the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 27 Jun 2024
Leveraging the satellite-based climate data record CLARA-A3 to understand trends and climate regimes relevant for solar energy applications over Europe
Abstract. Efficient transitioning to renewable energy requires fundamental understanding of the past and future climate change. This is particularly true in the case of solar energy since the surface incoming solar radiation (SIS) is regulated heavily by atmospheric essential climate variables (ECVs) such as aerosols and clouds, and by their long-term trends. Given the complexity of the interactions and feedbacks in the Earth system, even small changes in ECVs could have large direct and indirect effects on SIS. The net efficacy of the designed solar energy systems therefore depends on how well we account for the role of ECVs in modulating SIS at decadal scales. In this study, by leveraging the satellite-based climate data record CLARA-A3, we investigate the recent trends in SIS and cloud properties over Europe during the 1982–2020 period. Further, we derive emerging climate regimes that are relevant for solar energy applications. Results show a large-scale increase in SIS in spring and early summer over Europe, particularly noticeable in April and June. The corresponding trends in cloud fraction and cloud optical thickness, and their correlation with SIS suggest an increasingly important role of clouds in defining the favorable and unfavorable climate regimes for solar energy applications. We note also a strong spatio-temporal variability in trends and correlations. The results provide valuable metrics for the evaluation of climate models that have a dynamically integrated solar energy component.
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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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Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2024-1805', Anonymous Referee #1, 14 Dec 2024
General comments
The authors present a research on solar radiation conditions over Europe, based on EUMETSAT’s CMSAF CLARA-A3 satellite data record. Their analysis includes also influencing factors and trends, and they introduce a new concept called climate regimes, which may be helpful for a variety of applications including future planning of solar energy. Overall, the paper is interesting, well-written, and interesting for the readers of Egusphere.
In the abstract and elsewhere, the authors state the conclusion that their results suggest an increasingly important role of clouds for solar radiation conditions. I have difficulties understanding which part of the presented results would really show that this is true. From general knowledge about aerosol trends, climate change and so on, it would seem possible (or perhaps even plausible), but from the results presented in this paper, I do not see how they would confirm that clouds today are more strongly regulating solar radiation conditions than, for example, 20 years ago. I suggest revising and being careful about putting forward only such conclusions that are confirmed by the results of this paper.
I also have some hesitation to accept the term climate regimes, which as used here more or less can be understood to be the composite of trends in SIS, cloud fraction, and cloud optical depth. Somehow, I find it a bit contradicting to call a trend composite climate regime. For me, it would be more natural to call it climate trend regime or something similar. Maybe the authors have already given this a lot of thought, but I would anyhow careful consideration once more on what term to use.
I recommend minor revisions.
Specific comments and suggestions
- L21-22 (“Net efficacy…”): a bit difficult to understand, perhaps a bit sloppy sentence. How would that knowledge influence the net efficacy?
- L56: Hammer et al., 2023, in reference list there is only one Hammer et al., with the year 2003.
- L71-72: I believe correlation between clouds and SIS is something that has been studied before. There is probably a wealth of publications based on ground-based measurements. Also, there is one recent satellite-based study (Post and Aun, 2024; https://doi.org/10.1016/j.oceano.2023.11.004) that is of particular interest here, worthwhile including in the references and discussing in conjunction with the results of the present paper. Post and Aun look at changes in cloudiness and SIS and how they correlate, and, in addition, they also evaluate the trends in the light of atmospheric circulation patterns.
- Figure 1 (and other figures): I suggest adding a label and unit to the color bar, and a title to the plot, so that the figure is more easily accessible stand-alone
- L148 (and elsewhere as needed): Oxford Languages (online resource) explains that bias is “a systematic distortion of a statistical result“. This is also how I understand bias: it is a systematic feature, that is the aggregated result of individual errors in a set of data. Thus, it does not make sense in my mind to calculate the standard deviation of the bias, but the standard deviation should be calculated from the errors (or differences). Same goes for the root-mean-squared error.
- Figure 2 and L156: figure uses RMSD while text says root mean squared bias.
- L191-192: Here, as a reader, I would like to have a bit more explained about what these studies found, without having the read them. Post & Aun (2024) mentioned above is relevant also here.
- L221: shouldn’t water vapour column also be mentioned here?
- L222: Please provide a reference for this sentence
- L236: Check sentence
- L240-241: Which studies? Please provide references.
- L250 (and elsewhere throughout the paper): Definition of the term climate regime, as discussed already above.
- L262: check sentence (in-cloud?)
- L342: How does the temperature and the moisture influence solar energy systems? References?
- L352-354: Related to the comment above: How does increasing temperature help increase net performance of a solar energy system? It is known that for photovoltaics, increasing cell temperature decreases the relative efficiency of the system.
- L356: spelling of water vapour. Also, maybe it would be helpful for readers to clarify whether the effect of water vapour is included in the CLARA SIS product (I guess it is).
- L401: please provide references
Citation: https://doi.org/10.5194/egusphere-2024-1805-RC1 -
AC1: 'Reply on RC1', Abhay Devasthale, 17 Apr 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1805/egusphere-2024-1805-AC1-supplement.pdf
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RC2: 'Comment on egusphere-2024-1805', Anonymous Referee #2, 10 Mar 2025
In this manuscript, an innovative approach is presented to analyze the long-term trend of SSI. The proposed concept is based on the synthesis of trends of SSI, cloud cover, cloud optical depth and humidity into a single quantity called “climate regime”. The methodology is applied to satellite derived cloud properties and SSI from CLARA-A3 over Europe. The paper is very interesting, well-written and represents a very relevant contribution to readers of EGU sphere as well as the solar energy community to better quantify the effect of climate change on the solar resource.
I suggest the following minor revisions.
Line 173: “covering the 1982-2020 period » Please precise that according to recent works on SSI trends, a steady brightening is expected over this period.
The term “climate regimes” can be misleading in the context of the paper as it can lead to confusion with large-scale circulation regimes. I would suggest using a different term such as e.g. “multi-variable trend class”.
Since aerosol and water vapor are affecting SSI, it would be important to clearly explain how these are treated in the retrieval of the cloud property (atmospheric correction) in section 2.1.
In lines 219-220, the authors wrote “The shortwave solar radiation reaching the surface is regulated by a number of atmospheric components and their feedbacks in the backdrop of increasing greenhouse gases. Among them, the most important are clouds and aerosols,… ». The absorption by water vapor is very important for SSI calculation but it is not mentioned in this paragraph and not treated in section 4. In contrast, it is addressed in section 5. This is confusing and I think that reconsidering the organisation of these two sections would improve the flow of the text.
SSI trends are assessed but it is not clear from the text if a statistical significance test has been applied. (it is briefly mentioned in L174-175). More details on this aspect would be helpful.
Figure 5 and Figure 6 show the trend considering liquid and ice water COD respectively. It is unclear whether the dataset have been split or not for generating these two figures. This makes the maps not easy to interpret.
Citation: https://doi.org/10.5194/egusphere-2024-1805-RC2 -
AC2: 'Reply on RC2', Abhay Devasthale, 17 Apr 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1805/egusphere-2024-1805-AC2-supplement.pdf
-
AC2: 'Reply on RC2', Abhay Devasthale, 17 Apr 2025
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-1805', Anonymous Referee #1, 14 Dec 2024
General comments
The authors present a research on solar radiation conditions over Europe, based on EUMETSAT’s CMSAF CLARA-A3 satellite data record. Their analysis includes also influencing factors and trends, and they introduce a new concept called climate regimes, which may be helpful for a variety of applications including future planning of solar energy. Overall, the paper is interesting, well-written, and interesting for the readers of Egusphere.
In the abstract and elsewhere, the authors state the conclusion that their results suggest an increasingly important role of clouds for solar radiation conditions. I have difficulties understanding which part of the presented results would really show that this is true. From general knowledge about aerosol trends, climate change and so on, it would seem possible (or perhaps even plausible), but from the results presented in this paper, I do not see how they would confirm that clouds today are more strongly regulating solar radiation conditions than, for example, 20 years ago. I suggest revising and being careful about putting forward only such conclusions that are confirmed by the results of this paper.
I also have some hesitation to accept the term climate regimes, which as used here more or less can be understood to be the composite of trends in SIS, cloud fraction, and cloud optical depth. Somehow, I find it a bit contradicting to call a trend composite climate regime. For me, it would be more natural to call it climate trend regime or something similar. Maybe the authors have already given this a lot of thought, but I would anyhow careful consideration once more on what term to use.
I recommend minor revisions.
Specific comments and suggestions
- L21-22 (“Net efficacy…”): a bit difficult to understand, perhaps a bit sloppy sentence. How would that knowledge influence the net efficacy?
- L56: Hammer et al., 2023, in reference list there is only one Hammer et al., with the year 2003.
- L71-72: I believe correlation between clouds and SIS is something that has been studied before. There is probably a wealth of publications based on ground-based measurements. Also, there is one recent satellite-based study (Post and Aun, 2024; https://doi.org/10.1016/j.oceano.2023.11.004) that is of particular interest here, worthwhile including in the references and discussing in conjunction with the results of the present paper. Post and Aun look at changes in cloudiness and SIS and how they correlate, and, in addition, they also evaluate the trends in the light of atmospheric circulation patterns.
- Figure 1 (and other figures): I suggest adding a label and unit to the color bar, and a title to the plot, so that the figure is more easily accessible stand-alone
- L148 (and elsewhere as needed): Oxford Languages (online resource) explains that bias is “a systematic distortion of a statistical result“. This is also how I understand bias: it is a systematic feature, that is the aggregated result of individual errors in a set of data. Thus, it does not make sense in my mind to calculate the standard deviation of the bias, but the standard deviation should be calculated from the errors (or differences). Same goes for the root-mean-squared error.
- Figure 2 and L156: figure uses RMSD while text says root mean squared bias.
- L191-192: Here, as a reader, I would like to have a bit more explained about what these studies found, without having the read them. Post & Aun (2024) mentioned above is relevant also here.
- L221: shouldn’t water vapour column also be mentioned here?
- L222: Please provide a reference for this sentence
- L236: Check sentence
- L240-241: Which studies? Please provide references.
- L250 (and elsewhere throughout the paper): Definition of the term climate regime, as discussed already above.
- L262: check sentence (in-cloud?)
- L342: How does the temperature and the moisture influence solar energy systems? References?
- L352-354: Related to the comment above: How does increasing temperature help increase net performance of a solar energy system? It is known that for photovoltaics, increasing cell temperature decreases the relative efficiency of the system.
- L356: spelling of water vapour. Also, maybe it would be helpful for readers to clarify whether the effect of water vapour is included in the CLARA SIS product (I guess it is).
- L401: please provide references
Citation: https://doi.org/10.5194/egusphere-2024-1805-RC1 -
AC1: 'Reply on RC1', Abhay Devasthale, 17 Apr 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1805/egusphere-2024-1805-AC1-supplement.pdf
-
RC2: 'Comment on egusphere-2024-1805', Anonymous Referee #2, 10 Mar 2025
In this manuscript, an innovative approach is presented to analyze the long-term trend of SSI. The proposed concept is based on the synthesis of trends of SSI, cloud cover, cloud optical depth and humidity into a single quantity called “climate regime”. The methodology is applied to satellite derived cloud properties and SSI from CLARA-A3 over Europe. The paper is very interesting, well-written and represents a very relevant contribution to readers of EGU sphere as well as the solar energy community to better quantify the effect of climate change on the solar resource.
I suggest the following minor revisions.
Line 173: “covering the 1982-2020 period » Please precise that according to recent works on SSI trends, a steady brightening is expected over this period.
The term “climate regimes” can be misleading in the context of the paper as it can lead to confusion with large-scale circulation regimes. I would suggest using a different term such as e.g. “multi-variable trend class”.
Since aerosol and water vapor are affecting SSI, it would be important to clearly explain how these are treated in the retrieval of the cloud property (atmospheric correction) in section 2.1.
In lines 219-220, the authors wrote “The shortwave solar radiation reaching the surface is regulated by a number of atmospheric components and their feedbacks in the backdrop of increasing greenhouse gases. Among them, the most important are clouds and aerosols,… ». The absorption by water vapor is very important for SSI calculation but it is not mentioned in this paragraph and not treated in section 4. In contrast, it is addressed in section 5. This is confusing and I think that reconsidering the organisation of these two sections would improve the flow of the text.
SSI trends are assessed but it is not clear from the text if a statistical significance test has been applied. (it is briefly mentioned in L174-175). More details on this aspect would be helpful.
Figure 5 and Figure 6 show the trend considering liquid and ice water COD respectively. It is unclear whether the dataset have been split or not for generating these two figures. This makes the maps not easy to interpret.
Citation: https://doi.org/10.5194/egusphere-2024-1805-RC2 -
AC2: 'Reply on RC2', Abhay Devasthale, 17 Apr 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1805/egusphere-2024-1805-AC2-supplement.pdf
-
AC2: 'Reply on RC2', Abhay Devasthale, 17 Apr 2025
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Cited
Abhay Devasthale
Sandra Andersson
Erik Engström
Frank Kaspar
Jörg Trentmann
Anke Duguay-Tetzlaff
Jan Fokke Meirink
Erik Kjellström
Tomas Landelius
Manu Anna Thomas
Karl-Göran Karlsson
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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