This work builds on the analyses made within the EUMETSAT ComboCloud project (contract EUM/CO/19/4600002352/THH) whose purpose was to develop AI-based solutions to infer key cloud parameters exploiting the combination of innovative features offered by upcoming satellite sensors, namely the Next Generation Atmospheric Sounding Interferometer (IASI-NG), and the Microwave Sounder (MWS). We present the potential of the developed solutions applied to real observations, from the instruments flying onboard the EUMETSAT MetOp satellites such as the Atmospheric Sounding Interferometer (IASI), the Advanced Microwave Sounding Unit (AMSU), and the Microwave Humidity Sounder (MHS) and validated against cloud products from an independent dataset of real observations. The validation demonstrated good agreement between reference and retrieved cloud key parameters, showing consistent range and spatial patterns.

Topics
Aeroacoustics, Artificial intelligence, Space instruments, Interferometry, Public policy and governance
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