Deep Ocean Remote Sensing and Its Application in the Ocean Warming Study in Recent Decades

Dear Colleagues,

Observing the subsurface and deeper ocean has become extremely important in recent decades following recent evidence suggesting the presence of widespread warming in the ocean’s interior as a response to the significant global warming (Earth’s Energy Imbalance—EEI). Indeed, EEI grew to unprecedented amounts in 2010–2018, much bigger than it was in previous years and decades. The ocean’s responses to this increase in EEI must be understood to fully evaluate the actual impact of global warming. Satellite remote sensing has helped us to conduct multiple sea-surface observations at various spatiotemporal scales for several decades, but these observations are confined to the ocean surface and cannot directly detect information beneath the surface, where many significant dynamic processes and features are located. Deeper ocean remote sensing has the ability to detect and depict the processes and features in the subsurface and deeper layer within the ocean, as well as their implications for climate systems on a large scale. However, the lack of consistent long-term and large-scale subsurface observation hinders the inference and recognition of subsurface and deeper ocean processes. Although deeper ocean remote sensing based on satellite sensors has been successfully developed to detect the ocean’s interior, many important ocean processes in the interior still need to be observed and studied from space, such as deeper ocean warming, climate variability, heat redistribution processes, internal dynamics, mixed layer variability, ocean circulation, biogeochemical processes, and so on, which relate to and greatly impact recent global climate change and ocean internal warming.

This Special Issue invites contributions to advances in deeper ocean remote sensing and its application in ocean warming studies based on satellite remote sensing and reports on recent attempts to combine all kinds of satellite sensors and remote sensing big data with other observations and techniques using empirical statistics, machine learning, deep learning, dynamic model, and data assimilation techniques to retrieve and reconstruct multidimensional and multiscale physical and biogeochemical parameters in the ocean’s interior, and further applied to the ocean warming and variability study. Furthermore, investigations on internal variability (from the coupled Earth–atmosphere system) and ocean intrinsic variability contributions that can blur the interpretation of ocean warming processes due to global warming are also welcomed.

Prof. Dr. Xiao-Hai Yan
Dr. William Llovel
Prof. Dr. Hua Su
Prof. Dr. Wei Zhuang
Guest Editors

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