Correction of NWP Ocean Surface Wind Biases with Machine Learning
IEEE International Geoscience and Remote Sensing Symposium (IEEE IGARSS 2024), Acting for Sustainability and Resilience, 7-12 July 2024, Athens, Greece.-- 4 pages, 3 figures, 1 table.-- © 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses,...
| Autores: | , , , |
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| Tipo de recurso: | otro |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/368594 |
| Acceso en línea: | http://hdl.handle.net/10261/368594 |
| Access Level: | acceso abierto |
| Palabra clave: | Stress-equivalent winds NWP biases Scatterometer Machine learning Neural networks |
| Sumario: | IEEE International Geoscience and Remote Sensing Symposium (IEEE IGARSS 2024), Acting for Sustainability and Resilience, 7-12 July 2024, Athens, Greece.-- 4 pages, 3 figures, 1 table.-- © 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works |
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