the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 15 Apr 2024
SLUCM+BEM (v1.0): A simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
Abstract. We propose a simple dynamic anthropogenic heat (QF) parameterisation for the Weather Research and Forecasting (WRF)-single-layer urban canopy model (SLUCM). The SLUCM is a remarkable physically based urban canopy model that is widely used worldwide. However, a limitation of SLUCM is that it considers a statistically based diurnal pattern of QF. Consequently, QF is not affected by outdoor temperature changes and the diurnal pattern of QF is constant throughout the simulation period. To address these limitations, based on the concept of a building energy model (BEM), which has been officially introduced in WRF, we propose a parameterisation to dynamically and simply simulate QF from buildings (QFB) through physically based calculation of the indoor heat load and input parameters for BEM and SLUCM. This method allows model users to simulate dynamic QF and electricity consumption (EC) according to factors such as outdoor temperature changes, building insulation, and heating and air conditioning (HAC) performance simply by setting the AHOPTION option in URBPRAM.TBL to 2. SLUCM+BEM was shown to simulate temporal variations of QFB and EC for HAC (ECHAC) and broadly reproduce the ECHAC estimates of more sophisticated BEM and ECHAC observations in the world’s largest metropolis, Tokyo. Our results demonstrate that SLUCM-BEM can be applied to urban climates worldwide.
Status: closed
-
RC1: 'Comment on egusphere-2024-681', Anonymous Referee #1, 02 Jul 2024
General comments
This paper by Takane et al. describes the model development efforts of adding a building energy model (BEM) into the single-layer urban canopy model (SLUCM) coupled with the Weather Research and Forecasting (WRF) model. I think it represents a significant advancement in WRF-SLUCM model development that will help expand the usage of WRF-SLUCM and make building energy-urban climate interaction studies more accessible for those with limited computational resources. However, I believe the following concerns need to be addressed before this paper can be published.
Specific comments
My major concern involves the apparent overestimation of HAC energy use as shown in Fig. 6 and Fig. 8, which is not clearly acknowledged, and the reason for this overestimation is insufficiently addressed. There are some key assumptions made in developing the simple BEM that may have affected the simulated HAC energy use, but their impacts are not discussed.
First, the impact of the neglected parameters (solar heat gain through windows, sensible heat gain through ventilation, and the latent heat load from dehumidification in summer) on the simulated HAC energy use was not addressed. While I agree with the author’s choice of not parameterizing these heat transfer processes based on the principle of keeping the model as simple as possible and to avoid the uncertainty introduced by not having good-quality data necessary to accurately parameterize these processes, I do think the effect of not including these factors should be acknowledged and analyzed.
Specifically, ignoring direct solar heat gain through windows should mean that the space heating in winter is likely overestimated and space cooling in summer underestimated (Sailor, 2011). Not considering ventilation should lead to an underestimation in both heat and cooling, whereas not considering dehumidification would also underestimate cooling energy consumption, especially for a city like Tokyo which has humid summers. The effects of these factors, when combined, compensate each other for heating energy use (i.e., the simulated heating energy use could be underestimated or overestimated as a result of ignoring these processes), but should lead to an underestimated cooling energy use. However, from Fig. 6, we see the SLUCM-BEM simulated EC_HAC in summer is almost universally higher than observations, i.e., SLUCM-BEM overestimates EC_HAC despite all the neglected factors which should actually lead to an underestimated EC_HAC. This suggests that the newly developed BEM likely has compensating factors that significantly overestimates summer EC_HAC, which leads to my second point of concern, as the reason for this overestimation is not sufficiently addressed in the discussion.
The authors discussed one possible cause of this overestimation which is that SLUCM-BEM does not consider weekday-weekend differences (L680 - 681). While this may explain the overestimation in the BC grids, it does not explain the overestimation in the residential districts. I would be interested to see the SLUCM-BEM results validated against the observation data for weekday only. If the overestimation is still there, it is an indication that other factors are at play.
I suspect another possible (perhaps more important) cause of this overestimation may be due to another assumption that SLUCM+BEM made: when computing H_in, SLUCM+BEM assumes constant interior wall and roof surface temperatures (TBLEND and TRLEND), which essentially functions as “HAC setpoints”, since a certain proportion of H_in will be removed/added during cooling/heating to maintain constant indoor surface temperatures. No indoor heat transfer processes (such as convection and radiation) are considered. This deviates from reality, as HAC setpoints dictate a constant indoor air temperature, rather than constant surface temperatures. More energy is required to keep indoor surfaces at the setpoints than to keep air temperature at the setpoints. This overestimation is also reflected in CLMU4 where a similar treatment of indoor temperature was employed (Oleson 2012; Oleson and Feddema, 2020). The authors should examine the implication of this assumption and, if at all possible, show the impact of this assumption on the simulated EC_HAC with simulations.
In summary, the key assumptions made in developing SLUCM+BEM model and their impacts should be thoroughly discussed so that future users are aware of these limitations when they interpret the results from the model.
Other comments/questions:
- The claim in the abstract, “Our results demonstrate that SLUCM-BEM can be applied to urban climates worldwide”, seems inadequately supported. The authors only simulated and presented results for Tokyo, which seems insufficient to claim the applicability of this model worldwide. I understand the authors might be saying that, because this simpler model requires fewer input parameters, it has better potential to be applied to cities globally than other more complicated models. If that is the case, the author should make it clear, as the current sentence might give readers the impression that SLUCM-BEM is ready to be applied globally, whereas in reality it stills requires collecting local data on many parameters (e.g., HSEQUIP_SCALE_FACTOR, HSEQUIP, AB_BUILD_RATIO, AC_FLOOR_RATIO) to be able to accurately simulate HAC energy use.
- The definition of anthropogenic heat is a bit unclear to me. From Eqs. 6 and 7, this included H_out, which partially comes from the conductive heat transfer through walls and roofs. This part of the energy is already in the climate systems, which is not “anthropogenic” by nature. Anthropogenic heat fluxes (AHF) datasets are also derived based on non-renewable primary energy consumption (e.g., Flanner, 2009; Varquez et al. 2021). The authors should clarify if they are using a definition different from those used in the AHF datasets to avoid confusion.
- It is intriguing to me that SLUCM+BEM (also CM-BEM in winter) is unable to reproduce the EC diurnal profile. Any thoughts on possible causes?
- In Fig. 10, the simulated EC-T sensitivities are presented. How do they compare with observations from Nakajima et al. 2022?
- In Fig. 11b, what is the reason for increased Qfb from not considering cooling towers? This is not because the Qfb,l is now released as Qfb,s, since Qfb = Qfb,l + Qfb,s, right?
Technical corrections/comments
- L35 – 36: I suggest the authors keep the abstract free of acronyms/jargons and avoid mentioning specifics like “by setting the AHOPTION option in URBPRAM.TBL to 2”, which would only make sense to WRF SLUCM users, whereas abstract should be written for a broader audience.
- Table 1: CLMU now has the capacity to consider partial AC in the form of AC adoption rate (Li et al., 2024).
- L108: missing “;” after “EC, electricity consumption”.
- L140: missing “)” after “Oleson and Feddema 2020”.
- L149: AHOPTION and its options have not been mentioned, which may make it confusing to readers. I suggest either keeping it more general without mentioning the name of this setting, or explicitly refer readers to section 2.1.
- L171: it seems AHOPTION = 0 represents Qf off. So it should be “… off or on by selecting 0 or 1 …, respectively”.
- Fig. 1: it is overall very difficult to follow due to the number of WRF-specific variables/settings used in this figure. I would suggest defining these variables in the caption, or replace them with actual names (like “wall temperature”) or mathematical symbols (something like T_wall) and define the symbols in the caption. Also, it should be made clear (either by mentioning in the caption or labeling it in the figure) that the box with the dashed line is the legend. Keeping only one of those legend boxes (the one in Figure 1c) is sufficient.
- L213 – 216: it might be better to reword this sentence so that each term is explained separately.
- L270 – 272: where is Qfb,s returned to?
- Table 2 is not very clear. I suggest formatting this table like the table in Fig. 12, so that it is clear on which rows these two models are sharing parameters. Also explain which set of TRLEND/TBLEND is for summer and which is for winter.
- L574: seems to be referencing Table 2 instead of Table 1.
- Fig. 11: for the maps, would it be better to present the differences in each case? E.g., instead of the current panel b map, present the difference between b map and a map (b minus a), and instead of panel c map, present c minus b, etc. This may make the effect more apparent. The diurnal profiles can be kept the same.
- L660 – 661: I think the focus of this sentence should be how SLUCM+BEM improves upon the “inadequate representation of building energy” in other single-layer UCMs, rather than emphasizing that SLUCM+BEM is the only single-layer UCM with a BEM that is coupled with WRF. This seems to downplay the importance of your work, as your model development efforts, although implemented in WRF, could be adapted and applied to other single-layer UCMs.
- L691 – 692: it is not accurate to say, “heat pumps are positioned as a renewable energy source”. Heat pumps by themselves are not a renewable energy source; rather, implementing heat pumps is a way to electrify buildings, which then can make use of renewable energy sources once we decarbonize our grid.
- L706: “skilfully” should be “skillfully”.
References:
Sailor, D. J. A review of methods for estimating anthropogenic heat and moisture emissions in the urban environment. International Journal of Climatology 31, 189–199 (2011).
Oleson, K. Contrasts between Urban and Rural Climate in CCSM4 CMIP5 Climate Change Scenarios. Journal of Climate 25, 1390–1412 (2012).
Oleson, K. W. & Feddema, J. Parameterization and Surface Data Improvements and New Capabilities for the Community Land Model Urban (CLMU). Journal of Advances in Modeling Earth Systems e2018MS001586 (2020) doi:10.1029/2018MS001586@10.1002/(ISSN)1942-2466.CESM2.
Flanner, M. G. Integrating anthropogenic heat flux with global climate models. Geophysical Research Letters 36, (2009).
Varquez, A. C. G., Kiyomoto, S., Khanh, D. N. & Kanda, M. Global 1-km present and future hourly anthropogenic heat flux. Scientific Data 8, 64 (2021).
Nakajima, K., Takane, Y., Fukuba, S., Yamaguchi, K. & Kikegawa, Y. Urban electricity–temperature relationships in the Tokyo Metropolitan Area. Energy and Buildings 256, 111729 (2022).
Li, X. et al. Enhancing Urban Climate-Energy Modeling in the Community Earth System Model (CESM) Through Explicit Representation of Urban Air-Conditioning Adoption. Journal of Advances in Modeling Earth Systems 16, e2023MS004107 (2024).
Citation: https://doi.org/10.5194/egusphere-2024-681-RC1 - AC1: 'Reply on RC1', Yuya Takane, 25 Sep 2024
-
RC2: 'Comment on egusphere-2024-681', Anonymous Referee #2, 05 Jul 2024
Summary
This well-motivated and well-written study will help to improve urban modeling using the SLUCM and have far-reaching impacts, especially since the SLUCM is the preferred UCM of WRF users. The methods and results are clear. I have some clarifying questions and a few small comments. Otherwise, the manuscript is ready for publication.
Major Comments
General: It is claimed in the abstract that the SLUCM-BEM can be applied to climates worldwide but was only simulated over Tokyo. The conclusion mentions future studies can do work of this nature, so right now it cannot be claimed that SLUCM+BEM can be used worldwide. Can an analysis be done for a distinctly different climate than Tokyo, but in a similar fashion? Some of the assumptions made may not be appropriate for different climates compared to Tokyo. How would the model work in more developing cities that may not have all the urban morphology data? The manuscript need not show all the same figures but perhaps a few highlighting similarities and differences. If it is too much for this manuscript, the worldwide claim should be removed from the abstract.
L19: AHOPTION and URBPRAM.TBL are jargon specific to urban modeling that a general audience will not have knowledge of. Suggest revising to define the terms first before mentioning.
L41-42: Doesn’t a third UCM option exist? The MLUCM/BEP on its own, i.e., not combined with the BEM. Why is that not mentioned?
L95: Describe AHOPTION and URBPRAM.TBL so that those not as familiar with urban modeling understand these terms. Additionally, describe what a change from AHOPTION from 1 to 2 means, i.e., what does 1 mean and what does 2 mean. This is later described in the Methods Section, but readers may be initially confused.
L214-216: Why were the full seasons not simulated, i.e., 01 June to 31 August and 01 December to 28 February? Additionally, why were these years chosen, and not a more recent season?
Section 3.2.1: Why were 05:00 and 14:00 LT analyzed? To capture minimum and maximum temperature?
General: How does runtime compare between SLUCM and SLUCM+BEM? Can this be added to the manuscript somewhere?
Minor Comments
L12: Remove “worldwide”. “Widely used” is sufficient, otherwise redundant.
Fig 10: Put summer and winter in different colors and add legend for the colors. Initially is confusing that there are two distinct groups for each plot until reading the caption.
Several figures should have the axes labels and legend text larger. These are Figures. 2, 3, 4, 5, 7, 9, and 11.
L413: Revise to “…and reaches…”.
Citation: https://doi.org/10.5194/egusphere-2024-681-RC2 - AC2: 'Reply on RC2', Yuya Takane, 25 Sep 2024
- AC3: 'Revision on egusphere-2024-681', Yuya Takane, 25 Sep 2024
- AC4: 'Comment on egusphere-2024-681', Yuya Takane, 25 Sep 2024
Status: closed
-
RC1: 'Comment on egusphere-2024-681', Anonymous Referee #1, 02 Jul 2024
General comments
This paper by Takane et al. describes the model development efforts of adding a building energy model (BEM) into the single-layer urban canopy model (SLUCM) coupled with the Weather Research and Forecasting (WRF) model. I think it represents a significant advancement in WRF-SLUCM model development that will help expand the usage of WRF-SLUCM and make building energy-urban climate interaction studies more accessible for those with limited computational resources. However, I believe the following concerns need to be addressed before this paper can be published.
Specific comments
My major concern involves the apparent overestimation of HAC energy use as shown in Fig. 6 and Fig. 8, which is not clearly acknowledged, and the reason for this overestimation is insufficiently addressed. There are some key assumptions made in developing the simple BEM that may have affected the simulated HAC energy use, but their impacts are not discussed.
First, the impact of the neglected parameters (solar heat gain through windows, sensible heat gain through ventilation, and the latent heat load from dehumidification in summer) on the simulated HAC energy use was not addressed. While I agree with the author’s choice of not parameterizing these heat transfer processes based on the principle of keeping the model as simple as possible and to avoid the uncertainty introduced by not having good-quality data necessary to accurately parameterize these processes, I do think the effect of not including these factors should be acknowledged and analyzed.
Specifically, ignoring direct solar heat gain through windows should mean that the space heating in winter is likely overestimated and space cooling in summer underestimated (Sailor, 2011). Not considering ventilation should lead to an underestimation in both heat and cooling, whereas not considering dehumidification would also underestimate cooling energy consumption, especially for a city like Tokyo which has humid summers. The effects of these factors, when combined, compensate each other for heating energy use (i.e., the simulated heating energy use could be underestimated or overestimated as a result of ignoring these processes), but should lead to an underestimated cooling energy use. However, from Fig. 6, we see the SLUCM-BEM simulated EC_HAC in summer is almost universally higher than observations, i.e., SLUCM-BEM overestimates EC_HAC despite all the neglected factors which should actually lead to an underestimated EC_HAC. This suggests that the newly developed BEM likely has compensating factors that significantly overestimates summer EC_HAC, which leads to my second point of concern, as the reason for this overestimation is not sufficiently addressed in the discussion.
The authors discussed one possible cause of this overestimation which is that SLUCM-BEM does not consider weekday-weekend differences (L680 - 681). While this may explain the overestimation in the BC grids, it does not explain the overestimation in the residential districts. I would be interested to see the SLUCM-BEM results validated against the observation data for weekday only. If the overestimation is still there, it is an indication that other factors are at play.
I suspect another possible (perhaps more important) cause of this overestimation may be due to another assumption that SLUCM+BEM made: when computing H_in, SLUCM+BEM assumes constant interior wall and roof surface temperatures (TBLEND and TRLEND), which essentially functions as “HAC setpoints”, since a certain proportion of H_in will be removed/added during cooling/heating to maintain constant indoor surface temperatures. No indoor heat transfer processes (such as convection and radiation) are considered. This deviates from reality, as HAC setpoints dictate a constant indoor air temperature, rather than constant surface temperatures. More energy is required to keep indoor surfaces at the setpoints than to keep air temperature at the setpoints. This overestimation is also reflected in CLMU4 where a similar treatment of indoor temperature was employed (Oleson 2012; Oleson and Feddema, 2020). The authors should examine the implication of this assumption and, if at all possible, show the impact of this assumption on the simulated EC_HAC with simulations.
In summary, the key assumptions made in developing SLUCM+BEM model and their impacts should be thoroughly discussed so that future users are aware of these limitations when they interpret the results from the model.
Other comments/questions:
- The claim in the abstract, “Our results demonstrate that SLUCM-BEM can be applied to urban climates worldwide”, seems inadequately supported. The authors only simulated and presented results for Tokyo, which seems insufficient to claim the applicability of this model worldwide. I understand the authors might be saying that, because this simpler model requires fewer input parameters, it has better potential to be applied to cities globally than other more complicated models. If that is the case, the author should make it clear, as the current sentence might give readers the impression that SLUCM-BEM is ready to be applied globally, whereas in reality it stills requires collecting local data on many parameters (e.g., HSEQUIP_SCALE_FACTOR, HSEQUIP, AB_BUILD_RATIO, AC_FLOOR_RATIO) to be able to accurately simulate HAC energy use.
- The definition of anthropogenic heat is a bit unclear to me. From Eqs. 6 and 7, this included H_out, which partially comes from the conductive heat transfer through walls and roofs. This part of the energy is already in the climate systems, which is not “anthropogenic” by nature. Anthropogenic heat fluxes (AHF) datasets are also derived based on non-renewable primary energy consumption (e.g., Flanner, 2009; Varquez et al. 2021). The authors should clarify if they are using a definition different from those used in the AHF datasets to avoid confusion.
- It is intriguing to me that SLUCM+BEM (also CM-BEM in winter) is unable to reproduce the EC diurnal profile. Any thoughts on possible causes?
- In Fig. 10, the simulated EC-T sensitivities are presented. How do they compare with observations from Nakajima et al. 2022?
- In Fig. 11b, what is the reason for increased Qfb from not considering cooling towers? This is not because the Qfb,l is now released as Qfb,s, since Qfb = Qfb,l + Qfb,s, right?
Technical corrections/comments
- L35 – 36: I suggest the authors keep the abstract free of acronyms/jargons and avoid mentioning specifics like “by setting the AHOPTION option in URBPRAM.TBL to 2”, which would only make sense to WRF SLUCM users, whereas abstract should be written for a broader audience.
- Table 1: CLMU now has the capacity to consider partial AC in the form of AC adoption rate (Li et al., 2024).
- L108: missing “;” after “EC, electricity consumption”.
- L140: missing “)” after “Oleson and Feddema 2020”.
- L149: AHOPTION and its options have not been mentioned, which may make it confusing to readers. I suggest either keeping it more general without mentioning the name of this setting, or explicitly refer readers to section 2.1.
- L171: it seems AHOPTION = 0 represents Qf off. So it should be “… off or on by selecting 0 or 1 …, respectively”.
- Fig. 1: it is overall very difficult to follow due to the number of WRF-specific variables/settings used in this figure. I would suggest defining these variables in the caption, or replace them with actual names (like “wall temperature”) or mathematical symbols (something like T_wall) and define the symbols in the caption. Also, it should be made clear (either by mentioning in the caption or labeling it in the figure) that the box with the dashed line is the legend. Keeping only one of those legend boxes (the one in Figure 1c) is sufficient.
- L213 – 216: it might be better to reword this sentence so that each term is explained separately.
- L270 – 272: where is Qfb,s returned to?
- Table 2 is not very clear. I suggest formatting this table like the table in Fig. 12, so that it is clear on which rows these two models are sharing parameters. Also explain which set of TRLEND/TBLEND is for summer and which is for winter.
- L574: seems to be referencing Table 2 instead of Table 1.
- Fig. 11: for the maps, would it be better to present the differences in each case? E.g., instead of the current panel b map, present the difference between b map and a map (b minus a), and instead of panel c map, present c minus b, etc. This may make the effect more apparent. The diurnal profiles can be kept the same.
- L660 – 661: I think the focus of this sentence should be how SLUCM+BEM improves upon the “inadequate representation of building energy” in other single-layer UCMs, rather than emphasizing that SLUCM+BEM is the only single-layer UCM with a BEM that is coupled with WRF. This seems to downplay the importance of your work, as your model development efforts, although implemented in WRF, could be adapted and applied to other single-layer UCMs.
- L691 – 692: it is not accurate to say, “heat pumps are positioned as a renewable energy source”. Heat pumps by themselves are not a renewable energy source; rather, implementing heat pumps is a way to electrify buildings, which then can make use of renewable energy sources once we decarbonize our grid.
- L706: “skilfully” should be “skillfully”.
References:
Sailor, D. J. A review of methods for estimating anthropogenic heat and moisture emissions in the urban environment. International Journal of Climatology 31, 189–199 (2011).
Oleson, K. Contrasts between Urban and Rural Climate in CCSM4 CMIP5 Climate Change Scenarios. Journal of Climate 25, 1390–1412 (2012).
Oleson, K. W. & Feddema, J. Parameterization and Surface Data Improvements and New Capabilities for the Community Land Model Urban (CLMU). Journal of Advances in Modeling Earth Systems e2018MS001586 (2020) doi:10.1029/2018MS001586@10.1002/(ISSN)1942-2466.CESM2.
Flanner, M. G. Integrating anthropogenic heat flux with global climate models. Geophysical Research Letters 36, (2009).
Varquez, A. C. G., Kiyomoto, S., Khanh, D. N. & Kanda, M. Global 1-km present and future hourly anthropogenic heat flux. Scientific Data 8, 64 (2021).
Nakajima, K., Takane, Y., Fukuba, S., Yamaguchi, K. & Kikegawa, Y. Urban electricity–temperature relationships in the Tokyo Metropolitan Area. Energy and Buildings 256, 111729 (2022).
Li, X. et al. Enhancing Urban Climate-Energy Modeling in the Community Earth System Model (CESM) Through Explicit Representation of Urban Air-Conditioning Adoption. Journal of Advances in Modeling Earth Systems 16, e2023MS004107 (2024).
Citation: https://doi.org/10.5194/egusphere-2024-681-RC1 - AC1: 'Reply on RC1', Yuya Takane, 25 Sep 2024
-
RC2: 'Comment on egusphere-2024-681', Anonymous Referee #2, 05 Jul 2024
Summary
This well-motivated and well-written study will help to improve urban modeling using the SLUCM and have far-reaching impacts, especially since the SLUCM is the preferred UCM of WRF users. The methods and results are clear. I have some clarifying questions and a few small comments. Otherwise, the manuscript is ready for publication.
Major Comments
General: It is claimed in the abstract that the SLUCM-BEM can be applied to climates worldwide but was only simulated over Tokyo. The conclusion mentions future studies can do work of this nature, so right now it cannot be claimed that SLUCM+BEM can be used worldwide. Can an analysis be done for a distinctly different climate than Tokyo, but in a similar fashion? Some of the assumptions made may not be appropriate for different climates compared to Tokyo. How would the model work in more developing cities that may not have all the urban morphology data? The manuscript need not show all the same figures but perhaps a few highlighting similarities and differences. If it is too much for this manuscript, the worldwide claim should be removed from the abstract.
L19: AHOPTION and URBPRAM.TBL are jargon specific to urban modeling that a general audience will not have knowledge of. Suggest revising to define the terms first before mentioning.
L41-42: Doesn’t a third UCM option exist? The MLUCM/BEP on its own, i.e., not combined with the BEM. Why is that not mentioned?
L95: Describe AHOPTION and URBPRAM.TBL so that those not as familiar with urban modeling understand these terms. Additionally, describe what a change from AHOPTION from 1 to 2 means, i.e., what does 1 mean and what does 2 mean. This is later described in the Methods Section, but readers may be initially confused.
L214-216: Why were the full seasons not simulated, i.e., 01 June to 31 August and 01 December to 28 February? Additionally, why were these years chosen, and not a more recent season?
Section 3.2.1: Why were 05:00 and 14:00 LT analyzed? To capture minimum and maximum temperature?
General: How does runtime compare between SLUCM and SLUCM+BEM? Can this be added to the manuscript somewhere?
Minor Comments
L12: Remove “worldwide”. “Widely used” is sufficient, otherwise redundant.
Fig 10: Put summer and winter in different colors and add legend for the colors. Initially is confusing that there are two distinct groups for each plot until reading the caption.
Several figures should have the axes labels and legend text larger. These are Figures. 2, 3, 4, 5, 7, 9, and 11.
L413: Revise to “…and reaches…”.
Citation: https://doi.org/10.5194/egusphere-2024-681-RC2 - AC2: 'Reply on RC2', Yuya Takane, 25 Sep 2024
- AC3: 'Revision on egusphere-2024-681', Yuya Takane, 25 Sep 2024
- AC4: 'Comment on egusphere-2024-681', Yuya Takane, 25 Sep 2024
Viewed
Since the preprint corresponding to this journal article was posted outside of Copernicus Publications, the preprint-related metrics are limited to HTML views.
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 286 | 0 | 0 | 286 | 0 | 0 |
- HTML: 286
- PDF: 0
- XML: 0
- Total: 286
- BibTeX: 0
- EndNote: 0
Viewed (geographical distribution)
Since the preprint corresponding to this journal article was posted outside of Copernicus Publications, the preprint-related metrics are limited to HTML views.
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1