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https://doi.org/10.5194/egusphere-2025-4861
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/egusphere-2025-4861
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
10 Nov 2025
| 10 Nov 2025
Eradiate: An Accurate and Flexible Radiative Transfer Model for Earth Observation and Atmospheric Science
Abstract. Eradiate is a new open-source 3D radiative transfer model designed to provide highly accurate results for various applications in Earth observation and atmospheric science. Its Monte Carlo ray tracing radiometric kernel is derived from Mitsuba 3, a research-oriented rendering system, and therefore benefits from many technological advances made in the computer graphics community. This foundation unlocks a path to improving radiative transfer simulation accuracy by facilitating the integration of models and numerical techniques developed by scientific communities that are otherwise compartmentalized. Eradiate currently covers the [250 nm, 3 μm] spectral region and offers advanced 3D surface modelling features, as well as a state-of-the-art 1D atmospheric model (plane-parallel and spherical-shell) and polarization support. Designed for modern scientific Python programming workflows, it is intended for use in interactive Python sessions such as Jupyter notebooks. Eradiate is thoroughly tested and validated against various radiative transfer benchmarks, ensuring its suitability for calibration and validation tasks. This paper introduces Eradiate from historical, scientific, and architectural perspectives. It elaborates on its feature set and showcases a variety of applications, with scenes ranging from simple 1D plane-parallel setups to complex, fully resolved 3D vegetated canopies and even large regions on Earth.
How to cite. Leroy, V., Marton, N., Emde, C., Misk, N., Gonzalez Almeida, M., Schunke, S., Cremer, N., Gascon, F., and Govaerts, Y.: Eradiate: An Accurate and Flexible Radiative Transfer Model for Earth Observation and Atmospheric Science, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-4861, 2025.
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- RC1: 'Comment on egusphere-2025-4861', Anonymous Referee #1, 12 Feb 2026
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RC2: 'Comment on egusphere-2025-4861', Anonymous Referee #2, 16 Feb 2026
# Review of the article "Eradiate: An Accurate and Flexible Radiative Transfer Model for Earth Observation and Atmospheric Science"The article is about the newly developed radiative transfer model Eradiate for the UV, visible, and near-infrared (UV-VIS-NIR) spectral range.Eradiate is a 3D radiative transfer model designed for applications in Earth observations and atmospheric science.It is capable of simulating radiative transfer in 1D atmospheres with 3D surfaces, including complex topography and vegetation, and is controlled via a Python interface.## General commentThe article is mostly well-written and provides a comprehensive overview of the Eradiate model, its capabilities, and its applications. There are some minor issues, which are discussed below. The model itself is a significant contribution to the field of radiative transfer modeling, especially due to its design and its potential applications in earth observation. It uses a (modified) radiometric kernel that was developed in the context of computer graphics, combining the problem of earth observation radiative transfer with techniques developed in computer graphics. Though radiative transfer and 3D rendering are closely related, they have been developed in different communities with different goals and requirements. By using the radiometric kernel from computer graphics, Eradiate benefits from advancements and rendering techniques developed in that field, which can result in improved efficiency in simulating radiative transfer processes.Eradiates main downside is that it does not provide a fully 3D atmosphere (including 3D clouds and aerosols), limiting its applications mostly to horizontally uniform atmospheres. This is a significant limitation because, in cases where the 3D structure of the surface is important, the 3D structure of the atmosphere (e.g., clouds) is often important as well. However, the authors are aware of this and plan to include a 3D atmosphere in a future version.## Minor issuesThough the article, as mentioned above, is mostly well-written, there are some minor issues. In Section 8, I understand that the authors want to provide an overview of the applications of Eradiate and, as they called the section "Applications and results", also provide some results of the model, which they do. I also do not expect a validation here, as this is done in Sect. 7. However, what is missing is a (detailed) discussion of the results. The results are presented in a very brief manner, and there is almost no discussion and explanation of the results, which is needed to understand their implications and the capabilities of the model.## Specific comments1. Lines 49-50: "The world is intrinsically three-dimensional, but most simulation tools, for performance reasons, currently represent the scene using a plane-parallel geometry...". Please provide examples of such simulation tools.2. Lines 184-192: Please add that you assume that the scatterers are totally randomly oriented, as Eq. 3 makes sense only under this assumption. If this is not assumed, then adjust the equation accordingly. Furthermore, explain the R matrices and the relationship of θxx to the incoming and outgoing directions.3. Lines 205-208: Please give references and briefly explain the methods.4. Lines 226-230: Please briefly explain the different BSDF models and their purpose (e.g., which are used for vegetation, which for soil, which include polarization, etc.). A table might be helpful here.5. Lines 237-238. The reference to Fig. 3 seems to be in the wrong place. It should be placed after "vegetated canopies" as there are no urban environments in Fig. 3.6. Lines 269-271: Must the database be predefined by the user? This paragraph is a bit confusing.7. Lines 271-276: Please explain the CKD mode in more detail. From your description, it is difficult to understand how the CKD mode works. Maybe a sketch could help to explain the CKD mode.8. Line 281: "110 cm-1". The unit seems to be wrong.9. Lines 288-292: Is it correct that Eradiate does not provide tools to calculate the scattering properties using the T-matrix method or Mie theory? If yes, please rephrase the paragraph to make this clear. If not, please explain how the scattering properties can be calculated in Eradiate.10. Lines 307-310: When you write that the sun is located at an infinite distance, the angular size of the sun (your emitter) is always infinitesimally small, but in the first sentence you write that the second illumination model is characterized by the angular size of the emitter. Either I am missing something or something in the text is not clear. Either way, this paragraph needs to be revised for clarity. Furthermore, a simple sketch could be helpful to explain the two illumination models.11. Lines 325-326: Can the reference surface be set to any direction? If yes, please explicitly state this. If not, rephrase the sentence accordingly.12. Lines 435-438: The sentence starting with "ROMC submissions..." is confusing. It is difficult to understand what the actual differences are and what the purpose of each mode is. Please rephrase the sentence to make it clear.13. Lines 439-449: Please explain briefly the different scenarios and measurements.14. Lines 468-474: Please explain/discuss the results that are shown in Fig. 8 in more detail. Saying that it is comparable to Fig. 8 of Emde et al. (2015) is not sufficient. Furthermore, please provide some more details about the scenario, e.g., what is the geometry of this scenario, where is the observation location, what aerosol was used, and apart from ozone, were there any other absorbers, etc.15. Line 498: What does "PICS" stand for? Please explain the acronym.16. Line 507: What is the *panellus* correlated-k distribution? Please explain.17. Line 547: I do not understand the purpose of this sentence. Please rephrase.18. Lines 551-553: Please explain what desert aerosol model was used and add some details about the model, e.g., which size distribution, etc.19. Lines 647-648: The sentence starting with "Various..." is difficult to read. Please rephrase.20. Lines 652-653: The sentence starting with "In order ..." is difficult to read. Please rephrase.21. Fig. 1: The figure could be misleading as you depict horizontally distributed clouds, but in the text you explicitly state that your atmosphere is 1D. Please clarify this in the text and/or adjust the figure accordingly.22. Table 2: The font size is very small; please increase the font size to make it more readable. Furthermore, the caption is confusing. Please explain what the different measurement abbreviations stand for and what the different scenarios are, or refer to the section where they are explained. See also comment 13.23. Fig. 8: Please increase the font size. Furthermore, it seems that the units are missing. What does "B3, eradiate, case 0" in the title of the plot mean?24. Fig. 10: The unit seems to be missing, or the caption is insufficient. Slightly increase the font size.25. Fig. 11: What does "VAA" stand for? Please explain the acronym.26. Fig. 12: It seems that the y-axis label is missing. Please explicitly state in the caption which of the three scenarios includes an atmosphere and which does not. The labels of the different lines are inconsistent with the text (lines 541-546). Please adjust.Citation: https://doi.org/
10.5194/egusphere-2025-4861-RC2
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Latest update: 28 Feb 2026
Vincent Leroy
CORRESPONDING AUTHOR
Rayference, Brussels, Belgium
Nicolae Marton
Rayference, Brussels, Belgium
Claudia Emde
Rayference, Brussels, Belgium
Nicolas Misk
Rayference, Brussels, Belgium
Misael Gonzalez Almeida
Rayference, Brussels, Belgium
Sebastian Schunke
formerly at: Rayference, Brussels, Belgium
Noelle Cremer
Serco SpA c/o European Space Agency (ESA), European Space Research Institute (ESRIN), Frascati, Italy
Ferran Gascon
European Space Agency (ESA), European Space Research Institute (ESRIN), Frascati, Italy
Yves Govaerts
Rayference, Brussels, Belgium
Short summary
Eradiate is open-source software that models how light travels through Earth's atmosphere and reflects off its surface. Using computer graphics rendering technology, it simulates satellite observations by accurately representing both surface and atmosphere in a unified framework. This bridges otherwise separate scientific communities, enabling the generation of accurate synthetic reference data to improve satellite products used for pollution tracking, climate monitoring, or land use assessment.
Eradiate is open-source software that models how light travels through Earth's atmosphere and...
The preprint presenting Eradiate v1.0.0 marks a substantial development in the convergence of the Earth Observation (EO) and Computer Graphics (CG) communities. By leveraging the Mitsuba 3 rendering system as its radiometric kernel, Eradiate introduces modern software engineering practices and high-performance computing techniques to the field of radiative transfer for atmospheric science. The unified 1D/3D framework and the Python-native interface are particularly commendable and address a genuine need for modular, extensible radiative transfer tools within this scientific community.
That said, a few aspects of the manuscript could be further developed to better clarify its unique scientific contribution, computational performance, and the practical implications of its most innovative features.
1. Positioning with respect to established 3D RT codes.
One aspect that would benefit from further elaboration is a more explicit comparison with existing 3D MC RT codes developed within the atmospheric community, most notably MYSTIC. MYSTIC has long been regarded as a reference implementation for 3D polarized radiative transfer in cloudy atmospheres. While the preprint convincingly demonstrates Eradiate’s accuracy and 3D capabilities, the manuscript could more clearly articulate what Eradiate offers beyond what is currently available in established tools such as MYSTIC. Since MYSTIC already handles 3D heterogeneity, polarization, and complex atmospheric configurations with high accuracy, it would strengthen the paper to clarify which physical, numerical, or architectural advances motivate a transition toward Eradiate for atmospheric RT users. A clearer positioning in this respect would help readers better appreciate the added scientific value of the framework.
2. CG advances.
The manuscript rightly emphasizes that building upon Mitsuba 3 enables Eradiate to benefit from advances originating in CG. However, the specific implications of these advances for atmospheric and EO applications could be further detailed. In CG, acceleration structures such as bounding volume hierarchies (BVH) have been central in managing geometric complexity efficiently, allowing traversal in approximately O(logN) time. For the EO community, this type of scalability is potentially transformative. It would therefore be valuable for the authors to elaborate on how these data structures concretely enable the simulation of highly resolved 3D scenes in EO contexts without incurring a prohibitive increase in computational cost. Even if large-scale demonstrations are beyond the scope of the present paper, a more explicit discussion of how CG advances are directly relevant to specific atmospheric science challenges (one of which is computational efficiency) would considerably strengthen the manuscript.
3. Performance benchmarking and convergence.
The validation against established benchmarks such as RAMI and IPRT is a strong point of the paper. To further reinforce the contribution, the manuscript could benefit from complementing these validation results with performance-oriented metrics. In particular, reporting convergence speed or computational time required to reach a given level of statistical uncertainty would provide valuable insight into the efficiency of the framework. Comparative elements with established atmospheric MCRT codes would help the community assess whether the modern architecture and CG-derived optimizations translate into tangible performance gains in realistic EO complex scenarios.
4. Differentiable rendering
An additional point that could enrich the manuscript concerns differentiable rendering, an increasingly active research direction within the CG community. Given that Eradiate is built on Mitsuba 3, which supports differentiable rendering capabilities, it would be worthwhile to discuss the potential integration of gradient-based radiance computations with respect to scene parameters. In the context of remote sensing, such capabilities could open promising perspectives for gradient-based inversion methods and sensitivity analysis. Even a forward-looking discussion of this aspect would highlight the long-term potential of the framework and further distinguish it from more traditional RT solvers.
Recommendations.
Eradiate v1.0.0 represents a sophisticated effort to modernize radiative transfer software for EO. The CG framework is technically impressive and well designed. To further enhance its impact and clarify its added value for the atmospheric and EO communities, the authors are encouraged to:
With these clarifications, the manuscript would provide an even clearer and more compelling case for the scientific contribution of Eradiate.