MCSTNet: a memory-contextual spatiotemporal transfer network for prediction of SST sequences and fronts with remote sensing data

Ocean fronts are a response to the variabilities of marine hydrographic elements and are an important mesoscale ocean phenomenon, playing a significant role in fish farming and fishing, sea-air exchange, marine environmental protection, etc. The horizontal gradients of sea surface temperature (SST)...

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Bibliographic Details
Published in:	Frontiers in Marine Science Vol. 10
Main Authors:	Ma, Ying, Liu, Wen, Chen, Ge, Zhong, Guoqiang, Tian, Fenglin
Format:	Journal Article
Language:	English
Published:	Lausanne Frontiers Research Foundation 16.05.2023 Frontiers Media S.A
Subjects:	Accuracy Air-water exchanges Aquaculture Environmental protection Fish Fish culture Fish farms Fishing Forecasting Fronts Marine environment MCSTNet Neural networks Oceanic analysis Oceanographic research Oceanography Optimization techniques Predictions Remote sensing Satellites Sea surface Sea surface temperature SST sequence and front prediction tasks Surface temperature the encoder-decoder structure the memory-contextual module the time transfer module Time series Training South China Sea Japan
ISSN:	2296-7745, 2296-7745
Online Access:	Get full text
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