the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A long-term dataset of simulated epilimnion and hypolimnion temperatures in 401 French lakes (1959–2020)
Najwa Sharaf
Jordi Prats
Nathalie Reynaud
Thierry Tormos
Tiphaine Peroux
Pierre-Alain Danis
Abstract. Understanding the thermal behavior of lakes is crucial for water quality management. Under climate change, lakes are warming and undergoing alterations in their thermal structure, including surface and deep-water temperatures. These changes require continuous monitoring due to the possible major ecological implications on water quality and lake processes. With the scarcity of long-term in situ water temperature datasets, we present a regional long-term water temperature dataset (LakeTSim: Lake Temperature Simulations) produced over 401 French lakes by combining numerical modelling and satellite thermal data. The dataset consists of daily epilimnion and hypolimnion temperatures for the period 1959–2020 simulated with the semi-empirical OKPLM (Ottosson-Kettle-Prats Lake Model). We also describe this model and its performance. We present the uncertainty analysis of simulations with default (parametrized with satellite thermal data over all lakes and in situ measurements) and calibrated (with in situ temperature measurements for each lake) model parameters as well as the sensitivity analysis of the latter. Overall, the 90 % confidence uncertainty range is largest for hypolimnion temperature simulations with a median of 8.5 ºC and 2.32 ºC respectively with default and calibrated parameter values. There is less uncertainty associated with epilimnion temperature simulations with a median of 5.42 ºC and 1.85 ºC before and after parameter calibration. This dataset will help provide insight into the thermal functioning of French lakes. It provides over six decades of epilimnion and hypolimnion temperature data, crucial for climate change studies at a regional scale. The dataset will also be of great advantage for decision making by stakeholders.
- Preprint
(1247 KB) - Metadata XML
- BibTeX
- EndNote
Najwa Sharaf et al.
Status: closed
-
RC1: 'Reviewer comments', Anonymous Referee #1, 11 Apr 2023
A long-term dataset of simulated epilimnion and hypolimnion temperatures in 401 lakes (1959-2020)
The manuscript presents a dataset of simulated lake water temperatures of 401 French lakes using a modelling approach. The modelling approach is well explained as well as the choices of how to calibrate (or not) the model parameters. I appreciate the fact that authors discuss the limitations of the dataset as well as the suitable applications, making clear for which purposes this dataset would be limiting.
I think that the presented dataset is relevant to leverage lake research in the context of climate change. The manuscript is overall well written but I suggest some modifications that I list in the attached pdf.
-
AC1: 'Reply on RC1', Najwa Sharaf, 14 Apr 2023
On behalf of my co-authors, I would like to thank the reviewer for taking the time to review our manuscript as well as for their comments and constructive feedback. All of their suggestions will be taken into account and the manuscript will be revised accordingly.
Best regards,
Najwa Sharaf on behalf of all co-authors
Citation: https://doi.org/10.5194/essd-2022-457-AC1
-
AC1: 'Reply on RC1', Najwa Sharaf, 14 Apr 2023
-
RC2: 'Comment on essd-2022-457', Anonymous Referee #2, 21 Apr 2023
In this study, Sharaf and co-authors present a regional long-term water temperature dataset (LakeTSim: Lake Temperature Simulations) for 401 French lakes by combining numerical modelling and satellite thermal data. The dataset consists of daily epilimnion and hypolimnion temperatures. Simulations have been carried out using the semi-empirical OKPLM model. The authors also describe the model and its performance (including uncertainty and sensitivity analysis). The manuscript is clear and well written. Concise and nice to read, but probably too concise in some parts (see below). I have two main comments relative to sections 4 and 6, which are reported below:
- Section 4: Please explain what do you mean by "default parameter values" in the case of air2water and Flake. As for the first model, I do not think that default parameters are available. Also, it is unclear if the comparison discussed at lines 233-244 is against OKPLM run with default parameters (to be fair) or not. At line 229 the authors refer to 409 lakes, but in Fig. 1 and relative text to 401 lakes. Why there are 8 lakes more in the first case? Was the forcing used to run OKPLM, air2water and Flake the same? At line 231 I understand that air2water and Flake were run only with SAFRAN. Why the comparison with air2water and Flake was not done considering the period 1959-2020?
- Section 6: the authors should explain how they performed the sensitivity analysis and provide details about CSS. This should be anticipated in section 3.4. In their sensitivity analysis, the authors combine model parameters and forcing uncertainty (at_factor, sw_factor, MAAT). This looks a bit unusual: at_factor, sw_factor, MAAT are not model parameters. The analysis of Figure 4 is qualitative and should be improved: for which parameters are relationships between CSS and depth statistically significant? Are there statistically significant relationships also with other morphometric/geografical variables? The same considerations on the need to improve the analysis apply to Figure 2.Minor comments:
L147 and L152: please, clarify what you mean by "an exponential smoothing function"
L155: please, provide information about the ALAMODE model.
L158-L163: please, provide the basic information to understand how the default "parameterization presented in Prats & Danis (2019)" has been derived. "The expression for epilimnion ..." and "the parameterization of hypolimnion ...": do the author mean "the values of the parameters"? Are expression and/or parametrization (i.e., equation) different compared to eq. 1-3?
L188-195: I would restructure the paragraph anticipating lines 192-195 before lines 189-192. The authors say that S2M was used for simulating the water temperature in lakes situated at altitudes higher than 900 m, but in table 1 I see that some lakes at higher elevations have been run with SAFRAN.
Figures 1 and 2: I found the colour map difficult to appreciate, especially in the case of reservoirs (crosses)
L201: I am not sure what "initial assessment of the quality of OKPLM simulations" has been described in the previous section.
Section 3.4: the authors did not specify what objective function has been used (RMSE, NSE, MAE, other?). Is the range 0-1 for D, E and beta motivated by any physical/mathematical reasoning, or could it be wider?
Table 2: in the caption the authors mention a tilde, but they use a circumflex accent.
L226: I think the authors should refer to https://hess.copernicus.org/articles/17/3323/2013/ for air2water.
Figure 3: please use capital letters for the parameters in the x-axis, as in the text. The font should be adjusted. mat should be modified into MAAT (also at line 265).Citation: https://doi.org/10.5194/essd-2022-457-RC2 -
AC2: 'Reply on RC2', Najwa Sharaf, 02 Jun 2023
On behalf of my co-authors, I would like to thank the reviewer for taking the time to review our manuscript and for their feedback. We have carefully considered the comments and suggestions provided by the reviewer and have addressed them in the attached document.
-
AC2: 'Reply on RC2', Najwa Sharaf, 02 Jun 2023
Status: closed
-
RC1: 'Reviewer comments', Anonymous Referee #1, 11 Apr 2023
A long-term dataset of simulated epilimnion and hypolimnion temperatures in 401 lakes (1959-2020)
The manuscript presents a dataset of simulated lake water temperatures of 401 French lakes using a modelling approach. The modelling approach is well explained as well as the choices of how to calibrate (or not) the model parameters. I appreciate the fact that authors discuss the limitations of the dataset as well as the suitable applications, making clear for which purposes this dataset would be limiting.
I think that the presented dataset is relevant to leverage lake research in the context of climate change. The manuscript is overall well written but I suggest some modifications that I list in the attached pdf.
-
AC1: 'Reply on RC1', Najwa Sharaf, 14 Apr 2023
On behalf of my co-authors, I would like to thank the reviewer for taking the time to review our manuscript as well as for their comments and constructive feedback. All of their suggestions will be taken into account and the manuscript will be revised accordingly.
Best regards,
Najwa Sharaf on behalf of all co-authors
Citation: https://doi.org/10.5194/essd-2022-457-AC1
-
AC1: 'Reply on RC1', Najwa Sharaf, 14 Apr 2023
-
RC2: 'Comment on essd-2022-457', Anonymous Referee #2, 21 Apr 2023
In this study, Sharaf and co-authors present a regional long-term water temperature dataset (LakeTSim: Lake Temperature Simulations) for 401 French lakes by combining numerical modelling and satellite thermal data. The dataset consists of daily epilimnion and hypolimnion temperatures. Simulations have been carried out using the semi-empirical OKPLM model. The authors also describe the model and its performance (including uncertainty and sensitivity analysis). The manuscript is clear and well written. Concise and nice to read, but probably too concise in some parts (see below). I have two main comments relative to sections 4 and 6, which are reported below:
- Section 4: Please explain what do you mean by "default parameter values" in the case of air2water and Flake. As for the first model, I do not think that default parameters are available. Also, it is unclear if the comparison discussed at lines 233-244 is against OKPLM run with default parameters (to be fair) or not. At line 229 the authors refer to 409 lakes, but in Fig. 1 and relative text to 401 lakes. Why there are 8 lakes more in the first case? Was the forcing used to run OKPLM, air2water and Flake the same? At line 231 I understand that air2water and Flake were run only with SAFRAN. Why the comparison with air2water and Flake was not done considering the period 1959-2020?
- Section 6: the authors should explain how they performed the sensitivity analysis and provide details about CSS. This should be anticipated in section 3.4. In their sensitivity analysis, the authors combine model parameters and forcing uncertainty (at_factor, sw_factor, MAAT). This looks a bit unusual: at_factor, sw_factor, MAAT are not model parameters. The analysis of Figure 4 is qualitative and should be improved: for which parameters are relationships between CSS and depth statistically significant? Are there statistically significant relationships also with other morphometric/geografical variables? The same considerations on the need to improve the analysis apply to Figure 2.Minor comments:
L147 and L152: please, clarify what you mean by "an exponential smoothing function"
L155: please, provide information about the ALAMODE model.
L158-L163: please, provide the basic information to understand how the default "parameterization presented in Prats & Danis (2019)" has been derived. "The expression for epilimnion ..." and "the parameterization of hypolimnion ...": do the author mean "the values of the parameters"? Are expression and/or parametrization (i.e., equation) different compared to eq. 1-3?
L188-195: I would restructure the paragraph anticipating lines 192-195 before lines 189-192. The authors say that S2M was used for simulating the water temperature in lakes situated at altitudes higher than 900 m, but in table 1 I see that some lakes at higher elevations have been run with SAFRAN.
Figures 1 and 2: I found the colour map difficult to appreciate, especially in the case of reservoirs (crosses)
L201: I am not sure what "initial assessment of the quality of OKPLM simulations" has been described in the previous section.
Section 3.4: the authors did not specify what objective function has been used (RMSE, NSE, MAE, other?). Is the range 0-1 for D, E and beta motivated by any physical/mathematical reasoning, or could it be wider?
Table 2: in the caption the authors mention a tilde, but they use a circumflex accent.
L226: I think the authors should refer to https://hess.copernicus.org/articles/17/3323/2013/ for air2water.
Figure 3: please use capital letters for the parameters in the x-axis, as in the text. The font should be adjusted. mat should be modified into MAAT (also at line 265).Citation: https://doi.org/10.5194/essd-2022-457-RC2 -
AC2: 'Reply on RC2', Najwa Sharaf, 02 Jun 2023
On behalf of my co-authors, I would like to thank the reviewer for taking the time to review our manuscript and for their feedback. We have carefully considered the comments and suggestions provided by the reviewer and have addressed them in the attached document.
-
AC2: 'Reply on RC2', Najwa Sharaf, 02 Jun 2023
Najwa Sharaf et al.
Model code and software
inrae/ALAMODE-okp: okplm v1.0.1 Jordi Prats-Rodríguez and Pierre-Alain Danis https://doi.org/10.5281/zenodo.7585615
Najwa Sharaf et al.
Viewed
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
488 | 116 | 26 | 630 | 13 | 17 |
- HTML: 488
- PDF: 116
- XML: 26
- Total: 630
- BibTeX: 13
- EndNote: 17
Viewed (geographical distribution)
Country | # | Views | % |
---|
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1