Enhanced Sea Surface Salinity Estimates Using Machine-Learning Algorithm With SMAP and High-Resolution Buoy Data-Reference-Cited by-同舟云学术

Enhanced Sea Surface Salinity Estimates Using Machine-Learning Algorithm With SMAP and High-Resolution Buoy Data

Published:2022 Issue: Volume:10 Page:74304-74317
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Kesavakumar Balakrishnan¹^ORCID,Shanmugam Palanisamy¹^ORCID,Venkatesan Ramasamy²

Affiliation:

1. Department of Ocean Engineering, Indian Institute of Technology Madras, Chennai, India

2. National Institute of Ocean Technology, Ministry of Earth Sciences, Chennai, India

Funder

Ministry of Earth Sciences (MoES), Government of India, Ocean Observation Network Program

National Geospatial Programme of Department of Science and Technology of the Government of India

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09825687.pdf?arnumber=9825687

Reference72 articles.

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3. Intrusion of the bay of Bengal water into the Arabian sea during winter monsoon and associated chemical and biological response;kumar;Geophys Res Lett,2004

4. Improvement of SMAP sea surface salinity in river-dominated oceans using machine learning approaches

5. Sea Surface Salinity Response to Tropical Cyclones Based on Satellite Observations

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