Wangxu Wei
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View article: Ocean Heat Content Sets Another Record in 2025
Ocean Heat Content Sets Another Record in 2025 Open
Global ocean warming continued unabated in 2025 in response to increased greenhouse gas concentrations and recent reductions in sulfate aerosols, reflecting the long-term accumulation of heat within the climate system, with conditions evol…
View article: A Self-Evolving AI Agent System for Climate Science
A Self-Evolving AI Agent System for Climate Science Open
Scientific progress in Earth science depends on integrating data across the planet's interconnected spheres. However, the accelerating volume and fragmentation of multi-sphere knowledge and data have surpassed human analytical capacity. Th…
Physics-Informed Machine Learning Reconstruction of High Resolution Ocean Subsurface Temperature Profiles From In-Situ and Satellite Observations Open
The irregular and incomplete coverage of in-situ ocean temperature profile observations is a major problem for various scientific applications in ocean and climate research and operational fields. However, high-resolution gridded datasets …
IAPv4 ocean temperature and ocean heat content gridded dataset Open
Ocean observational gridded products are vital for climate monitoring, ocean and climate research, model evaluation, and supporting climate mitigation and adaptation measures. This paper describes the 4th version of the Institute of Atmosp…
Comment on essd-2024-42 Open
Abstract. Ocean observational gridded products are vital for climate monitoring, ocean and climate research, model evaluation, and supporting climate mitigation and adaptation measures. This paper describes the 4th version of the Institute…
Comment on essd-2024-42 Open
Abstract. Ocean observational gridded products are vital for climate monitoring, ocean and climate research, model evaluation, and supporting climate mitigation and adaptation measures. This paper describes the 4th version of the Institute…
Comment on essd-2024-42 Open
Abstract. Ocean observational gridded products are vital for climate monitoring, ocean and climate research, model evaluation, and supporting climate mitigation and adaptation measures. This paper describes the 4th version of the Institute…
Comment on essd-2024-42 Open
Abstract. Ocean observational gridded products are vital for climate monitoring, ocean and climate research, model evaluation, and supporting climate mitigation and adaptation measures. This paper describes the 4th version of the Institute…
IAPv4 ocean temperature and ocean heat content gridded dataset Open
Ocean observational gridded products are vital for climate monitoring, ocean and climate research, model evaluation, and supporting climate mitigation and adaptation measures. This paper describes the 4th version of the Institute of Atmosp…
View article: Reconstructing ocean subsurface salinity at high resolution using a machine learning approach
Reconstructing ocean subsurface salinity at high resolution using a machine learning approach Open
A gridded ocean subsurface salinity dataset with global coverage is useful for research on climate change and its variability. Here, we explore the feed-forward neural network (FFNN) approach to reconstruct a high-resolution (0.25∘ × 0.25∘…
View article: Comment on essd-2022-236
Comment on essd-2022-236 Open
Abstract. A gridded ocean subsurface salinity dataset with global coverage is useful for research on climate change and its variability. Here, we explore the feed-forward neural network (FFNN) approach to reconstruct a high-resolution (0.2…
View article: Comment on essd-2022-236
Comment on essd-2022-236 Open
Abstract. A gridded ocean subsurface salinity dataset with global coverage is useful for research on climate change and its variability. Here, we explore the feed-forward neural network (FFNN) approach to reconstruct a high-resolution (0.2…
View article: Comment on essd-2022-236
Comment on essd-2022-236 Open
Abstract. A gridded ocean subsurface salinity dataset with global coverage is useful for research on climate change and its variability. Here, we explore the feed-forward neural network (FFNN) approach to reconstruct a high-resolution (0.2…