SEVIRI Hyper-Fast Forward Model with Application to Emissivity Retrieval

Area of Science:

• Earth Observation
• Atmospheric Science
• Radiative Transfer Modeling

Background:

• Accurate and timely processing of multi-spectral imager data, like SEVIRI, is crucial for Earth observation.
• Fast radiative transfer calculations are essential for real-time analysis of infrared radiances.

Purpose of the Study:

• To develop and implement a novel, computationally efficient forward radiative transfer model for SEVIRI data.
• To apply this model for the near real-time retrieval of surface parameters, with a focus on emissivity.

Main Methods:

• Development of a new radiative transfer forward model for SEVIRI, achieving a ≈7-fold improvement in computational speed.
• Application of an inverse scheme using a Kalman filter for sequential processing of SEVIRI observations.
• Validation using in situ measurements from a 2017 field experiment in the Namib Desert and comparison with Infrared Atmospheric Sounder Interferometer (IASI) data.

Main Results:

• The new model enables SEVIRI data processing at nearly real-time speeds.
• Retrieved surface emissivities show good agreement with in situ observations and IASI retrievals.
• Average differences in emissivity retrievals are consistently below 0.01.

Conclusions:

• The developed radiative transfer model significantly enhances the efficiency of SEVIRI data processing.
• The model facilitates accurate, near real-time retrieval of surface emissivity.
• The findings support improved monitoring of surface properties using satellite observations.