the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 11 Apr 2022
Assessing the performance of various fire weather indices for wildfire occurrence in Northern Switzerland
Abstract. Fire weather indices are widely used to understand and assess meteorological fire hazard. However, in complex regions such as Switzerland with mountainous and hilly terrain, it is difficult to select an appropriate index. In this study, we validate the performance of 14 fire weather indices, four meteorological variables, and a logistic regression model to predict wildfire occurrence for different ecoregions in the canton of Bern in Northern Switzerland with respect to historical fire records from 1981 to 2020. We find that the performance of the indices varies seasonally and regionally. The spring season (March–May) shows that the Canadian Fine Fuel Moisture Content and other indices that respond readily to weather changes perform best. In summer (June–August) and autumn (September–November), the Canadian Buildup Index and Drought Code – indices that describe persistent hot and dry conditions – perform best. Overall, seasonal differences in performance are larger than inter-regional differences. Finally, we show that a logistic regression model trained on local historical fire activity can outperform existing fire weather indices and can be used for medium-range weather forecasting or climate change studies, using only daily averages of meteorological variables as input.
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RC1: 'Comment on egusphere-2022-92', Anonymous Referee #1, 27 Jul 2022
In short, this manuscript has too many problems/flaws to be accepted. This manuscript is characterized by:
(a) insufficient data and an inadequate methodology;
(b) have very little scientific significance, do not represent a substantial contribution to the understanding of natural hazards and their consequences, without new significant concepts, ideas, methods or data;
(c) be very confusing, with unclear, unnecessary sentences and even wrong statements;
To explain this assessment, please consider the following:
(i) the title does not adequately describe the study performed; on the one hand, the authors do more than evaluate fire meteorological indices (FWI), as they compare the FWIs among themselves, with meteorological variables and logistic models; on the other hand, they only do so in three specific locations in the Bern Canton; this is the only contribution of this study, but raises several questions;
(ii) One of these questions is how can it be said that a study is carried out for the entire northern region of Switzerland (which is a subjective definition) when, in fact, a study is carried out in the canton of Bern, i.e., in only a sub-region of northern Switzerland?
(iii) Another question, and perhaps the most important, is how it can be said that a study is carried out for an entire region of northern Switzerland that the authors characterize as having a complex and diverse landscape, with mountainous and hilly terrain, using data from only 3 locations?
(iv) For the authors to be able to state that their results are valid for the northern region of Switzerland, or rather, for the 3 ecoregions of the northern region, they have to demonstrate that the information collected in only 3 meteorological stations (one weather station in each ecoregion) is sufficient to characterize the climate variability associated with the enormous landscape diversity (e.g., topography, vegetation), which the authors recognize characterize each of the regions;
(v) The decision to use data from only three stations is strange because the authors recognize the difficulty (or impossibility) of carrying out this study under these conditions (e.g., “…single weather station observations cannot capture the spatial heterogeneity within a complex topography…”, line 141; “…weather stations are not necessarily located near the fire site and therefore don’t have the same micro climate. This is especially true for the complex and diverse landscape of Switzerland with its steep topography and mixed forest types, and also due to local wind systems and localized convective precipitation during summers that may or may not hit a weather station. In addition, weather stations are located in open areas and may not present fuel moisture in forests”, lines 366-370); the problem is not necessarily the use of only data from weather stations, which provide precious local meteorological information, but the small number of stations used in the study and the non-complementarity with other existing databases;
(vi) apparently, the authors confuse fundamental concepts; for example, is this study about fires or wildfires? The authors seem to consider that danger is equal to hazard or risk; the concepts are related, but they are not (definitely) the same; some examples are:
- …” Fire weather indices are widely used to understand and assess meteorological fire hazard”…, (Line 1)
- ..." provide a measure of the daily fire danger, i.e., the risk of fire occurrence"..., (line 14);
- sometimes (lines 334-337) “a fire danger rating system consisting of multiple, seasonally and regionally varying indices could be implemented for real-time prediction using meteorological forecasts, which is also proposed by Reineking et al. (2010) for the southern Canton Ticino. This could improve the risk assessment …”; or, the same approach can be used “to improve fire hazard prediction in the study area” (lines 390-392).
(vii) The authors opted for methodological approaches that they have to explain because they do not seem to be the most appropriate. The authors aim to “estimate”/relate the fire occurrences/number of fire days with FWIs and meteorological variables. However, as the authors know and can check (https://cwfis.cfs.nrcan.gc.ca/background/summary/fwi), the “The Canadian Forest Fire Weather Index (FWI) System consists of six components that account for the effects of fuel moisture and weather conditions on fire behaviour”; It is obvious that suitable weather and fuel humidity conditions for fire behaviour are also suitable for ignition, but the indices used by the authors were not developed to assess the impact of weather conditions and fuel humidity on the number of fires. The authors also recognize this, as they state “Because fire weather indices are based solely on meteorological information, they cannot provide perfect prediction of fire occurrence, but rather measure antecedent conditions (Andela et al., 2017). Furthermore, they are based on empirically derived correlations between weather and fire for specific climatic and vegetation conditions. This means that the transferability of the indices to other regions and under changing climatic conditions is limited” (lines 33-37); in addition, the authors state (lines 28-35, 193) and show (e.g., figure 2) that: (a) natural wildfires (caused by weather conditions/lightning strikes) are only a tiny fraction of all wildfires; (b) the vast majority of the wildfires are caused by humans; (c) “Fires with an unknown ignition source are probably human-caused”, and (d) (consequently) “Other non-meteorological factors that we have not considered here play a critical role in fire occurrence, particularly human activities to ignite but also to prevent fires”. This means that if the authors intend to use the FWIs as factors/parameters/predictors of the number of fires, must start to model the number of fires/fire days as a function of the FWIs; it is not sufficient to present “percentile score during fire days… percentile score during fire days” (Figure 3) or “Time series of yearly number of recorded fire days… extreme index days … and extreme logit days” (Figure 4), because much unrelated time series present similar variability.
(viii) the authors state that “Because fire weather indices are based solely on meteorological information, they cannot provide perfect prediction of fire occurrence, but rather measure antecedent conditions (Andela et al., 2017). Furthermore, they are based on empirically derived correlations between weather and fire for specific climatic and vegetation conditions. This means that the transferability of the indices to other regions and under changing climatic conditions is limited (Weibel et al., 2010; Reineking et al., 2010; Krawchuk and Moritz, 2011), and their application outside the "area of origin" requires careful evaluation and adaptation (Weibel, 2009; Wotton et al., 2009; Padilla et al., 2011; de Jong et al., 2016; Bekar et al., 2020).” So, my obvious question is: did you adapt the FWIs to the characteristics of the study region before trying to assess their performance or relate them to the fire incidence? Can the author assess or compare FWIs without prior adaptation/calibration?
(ix) the authors often use “significant” and “significantly” to describe your results. What is the relationship between these adjectives and statistical significance? Which tests did you use to assess the statistical significance? What is the statistical significance of your results?
(x) Language is often confusing and incorrect. Some examples are the following:
- “However, in complex regions such as Switzerland with mountainous and hilly terrain, it is difficult to select an appropriate index.”, (lines 1-2); “It is difficult to find an appropriate fire weather index, especially for regions with complex and diverse terrain”, (line 41). Why is it so difficult? is it not enough to make a performance and comparative analysis? Where does the difficulty lie? The authors provide an answer to this question, but they did not carry out this study in the way they claim to be appropriate;
- “Fire weather indices are commonly used by fire management agencies to asses and predict weather conditions that are most conducive to wildfire” (lines 13-14); it is obvious that it is not the FWIs that can predict the weather, but the atmospheric models;
- ”Because it is a linear model using only daily means as input”…, (line 134); if I understand correctly, one “input” is the “WeekRain” which is not a daily mean;
- The authors state (and repeat the idea) that “… statistical models trained on local fire statistics indirectly incorporate non-meteorological factors while still using only meteorological information as input”; as stated, this is not true. If this was true, why do you state that “Other non-meteorological factors that we have not considered here play a critical role in fire occurrence, particularly human activities to ignite but also to prevent fires. A first step in overcoming these limitations is to combine fire weather indices with non-meteorological factors such as forest composition, topography, and human activities”?
- The authors did not develop models of the fire days based on the FWI, meteorological variables or logit; however, in section 3.4, they use concepts of underestimation and overestimation!
- “how fire behaviour changes from spring to summer due to the soil layers”, what does this mean? What properties of the soil layers?
- Lines 306-308, what situation? Summer, dry periods or convective precipitation?
- Lines 324-329: the used dataset includes foehn winds?
- The authors should avoid using subjective concepts, such as large, small, and slight, especially without providing some figures to clarify;
(xi) Although accepting the results presented as sufficient to justify a publication, the discussion of results is poor, especially considering the current knowledge on the subjects covered in the manuscript, which is not conveniently mentioned in the main text of the manuscript and portrayed in the reference list.
Given the serious problems existing at this stage of the study/manuscript, suggestions/comments on more specific issues and minor flaws will not be presented.
Citation: https://doi.org/10.5194/egusphere-2022-92-RC1 -
AC1: 'Response to all reviewers', Daniel Steinfeld, 01 Sep 2022
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-92/egusphere-2022-92-AC1-supplement.pdf
-
RC2: 'Comment on egusphere-2022-92', Anonymous Referee #2, 28 Jul 2022
Although the results of the article are interesting for some people, I do not think that the results and discussion appeal to a wide audience and more importantly contribute anything new to the understanding of natural hazards. The ideas and applied methods in the article are not innovative. Moreover, I don't think the article is writtten and structured properly. Therefore, I suggest a rejection for the submission.
1) Fire hazard is not the same as fire danger. I believe fire hazard is more related to fuel than fire weather. In the context of fire weather indices, it is more appropriate to use fire danger. I suggest removing the fire hazard term from the paper unless what you are talking is mean fire hazard.
2) In the title and throughout the paper, you use the term Northern Switzerland; however, your study area only consists of Canton of Bern. Please use Bern instead of NS.
3) Line 27 - please add a reference.
4) Line 28 - please do not start the sentence with more than one reference. Instead, you can use phrases like “number of studies have identified.” Place the references at the end of the sentence.
5) Line 39 - Comma is needed after “In this paper”
6) Line 48 - Comma is needed after “e.g., distance to infrastructure.”
7) Line 60 - The sentence that starts with “This increase is consistent with …” is too long. Please split it into two sentences.
8) Line 72 - I do not think the sentence that starts with “The study is conducted under the Wyss Academy …” is necessary for the introduction. Maybe place it in the acknowledgments.
9) Line 83 - Fire Database is not a special name. Please change it to database with lower case d.
10) Line 104 - Change “we use here” to “Here, we use”
10) I do not understand why you needed MODIS data for this study. On the one hand, you state that fire records are mostly complete and on the other hand you use MODIS data to complete your fire records. Moreover, what exactly you did with the MODIS data is not fully clear. For instance, Is the Swiss plateau the same as your study region plateau? If you are concerned about missing data in your fire database, you are only fixing half of your problem. You use MODIS data for 2003-2020; however, your time period is 1980-2020. Isn’t this creating a problem in your database?
11) Line 115 - Same with comment 9. Please use fire weather indices with lower case letters.
12) Validation metric methodology (Line 144-160) is not clear to me. I had to visit Arpaci 2013 in order to understand the method. However, in their paper, they say the perfect index has an intercept of 100, and in your paper, you state that it is 1. Is this difference related to Theil–Sen method? If so, it needs to be explained more clearly. Moreover, you only have two sentences (Line 151-154) that explain the percentile method, and one of them cites a figure from a different paper. A reader should be able to understand the methodology without needing another paper. Please include more details and explain the methodology better.
13) Line 152 - please consider using “categorize days” instead of “divide days”
14) Line 175 - + 2 K? What does K mean here? Kelvin?
15) Results section starts with an explanatory analysis of the whole database, which includes the data you are not interested. Is this really needed? Please consider removing that part (Line 170-178).
16) Line 207 - you define “perform well” performance above 0.6. Is this metric similar to AUC (0.5 as random)? If so, I would not call performance above 0.6 as well. Maybe moderate? Please add a reference to the methodology that shows how this performance is evaluated.
17) Line 211 - Change “Neserov” to “Nesterov”
18) Line 214 - Unnecessary space in the parenthesis -> ( score
19) Line 225 - Please fix spaces in the parentheses
20) Line 222 - Change “Neserov” to “Nesterov”
21) Line 228 - no space after comma -> Again,Sharples
22) Figure 4 has lines that reach out of the plot borders. I don’t think this is a good figure. You probably aimed to have better visibility of the lines by leaving that parts out. However, please, at least, add info about where the lines reach their max. Maybe add a text above those lines?
23) Line 294 - performed overall well is not a good choice of words. Performed well overall or overall, performed well?
24) Line 314 - “M68dwd requires a snow layer as input, which we did not provide.” You should state this kind of information in the methodology.
25) Line 339 - change basin to basis.
26) Line 339 and 340 - please rephrase this sentence and also remove the focus of the next study part. -> (simulate future changes to fire based on future climate projection (the focus of a next study).
27) Line 385 - Is there a test and p-value here? If not, please do not use the term significant.Citation: https://doi.org/10.5194/egusphere-2022-92-RC2 -
AC2: 'Response to all reviewers', Daniel Steinfeld, 01 Sep 2022
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-92/egusphere-2022-92-AC2-supplement.pdf
-
AC2: 'Response to all reviewers', Daniel Steinfeld, 01 Sep 2022
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2022-92', Anonymous Referee #1, 27 Jul 2022
In short, this manuscript has too many problems/flaws to be accepted. This manuscript is characterized by:
(a) insufficient data and an inadequate methodology;
(b) have very little scientific significance, do not represent a substantial contribution to the understanding of natural hazards and their consequences, without new significant concepts, ideas, methods or data;
(c) be very confusing, with unclear, unnecessary sentences and even wrong statements;
To explain this assessment, please consider the following:
(i) the title does not adequately describe the study performed; on the one hand, the authors do more than evaluate fire meteorological indices (FWI), as they compare the FWIs among themselves, with meteorological variables and logistic models; on the other hand, they only do so in three specific locations in the Bern Canton; this is the only contribution of this study, but raises several questions;
(ii) One of these questions is how can it be said that a study is carried out for the entire northern region of Switzerland (which is a subjective definition) when, in fact, a study is carried out in the canton of Bern, i.e., in only a sub-region of northern Switzerland?
(iii) Another question, and perhaps the most important, is how it can be said that a study is carried out for an entire region of northern Switzerland that the authors characterize as having a complex and diverse landscape, with mountainous and hilly terrain, using data from only 3 locations?
(iv) For the authors to be able to state that their results are valid for the northern region of Switzerland, or rather, for the 3 ecoregions of the northern region, they have to demonstrate that the information collected in only 3 meteorological stations (one weather station in each ecoregion) is sufficient to characterize the climate variability associated with the enormous landscape diversity (e.g., topography, vegetation), which the authors recognize characterize each of the regions;
(v) The decision to use data from only three stations is strange because the authors recognize the difficulty (or impossibility) of carrying out this study under these conditions (e.g., “…single weather station observations cannot capture the spatial heterogeneity within a complex topography…”, line 141; “…weather stations are not necessarily located near the fire site and therefore don’t have the same micro climate. This is especially true for the complex and diverse landscape of Switzerland with its steep topography and mixed forest types, and also due to local wind systems and localized convective precipitation during summers that may or may not hit a weather station. In addition, weather stations are located in open areas and may not present fuel moisture in forests”, lines 366-370); the problem is not necessarily the use of only data from weather stations, which provide precious local meteorological information, but the small number of stations used in the study and the non-complementarity with other existing databases;
(vi) apparently, the authors confuse fundamental concepts; for example, is this study about fires or wildfires? The authors seem to consider that danger is equal to hazard or risk; the concepts are related, but they are not (definitely) the same; some examples are:
- …” Fire weather indices are widely used to understand and assess meteorological fire hazard”…, (Line 1)
- ..." provide a measure of the daily fire danger, i.e., the risk of fire occurrence"..., (line 14);
- sometimes (lines 334-337) “a fire danger rating system consisting of multiple, seasonally and regionally varying indices could be implemented for real-time prediction using meteorological forecasts, which is also proposed by Reineking et al. (2010) for the southern Canton Ticino. This could improve the risk assessment …”; or, the same approach can be used “to improve fire hazard prediction in the study area” (lines 390-392).
(vii) The authors opted for methodological approaches that they have to explain because they do not seem to be the most appropriate. The authors aim to “estimate”/relate the fire occurrences/number of fire days with FWIs and meteorological variables. However, as the authors know and can check (https://cwfis.cfs.nrcan.gc.ca/background/summary/fwi), the “The Canadian Forest Fire Weather Index (FWI) System consists of six components that account for the effects of fuel moisture and weather conditions on fire behaviour”; It is obvious that suitable weather and fuel humidity conditions for fire behaviour are also suitable for ignition, but the indices used by the authors were not developed to assess the impact of weather conditions and fuel humidity on the number of fires. The authors also recognize this, as they state “Because fire weather indices are based solely on meteorological information, they cannot provide perfect prediction of fire occurrence, but rather measure antecedent conditions (Andela et al., 2017). Furthermore, they are based on empirically derived correlations between weather and fire for specific climatic and vegetation conditions. This means that the transferability of the indices to other regions and under changing climatic conditions is limited” (lines 33-37); in addition, the authors state (lines 28-35, 193) and show (e.g., figure 2) that: (a) natural wildfires (caused by weather conditions/lightning strikes) are only a tiny fraction of all wildfires; (b) the vast majority of the wildfires are caused by humans; (c) “Fires with an unknown ignition source are probably human-caused”, and (d) (consequently) “Other non-meteorological factors that we have not considered here play a critical role in fire occurrence, particularly human activities to ignite but also to prevent fires”. This means that if the authors intend to use the FWIs as factors/parameters/predictors of the number of fires, must start to model the number of fires/fire days as a function of the FWIs; it is not sufficient to present “percentile score during fire days… percentile score during fire days” (Figure 3) or “Time series of yearly number of recorded fire days… extreme index days … and extreme logit days” (Figure 4), because much unrelated time series present similar variability.
(viii) the authors state that “Because fire weather indices are based solely on meteorological information, they cannot provide perfect prediction of fire occurrence, but rather measure antecedent conditions (Andela et al., 2017). Furthermore, they are based on empirically derived correlations between weather and fire for specific climatic and vegetation conditions. This means that the transferability of the indices to other regions and under changing climatic conditions is limited (Weibel et al., 2010; Reineking et al., 2010; Krawchuk and Moritz, 2011), and their application outside the "area of origin" requires careful evaluation and adaptation (Weibel, 2009; Wotton et al., 2009; Padilla et al., 2011; de Jong et al., 2016; Bekar et al., 2020).” So, my obvious question is: did you adapt the FWIs to the characteristics of the study region before trying to assess their performance or relate them to the fire incidence? Can the author assess or compare FWIs without prior adaptation/calibration?
(ix) the authors often use “significant” and “significantly” to describe your results. What is the relationship between these adjectives and statistical significance? Which tests did you use to assess the statistical significance? What is the statistical significance of your results?
(x) Language is often confusing and incorrect. Some examples are the following:
- “However, in complex regions such as Switzerland with mountainous and hilly terrain, it is difficult to select an appropriate index.”, (lines 1-2); “It is difficult to find an appropriate fire weather index, especially for regions with complex and diverse terrain”, (line 41). Why is it so difficult? is it not enough to make a performance and comparative analysis? Where does the difficulty lie? The authors provide an answer to this question, but they did not carry out this study in the way they claim to be appropriate;
- “Fire weather indices are commonly used by fire management agencies to asses and predict weather conditions that are most conducive to wildfire” (lines 13-14); it is obvious that it is not the FWIs that can predict the weather, but the atmospheric models;
- ”Because it is a linear model using only daily means as input”…, (line 134); if I understand correctly, one “input” is the “WeekRain” which is not a daily mean;
- The authors state (and repeat the idea) that “… statistical models trained on local fire statistics indirectly incorporate non-meteorological factors while still using only meteorological information as input”; as stated, this is not true. If this was true, why do you state that “Other non-meteorological factors that we have not considered here play a critical role in fire occurrence, particularly human activities to ignite but also to prevent fires. A first step in overcoming these limitations is to combine fire weather indices with non-meteorological factors such as forest composition, topography, and human activities”?
- The authors did not develop models of the fire days based on the FWI, meteorological variables or logit; however, in section 3.4, they use concepts of underestimation and overestimation!
- “how fire behaviour changes from spring to summer due to the soil layers”, what does this mean? What properties of the soil layers?
- Lines 306-308, what situation? Summer, dry periods or convective precipitation?
- Lines 324-329: the used dataset includes foehn winds?
- The authors should avoid using subjective concepts, such as large, small, and slight, especially without providing some figures to clarify;
(xi) Although accepting the results presented as sufficient to justify a publication, the discussion of results is poor, especially considering the current knowledge on the subjects covered in the manuscript, which is not conveniently mentioned in the main text of the manuscript and portrayed in the reference list.
Given the serious problems existing at this stage of the study/manuscript, suggestions/comments on more specific issues and minor flaws will not be presented.
Citation: https://doi.org/10.5194/egusphere-2022-92-RC1 -
AC1: 'Response to all reviewers', Daniel Steinfeld, 01 Sep 2022
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-92/egusphere-2022-92-AC1-supplement.pdf
-
RC2: 'Comment on egusphere-2022-92', Anonymous Referee #2, 28 Jul 2022
Although the results of the article are interesting for some people, I do not think that the results and discussion appeal to a wide audience and more importantly contribute anything new to the understanding of natural hazards. The ideas and applied methods in the article are not innovative. Moreover, I don't think the article is writtten and structured properly. Therefore, I suggest a rejection for the submission.
1) Fire hazard is not the same as fire danger. I believe fire hazard is more related to fuel than fire weather. In the context of fire weather indices, it is more appropriate to use fire danger. I suggest removing the fire hazard term from the paper unless what you are talking is mean fire hazard.
2) In the title and throughout the paper, you use the term Northern Switzerland; however, your study area only consists of Canton of Bern. Please use Bern instead of NS.
3) Line 27 - please add a reference.
4) Line 28 - please do not start the sentence with more than one reference. Instead, you can use phrases like “number of studies have identified.” Place the references at the end of the sentence.
5) Line 39 - Comma is needed after “In this paper”
6) Line 48 - Comma is needed after “e.g., distance to infrastructure.”
7) Line 60 - The sentence that starts with “This increase is consistent with …” is too long. Please split it into two sentences.
8) Line 72 - I do not think the sentence that starts with “The study is conducted under the Wyss Academy …” is necessary for the introduction. Maybe place it in the acknowledgments.
9) Line 83 - Fire Database is not a special name. Please change it to database with lower case d.
10) Line 104 - Change “we use here” to “Here, we use”
10) I do not understand why you needed MODIS data for this study. On the one hand, you state that fire records are mostly complete and on the other hand you use MODIS data to complete your fire records. Moreover, what exactly you did with the MODIS data is not fully clear. For instance, Is the Swiss plateau the same as your study region plateau? If you are concerned about missing data in your fire database, you are only fixing half of your problem. You use MODIS data for 2003-2020; however, your time period is 1980-2020. Isn’t this creating a problem in your database?
11) Line 115 - Same with comment 9. Please use fire weather indices with lower case letters.
12) Validation metric methodology (Line 144-160) is not clear to me. I had to visit Arpaci 2013 in order to understand the method. However, in their paper, they say the perfect index has an intercept of 100, and in your paper, you state that it is 1. Is this difference related to Theil–Sen method? If so, it needs to be explained more clearly. Moreover, you only have two sentences (Line 151-154) that explain the percentile method, and one of them cites a figure from a different paper. A reader should be able to understand the methodology without needing another paper. Please include more details and explain the methodology better.
13) Line 152 - please consider using “categorize days” instead of “divide days”
14) Line 175 - + 2 K? What does K mean here? Kelvin?
15) Results section starts with an explanatory analysis of the whole database, which includes the data you are not interested. Is this really needed? Please consider removing that part (Line 170-178).
16) Line 207 - you define “perform well” performance above 0.6. Is this metric similar to AUC (0.5 as random)? If so, I would not call performance above 0.6 as well. Maybe moderate? Please add a reference to the methodology that shows how this performance is evaluated.
17) Line 211 - Change “Neserov” to “Nesterov”
18) Line 214 - Unnecessary space in the parenthesis -> ( score
19) Line 225 - Please fix spaces in the parentheses
20) Line 222 - Change “Neserov” to “Nesterov”
21) Line 228 - no space after comma -> Again,Sharples
22) Figure 4 has lines that reach out of the plot borders. I don’t think this is a good figure. You probably aimed to have better visibility of the lines by leaving that parts out. However, please, at least, add info about where the lines reach their max. Maybe add a text above those lines?
23) Line 294 - performed overall well is not a good choice of words. Performed well overall or overall, performed well?
24) Line 314 - “M68dwd requires a snow layer as input, which we did not provide.” You should state this kind of information in the methodology.
25) Line 339 - change basin to basis.
26) Line 339 and 340 - please rephrase this sentence and also remove the focus of the next study part. -> (simulate future changes to fire based on future climate projection (the focus of a next study).
27) Line 385 - Is there a test and p-value here? If not, please do not use the term significant.Citation: https://doi.org/10.5194/egusphere-2022-92-RC2 -
AC2: 'Response to all reviewers', Daniel Steinfeld, 01 Sep 2022
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-92/egusphere-2022-92-AC2-supplement.pdf
-
AC2: 'Response to all reviewers', Daniel Steinfeld, 01 Sep 2022
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