Building a Learning Database for the Neural Network Retrieval of Sea Surface Salinity from SMOS Brightness Temperatures

Autor: Ammar, Adel, Labroue, Sylvie, Obligis, Estelle, Crépon, Michel, Thiria, Sylvie

This article deals with an important aspect of the neural network retrieval of sea surface salinity (SSS) from SMOS brightness temperatures (TBs). The neural network retrieval method is an empirical approach that offers the possibility of being indep

Externí odkaz: http://arxiv.org/abs/1601.04296

Neural approach to inverting complex system: Application to ocean salinity profile estimation from surface parameters

Autor: Gueye, Mbaye Babacar, Niang, Awa, Arnault, Sabine, Thiria, Sylvie, Crépon, Michel

Publikováno v: In Computers and Geosciences November 2014 72:201-209

Atmospheric correction of MERIS data for case-2 waters using a neuro-variational inversion

Autor: Brajard, Julien, Santer, Richard, Crépon, Michel, Thiria, Sylvie

Publikováno v: In Remote Sensing of Environment November 2012 126:51-61

Comment on the paper 'Characteristic time scales of decadal to centennial changes in global surface temperatures over the past 150 years ' by J.L. Le Mouël, F. Lopes and V. Courtillot First published: 14 October 2019 in Earth and Space Science

Autor: Cuypers, Yannis, Codron, Francis, Crépon, Michel

Publikováno v: Earth and Space Science
Earth and Space Science, American Geophysical Union/Wiley, 2021, 8 (4), pp.e2020EA001298. ⟨10.1029/2020EA001298⟩
Earth and Space Science, 2021, 8 (4), pp.e2020EA001298. ⟨10.1029/2020EA001298⟩

International audience; Based on Singular Spectral Analysis (SSA) analysis of global earth surface temperature and solar activity (sun spots) Le Mouël et al (2019) suggest that the variability in Earth surface temperature observed since 1850 is natu

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::563f12a8695246c53a233377c3c66b84
https://hal.archives-ouvertes.fr/hal-03171976/file/2020EA001298.pdf

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