the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 24 May 2024
The impact of coupled 3D radiative transfer on surface radiation and cumulus clouds over land
Abstract. Radiative transfer is a 3D process, but most atmospheric models consider radiation only in the vertical direction for computational efficiency. This results in inaccurate surface radiation fields, as the horizontal transport of radiation is neglected. Previous work on 3D radiative effects mainly used 3D radiative transfer uncoupled from the flow solver. In contrast, our current work uses 3D radiative transfer coupled to the flow solver to study its impact on the development of clouds and the resulting impact on the domain-averaged surface solar irradiance. To this end, we performed a series of realistic Large-Eddy simulations with MicroHH. To improve the level of realism of our radiation, we first included the direct effect of aerosols using aerosol data from the CAMS global reanalysis. Next, we performed simulations with 1D radiative transfer and with a coupled ray tracer, for 12 days on which shallow cumulus clouds formed over Cabauw, the Netherlands. In general, simulations with the coupled ray tracer have a higher domain-averaged liquid water path, larger clouds, and similar cloud cover compared to simulations with 1D radiative transfer. Furthermore, the domain-averaged direct radiation is decreased with 3D radiative transfer and the diffuse radiation is increased. However, the average difference in global radiation is less than 1 W m-2, as the increase in global radiation from uncoupled 3D radiative transfer is counterbalanced by a decrease in global radiation caused by changes in cloud properties.
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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-1519', Anonymous Referee #1, 16 Jun 2024
- AC1: 'Reply on RC1', Mirjam Tijhuis, 25 Jul 2024
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RC2: 'Comment on egusphere-2024-1519', Anonymous Referee #2, 18 Jun 2024
Review of the manuscript “The impact of coupled 3D radiative transfer on surface radiation and cumulus clouds over land" by Tijhuis et al., 2024
In this manuscript, the authors study the effects of 3D atmospheric radiation transfer (RT) on the surface’s energy budget and cloud’s properties for cumulus cloud fields over land. They analyze a unique dataset of a dozen Large eddy simulations (LES) with online calculations of 3D RT in the solar spectrum. This is unique since all LES simulations use 1D RT to decrease computational load. Here the issue is solved by using GPU for enhanced calculations.
The novel dataset allows studying the effects of 3D radiation transfer on clouds’ dynamics and general properties like cloud cover, thickness and water density.
I think that the paper is suitable for publication in ACP, the analysis is complete and convincing, and the paper is clearly written. I believe that after a few clarifications the paper will be ready for submission, hence, I suggest a minor revision.
Major comments:
- L.88: Can the authors explain why they chose a skin heat capacity of zero for the interactive surface and how realistic it is? To a none expert in the matter, it sounds like this could cause quick and unrealistic warming of the surface that can highly influence shallow convection.
- L.161-166: This part of the paper is unclear. Please explain if aerosols affect the dynamics of the simulations. In short, how are the microphysical processes handled? Are aerosol radiative effects and horizontal variability coupled to in the simulations?
- L.180-187: Please explain how cloud cover is defined. This is a tricky definition that can make comparisons between different datasets complicated (especially models to observations). Since the 1D and 3D don’t show much difference, I suggest showing the sensitivity of 3D to different definitions or choices of thresholds.
- L.320: It is reasonable to assume that changes in cloud properties like cloud cover and optical thickness are most important for global surface radiation and scene albedo. The current version of Fig. 3 suggests that other processes influence cloud cover more than the radiative transfer scheme (RT). This raises the question of how important 3D effects are for surface or total energy budget.        Can the authors elaborate on this in the discussion and maybe even compare the bias caused by using 1D RT with other known biases and uncertainties in cloud or atmospheric modeling (like the choice of advection scheme, model resolution, microphysical scheme, etc.,)?
Minor comments:
- L.147: I suggest using different names for the decomposed effects. Uncoupled is quite confusing and at the start can also be interpreted by the reader as 3D-1Drad3D. I would suggest something like Radiative-only. The cloud effect  could be referred to as the 3D-coupling effect or dynamic effects.
- L.198: Can the authors please explain why they chose to use the characteristic length scale and what is its physical meaning? Why wasn’t a simpler measure of cloud size like mean size used?
- L.209: I wonder what are the effects of these findings on the scene albedo (top of the atmosphere upwelling fluxes). If cloud cover is the same but the clouds are thicker, does it mean a larger cloud radiative effect?
- L.224: Please explain what is the displacement distance. Does it change with the radiative transfer scheme? If LWP is higher then clouds might live longer and be more advected.
- L.241: Can the authors explain how the spread is quantified? Since the presentation is of only 3 cases, statistical measures are ambiguous, could be better to simply plot all three time series.
- L.149-255: It took me a minute to understand the discussion about the splitting methods. Might be clearer to mention the two methods by referring to Fig.1 or showing it mathematically (e.g., 3D-1Drad3D vs. 3Drad1D-1D). Â
- L.322-326: I think that the authors can show the role of 3D radiative transfer on Earth’s energy budget with not a lot of extra effort. What are the changes in atmospheric heating and top of the atmosphere fluxes? Does decreased diffused radiation on the surface means increased heating rates in the atmospheric or higher scene albedo at the top-of-the-atmosphere? Might be worth to have even a short discussion on this as well.
- L.336: Is there a reason to assume that the findings of this paper will be different away from the mid-latitudes? Dror et al., (IEEE, 2020) showed that a dominant subset of such clouds doesn’t have a strong latitudinal dependence.
Technical comments:
- L.17: In cloud and weather modeling communities Cloud resolving models are usually referred to course resolution models on a scale of 1 km.
- L.90: Worth mentioning that RRTM is 1D, and explain, even in short, the ray tracing concept and the novelty of the GPU usage (in Veerman et al., 2022 line 90).
- L.160: This is not very clear, does aerosol vertical profile change with time in simulations?
- 5: Adding y-axis labels as in Fig.6 would make the figure clearer.
- 6 captions: Which dataset is presented, worth mentioning it’s for all 12 days.
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Citation: https://doi.org/10.5194/egusphere-2024-1519-RC2 - AC2: 'Reply on RC2', Mirjam Tijhuis, 25 Jul 2024
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RC3: 'Comment on egusphere-2024-1519', Anonymous Referee #3, 24 Jun 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1519/egusphere-2024-1519-RC3-supplement.pdf
- AC3: 'Reply on RC3', Mirjam Tijhuis, 25 Jul 2024
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-1519', Anonymous Referee #1, 16 Jun 2024
- AC1: 'Reply on RC1', Mirjam Tijhuis, 25 Jul 2024
-
RC2: 'Comment on egusphere-2024-1519', Anonymous Referee #2, 18 Jun 2024
Review of the manuscript “The impact of coupled 3D radiative transfer on surface radiation and cumulus clouds over land" by Tijhuis et al., 2024
In this manuscript, the authors study the effects of 3D atmospheric radiation transfer (RT) on the surface’s energy budget and cloud’s properties for cumulus cloud fields over land. They analyze a unique dataset of a dozen Large eddy simulations (LES) with online calculations of 3D RT in the solar spectrum. This is unique since all LES simulations use 1D RT to decrease computational load. Here the issue is solved by using GPU for enhanced calculations.
The novel dataset allows studying the effects of 3D radiation transfer on clouds’ dynamics and general properties like cloud cover, thickness and water density.
I think that the paper is suitable for publication in ACP, the analysis is complete and convincing, and the paper is clearly written. I believe that after a few clarifications the paper will be ready for submission, hence, I suggest a minor revision.
Major comments:
- L.88: Can the authors explain why they chose a skin heat capacity of zero for the interactive surface and how realistic it is? To a none expert in the matter, it sounds like this could cause quick and unrealistic warming of the surface that can highly influence shallow convection.
- L.161-166: This part of the paper is unclear. Please explain if aerosols affect the dynamics of the simulations. In short, how are the microphysical processes handled? Are aerosol radiative effects and horizontal variability coupled to in the simulations?
- L.180-187: Please explain how cloud cover is defined. This is a tricky definition that can make comparisons between different datasets complicated (especially models to observations). Since the 1D and 3D don’t show much difference, I suggest showing the sensitivity of 3D to different definitions or choices of thresholds.
- L.320: It is reasonable to assume that changes in cloud properties like cloud cover and optical thickness are most important for global surface radiation and scene albedo. The current version of Fig. 3 suggests that other processes influence cloud cover more than the radiative transfer scheme (RT). This raises the question of how important 3D effects are for surface or total energy budget.        Can the authors elaborate on this in the discussion and maybe even compare the bias caused by using 1D RT with other known biases and uncertainties in cloud or atmospheric modeling (like the choice of advection scheme, model resolution, microphysical scheme, etc.,)?
Minor comments:
- L.147: I suggest using different names for the decomposed effects. Uncoupled is quite confusing and at the start can also be interpreted by the reader as 3D-1Drad3D. I would suggest something like Radiative-only. The cloud effect  could be referred to as the 3D-coupling effect or dynamic effects.
- L.198: Can the authors please explain why they chose to use the characteristic length scale and what is its physical meaning? Why wasn’t a simpler measure of cloud size like mean size used?
- L.209: I wonder what are the effects of these findings on the scene albedo (top of the atmosphere upwelling fluxes). If cloud cover is the same but the clouds are thicker, does it mean a larger cloud radiative effect?
- L.224: Please explain what is the displacement distance. Does it change with the radiative transfer scheme? If LWP is higher then clouds might live longer and be more advected.
- L.241: Can the authors explain how the spread is quantified? Since the presentation is of only 3 cases, statistical measures are ambiguous, could be better to simply plot all three time series.
- L.149-255: It took me a minute to understand the discussion about the splitting methods. Might be clearer to mention the two methods by referring to Fig.1 or showing it mathematically (e.g., 3D-1Drad3D vs. 3Drad1D-1D). Â
- L.322-326: I think that the authors can show the role of 3D radiative transfer on Earth’s energy budget with not a lot of extra effort. What are the changes in atmospheric heating and top of the atmosphere fluxes? Does decreased diffused radiation on the surface means increased heating rates in the atmospheric or higher scene albedo at the top-of-the-atmosphere? Might be worth to have even a short discussion on this as well.
- L.336: Is there a reason to assume that the findings of this paper will be different away from the mid-latitudes? Dror et al., (IEEE, 2020) showed that a dominant subset of such clouds doesn’t have a strong latitudinal dependence.
Technical comments:
- L.17: In cloud and weather modeling communities Cloud resolving models are usually referred to course resolution models on a scale of 1 km.
- L.90: Worth mentioning that RRTM is 1D, and explain, even in short, the ray tracing concept and the novelty of the GPU usage (in Veerman et al., 2022 line 90).
- L.160: This is not very clear, does aerosol vertical profile change with time in simulations?
- 5: Adding y-axis labels as in Fig.6 would make the figure clearer.
- 6 captions: Which dataset is presented, worth mentioning it’s for all 12 days.
Â
Citation: https://doi.org/10.5194/egusphere-2024-1519-RC2 - AC2: 'Reply on RC2', Mirjam Tijhuis, 25 Jul 2024
-
RC3: 'Comment on egusphere-2024-1519', Anonymous Referee #3, 24 Jun 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1519/egusphere-2024-1519-RC3-supplement.pdf
- AC3: 'Reply on RC3', Mirjam Tijhuis, 25 Jul 2024
Peer review completion
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Bart J. H. van Stratum
Chiel C. van Heerwaarden
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(1221 KB) - Metadata XML