the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 23 Nov 2022
A Comprehensive Dataset for Earth System Models in a Permafrost Region: Meteorological, Permafrost, and Carbon Observations (2011–2020) in Northeastern Qinghai-Tibet Plateau
Abstract. It’s important to understand the role of permafrost in the future climate and water resources management, for huge storage of soil organic carbon and ground ice in the permafrost. To date, large uncertainties still exist in permafrost simulations for many reasons. One reason is being a lack of long-term meteorological, permafrost and carbon observations. Here, we therefore present datasets for air temperatures, precipitation, soil temperature and moisture, active layer thickness, ground temperatures at different depths, soil organic carbon contents, and ecosystem carbon emission rates for the Qilian Mountains of the Northeastern Qinghai-Tibetan Plateau during 2011–2020. The data come from 5 automatic meteorological stations, 21 boreholes with depths from 11.5 to 149.3 m, and 12 active layer monitoring sites, which are used to obtain the hydrothermal and thermal states, and climate change in the study area. Soil organic carbon contents is available from 10 deep boreholes, down to a depth of 20 m. Ecosystem respiration rates are obtained from the prevalent vegetation types of alpine wet meadow, meadow, and steppe for the growing seasons. This decade’s high-quality datasets are expected to serve as useful inputs for earth system models, and are for researchers working in those disciplines including geophysics, ecology, and hydrology in alpine environments. The datasets are available from the National Tibetan Plateau/Third Pole Environment Data Center and can be downloaded from http://dx.doi.org/10.11888/Cryos.tpdc.272840 (Mu and Peng, 2022).
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RC1: 'Comment on essd-2022-347', Anonymous Referee #1, 25 Nov 2022
The paper submitted by Mu et al. describes a permafrost dataset compiled from measurements in NE Qinghai-Tibet Plateau. The dataset includes Meteorological, Permafrost, and Carbon data. Such datasets and associated analysis are valuable because they can be utilized for model calibration and validation and also to the ecohydrological process study. For these reasons, this database should be of interest to many aspects, e.g. environmental impact assessment, mechanism study etc. However the manuscript does require a number of revisions before it can be accepted for publication.
Since the paper is about the dataset description, it should be more focus on the dataset, not others. For example, the introduction and the Location description of this study seems so detail. It could show the significant of this study, and simple the introduction and the location.
For the field core sample, it seems that the soil samples are mostly used for the organic analysis. But it does not see a more detail description in the laboratory test.
In the Section 3, it provides a more description on each datasets. Meanwhile, it gives a more detail about the analysis. Because the paper is a datasets study, it should simple the analysis. So, the authors can relative simple the analysis in this section.
A number of specific comments are provided below. I hope the authors find the comments helpful in preparing an improved manuscript that should be acceptable for publication.
Specific Comments
L1, the title can be simpler, e.g. A Comprehensive Dataset in a Heihe River Basin Permafrost Region (2011–2020)
L40, it should give the specify study area, not the whole Qilian Mountain.
L135, This study focus on the Heihe River Basin, it should give the permafrost area in this study area.
L156-157, The vegetation types are not used in this study, it seems not useful here.
L189, in table 2, the monitoring depth seems not the same. The reasons are for what?
L191, delete the Comprehensive.
L208, about the figure 3, it should be give the detail information. E.g. who and where the photo is from?
L237, delete the - before cm in this sentence “30–40-cm-long drilled core”.
L238, delete the name of the laboratory.
L251 Figure 4 can be more detail for this photo.
L305 (PP systems, Amesbury, MA, USA), give the full name for the first time.
L461 seasonally frozen ground, permafrost, both could be as the frozen ground in this sentence.
Citation: https://doi.org/10.5194/essd-2022-347-RC1 -
RC2: 'Comment on essd-2022-347', Anonymous Referee #2, 14 Jan 2023
General comments
The authors present a comprehensive dataset for Earth system models in a permafrost region. The provided data are unique but there are some issues with the data quality
1. Poor Data Quality
I downloaded and explored the datasets. In general, the data quality present in this study appears to be very difficult to be reviewed or/and verified, and some seem incorrect.
Precipitation: The annual total precipitation at the PT1 site was 0 mm in 2020. Is that correct? Further, precipitation in winter is always 0 mm at the PT1 site and very minimal (0–2 mm) at the others. This means there is no snow at these sites, right? Could it be that the precipitation instrument is unable to measure solid precipitation?
Radiation: Upward long-wave radiation can be both negative and positive while downward long-wave radiation is always negative and short-wave radiation is always positive. How do you define a negative value for long-wave radiation? Direction? In fact, the absolute value of long-wave radiation was significantly smaller than at other sites on the Tibetan Plateau (see Figure 2 from Yang et al., 2006). The authors presented daily mean upward and downward radiation (Figure 5) but shared monthly mean. Further, the radiations in the "Meteorological data.xlsx" file seem to be the monthly net sum of short- and long-wave radiation, but the authors do not provide details in the "File "Description" file. As a result, it is very difficult for readers to follow the paper and verify the accuracy of the data.
Permafrost thickness: For sites that do not penetrate the entire layer of permafrost, it appears that the authors extrapolated borehole temperatures to simulate permafrost thickness. For example, the observed depth at the EboB site was 11.5 m (Table 1) but the estimated permafrost thickness was about 82 m (Table 8). I can understand that temperature extrapolation was widely used for permafrost thickness estimation (Wu et al., 2010). However, the method's suitability is based on the assumption that the ground temperature varies linearly with depth. Permafrost temperature at shallow depth was strongly affected by recent global warming and its gradient may not be suitable for permafrost thickness estimation. This would also be challenging for the other sites with shallow observation depth and thick permafrost. Unfortunately, this could not be evaluated as the permafrost temperature profile was not available. Would you mind explaining why only the MAGT at one depth was uploaded despite temperatures being measured at multiple depths (Table 2)?
2. Coarse temporal resolution
A major purpose of the datasets is to support ESM development in permafrost regions, based on the proposed title. However, the datasets shared were aggregated to monthly mean/sum, although the present data in the paper is daily mean (i.e., Figure 5). High temporal resolution is generally required for the development and evaluation of models with rich processes. As a result of the coarse temporal resolution, the unique datasets are not sufficient to be used as a benchmark for ESM-based permafrost simulations.
Specific comments
- P2, L54: permafrost region should be 21.8% or 22% based on Obu et al., 2019.
- P3, L76: Burke et al., 2020 reported the permafrost physics in state-of-the-art ESMs, please consider updating the reference.
- P3, L79–80: One significant drawback of the ESM or LSM is the shallow soil profile.
- P3, L84–85: Most permafrost-specific observation networks, i.e. GTN-P and CALM, do not have atmospheric observations, and hence could not be treated as sites for ESM/LSM-based permafrost simulation and evaluation. This is why the network authors present here are important.
- P5, L142: The MAAT presented here, i.e., 6–10°C, differs from the authors' results shown in Figure 6.
- P6, L159: Active layer observations in seasonally frozen ground? Are you sure?
- P21, L392: Is there a reason for the slight decrease in permafrost temperature at PT8?
Tables and Figures
Figure 1
Could you please give an overall picture of the observations, such as the types of measurements? For example, different colors/symbols for a, b, and c observation types in your Table 1?Figure 5
In d: air humidity could not be greater than 100%, please keep the y-lab between 0–100.
In f, "atmosphere pressure" or air pressure?Figure 8
How do you get the soil temperature greater than (the deepest observation was at 0.8 m in the figure) the measured depth, i.e., 0.77 m (see your table 4)Table 7
Please also add the changing rate of ALT here.References
Obu, J., Westermann, S., Bartsch, A., Berdnikov, N., Christiansen, H. H., Dashtseren, A., Delaloye, R., Elberling, B., Etzelmüller, B., Kholodov, A., Khomutov, A., Kääb, A., Leibman, M. O., Lewkowicz, A. G., Panda, S. K., Romanovsky, V., Way, R. G., Westergaard-Nielsen, A., Wu, T., … Zou, D. (2019). Northern Hemisphere permafrost map based on TTOP modelling for 2000–2016 at 1 km2 scale. Earth-Science Reviews, 193 (October 2018), 299–316. https://doi.org/10.1016/j.earscirev.2019.04.023
Burke, E. J., Zhang, Y., & Krinner, G. (2020). Evaluating permafrost physics in the Coupled Model Intercomparison Project 6 (CMIP6) models and their sensitivity to climate change. The Cryosphere, 14(9), 3155–3174. https://doi.org/10.5194/tc-14-3155-2020
Yang, K., Koike, T., Stackhouse, P., Mikovitz, C., and Cox, S. J. (2006), An assessment of satellite surface radiation products for highlands with Tibet instrumental data, Geophys. Res. Lett., 33, L22403, doi:10.1029/2006GL027640.
Wu, Q., Zhang, T., & Liu, Y. (2010). Permafrost temperatures and thickness on the Qinghai-Tibet Plateau. Global and Planetary Change, 72(1–2), 32–38. https://doi.org/10.1016/j.gloplacha.2010.03.001Citation: https://doi.org/10.5194/essd-2022-347-RC2 -
AC1: 'Comment on essd-2022-347', Xiaoqing Peng, 15 Mar 2023
Dear All,
The system of National Tibetan Plateau Data Center (TPDC) has been updated recently. So the new availability link of the dataset can be from https://data.tpdc.ac.cn/en/disallow/1f69f439-9539-45bb-88ce-016af7d748cf/ .
Thanks,
Xiaoqing Peng
Citation: https://doi.org/10.5194/essd-2022-347-AC1 -
RC3: 'Comment on essd-2022-347', Anonymous Referee #3, 21 Mar 2023
Cui et al present a detailed dataset from an understudied permafrost region that has utility in resolving spatial and temporal uncertainty in the QTP. The data presented are useful for synthesis activities but require additional detail before publishing. The manuscript would benefit from better organization of Sections 2 and 3 (Monitoring Network and Data Processing and Analysis). Broadly, the authors present the dataset for utility in Earth System Models, but the coarse temporal resolution presented are not appropriate for such.
Data
The data “read me” (file description) file needs units for all measurements. More details are needed on how data were synthesized and aggregated. Station information and file descriptions should be aggregated into one file. Formats for dates in the datasets need to be specified where missing. Significant figures should be standardized across datasets. NAs should be inserted where there are data gaps. For all datasets, the higher resolution data should be presented.
Active layer thickness: What is the temporal resolution for each of these yearly measurements? Were these averaged across the year? How often were measurements taken?
Soil temperature and moisture: The manuscript describes daily measurements, but the published data are monthly. The higher resolution data should be presented.
Meteorological data: The higher resolution (30 min) data should be presented and not daily averages. Atmospheric pressure should be relabeled as air pressure.
Soil carbon: If the number column here is referring to sample number, that can be removed.
Specific Comments
Lines 1-3: The title can be simplified and should reference the Heihe River basin.
Line 41: This should be “automated” rather than “automatic”.
Line 51: Dataset URL should be updated to https://data.tpdc.ac.cn/en/disallow/1f69f439-9539-45bb-88ce-016af7d748cf/.
Line 54: Obu et al. (2019) has the number at 22% of exposed land area is underlain by permafrost.
Lines 61-64: Citation needed.
Line 141: Specify that this is mean annual air temperature
Line 158: Should be “At these boreholes..”
Lines 161-163: Data sources for the DEM and permafrost extent layers?
Line 198: From Figure 3a, the net radiometer and precipitation gauge appear to be lower than 2 meter height.
Line 232: Here, you state that borehole depths are 20 m, but in line 172, you state that “The depths of the boreholes range from 11.5 to 149.3 m”. Please clarify.
Line 249: Clarification needed: ultimately, were there 3 replicates of NEE and Reco for each vegetation type at 10 sites?
Line 279: This should be Elementar, not Elemental.
Line 290: Standard denotation for ecosystem respiration is ER or Reco.
Line 394: How are you inferring permafrost thickness from ground temperatures? Do you mean to say depth of permafrost, rather than thickness? Or if this is temperature-extrapolated permafrost thickness, the assumption if linearity of temperature with depth, but this may not be appropriate for shallow depths.
Table 3: Wind velocity should be wind speed, and wind direction is missing from the table.
Citation: https://doi.org/10.5194/essd-2022-347-RC3 -
EC1: 'Editor Comment on essd-2022-347', James Thornton, 11 May 2023
Dear Authors,
Many thanks for your revised manuscript and associated responses to the reviewers' comments.
Since the reviewers identified some data (and metadata quality issues), I intend to send this revised version out again for further review.
However, some of your responses appear to be missing some important details, which I would like to clarify before proceeding.
For example, you write in relation to some of the data: "We check [sic] it once again for this time. And we deleted some incorrect data. Hopefully it is good now", and "About the upward long-wave radiation, we check it again, and found some errors, and revised it again".
I would appreciate it if you could provide further information regarding which specific data have been deleted, what proportion of the entire dataset they form, and the regard(s) in which they were deemed erroneous / incorrect.
I would also be grateful if you would confirm that the dataset now posted (https://data.tpdc.ac.cn/en/disallow/1f69f439-9539-45bb-88ce-016af7d748cf/) contains the full set of higher temporal resolution as requested by the reviewers.
Please make these clarifications in the form of a public comment as soon as possible. I will then hopefully be able to continue to advance the review process.
Best wishes,
James Thornton
Citation: https://doi.org/10.5194/essd-2022-347-EC1 -
AC2: 'Reply on EC1', Xiaoqing Peng, 12 May 2023
Response: Thanks for your great comments. It found that the precipitation instrument is the TE525MM, which can be only measured the rainfall. So, we deleted the solid precipitation for this measurement. Another is the upward long-wave radiation, we found that there is one error for the correction equation in the data logger program in the data logger collector, which has been confirmed with the instrument merchant engineer. So the upward long-wave radiation has been revised in this version. For the missing value, we also added the NaN value in this version.
For the temporal resolution, we have uploaded the daily resolution this time, which can be satisfied by the model simulations.
Citation: https://doi.org/10.5194/essd-2022-347-AC2
-
AC2: 'Reply on EC1', Xiaoqing Peng, 12 May 2023
Status: closed
-
RC1: 'Comment on essd-2022-347', Anonymous Referee #1, 25 Nov 2022
The paper submitted by Mu et al. describes a permafrost dataset compiled from measurements in NE Qinghai-Tibet Plateau. The dataset includes Meteorological, Permafrost, and Carbon data. Such datasets and associated analysis are valuable because they can be utilized for model calibration and validation and also to the ecohydrological process study. For these reasons, this database should be of interest to many aspects, e.g. environmental impact assessment, mechanism study etc. However the manuscript does require a number of revisions before it can be accepted for publication.
Since the paper is about the dataset description, it should be more focus on the dataset, not others. For example, the introduction and the Location description of this study seems so detail. It could show the significant of this study, and simple the introduction and the location.
For the field core sample, it seems that the soil samples are mostly used for the organic analysis. But it does not see a more detail description in the laboratory test.
In the Section 3, it provides a more description on each datasets. Meanwhile, it gives a more detail about the analysis. Because the paper is a datasets study, it should simple the analysis. So, the authors can relative simple the analysis in this section.
A number of specific comments are provided below. I hope the authors find the comments helpful in preparing an improved manuscript that should be acceptable for publication.
Specific Comments
L1, the title can be simpler, e.g. A Comprehensive Dataset in a Heihe River Basin Permafrost Region (2011–2020)
L40, it should give the specify study area, not the whole Qilian Mountain.
L135, This study focus on the Heihe River Basin, it should give the permafrost area in this study area.
L156-157, The vegetation types are not used in this study, it seems not useful here.
L189, in table 2, the monitoring depth seems not the same. The reasons are for what?
L191, delete the Comprehensive.
L208, about the figure 3, it should be give the detail information. E.g. who and where the photo is from?
L237, delete the - before cm in this sentence “30–40-cm-long drilled core”.
L238, delete the name of the laboratory.
L251 Figure 4 can be more detail for this photo.
L305 (PP systems, Amesbury, MA, USA), give the full name for the first time.
L461 seasonally frozen ground, permafrost, both could be as the frozen ground in this sentence.
Citation: https://doi.org/10.5194/essd-2022-347-RC1 -
RC2: 'Comment on essd-2022-347', Anonymous Referee #2, 14 Jan 2023
General comments
The authors present a comprehensive dataset for Earth system models in a permafrost region. The provided data are unique but there are some issues with the data quality
1. Poor Data Quality
I downloaded and explored the datasets. In general, the data quality present in this study appears to be very difficult to be reviewed or/and verified, and some seem incorrect.
Precipitation: The annual total precipitation at the PT1 site was 0 mm in 2020. Is that correct? Further, precipitation in winter is always 0 mm at the PT1 site and very minimal (0–2 mm) at the others. This means there is no snow at these sites, right? Could it be that the precipitation instrument is unable to measure solid precipitation?
Radiation: Upward long-wave radiation can be both negative and positive while downward long-wave radiation is always negative and short-wave radiation is always positive. How do you define a negative value for long-wave radiation? Direction? In fact, the absolute value of long-wave radiation was significantly smaller than at other sites on the Tibetan Plateau (see Figure 2 from Yang et al., 2006). The authors presented daily mean upward and downward radiation (Figure 5) but shared monthly mean. Further, the radiations in the "Meteorological data.xlsx" file seem to be the monthly net sum of short- and long-wave radiation, but the authors do not provide details in the "File "Description" file. As a result, it is very difficult for readers to follow the paper and verify the accuracy of the data.
Permafrost thickness: For sites that do not penetrate the entire layer of permafrost, it appears that the authors extrapolated borehole temperatures to simulate permafrost thickness. For example, the observed depth at the EboB site was 11.5 m (Table 1) but the estimated permafrost thickness was about 82 m (Table 8). I can understand that temperature extrapolation was widely used for permafrost thickness estimation (Wu et al., 2010). However, the method's suitability is based on the assumption that the ground temperature varies linearly with depth. Permafrost temperature at shallow depth was strongly affected by recent global warming and its gradient may not be suitable for permafrost thickness estimation. This would also be challenging for the other sites with shallow observation depth and thick permafrost. Unfortunately, this could not be evaluated as the permafrost temperature profile was not available. Would you mind explaining why only the MAGT at one depth was uploaded despite temperatures being measured at multiple depths (Table 2)?
2. Coarse temporal resolution
A major purpose of the datasets is to support ESM development in permafrost regions, based on the proposed title. However, the datasets shared were aggregated to monthly mean/sum, although the present data in the paper is daily mean (i.e., Figure 5). High temporal resolution is generally required for the development and evaluation of models with rich processes. As a result of the coarse temporal resolution, the unique datasets are not sufficient to be used as a benchmark for ESM-based permafrost simulations.
Specific comments
- P2, L54: permafrost region should be 21.8% or 22% based on Obu et al., 2019.
- P3, L76: Burke et al., 2020 reported the permafrost physics in state-of-the-art ESMs, please consider updating the reference.
- P3, L79–80: One significant drawback of the ESM or LSM is the shallow soil profile.
- P3, L84–85: Most permafrost-specific observation networks, i.e. GTN-P and CALM, do not have atmospheric observations, and hence could not be treated as sites for ESM/LSM-based permafrost simulation and evaluation. This is why the network authors present here are important.
- P5, L142: The MAAT presented here, i.e., 6–10°C, differs from the authors' results shown in Figure 6.
- P6, L159: Active layer observations in seasonally frozen ground? Are you sure?
- P21, L392: Is there a reason for the slight decrease in permafrost temperature at PT8?
Tables and Figures
Figure 1
Could you please give an overall picture of the observations, such as the types of measurements? For example, different colors/symbols for a, b, and c observation types in your Table 1?Figure 5
In d: air humidity could not be greater than 100%, please keep the y-lab between 0–100.
In f, "atmosphere pressure" or air pressure?Figure 8
How do you get the soil temperature greater than (the deepest observation was at 0.8 m in the figure) the measured depth, i.e., 0.77 m (see your table 4)Table 7
Please also add the changing rate of ALT here.References
Obu, J., Westermann, S., Bartsch, A., Berdnikov, N., Christiansen, H. H., Dashtseren, A., Delaloye, R., Elberling, B., Etzelmüller, B., Kholodov, A., Khomutov, A., Kääb, A., Leibman, M. O., Lewkowicz, A. G., Panda, S. K., Romanovsky, V., Way, R. G., Westergaard-Nielsen, A., Wu, T., … Zou, D. (2019). Northern Hemisphere permafrost map based on TTOP modelling for 2000–2016 at 1 km2 scale. Earth-Science Reviews, 193 (October 2018), 299–316. https://doi.org/10.1016/j.earscirev.2019.04.023
Burke, E. J., Zhang, Y., & Krinner, G. (2020). Evaluating permafrost physics in the Coupled Model Intercomparison Project 6 (CMIP6) models and their sensitivity to climate change. The Cryosphere, 14(9), 3155–3174. https://doi.org/10.5194/tc-14-3155-2020
Yang, K., Koike, T., Stackhouse, P., Mikovitz, C., and Cox, S. J. (2006), An assessment of satellite surface radiation products for highlands with Tibet instrumental data, Geophys. Res. Lett., 33, L22403, doi:10.1029/2006GL027640.
Wu, Q., Zhang, T., & Liu, Y. (2010). Permafrost temperatures and thickness on the Qinghai-Tibet Plateau. Global and Planetary Change, 72(1–2), 32–38. https://doi.org/10.1016/j.gloplacha.2010.03.001Citation: https://doi.org/10.5194/essd-2022-347-RC2 -
AC1: 'Comment on essd-2022-347', Xiaoqing Peng, 15 Mar 2023
Dear All,
The system of National Tibetan Plateau Data Center (TPDC) has been updated recently. So the new availability link of the dataset can be from https://data.tpdc.ac.cn/en/disallow/1f69f439-9539-45bb-88ce-016af7d748cf/ .
Thanks,
Xiaoqing Peng
Citation: https://doi.org/10.5194/essd-2022-347-AC1 -
RC3: 'Comment on essd-2022-347', Anonymous Referee #3, 21 Mar 2023
Cui et al present a detailed dataset from an understudied permafrost region that has utility in resolving spatial and temporal uncertainty in the QTP. The data presented are useful for synthesis activities but require additional detail before publishing. The manuscript would benefit from better organization of Sections 2 and 3 (Monitoring Network and Data Processing and Analysis). Broadly, the authors present the dataset for utility in Earth System Models, but the coarse temporal resolution presented are not appropriate for such.
Data
The data “read me” (file description) file needs units for all measurements. More details are needed on how data were synthesized and aggregated. Station information and file descriptions should be aggregated into one file. Formats for dates in the datasets need to be specified where missing. Significant figures should be standardized across datasets. NAs should be inserted where there are data gaps. For all datasets, the higher resolution data should be presented.
Active layer thickness: What is the temporal resolution for each of these yearly measurements? Were these averaged across the year? How often were measurements taken?
Soil temperature and moisture: The manuscript describes daily measurements, but the published data are monthly. The higher resolution data should be presented.
Meteorological data: The higher resolution (30 min) data should be presented and not daily averages. Atmospheric pressure should be relabeled as air pressure.
Soil carbon: If the number column here is referring to sample number, that can be removed.
Specific Comments
Lines 1-3: The title can be simplified and should reference the Heihe River basin.
Line 41: This should be “automated” rather than “automatic”.
Line 51: Dataset URL should be updated to https://data.tpdc.ac.cn/en/disallow/1f69f439-9539-45bb-88ce-016af7d748cf/.
Line 54: Obu et al. (2019) has the number at 22% of exposed land area is underlain by permafrost.
Lines 61-64: Citation needed.
Line 141: Specify that this is mean annual air temperature
Line 158: Should be “At these boreholes..”
Lines 161-163: Data sources for the DEM and permafrost extent layers?
Line 198: From Figure 3a, the net radiometer and precipitation gauge appear to be lower than 2 meter height.
Line 232: Here, you state that borehole depths are 20 m, but in line 172, you state that “The depths of the boreholes range from 11.5 to 149.3 m”. Please clarify.
Line 249: Clarification needed: ultimately, were there 3 replicates of NEE and Reco for each vegetation type at 10 sites?
Line 279: This should be Elementar, not Elemental.
Line 290: Standard denotation for ecosystem respiration is ER or Reco.
Line 394: How are you inferring permafrost thickness from ground temperatures? Do you mean to say depth of permafrost, rather than thickness? Or if this is temperature-extrapolated permafrost thickness, the assumption if linearity of temperature with depth, but this may not be appropriate for shallow depths.
Table 3: Wind velocity should be wind speed, and wind direction is missing from the table.
Citation: https://doi.org/10.5194/essd-2022-347-RC3 -
EC1: 'Editor Comment on essd-2022-347', James Thornton, 11 May 2023
Dear Authors,
Many thanks for your revised manuscript and associated responses to the reviewers' comments.
Since the reviewers identified some data (and metadata quality issues), I intend to send this revised version out again for further review.
However, some of your responses appear to be missing some important details, which I would like to clarify before proceeding.
For example, you write in relation to some of the data: "We check [sic] it once again for this time. And we deleted some incorrect data. Hopefully it is good now", and "About the upward long-wave radiation, we check it again, and found some errors, and revised it again".
I would appreciate it if you could provide further information regarding which specific data have been deleted, what proportion of the entire dataset they form, and the regard(s) in which they were deemed erroneous / incorrect.
I would also be grateful if you would confirm that the dataset now posted (https://data.tpdc.ac.cn/en/disallow/1f69f439-9539-45bb-88ce-016af7d748cf/) contains the full set of higher temporal resolution as requested by the reviewers.
Please make these clarifications in the form of a public comment as soon as possible. I will then hopefully be able to continue to advance the review process.
Best wishes,
James Thornton
Citation: https://doi.org/10.5194/essd-2022-347-EC1 -
AC2: 'Reply on EC1', Xiaoqing Peng, 12 May 2023
Response: Thanks for your great comments. It found that the precipitation instrument is the TE525MM, which can be only measured the rainfall. So, we deleted the solid precipitation for this measurement. Another is the upward long-wave radiation, we found that there is one error for the correction equation in the data logger program in the data logger collector, which has been confirmed with the instrument merchant engineer. So the upward long-wave radiation has been revised in this version. For the missing value, we also added the NaN value in this version.
For the temporal resolution, we have uploaded the daily resolution this time, which can be satisfied by the model simulations.
Citation: https://doi.org/10.5194/essd-2022-347-AC2
-
AC2: 'Reply on EC1', Xiaoqing Peng, 12 May 2023
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