argo data 1gaussian processes 1ocean heat content 1spatio-temporal modeling 1uncertainty quantification 1
From the 1 of 3 linked papers with an AI index.
3 papers
stat.AP2026
Improved Global Ocean Heat Content Estimation by Modeling Vertical Spatio-Temporal Dependence
Thea Sukianto, Donata Giglio, Mikael Kuusela
The paper introduces a method that jointly models two ocean pressure layers using bivariate locally stationary Gaussian processes to improve global ocean heat content estimates and…
stat.AP2026
Locally stationary Argo ocean heat content estimates: Modeling, validation and uncertainty quantification
Thea Sukianto, Mikael Kuusela, Donata Giglio +3
Argo profiling floats measure seawater temperature and salinity in the upper 2000 meters of the ocean. These floats are uniquely capable of measuring the global Ocean Heat Content…
stat.AP2025
Seasonal trend assessment of US extreme precipitation via changepoint segmentation
Jaechoul Lee, Mintaek Lee, Thea Sukianto
Most climate trend studies analyze long-term trends as a proxy for climate dynamics. However, when examining seasonal data, it is unrealistic to assume that long-term trends remain…