdcbrm4fizddj74

Assimilating NOAA SST data into the BSH operational circulation model for the North and Baltic Seas: Inference about the data

Svetlana N. Losa, Sergey Danilov, Jens Schröter, Lars Nerger, Silvia Maβmann, Frank Janssen
2012 Journal of Marine Systems  
Here we apply the localized Singular Evolutive Interpolated Kalman (SEIK) filter for assimilating the NOAA AVHRR-derived sea surface temperature (SST) data.  ...  The operational ocean prediction model for the North and Baltic Seas of the German Maritime and Hydrographic Agency (BSH) is augmented with a multivariate data assimilation (DA) system.  ...  Acknowledgments The authors are grateful to Tijana Janjić for valuable discussions on localization; to NOAA and BSH SST satellite data service for providing the data.  ... 
doi:10.1016/j.jmarsys.2012.07.008 fatcat:6zx2cdlxcbgpblxnk2u4zg4yim

Improved ocean prediction skill and reduced uncertainty in the coastal region from multi-model super-ensembles

Michel Rixen, Jeffrey W. Book, Alessandro Carta, Vittorio Grandi, Lavinio Gualdesi, Richard Stoner, Peter Ranelli, Andrea Cavanna, Pietro Zanasca, Gisella Baldasserini, Alex Trangeled, Craig Lewis (+22 others)
2009 Journal of Marine Systems  
New Kalman filter and particle filter based SE methods, which allow for dynamic evolution of weights and associated uncertainty, are compared to standard SE techniques and numerical models.  ...  In the highly dynamic coastal ocean, the presence of small-scales processes, the lack of real-time data, and the limited skill of operational models at the meso-scale have so far limited the application  ...  The NCOM sea surface temperature (SST) was relaxed towards a satellite SST analysis.  ... 
doi:10.1016/j.jmarsys.2009.01.014 fatcat:kjulnmofefekdnwwjvyyphvtpq

Joint Interpolation and Representation Learning for Irregularly Sampled Satellite-Derived Geophysical Fields

Ronan Fablet, Maxime Beauchamp, Lucas Drumetz, François Rousseau
2021 Frontiers in Applied Mathematics and Statistics  
The end-to-end learning procedure jointly solves the reconstruction of gap-free fields and the training of the considered priors.  ...  Through different case studies, including observing system simulation experiments for sea surface geophysical fields, we demonstrate the relevance of the proposed framework compared with optimal interpolation  ...  of geophysical dynamics from satellite remote sensing data.  ... 
doi:10.3389/fams.2021.655224 fatcat:ppr53cnns5gchavssyaoaqx4ci

A HMM-based model to geolocate pelagic fish from high-resolution individual temperature and depth histories: European sea bass as a case study

Mathieu Woillez, Ronan Fablet, Tran-Thanh Ngo, Maxime Lalire, Pascal Lazure, Hélène de Pontual
2016 Ecological Modelling  
As a case study, we consider long time series of data storage tags (DSTs) deployed on European sea bass for which individual migration tracks are reconstructed for the first time.  ...  We performed a sensitivity analysis on synthetic and real data in order to assess the robustness of the reconstructed tracks with respect to model parameters, chosen reference geophysical fields and the  ...  Satellite data were obtained from the Centre de Recherche et d'Exploitation Satellitaire (CERSAT), at IFREMER, Plouzané (France) on behalf of ESA/Medspiration project.  ... 
doi:10.1016/j.ecolmodel.2015.10.024 fatcat:y3wkjxpcd5bsbp6andqdxrg7sa

Coupling a two-way nested primitive equation model and a statistical SST predictor of the Ligurian Sea via data assimilation

A. Barth, A. Alvera-Azcárate, J.-M. Beckers, M. Rixen
2006 Ocean Modelling  
In this work, the system of two-way nested models centred in the Ligurian Sea and the satellite-based ocean forecasting (SOFT) system predicting the sea surface temperature (SST) are used.  ...  The data assimilation scheme is a simplified reduced order Kalman filter based on a constant error space.  ...  Acknowledgements Alberto Alvarez is acknowledged for providing the data of the SOFT predictor.  ... 
doi:10.1016/j.ocemod.2006.02.003 fatcat:pyfqj5z33veh3l26i4vree6cou

Improving light and temperature based geolocation by unscented Kalman filtering

Chi H. Lam, Anders Nielsen, John R. Sibert
2008 Fisheries Research  
These tracks can be further improved by including the tag measured sea-surface temperature and matching it to external sea-surface temperature (SST) data.  ...  UKFSST offers better handling of non-linearities in Kalman filter, and provides a statistically sound model for geolocation applications, as opposed to ad hoc SST matching approaches.  ...  We acknowledge the NOAA CoastWatch Program, NOAA NESDIS Office of Satellite Data Processing and Distribution, and NASA's Goddard Space Flight Center, OceanColor Web for providing the Blended Sea Surface  ... 
doi:10.1016/j.fishres.2007.11.002 fatcat:6jhgsj2ncjgg3n34mgm5qocvhm

Weighted ensemble transform Kalman filter for image assimilation

SEBASTIEN Beyou, ANNE Cuzol, SAI Subrahmanyam Gorthi, ETIENNE Mémin
2013 Tellus: Series A, Dynamic Meteorology and Oceanography  
It has been in particular applied for the reconstruction of oceanic surface current vorticity fields from Sea Surface Temperature satellite data.  ...  This paper proposes an extension of the Weighted Ensemble Kalman filter (WEnKF) proposed by Papadakis et al. (2010) for the assimilation of image observations.  ...  Real satellite sequence of SST (sea surface temperature) images. Dark blue regions indicate missing data due to the cloud cover or land regions.  ... 
doi:10.3402/tellusa.v65i0.18803 fatcat:w2w5hnxfwraf3idspkt4qsydmq

Depth-averaged instantaneous currents in a tidally dominated shelf sea from glider observations

Lucas Merckelbach
2016 Biogeosciences  
The algorithm uses a first-order Butterworth low pass filter to estimate the residual current component, and a Kalman filter based on the linear shallow water equations for the tidal component.  ...  A comparison of data from a glider experiment with current data from an acoustic Doppler current profilers deployed nearby shows that the standard deviations for the east and north current components are  ...  This work was jointly financially supported by GROOM of the 7th Framework Programme of the European Union under grant agreement no. 284321 and through the Coastal Observing System for Northern and Arctic  ... 
doi:10.5194/bg-13-6637-2016 fatcat:pxxdp5bwzvcxnpvfthlvqbau3a
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