مؤتمر
Filtering Internal Tides from Wide-Swath Altimeter Data Using Convolutional Neural Networks
العنوان: | Filtering Internal Tides from Wide-Swath Altimeter Data Using Convolutional Neural Networks |
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المؤلفون: | Lguensat, Redouane, Fablet, Ronan, Le Sommer, Julien, Metref, Sammy, Cosme, Emmanuel, Ouenniche, Kaouther, Drumetz, Lucas, Gula, Jonathan |
بيانات النشر: | IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, 2020, pp. 3904-3907 |
سنة النشر: | 2020 |
المجموعة: | Ifremer (French Research Institute for Exploitation of the Sea): Archimer |
مصطلحات موضوعية: | Internal Gravity Waves, Filtering, Deep Learning, Sea Surface Height, SWOT |
الوصف: | The upcoming Surface Water Ocean Topography (SWOT) satellite altimetry mission is expected to yield two-dimensional high-resolution measurements of Sea Surface Height (SSII), thus allowing for a better characterization of the mesoscale and submesoscale eddy field. However, to fulfill the promises of this mission, filtering the tidal component of the SSH measurements is necessary. This challenging problem is crucial since the posterior studies done by physical oceanographers using SWOT data will depend heavily on the selected filtering schemes. In this paper, we cast this problem into a supervised learning framework and propose the use of convolutional neural networks (ConvNets) to estimate fields free of internal tide signals. Numerical experiments based on an advanced North Atlantic simulation of the ocean circulation (eNATL60) show that our ConvNet considerably reduces the imprint of the internal waves in SSII data even in regions unseen by the neural network. We also investigate the relevance of considering additional data from other sea surface variables such as sea surface temperature (SST). |
نوع الوثيقة: | conference object report |
وصف الملف: | application/pdf |
اللغة: | English |
العلاقة: | https://archimer.ifremer.fr/doc/00719/83102/88335.pdfTest; https://archimer.ifremer.fr/doc/00719/83102Test/ |
DOI: | 10.1109/IGARSS39084.2020.9323531 |
الإتاحة: | https://doi.org/10.1109/IGARSS39084.2020.9323531Test https://archimer.ifremer.fr/doc/00719/83102/88335.pdfTest https://archimer.ifremer.fr/doc/00719/83102Test/ |
حقوق: | info:eu-repo/semantics/openAccess ; restricted use |
رقم الانضمام: | edsbas.BAA67F56 |
قاعدة البيانات: | BASE |
DOI: | 10.1109/IGARSS39084.2020.9323531 |
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