the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
MONKI: a three-dimensional Monte Carlo simulator of total and polarised radiation reflected by planetary atmospheres
Abstract. Spectropolarimetry is a powerful tool for characterising planetary atmospheres and surfaces. For the design and operation of spectro(polari)metric instrumentation, numerically simulated signals of the measured radiation are essential. Here we present MONKI (Monte Carlo KNMI), an efficient and accurate radiative transfer code written in Fortran, based on the Monte Carlo method. MONKI computes both total and polarised radiances reflected and transmitted by a planetary atmosphere, fully accounting for the polarisation of light in all orders of scattering. MONKI can handle atmospheres that are horizontally homogeneous, as well as those with horizontal inhomogeneities, such as three-dimensional (3D) patchy clouds. We validate MONKI through comparisons with various other radiative transfer codes and demonstrate that it converges reliably even for optically thick and strongly polarising atmospheres. Finally, we present sample simulations of sunlight reflected by the Earth and Venus, and explain the total and polarised radiance features by analysing the altitudes at which the photons are scattered. We conclude that MONKI is a versatile and accurate tool, suitable for simulations and detailed analyses of locally reflected light by the Earth, Venus, and, in principle, any other planet.
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RC1: 'Comment on egusphere-2025-2197', Anonymous Referee #1, 03 Sep 2025
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First of all, I apologize to the authors and the editor(s) for the delay in producing this referee report.
The manuscript describes a new implementation of the Monte Carlo (MC) method to solve the vector radiative transfer equation. The manuscript confirms recent evidence that MC methods can combine both flexibility and accuracy. The first had long been clear, and indeed MC methods had been the usual choice for complex geometries. The second attribute, however, had been less obvious to the radiative transfer community. The current paper gives further evidence that MC methods are "exact" and, when properly implemented, can achieve arbitrary accuracies if one is willing to pay the cost of running sufficiently long simulations. In my opinion, this is the main point of the paper and I believe it's an important one.
The manuscript provides enough context to understand the implementation of the MC method, and demonstrates sufficiently its performance with comparisons against standard benchmark cases. This said, my main criticism of the manuscript, however, is that the implementation is based on "intuition", i.e. on tracking what happens to the simulated photons at each collision event. That makes it difficult to understand, for example, why neglecting the polarization state of the photon may lead to solutions that fail to convergence. In the same vein, it's difficult to understand why the implementation neglects variance reduction techniques. The integral formulation described in Garcia Munoz & Mills, 2015 (based on O'Brien, JQSRT, 1992) gives a more straightforward framework to tackle these issues.Â
The manuscript is very well written. References in the manuscript seem complete.
I didn't check, but the MC implementation appears to be publicly available, which will help further disseminate the ideas developed here.Â
I recommend the manuscript for publication, after addressing the following very minor comments.
Methods. It took me a while to figure out that the MC implementation is valid only for plane-parallel atmospheres, perhaps because the introduction mentions the application of polarimetry to disk-integrated observations. I suggest making it clear in the Introduction (#1) or Methods (#2) sections.Â
* line ~16. w.r.t. is not standard, I think.
* line ~20. "at the top of at the atmosphere". Language issue.
* Fig. 1. In my printout, angles theta' and phi' become corrupt. It may just be a problem with my pdf reader though. Further, it would help if you could show the actual geometry of the problem, with the cells in both the x and y directions. This would make it clearer that the current geometry is plane parallel.Â
* In Methods section, please state how V>0 is defined.Â
* line ~150. "w will become zero upon TOTAL absorption".
* line ~166. Having the code decide between scattering by a gas molecule or an aerosol particle (or different types of them, if different aerosol types coexist) is inefficient in a MC method. It would be notably faster if the optical (scattering, absorption) properties are properly averaged and assigned to "average" particles. Could the authors please comment on this?
* pg. 8. Footnote. Setting w=1e-16 to terminate a simulation seems unnecessarily stringent. My guess is that the calculation converges for w~1e-6. Could the authors please confirm this statement?
* pg. 9. Just wondering, how easy would it be to extend the surface treatment to non-Lambertian reflection?
* line ~261. "In the backward mode, every photon that is not completely absorbed contributes to the result, assuming that the light source is at an infinite distance." I was a bit puzzled to read this. My understanding is that the backward model works best when the observer has a narrow entry cone or, equivalently, when the observer is very far. For the backward implementation, it is no problem if the star subtends a finite solid angle.
* line ~324. Did the authors "switch off" the direction sampling based on the polarization state of the photon and, in that case, did they run into problems to converge the model? I feel curious to know the answer.
Citation: https://doi.org/10.5194/egusphere-2025-2197-RC1
Model code and software
MONKI (Monte Carlo KNMI) Victor Trees https://doi.org/10.5281/zenodo.15380811
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