A physics-aware data-driven surrogate approach for fast atmospheric radiative transfer inversion

Abstract

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 objective is to collect interferometric measurements in the Far-InfraRed (FIR) spectral range, which accounts for 50\% of Earth's outgoing longwave radiation emitted into space, and will be observed from space for the first time. Accurate measurements of the FIR at the top of the atmosphere are crucial for improving climate models. Current instruments are insufficient, necessitating the development of advanced computational techniques. To ensure the quality of the mission data, an End-to-End Simulator (E2ES) was developed to simulate the measurement process and evaluate the effects of instrument characteristics and environmental factors. The core challenge of the mission is solving the retrieval problem, which involves estimating atmospheric properties from the radiance spectra observed by the satellite. This problem is ill-posed and regularization techniques are necessary. In this work, we present a novel and fast data-driven approach to approximate the inverse mapping. In the first phase, we generate an initial approximation of the inverse mapping using only simulated FORUM data. In the second phase, we improve this approximation by introducing climatological data as a priori information and using a neural network to estimate the optimal regularization parameters. While our approach does not match the precision of full-physics retrieval methods, its key advantage is the ability to deliver results almost instantaneously, making it highly suitable for real-time applications. Furthermore, the proposed method can provide more accurate a priori estimates for full-physics methods, thereby improving the overall accuracy of the retrieved atmospheric profiles.

Figures (13)

• Figure 1: Left panel: FORUM orbit with upwelling radiation seen by the instrument. Right panel: Radiative transfer and the discretization of the atmosphere. The downwelling radiation is indicated in red and the upwelling radiation is in green. In each atmospheric layer, the attenuation factor is highlighted with the purple arrow, while the thermal emission is highlighted with the yellow arrow.
• Figure 2: Solution scheme where the different steps are represented with arrows of different colors with the related section indication: purple for data-driven step, blue for regularization step and green for regularization parameters computation and estimation.
• Figure 3: Geolocations of cases in TN1, represented by black dots for both January and July.
• Figure 4: Geolocations of cases in TS1 and TS2 for both January and July, with red squares for TS1 and black dots for TS2.
• Figure 5: Singular values representation of matrix $\bfY$. The singular values in decreasing magnitude. The rapid decline in the singular values suggests that the first few components capture most of the information, allowing for dimensionality reduction without significant loss of information.