“来自遥感和观测的神经合成剖面(NeSPReSO) -重建墨西哥湾的温度和盐度场”[海洋模拟196(2025)102550]的勘误表

IF 2.9 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES
Jose R. Miranda , Olmo Zavala-Romero , Luna Hiron , Eric P. Chassignet , Bulusu Subrahmanyam , Thomas Meunier , Robert W. Helber , Enric Pallas-Sanz , Miguel Tenreiro
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摘要

本文章由计算机程序翻译,如有差异,请以英文原文为准。
Corrigendum to “Neural Synthetic Profiles from Remote Sensing and Observations (NeSPReSO) — Reconstructing temperature and salinity fields in the Gulf of Mexico” [Ocean Modelling 196 (2025) 102550]
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来源期刊
Ocean Modelling
Ocean Modelling 地学-海洋学
CiteScore
5.50
自引率
9.40%
发文量
86
审稿时长
19.6 weeks
期刊介绍: The main objective of Ocean Modelling is to provide rapid communication between those interested in ocean modelling, whether through direct observation, or through analytical, numerical or laboratory models, and including interactions between physical and biogeochemical or biological phenomena. Because of the intimate links between ocean and atmosphere, involvement of scientists interested in influences of either medium on the other is welcome. The journal has a wide scope and includes ocean-atmosphere interaction in various forms as well as pure ocean results. In addition to primary peer-reviewed papers, the journal provides review papers, preliminary communications, and discussions.
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