4 papers · 1 filter
Application of the latent twins approach for clear sky retrieval from IASI observations
Michele Martinazzo, Cristina Sgattoni, Marco Menarini +3
In recent years, data-driven approaches emerged as alternatives to traditional physics-based retrievals, taking advantage of machine learning techniques such as learnable pseudoinv…
Latent Twins: A Framework for Scene Recognition and Fast Radiative Transfer Inversion in FORUM All-Sky Observations
Cristina Sgattoni, Luca Sgheri, Matthias Chung +1
The FORUM (Far-infrared Outgoing Radiation Understanding and Monitoring) mission will provide, for the first time, systematic far-infrared spectral measurements of Earth's outgoing…
Machine Learning for Cloud Detection in IASI Measurements: A Data-Driven SVM Approach with Physical Constraints
Chiara Zugarini, Cristina Sgattoni, Luca Sgheri
Cloud detection is fundamental for the interpretation and operational exploitation of hyperspectral infrared sounders, yet the capability of infrared radiances alone to provide rel…
A physics-aware data-driven surrogate approach for fast atmospheric radiative transfer inversion
Cristina Sgattoni, Luca Sgheri, Matthias Chung
FORUM (Far-infrared Outgoing Radiation Understanding and Monitoring) was selected in 2019 as the ninth Earth Explorer mission by the European Space Agency (ESA). Its primary object…