1. Radiative transfer models (RTMs) are critical in supporting Earth Observation applications such as vicarious calibration.
2. Four different 1D radiative transfer models were compared in actual usage conditions corresponding to the simulation of satellite observations over Libya-4, a bright desert PICS.
3. The differences between the models typically vary between 0.5 and 3.5% depending on the spectral region and the shape of the sensor spectral response.
The article "Radiative Transfer Model Comparison with Satellite Observations over CEOS Calibration Site Libya-4" provides a detailed comparison of four radiative transfer models (RTMs) used in Earth Observation applications. The authors highlight the importance of RTMs in supporting various EO applications, including vicarious calibration, retrieval algorithm verification, and satellite data assimilation. They note that these models simulate electromagnetic radiation propagation in highly idealized media, typically a 1D plane-parallel atmosphere with an underlying flat surface.
The authors compare the four RTMs in actual usage conditions as those employed by vicarious calibration methods. They use simulated radiance over a bright pseudo-invariant calibration site (PICS), Libya-4, to achieve this objective. The authors note that such an application requires the simulation of top-of-atmosphere Bidirectional Reflectance Factor (BRF) in the 400–2500 nm spectral interval. They use satellite observations acquired by six different radiometers over Libya-4 to define these conditions.
The article provides a comprehensive overview of the different RTMs and their implementation, highlighting differences in their parametrization for Rayleigh scattering, molecular absorption, number of active molecules or number of quadrature points. The authors note that discrepancies exist among these models due to differences in their implementation and numerical approximations.
The article presents its findings clearly and concisely, providing quantitative results on the differences between the four RTMs operated with similar input parameters. However, it is important to note that the study only compares four RTMs and uses simulated data from one PICS location. Therefore, it may not be representative of all possible scenarios or locations.
Additionally, while the article acknowledges potential biases due to differences in model implementation and numerical approximations, it does not explore potential biases due to other factors such as model assumptions or simplifications. For example, the assumption of a 1D plane-parallel atmosphere with an underlying flat surface may not be representative of all real-world scenarios.
Overall, the article provides valuable insights into the differences between RTMs used in EO applications and highlights the importance of benchmarking these models to quantify their accuracy. However, it is important to consider potential biases and limitations when interpreting the results.