the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 23 Jul 2026
The impact of climate extremes on northern and southern hemisphere seasonal ecosystem productivity over four decades to 2018
Abstract. Climate extremes affect ecosystem performance across the globe, including net seasonal productivity (NSP), the difference between land surface carbon uptake in summer and release in winter. In this study we correlated estimates of NSP, obtained from atmospheric carbon (C) observations, with curated climate extreme indices that span from 1977 to 2018, split between the Northern (NH) and Southern hemispheres (SH). In the NH, wet climate extremes correlated with an increase in summer uptake of C, and hot climate extremes were correlated with reduced winter release of C. Together, hotter and wetter climate extremes in the NH correlated with increased NSP, a finding that supports a beneficial effect of warming climates in high latitude seasonal NH forests, where cold temperatures typically limit ecosystem productivity. In the SH, all 10 hot climate extremes examined correlated negatively with summer C uptake, and NSP in the SH was negatively correlated with hot extremes but positively correlated with wet and cold extremes. The results indicate that seasonality in the SH, which is predominately located in warm tropical and subtropical forests, seem to be more deleteriously impact by heat than the NH, presumably due to the ambient temperature of SH forests being already close to biological heat thresholds such as photosynthetic heat stability. Increases in the Southern Oscillation Index (SOI) in the NH was associated with wetter and hotter climates that drove down winter C loss and led to increases in NSP. In the SH an increase in the SOI was associated with wetter climates that correlated with increased summer C uptake and NSP. The findings highlight the contrast between NH and SH seasonal C flux responses to climate extremes, and the importance of climate drivers of temperature and rainfall extremes in determining global ecosystem performance.
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2026-3927', Anonymous Referee #1, 24 Sep 2026
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AC1: 'Reply on RC1', Andrew Scafaro, 20 Oct 2026
The manuscript presents an approach for understanding the impact of meteorological extremes on the global uptake of carbon on an annual, hemispheric scale. By linking the atmospheric record of CO2 recorded at a northern and southern hemisphere tall tower observatory with a record of global extremes, the authors explore the statistical relationship between temperature and moisture extremes with the annual carbon uptake and release. Methodologically, the authors would better support their results and conclusions by demonstrating the relationship between aggregated extreme events and the variability of the global carbon cycle. The authors would better demonstrate the novelty/importance of their analysis if they more adequately located their results within the large corpus of literature addressing extreme events and the interannual variability of the carbon cycle. Without this, the novelty and potential impact of this paper are difficult to assess.
Response: Thank you to the reviewer for spending their time on assessing the manuscript, we appreciate the feedback. We will better address the aggregation of extreme events and novelty/importance in the larger literature addressing extreme events and the carbon cycle. Details are given in the responses to specific comments below.
Major comments:
The major analysis of the paper relates meteorological extremes aggregated hemispherically and annually with seasonal hemispheric carbon uptake and release. However, the meteorological extremes represent short-term events and/or local extremes. It is unclear how these short-term anomalies when aggregated statistically should reflect the function of the hemisphere as a whole over time. Perhaps the authors can better describe how these years represent non-extreme, longer-term fluctuations in temperature and water availability, and how the extremes deviate from that longer state.
While the temperature-related extreme indices (hot and cold) can be reasonably associated with the high-uptake and high-release periods of the analysis. With the wet indices, there is no clear relationship over the annual cycle. A wet extreme could occur in either during uptake or release, which would lead to different interpretation. It would be instructive to see the relationship of the extreme events averaged over the uptake and release periods identified in the paper.
In the southern hemisphere the uptake and release periods in tropical regions may have stronger association with wet and dry seasons rather than the summer/winter. The methodology does capture this by finding the longer season, but the discussion does not address how the differences in SH seasonality impact the analysis.
In the introduction, the authors discuss the role of fossil fuel burning in the atmospheric signal captured by Mauna Loa and Kennaook/Cape Grim, and control for the increasing trend in CO2 However, other non-biogenic fluxes such as fire are not discussed. These fluxes could potentially be more fully controlled using estimated fossil fuel and fire emission datasets.
Response:
“However, the meteorological extremes represent short-term events and/or local extremes. It is unclear how these short-term anomalies when aggregated statistically should reflect the function of the hemisphere as a whole over time.”
The reviewer is correct that we correlated both non-aggregated and aggregated indices with seasonal carbon exchange. Importantly, the number of aggregated indices (e.g. all the TX and TN 10 and 90p indices) used in our analyses exceeded that of the non-aggregated indices (e.g. TXx - the maximum daily maximum temperature for the year). To address the reviewer’s comments, we will reanalyse the correlations between seasonal exchange and climate indices only for those that are aggregated values that would be more expected to influence the season in question.
“Perhaps the authors can better describe how these years represent non-extreme, longer-term fluctuations in temperature and water availability, and how the extremes deviate from that longer state.”
We agree that the climate extremes in many instances would be reflecting the broader changes on the climate that we did not assess. For example, the TX90p is the percentage of days with daily maximum temperatures exceeding the 90th percentile throughout the year. This would likely reflect a generally warmer year and not just extreme heat which would be influencing ecosystem seasonality. While we would like to maintain the focus on extremes, we will add an analysis of seasonal mean maximum, mean minimum, and seasonal precipitation amounts to determine how much the climate extreme indices are reflecting yearly climate variation outside of the extremes. We will download the data from the Climdex database (the same that we have already used for the HadEX3 climate dataset), and use the BEST (Berkeley Earth Surface Temperature) dataset that is curated over the same period and covers global weather observations such as the mean daily maximum and minimum temperatures, and monthly precipitation values.
“A wet extreme could occur in either during uptake or release, which would lead to different interpretation. It would be instructive to see the relationship of the extreme events averaged over the uptake and release periods identified in the paper.”
Many of the HadEX3 indices can be split by month, including most of the wet indices like R10mm and R20mm as examples. We will split indices from annual to seasonal where the monthly data is available to make the climate data better align with the seasonal carbon exchange data.
“In the southern hemisphere the uptake and release periods in tropical regions may have stronger association with wet and dry seasons rather than the summer/winter. The methodology does capture this by finding the longer season, but the discussion does not address how the differences in SH seasonality impact the analysis.”
We will add a more comprehensive discussion of how the longer growing season of the south interacts with climate extremes and the interplay between seasonality of rainfall, seasonal length and climate vulnerability.
“In the introduction, the authors discuss the role of fossil fuel burning in the atmospheric signal captured by Mauna Loa and Kennaook/Cape Grim, and control for the increasing trend in CO2 However, other non-biogenic fluxes such as fire are not discussed. These fluxes could potentially be more fully controlled using estimated fossil fuel and fire emission datasets.”
We will add to the Introduction a statement about the potential for fires to impact on the seasonal CO2 signal. Our preference, however, will be to not undertake additional analyses regarding fire emissions over and above the existing analyses that account for the upward annual trend in CO2 that results from anthropogenic emissions (which represent <10% of overall ecosystem exchange as stated in the Introduction). Our view is that adding seasonal human emissions would not make a material effect on the analysis and only add complexity.
Minor comments:
A table of the extreme indices would be a helpful inclusion
Response: The comment by RC1, and a similar one by RC2, highlight that the current presentation of the climate extreme indices is not as clear as it could be. We will add a table that lists and describes the climate extreme indices for greater clarity.
The use of C as a unit can be confusing since you are converting CO2, but not accounting for all atmospheric C (e.g. methane).
Response: We will clearly define in the introduction that in this report C is referring to atmospheric carbon derived from CO2 and not total atmospheric C from other sources such as methane. We converted CO2 to C because it is conventionally used in the analysis of seasonal ecosystem carbon exchange (please refer to many of the citations provided in the Introduction).
Small corrections:
27 – impact -> impacted
Response: will correct.
30 – was -> were
Response: will correct.
Introduction
49 – through global… -> from global
Response: will correct.
87 – matching -> comparing
Response: will correct.
Materials and Methods
165 - which indices?
Response: will specify which indices
169 – This sentence is unclear
Response: will clarify the sentence.
189-194 – PRCP, PRCPTOT not defined
Response: will define and add to the newly created table defining climate indices.
Citation: https://doi.org/10.5194/egusphere-2026-3927-AC1
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AC1: 'Reply on RC1', Andrew Scafaro, 20 Oct 2026
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RC2: 'Comment on egusphere-2026-3927', Anonymous Referee #2, 02 Oct 2026
Summary
This manuscript examines associations between climate extremes and seasonal carbon exchange in both hemispheres over 1977–2018, using detrended CO₂ records from two stations. The authors report contrasting relationships between hot extremes and net seasonal productivity (NSP) across hemispheres, and positive associations between SOI and NSP in both.
The hemispheric comparison addresses an interesting question. However, the interpretation of the atmospheric observations, the definition and ecological meaning of NSP, and the statistical support for the principal conclusions require further clarification and analysis. Several inconsistencies between the text and figures also need to be resolved, and the clarity of the writing should be improved.
Major:
1. Representativeness of the atmospheric CO₂ records
The interpretation of the records as quantitative estimates of hemispheric terrestrial carbon uptake and release requires stronger justification (Lines 120–142). Their status as high-quality baseline stations does not necessarily mean that their seasonal CO₂ variations represent integrated terrestrial fluxes across the respective hemispheres. Many other factors could impact the records. Please explain the spatial representativeness of each station and assess the uncertainty introduced by using one station per hemisphere. Independent comparisons with other stations or atmospheric inversion estimates would strengthen the interpretation. If such validation is not feasible, the authors should explicitly acknowledge this limitation and narrow their hemispheric ecosystem-level conclusions accordingly.
2. Definition and calculation of NSP
The physical meaning of NSP needs to be established more clearly (Lines 128–161). Please explain how this quantity differs from established measures such as net ecosystem productivity (NEP), seasonal CO₂ amplitude, and anomalies in atmospheric CO₂ growth, and why it provides a useful measure of ecosystem performance.
The authors calculate NSP after detrending the atmospheric CO₂ records. Please justify this choice and explain how removing the long-term trend affects the physical meaning and ecological interpretation of the resulting NSP estimates.
Providing explicit equations for seasonal uptake, release, and NSP, including the sign conventions and the pairing of uptake and release periods across calendar years would be super helpful for readers to understand the method clearly.
This clarification is especially necessary because the definition in Lines 160–161 appears to have the opposite subtraction order from the Figure 2 caption.
3. Statistical support for the climate-carbon relationships
The statistical evidence supporting the principal conclusions needs to be strengthened. Many correlations in Figure 4 are weak, with coefficients around ±0.2, yet their directions are used to support broad conclusions about the effects of hot and wet extremes on carbon exchange. Confidence intervals and significance levels are not provided. Please report the sample size, correlation coefficient, uncertainty, and statistical significance for the relationships discussed, and distinguish exploratory patterns from statistically supported findings. Section 3.3 would also benefit from reporting the variance explained by SOI, alongside regression slopes and significance levels.
4. Some mechanistic interpretations exceed the evidence presented
The analyses establish associations but do not directly identify causal effects of climate extremes on ecosystem carbon exchange. Statements that particular extremes “drive” changes in uptake, release, or NSP should therefore be moderated unless supported by additional analyses that address competing explanations.
5. Concerns for using annual index to explain the seasonal pattern
Please justify correlating annual climate indices with seasonal carbon uptake and release. Annual extremes may occur outside the corresponding carbon-exchange period, particularly when seasons span calendar years. Clarifying the temporal alignment and assessing seasonally matched indices would strengthen the interpretation.
Minor:
Abstract: The abstract currently reads largely as a catalogue of results. I would suggest authors provide a clearer statement of the knowledge gap and its importance, briefly describe the approach, and focus on principal findings.
Climate indexes: Many climate indices appear to show similar behaviour and may contain overlapping information. Please examine their intercorrelations and address multiple testing. Consistent signs across closely related indices should not be interpreted as independent evidence. The claim of contrasting hemispheric responses would also be strengthened by directly testing whether the relationships differ between hemispheres, rather than relying on opposite signs.
Section 2.3, beginning at Line 163: This section reads primarily as a list of index definitions. Please explain the rationale for selecting these indices and grouping them into the five categories. A table could present the definitions more clearly while allowing the main text to focus on their relevance to the research question.
Language and consistency: Please edit the manuscript for grammatical clarity and consistent terminology, particularly for carbon uptake, release, NSP, and climate extreme categories. Ensure that the abstract, results, discussion, and figure captions describe the same quantities and relationships.
Line & Figure comments:
Line 24: Please define the period referred to as “summer” in each hemisphere and use this terminology consistently throughout the manuscript.
Line 27: Revise “seem to be more deleteriously impact” to “seems to be more deleteriously impacted,” or rewrite the sentence for clarity.
Line 61: Please verify the citation to Dunn et al. (2020). As listed in the references, this paper describes the HadEX3 dataset and does not appear to be the appropriate source for the preceding claim about the latitudinal pattern of CO₂ fertilization. Please check the correspondence between other claims and their cited sources as well.
Lines 230–231: The reference to Figure 2c appears incorrect because the sentence discusses exchange rates, which are shown in Figure 2a.
Line 234: The Southern Hemisphere NSP trend is reported as 0.001 Pg C yr⁻¹, whereas the Figure 2d legend gives 0.003 Pg C yr⁻¹. Please reconcile these values and systematically check numerical consistency between the text and figures across the paper.
Figures 3–5 captions, including Line 318: “Temperature extreme index” is used even though the analyses include precipitation indices. Do you refer to the “climate extreme index”? If yes, please use “climate extreme index” consistently where both temperature and precipitation are included.
Figure 4 placement: Please place Figure 4 closer to Section 3.2, where its results are discussed. Its current placement after Section 3.3 makes the sequence harder to follow.
Figure 5: The overlapping circle and square markers are difficult to distinguish. Consider using separate panels, transparency, or more distinct marker styles. Although the caption explains the solid and dashed lines, adding this information to the figure legend would improve readability.
Line 410: The link between the proposed cellular heat-stress responses, their energetic costs, and the observed hemispheric-scale correlations with DTR is unclear. Please explain the intermediate steps and provide supporting evidence, or explicitly present this mechanism as a hypothesis.
Citation: https://doi.org/10.5194/egusphere-2026-3927-RC2 -
AC2: 'Reply on RC2', Andrew Scafaro, 20 Oct 2026
Summary
This manuscript examines associations between climate extremes and seasonal carbon exchange in both hemispheres over 1977–2018, using detrended CO₂ records from two stations. The authors report contrasting relationships between hot extremes and net seasonal productivity (NSP) across hemispheres, and positive associations between SOI and NSP in both.
The hemispheric comparison addresses an interesting question. However, the interpretation of the atmospheric observations, the definition and ecological meaning of NSP, and the statistical support for the principal conclusions require further clarification and analysis. Several inconsistencies between the text and figures also need to be resolved, and the clarity of the writing should be improved.
Response: We thank the reviewer for their time reading and considering our manuscript. With the updates we will make in response to both RC1 and RC2 comments we are confident we can have an updated manuscript that addresses the concerns raised.
Major:
- Representativeness of the atmospheric CO₂ records
The interpretation of the records as quantitative estimates of hemispheric terrestrial carbon uptake and release requires stronger justification (Lines 120–142). Their status as high-quality baseline stations does not necessarily mean that their seasonal CO₂ variations represent integrated terrestrial fluxes across the respective hemispheres. Many other factors could impact the records. Please explain the spatial representativeness of each station and assess the uncertainty introduced by using one station per hemisphere. Independent comparisons with other stations or atmospheric inversion estimates would strengthen the interpretation. If such validation is not feasible, the authors should explicitly acknowledge this limitation and narrow their hemispheric ecosystem-level conclusions accordingly.
Response: Due to the mixing of atmosphere within each hemisphere, it is not possible to strictly limit the atmospheric CO2 observations to distinct latitudes as it is for the climate data which is based on weather stations at specific geographical locations. However, it is true that atmospheric CO2 observation stations that are in higher northern latitudes do pick up a stronger seasonal CO2 exchange signal as they are obtaining a greater signal from the high latitude forests in the northern hemisphere. To better capture spatial resolution of carbon exchange and link it to latitudinal restricted climate data we will expand the CO2 atmospheric observation data to include Barrow, Alaska, and the South Pole stations run by NOAA. This may show latitudinal dependent seasonality that is at a finer scale than hemispheres.
- Definition and calculation of NSP
The physical meaning of NSP needs to be established more clearly (Lines 128–161). Please explain how this quantity differs from established measures such as net ecosystem productivity (NEP), seasonal CO₂ amplitude, and anomalies in atmospheric CO₂ growth, and why it provides a useful measure of ecosystem performance.
Response: We will write a better explanation of what net seasonal productivity (NSP) is including providing the units and explaining its different from other similar metrics. It is different to net ecosystem productivity because it is not measuring ecosystem CO2 uptake minus CO2 release per unit of area. Rather it is the seasonal CO2 uptake minus the seasonal CO2 release over an entire year and for an entire hemisphere. It is equivalent to seasonal CO2 amplitude, but we did not name it as amplitude because that is a name based on using a sigmoidal wave function to the atmospheric CO2 observation data, a method that we did not use. We will consider also changing the name if we can conceive of a more appropriate term (e.g. annual seasonal gain).
The authors calculate NSP after detrending the atmospheric CO₂ records. Please justify this choice and explain how removing the long-term trend affects the physical meaning and ecological interpretation of the resulting NSP estimates.
Response: The long-term upward trend in atmospheric CO2 was removed because this confounds the seasonal CO2 flux of ecosystems. The upward trend is primarily caused by human emissions increasing over time and if we did not remove the upward trend, it would be difficult to disentangle the human induced changes in atmospheric CO2 from ecosystem fluxes. It is a standard procedure in the literature examining seasonal ecosystem flux from atmospheric CO2 observations to remove the background CO2 trend. Please refer to the example of Forkel et al. 2016, Science (351) pg. 696-699.
Providing explicit equations for seasonal uptake, release, and NSP, including the sign conventions and the pairing of uptake and release periods across calendar years would be super helpful for readers to understand the method clearly.
Response: We will add the equations that we used to make it easier for the reader to understand what calculations were performed.
This clarification is especially necessary because the definition in Lines 160–161 appears to have the opposite subtraction order from the Figure 2 caption.
Response: The caption of Figure 2 is incorrect and thus the inconsistency with Lines 160-161. We will correct the caption.
- Statistical support for the climate-carbon relationships
The statistical evidence supporting the principal conclusions needs to be strengthened. Many correlations in Figure 4 are weak, with coefficients around ±0.2, yet their directions are used to support broad conclusions about the effects of hot and wet extremes on carbon exchange. Confidence intervals and significance levels are not provided. Please report the sample size, correlation coefficient, uncertainty, and statistical significance for the relationships discussed, and distinguish exploratory patterns from statistically supported findings. Section 3.3 would also benefit from reporting the variance explained by SOI, alongside regression slopes and significance levels.
Response: Individual climate index correlations with seasonal CO2 data are often not strong. That is why we were careful not to draw conclusions from single correlations but rather from the patterns that emerged from multiple climate indices that correlated in a similar manner. For example, a pattern of all hot categorised climate indices having positive correlations with seasonal uptake in the northern hemisphere was strong evidence of heat benefiting seasonal uptake in the north rather than the correlation of a single hot related climate extreme taken in isolation. To make the analysis more statistically rigorous, we will add confidence intervals, sample sizes and statistical significance metrics for each relationship based on linear regression analysis and add this to the results as suggested.
- Some mechanistic interpretations exceed the evidence presented
The analyses establish associations but do not directly identify causal effects of climate extremes on ecosystem carbon exchange. Statements that particular extremes “drive” changes in uptake, release, or NSP should therefore be moderated unless supported by additional analyses that address competing explanations.
Response: We will modify our language so that it is clear we are not inferring causation but rather only correlation (i.e. we will remove wording like “drive changes”).
- Concerns for using annual index to explain the seasonal pattern
Please justify correlating annual climate indices with seasonal carbon uptake and release. Annual extremes may occur outside the corresponding carbon-exchange period, particularly when seasons span calendar years. Clarifying the temporal alignment and assessing seasonally matched indices would strengthen the interpretation.
Response: As addressed in the responses to RC1, we will amend our dataset to subset the climate indices by month and match the data by the seasonal cutoffs used in the CO2 exchange analysis.
Minor:
Abstract: The abstract currently reads largely as a catalogue of results. I would suggest authors provide a clearer statement of the knowledge gap and its importance, briefly describe the approach, and focus on principal findings.
Response: We will reword the abstract with the suggestions in mind.
Climate indexes: Many climate indices appear to show similar behaviour and may contain overlapping information. Please examine their intercorrelations and address multiple testing. Consistent signs across closely related indices should not be interpreted as independent evidence. The claim of contrasting hemispheric responses would also be strengthened by directly testing whether the relationships differ between hemispheres, rather than relying on opposite signs.
Response: The added statistics as mentioned in the previous comment will help to address this. We will also create a table that better explains each of the climate indices. We will present figures that directly show whether the relationships differ between hemispheres and not simply the patters of change across hemispheres as suggested.
Section 2.3, beginning at Line 163: This section reads primarily as a list of index definitions. Please explain the rationale for selecting these indices and grouping them into the five categories. A table could present the definitions more clearly while allowing the main text to focus on their relevance to the research question.
Response: As suggested by RC1 as well, we will add a table that lists the climate indices and defines them to make it easier for the reader. A table is provided in the article by Dunn et al. 2020 (https://doi.org/10.1029/2019JD032263) but we understand it is more convenient for the reader if a similar table is included within this study.
Language and consistency: Please edit the manuscript for grammatical clarity and consistent terminology, particularly for carbon uptake, release, NSP, and climate extreme categories. Ensure that the abstract, results, discussion, and figure captions describe the same quantities and relationships.
Response: We will tidy up the language and make sure we are consistent with quantities and the relationship terms presented.
Line & Figure comments:
Line 24: Please define the period referred to as “summer” in each hemisphere and use this terminology consistently throughout the manuscript.
Response: We will define “summer” and use it throughout.
Line 27: Revise “seem to be more deleteriously impact” to “seems to be more deleteriously impacted,” or rewrite the sentence for clarity.
Response: We will change the wording as suggested.
Line 61: Please verify the citation to Dunn et al. (2020). As listed in the references, this paper describes the HadEX3 dataset and does not appear to be the appropriate source for the preceding claim about the latitudinal pattern of CO₂ fertilization. Please check the correspondence between other claims and their cited sources as well.
Response: We will double check all references to make sure the correct citation is being used at the appropriate place.
Lines 230–231: The reference to Figure 2c appears incorrect because the sentence discusses exchange rates, which are shown in Figure 2a.
Response: We will correct this mistake
Line 234: The Southern Hemisphere NSP trend is reported as 0.001 Pg C yr⁻¹, whereas the Figure 2d legend gives 0.003 Pg C yr⁻¹. Please reconcile these values and systematically check numerical consistency between the text and figures across the paper.
Response: We will correct this mistake and check to make sure all text and figures are consistent with the final values obtained.
Figures 3–5 captions, including Line 318: “Temperature extreme index” is used even though the analyses include precipitation indices. Do you refer to the “climate extreme index”? If yes, please use “climate extreme index” consistently where both temperature and precipitation are included.
Response: We will change from “index” to “indices”.
Figure 4 placement: Please place Figure 4 closer to Section 3.2, where its results are discussed. Its current placement after Section 3.3 makes the sequence harder to follow.
Response: We will replace Figure 4 closer to its text section, noting that for the final article we will likely not have control of figure locations.
Figure 5: The overlapping circle and square markers are difficult to distinguish. Consider using separate panels, transparency, or more distinct marker styles. Although the caption explains the solid and dashed lines, adding this information to the figure legend would improve readability.
Response: We will use more distinct marker styles to make the figure clearer.
Line 410: The link between the proposed cellular heat-stress responses, their energetic costs, and the observed hemispheric-scale correlations with DTR is unclear. Please explain the intermediate steps and provide supporting evidence, or explicitly present this mechanism as a hypothesis.
Response: We will reword this section to make the points clearer to the reader.
Citation: https://doi.org/10.5194/egusphere-2026-3927-AC2
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AC2: 'Reply on RC2', Andrew Scafaro, 20 Oct 2026
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Referee report:
Title: The impact of climate extremes on northern and southern hemisphere seasonal ecosystem productivity over four decades to 2018
Author(s): Andrew P. Scafaro, Owen K. Atkin
MS No.: egusphere-2026-3927
MS type: Research article
The manuscript presents an approach for understanding the impact of meteorological extremes on the global uptake of carbon on an annual, hemispheric scale. By linking the atmospheric record of CO2 recorded at a northern and southern hemisphere tall tower observatory with a record of global extremes, the authors explore the statistical relationship between temperature and moisture extremes with the annual carbon uptake and release. Methodologically, the authors would better support their results and conclusions by demonstrating the relationship between aggregated extreme events and the variability of the global carbon cycle. The authors would better demonstrate the novelty/importance of their analysis if they more adequately located their results within the large corpus of literature addressing extreme events and the interannual variability of the carbon cycle. Without this, the novelty and potential impact of this paper are difficult to assess.
Major comments:
Minor comments:
Small corrections:
27 – impact -> impacted
30 – was -> were
Introduction
49 – through global… -> from global
87 – matching -> comparing
Materials and Methods
165 - which indices?
169 – This sentence is unclear
189-194 – PRCP, PRCPTOT not defined