the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 23 Apr 2024
How to observe the small-scale spatial distribution of surface solar irradiance, and how is it influenced by cumulus clouds?
Abstract. The amount of solar radiation reaching the Earth surface (SSI) is critical for a variety of applications, ranging from surface-atmosphere interactions to solar energy. SSI is characterized by a large spatiotemporal variability, in particular in the presence of broken clouds. This results in complex spatial patterns of shadows and sunlight directly related to clouds' geometry and physical properties. Although key in many respects, the instantaneous spatial distribution of SSI remains largely unexplored. Here, we use unique observations from a dense network of pyranometers deployed during the HOPE field campaign to investigate the SSI spatial distribution. For cumulus scenes, bimodal distributions are found, with one mode corresponding to cloud shadows and the other to sunlit areas with enhanced SSI exceeding clear-sky values. Combining large-eddy simulations of cumulus clouds with Monte Carlo ray tracing, we demonstrate the capability of advanced numerical tools to reproduce the observed distributions and quantify the impact of cloud geometrical and physical properties on both modes. In particular, cloud cover strongly modulates their amplitudes, in addition to their location and width, which are also sensitive to cloud height, geometrical depth, and liquid water content. Combining observations and simulations, we propose sampling strategies to estimate the instantaneous spatial distribution of SSI with a limited number of sensors, highlighting that 10 pyranometers integrated over 10 min can capture most details of the full distribution. Such a strategy could be used for future campaigns to further investigate SSI distributions and their impact on land-atmosphere exchanges or PV farm management.
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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
(14444 KB)
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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.
- Preprint
(14444 KB) - Metadata XML
- BibTeX
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- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2024-1064', Anonymous Referee #1, 15 May 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1064/egusphere-2024-1064-RC1-supplement.pdf
- AC1: 'Reply on RC1', zili he, 18 Jul 2024
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RC2: 'Comment on egusphere-2024-1064', Anonymous Referee #2, 07 Jun 2024
Main comments
- The paper contains many interesting insights in an interesting topic. The paper however could be much improved in its presentation, as it is at several points unclear in its goals (I will explain below), and also contains many interesting results in the figures and tables that are not explained in the text. Also, the observational strategy is not generic, as it only applied to cumulus, it would be nice of some deeper reflection on other cloud types is added to the paper.
- The paper is in fact a two part paper, first it explains ideas and theory on how to observe the detailed spatial distribution of surface solar irradiance, and in the second part details about radiation under cumulus fields are explained. It got a little bit confused while reading the second part, as I expected there that an elaborate study would be presented on how to optimally observe radiation under cumulus clouds, but instead it presented a (very nice) sensitivity study to how the distributions of SSI change with cloud properties. I would like to ask the authors to rethink the exact purpose of this paper and to give the paper a clear and well-defined purpose. In my view, the best would be to focus the entire paper on the measurement strategy of SSI and create a dedicated study on SSI distributions and cloud properties, or to see how this information can be used to optimize measurement strategy.
- Table 2 contains many interesting insights in the impact of cloud properties on surface radiation, but only very few results are mentioned in the text. Please reflect deeper on this Table and the figures in the section, there is much more to learn from it.
- Probably my biggest concern on the usefulness of the results of this paper is the absence of aerosols in the analysis and the radiation computations. As, for instance, Gristey has shown in his papers, aerosols largely change the probability distributions of SSI, and the direct/diffuse partitioning. If this paper is aiming for designing optimal measurement strategies, but at the same time performs computations on a situation that will not occur in reality, how applicable are the strategies then? I suggest the authors include at least some computations on aerosols to show the sensitivity.
Detailed comments
- Why did the authors select cumulus clouds to do this study? Are they most relevant, or most appealing?
- In my view, the selection procedure is unnecessarily complex. Why did the authors choose for such a detail level in selecting the case study?
- The exact resolutions of the LES and ray tracer computations are a little unclear. It is stated that the RT is ran using 5x5m2 squares, but the LES is much coarser, so why is this high resolution used?
- How are the photon paths distributed over the different spectral computations? There are 15000 per 5x5m2 pixel, but is this per quadrature point, per band, or in total?
Citation: https://doi.org/10.5194/egusphere-2024-1064-RC2 - AC2: 'Reply on RC2', zili he, 18 Jul 2024
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-1064', Anonymous Referee #1, 15 May 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1064/egusphere-2024-1064-RC1-supplement.pdf
- AC1: 'Reply on RC1', zili he, 18 Jul 2024
-
RC2: 'Comment on egusphere-2024-1064', Anonymous Referee #2, 07 Jun 2024
Main comments
- The paper contains many interesting insights in an interesting topic. The paper however could be much improved in its presentation, as it is at several points unclear in its goals (I will explain below), and also contains many interesting results in the figures and tables that are not explained in the text. Also, the observational strategy is not generic, as it only applied to cumulus, it would be nice of some deeper reflection on other cloud types is added to the paper.
- The paper is in fact a two part paper, first it explains ideas and theory on how to observe the detailed spatial distribution of surface solar irradiance, and in the second part details about radiation under cumulus fields are explained. It got a little bit confused while reading the second part, as I expected there that an elaborate study would be presented on how to optimally observe radiation under cumulus clouds, but instead it presented a (very nice) sensitivity study to how the distributions of SSI change with cloud properties. I would like to ask the authors to rethink the exact purpose of this paper and to give the paper a clear and well-defined purpose. In my view, the best would be to focus the entire paper on the measurement strategy of SSI and create a dedicated study on SSI distributions and cloud properties, or to see how this information can be used to optimize measurement strategy.
- Table 2 contains many interesting insights in the impact of cloud properties on surface radiation, but only very few results are mentioned in the text. Please reflect deeper on this Table and the figures in the section, there is much more to learn from it.
- Probably my biggest concern on the usefulness of the results of this paper is the absence of aerosols in the analysis and the radiation computations. As, for instance, Gristey has shown in his papers, aerosols largely change the probability distributions of SSI, and the direct/diffuse partitioning. If this paper is aiming for designing optimal measurement strategies, but at the same time performs computations on a situation that will not occur in reality, how applicable are the strategies then? I suggest the authors include at least some computations on aerosols to show the sensitivity.
Detailed comments
- Why did the authors select cumulus clouds to do this study? Are they most relevant, or most appealing?
- In my view, the selection procedure is unnecessarily complex. Why did the authors choose for such a detail level in selecting the case study?
- The exact resolutions of the LES and ray tracer computations are a little unclear. It is stated that the RT is ran using 5x5m2 squares, but the LES is much coarser, so why is this high resolution used?
- How are the photon paths distributed over the different spectral computations? There are 15000 per 5x5m2 pixel, but is this per quadrature point, per band, or in total?
Citation: https://doi.org/10.5194/egusphere-2024-1064-RC2 - AC2: 'Reply on RC2', zili he, 18 Jul 2024
Peer review completion
Journal article(s) based on this preprint
Data sets
How to observe the small-scale spatial distribution of surface solar irradiance, and how is it influenced by cumulus clouds? Zili He, Quentin Libois, Najda Villefranque, Hartwig Deneke, Jonas Witthuhn, and Fleur Couvreux https://doi.org/10.5281/zenodo.10948326
samd_dataset SAMD, Registry of Research Data Repositories https://doi.org/10.17616/R3D944
HD(CP)2 short term observations, sw broadband downwelling radiation (surface) data of Pyranometer network (no. 00), HOPE campaign by TROPOS, data version 00 Madhavan Bomidi https://www.cen.uni-hamburg.de/icdc/data/atmosphere/samd-st-datasets/samd-st-hope.html
Model code and software
htrdr version 0.8.1 meso-star https://www.meso-star.com/projects/htrdr/htrdr.html
Meso-NH, version 5.4.3 LAERO, CNRM http://mesonh.aero.obs-mip.fr/mesonh/dir_open/dir_MESONH/MNH-V5-4-3.tar.gz
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- 1
Zili He
Najda Villefranque
Hartwig Deneke
Jonas Witthuhn
Fleur Couvreux
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(14444 KB) - Metadata XML