Consistent response of European summers to the latitudinal temperature gradient over the Holocene

Domain: earth_science
Published: 2025-11-19
Editorial outcome: major_revision

Abstract
The drivers behind the current decadal trend toward longer and more extreme European summers are widely discussed. This is attributed to changes in the mid-latitude summer atmospheric circulation in response to Arctic Amplification and weakening of the latitudinal temperature gradients (LTGs), as well as to reduced aerosol emissions over Europe since the 1980s. However, causal links remain uncertain, limiting confidence in future projections. To gain statistical insights, evidence over periods longer than the instrumental record is necessary. Using seasonally resolved lake sediments, we reconstruct the evolution of the European summer-to-annual ratio over the last ten millennia. Our results indicate that summer weather dominated during the mid-Holocene, with an average of 195 summer days per year—falling within the extreme upper tail of summer distributions in the early- and late-Holocene. The Holocene variability in summer days aligns closely with simulated past changes in the LTG, supporting the hypothesis that dynamical processes influence mid-latitude seasonal weather on decadal to millennial timescales. A 1°C decrease in LTG would extend the summer season by ~6 days, potentially adding up to 42 summer days by 2100 under a business-as-usual scenario. These findings provide key observational constraints for understanding and projecting seasonal impacts on ecosystems and society.

Introduction
The annual cycle of atmospheric circulation and associated weather regimes establishes the climate seasonal clock by determining the characteristic timing and recurrence of seasonal conditions. In the North Atlantic (NA)-European region, atmospheric circulation is prevailed by westerlies that transport heat and moisture from the ocean to the continent, thereby reducing the ocean-land surface temperature gradient and exerting a strong influence on the climate. Additionally, a persistent high-pressure system over northern Europe, the so-called Scandinavian Blocking (SB), can divert the jet stream, creating a meandering, meridional flow and leading to prolonged climate extremes1,2 (Fig. 1). According to the relationship between daily sea level pressure and continental temperature, the European climate seasonal clock is divided into two main seasons: summer and winter2. The onset of each season is determined by the shift in the sign of the regression coefficients between these two parameters2. The summer is the season when the continent is warmer than the ocean, and westerlies act as a source of cooling for Europe. However, the SB circulation may occasionally divert westerly winds and promote the advection of warm air masses over central and northern Europe, triggering summer heat and rainfall extremes3 (Fig. 1a, b). The winter is the period when the continent is cooler than the ocean, so westerlies moderate European temperature, whereas a strengthening of blocking circulation can lead to cold spells (Fig. 1c, d). The likelihood of extreme events depends on the intensity of the SB, i.e. risk of blocking. This is associated with the strength of the zonal winds1,4 leading to a situation where weaker and meandering mean westerlies might promote atmospheric blocking (Fig. 1).

In the last decades, European summers have been lengthening2,5,6 with more recurrent and persistent weather extremes3,7–10 likely in response to the human-induced Arctic Amplification (AA), i.e. the faster warming of the Arctic compared to the global average11. It is widely recognised that longer summers2,5,6 versus shorter winters5 is largely a consequence of the earlier snowmelt across northern Eurasia driven by increasing greenhouse gas radiative forcing. This shift modifies the seasonal cycle of zonal advection and its interaction with the SB, leading to an earlier onset of summer-like weather patterns2. In contrast, the drivers behind the increasing frequency and persistence of weather extremes are a subject of ongoing debate12. A weakening of the equator-to-pole LTG has been suggested as a possible driver explaining the influence of the AA on mid-latitude weather patterns associated with extreme events3,13. This is thought to occur via a strengthening of the SB in response to a sequence of dynamical processes initiated by a weaker LTG, including a reduction in jet stream intensity and a slowdown of Rossby wave phase speed7,14–16 (Fig. 1b, d). Another hypothesis highlights the role of anthropogenic aerosols reduction over Europe from the 1980s17 as a consequence of the relocation of a large number of manufactures from North America and Europe towards Asia. This has been suspected to have played a role on the localisation of the Eurasian westerly jet over Europe and the intensification of summer weather extremes17,18. Yet, the precise contribution of the LTG to the ongoing reorganisation of atmospheric circulation linked to these extremes remains unresolved. Despite recent observations of both longer summers and more persistent extreme events, the two phenomena have been studied separately in the literature. The statistical robustness of the potential drivers is still weak and they are not accurately simulated by models19–21, mainly because the short instrumental period22,23 and the potential influence of multidecadal internal variability on the observed relationships19. In particular, large uncertainty exists about the dynamical aspects induced by a change in the LTG1,13. To contribute to this debate, this study seeks to offer a longer-term view of the natural link between the AA, the LTG and changing seasons, and evaluate the statistical robustness of this relationship.

The Holocene, the current interglacial period (last 11,700 years), is suitable to investigate whether dynamical processes induced by a weakening of the LTG may explain past changes in the European seasonal weather, hence part of the present and future variability13. This is because there were high-latitude warming and weaker LTGs between ca. 8−4 cal kyr BP24, as well as weak westerly circulation in summer and strengthening of the SB25,26. In this context, defining the summer season carefully is essential. Most of the studies investigating the current trend toward longer summers define the seasons according to the temperature seasonality e.g. refs. 5,27, so do published palaeoproxies reporting seasonal variability in the past e.g. refs. 28–30. However, temperature seasonality would reflect the influence of direct seasonal radiative forcing rather than the persistence of characteristic atmospheric patterns that define the seasons2. In this study, we adopt the definition of European climate seasons from Cassou and Cattiaux (2016)2 which is based on the variable influence of mid-latitude atmospheric circulation—including the role of the SB—on European climate. This definition might provide a more comprehensive evaluation of the evolution of summer weather during the Holocene than using seasonality based on temperature only. In addition, it provides the possibility to evaluate the influence of large-scale temperature gradients on longer timescales than the instrumental record, if the likelihood of extreme summer events (e.g., heatwaves) may increase during longer periods of that season.

In this study, we reconstruct Holocene seasonal variability by disentangling the cumulative seasonal signals preserved in annually resolved palaeoclimatological records (i.e., season-to-annual ratio). We use the couplet of seasonal laminations (varves) as a proxy for the relative contributions of summer and winter weather to each year during the last ten millennia. Following the proxy calibration with the duration of winter and summer2 during the last century, we compare these reconstructions with a transient climate simulation of the LTG in the NA-European region to establish the link between the climatic driver and the seasonal response.

Results
Evolution of European summer days during the Holocene
Varved sediments provide annually laminated records in which each varve is made of seasonal laminae, hence potential proxies for reconstructing the ratio of one season to another in every single year. The total varve thickness is the primary proxy to report the annual rate of deposition and sedimentation in response to changing external (climate) forcing31–34. Unfortunately, variability in the thickness of seasonal laminae is not often investigated or reported by authors, and this information is not easily available. On the other hand, the seasonal interpretation of the laminations must be investigated carefully as the laminae forming a varve do not always represent sedimentation during the entire season but short-lived events that often happen in a few days or weeks. This happens in some of the well-known European varved records, such as the monospecific diatoms bloom that forms one of the two laminae of the varves preserved in Lake Meerfelder Maar35, or the multiple event-layering pattern within the varves of Lake Montcortés36 and Lake Żabińskie37. According to the available literature on data repositories38 (https://varve.gfz-potsdam.de/database; https://pastglobalchanges.org/science/end-aff/varves-wg/data; https://www.pangaea.de/; https://www.ncei.noaa.gov/access/paleo-search/), the two unique European varved sediment records with 1) a continuous summer-winter type seasonality comparable to the European climate season pattern (Supplementary Information), and 2) available laminae thickness data during the Holocene, are Nautajärvi (Finland) and Diss Mere (England) (Fig. 1). Nautajärvi is varved from 9.85 thousands of years before 1950 CE (hereafter cal kyr BP) to present39. Diss Mere preserved varves from 10.3 to 2.1 cal kyr BP40. Intensification of human impact in the last two thousand years prevented from varve preservation in this lake40, although the two-season lake cycle and seasonal deposition remained unchanged41. Further details on the varve formation, environmental interpretation and chronologies of these records are provided in the Supplementary Information. The palaeolimnological study of these records is also supported by lake monitoring surveys that allowed a detailed study of their seasonal sedimentation cycles and the validation of the summer and winter nature of the varve structure41,42. Since varves are still preserved in Nautajärvi, we compared the season-to-annual ratio—defined as the percentage of the seasonal lamina thickness relative to the total annual varve—with the number of European summer and winter days from Cassou & Cattiaux (2016)2 (Fig. 2a, Supplementary Figs. 2, 3 and Supplementary Information). The comparison and correlation were conducted at annual resolution for the longest possible overlapped period between reanalysis and varve thickness data, from 1900 to 1940 CE (Supplementary Information, Supplementary Figs. 1–3). The calibration is based on a simple linear regression model estimating the relationship between the number of summer days over the instrument period and the percentage of the summer lamina contributing to the varve thickness (“Methods”, Fig. 2a, b, Supplementary Information). The correlation is significant for the length of both the summer (r=0.76, p-value<0.001) and the winter season (r=0.78, p-value<0.001) (Fig. 2a, Supplementary Fig. 2 and Supplementary Information). These high correlations suggest that the season-to-annual ratio in the varve data capture the variability of the European climate seasons and can be used as a proxy for its Holocene reconstruction.

Figure 2c shows the evolution of the season-to-annual ratios from the two varved records during the Holocene. In Nautajärvi, the summer contribution is compared to an available pollen-based reconstruction of the growing degree-days (GDD: annual sum of the number of degrees the daily average temperature is above 5°C each day) from the same sediments43 (Fig. 2c, orange and grey line). Although GDD represents cumulative thermal energy rather than the direct length of summer, it provides an independent temperature-based estimate of the evolution of the Holocene summer season for comparison with our reconstruction. Both proxies indicate a gradual shift toward longer and likely more intense summers from the early to mid-Holocene, followed by a trend toward shorter and cooler summers in the late Holocene. The Diss Mere reconstructions show similar results. The Holocene summer-to-annual ratio in the two lakes are well correlated (r=0.79, p-value<0.001; Fig. 2c, Supplementary Fig. 3a–c), which we interpret as both lakes recording a regional signal for northern-central, western Europe. We reconstructed past European summer weather days per year (Figs. 2d, 3a) by applying the calibration-based regression (Fig. 2a) to the mean summer-to-annual ratio from the two varved archives (Supplementary Fig. 3). The range of variability of summer days a year during the Holocene goes from 164 to 202 (Fig. 2d, Supplementary Fig. 3e). The histograms displayed in Fig. 2d show the frequency and distribution of the summer days during the early-, mid- and late-Holocene. Mid-Holocene’s distribution is bell-shaped and centred around 195 days, with most years between 192 and 199 of summer days. In contrast, early- and late-Holocene distributions are wider and skewed to the right (early-Holocene) and to the left (late-Holocene), but both with a peak around 189 summer days. Although there is some overlap with the mid-Holocene distribution, averaged summers in this period can be considered extreme in the early- and mid-Holocene and happened less than 100 times (Fig. 2d).

Long-term validation of the role of the LTG on European summers
The LTG has an important impact on the Earth’s climate system by influencing the intensity and position of mid-latitude storms, the tropical Hadley Cell, sub-tropical high and sub-polar low pressure centres27. Therefore, the LTG represents a fundamental driver for assessing the responses of atmospheric circulation to climate change20. To examine the link between the LTG and European summers without the influence of anthropogenic forcing, we analysed the Holocene evolution of the simulated equator-to-pole LTG in the NA realm and compared it with the reconstructed European summer days (Fig. 3a, Supplementary Fig. 3d, e). To estimate the NA-grided LTG at the highest temporal resolution possible, we extracted it from the TraCE-21ka simulation (“Methods”). TraCE-21ka provides a 10-yr resolution and mainly represents the response to a wider range of external forcing during the last 21 kyr BP. The simulated LTG displayed a U-shaped trend through the last 10 kyr that agrees with an empirical proxy-based LTG reconstruction for Europe24 (Fig. 3a, Supplementary Fig. 4). The simulated LTG was strong during the early Holocene but abruptly decreased by 2.2°C in less than 100 years at ca. 8 cal kyr BP. It stayed weak until ca. 3 cal kyr BP, when the LTG increased to 1.3°C within a 500-year interval. The simulated LTG over the NA-European sector differs from the gradual long-term increase in the LTG previously reconstructed for the whole NH based on zonal averages44, which was mainly driven by the latitudinal insolation gradient44 (Supplementary Fig. 4). However, the authors44 note that the Laurentide Ice Sheet could likely affect temperature and circulation in the NA region with an impact on the regional LTG, which was previously argued by Davis and Brewer (2009)24. To gain understanding on the drivers of the regional LTG in the TraCE-21ka simulation, we used the available attribution experiments with individual external forcing (greenhouse gasses, insolation, ice sheet changes and meltwater flux; Fig. 3b). We then compared the combined (i.e. sum of individual forcing experiments) and the full simulations including all forcings to assess their temporal evolution and test for linearities in the LTG responses (Fig. 3b). The close match between the full-forcing simulation and the combined sum indicates that the simulated LTG response to individual forcings is largely linear. However, some differences exist in the amplitude and variability, which may be explained by the effect of either non-linearities or internal variability. Nevertheless, for the long-term trend, we were able to attribute the variations seen in the simulations to the specific forcing from each attribution simulation. According to these experiments, the variability of the regional LTG responded mostly to the cryosphere through the changing continental ice distribution and meltwater flux to the ocean until ca. 5 cal kyr BP. From then to the present, orbital forcing, including the latitudinal insolation gradient, mainly drove the variability (Fig. 3b).

The comparison of the Holocene evolution of the simulated LTG and proxy-based reconstruction of summer days shows that both time series are significantly correlated (r=0.6, p<0.001) and vary at a consistent ratio to each other over time (Supplementary Fig. 3d, e). The scaling factor (5.6 days: 1°C) has been calculated as the ratio of the standard deviation of the two time series (Supplementary Fig. 3e). We conducted a similar analysis using TraCE-21ka-simulated summer mean temperature for the European grid between 50–70°N. While the correlation is lower, it remains significant (r=0.45, p<0.001), indicating that longer summers generally coincide with higher mean summer temperatures. Yet, the stronger link to the LTG implies that more than surface temperature alone governs the annual distribution of summer days. Approximately 36% of the variability in reconstructed European summer days is explained by the LTG, compared with only 20% explained by simulated summer temperature. This supports the notion that the LTG may exert a more dynamic influence on mid-latitude seasons through its impact on atmospheric circulation. In particular, the relationship between the equator-to-pole LTG and summer weather may be mediated by the occurrence of more frequent and persistent extreme events, which increase the number of hot days and, consequently, raise the mean summer temperature. Additionally, the good agreement between proxy data and model simulations during the Holocene, which is relatively unusual45, adds evidence to support the long-term influence of the LTG on changing European seasons from decadal to millennial timescales.

Holocene context for future summers
Our study shows that the LTG varied by up to 5°C over the past ten thousand years, accompanied by shifts of up to a month in the number of summer days during the Holocene (Figs. 2d, 3). During the instrumental period, we plotted the simulated LTG alongside 10-yr averaged values of LTG calculated from reanalysis and instrumental data during the hindcast period (1960–1990 CE). Although the TraCE-21ka model provides three data points for this interval, they align well with instrumental observations (Fig. 4), supporting the comparison of Holocene results with recent observations and future projections.

Reanalysis and instrumental data show that the interannual variability of the LTG have varied within the Holocene values with changes in the number of summer days of up to 20 days (Fig. 4). However, the correlation decreases but is still statistically significant (r=0.26; p-value=0.002). This might be related to the interplay of other anthropogenic factors, such as changes in aerosols46, or to the fact that this link remains low at the interannual timescale, blurred by the noise of a number of other short-term processes. Since the 1980s, the LTG has shown a gradual weakening alongside a trend toward lengthy summer (Fig. 4), consistent with previous studies2,5, and accompanied in recent decades by increases in the intensity and frequency of summer extremes8,47 as well as phenological shifts in plants and animals48,49.

Taking an ensemble of CMIP6 projections for the North Atlantic LTG until 2100 CE, we find that the values would continue to decrease over the next 75 years up to −4.6°C in the lowest emission scenario (SSP1-2.6), and up to −11.6°C in the highest emission scenario (SSP5-8.5) (Fig. 4). Considering the mean for each emission scenario, the LTG would have surpassed the minimum values reached in the Holocene (−2.3°C) by 2050 in all emission scenarios (Fig. 4). Investigating what the changes are likely to be in the seasonal cycle once the LTG passes beyond Holocene thresholds is out of scope of this study as both anthrophonic factors and positive and negative feedback loops might influence summer weather in the future. However, as a simplistic approach assuming the linear influence of the LTG observed in the Holocene only, past observations suggest an addition of 13 days to the mean of industrial European summers under SSP1-2.6 and up to 42 more days under SSP5-8.5 by 2100 CE (Fig. 4). This estimation exceeds the length of the summer season under the business-as-usual scenario reported by Cassou and Cattiaux (2016)2 by 22 days. Direct comparison with CMIP5 and CMIP6 projections is difficult, as seasonal durations vary across studies depending on how seasons are defined—for instance, whether based solely on temperature—and on how many seasons are distinguished—whether spring and autumn are considered5.

To conclude, our observation-based estimate of the link between summer days and LTG during the Holocene provides a long-term observational constraint that is likely less influenced by internal variability than the short instrumental period2. A simple linear regression model indicates a larger future increase in summer days and associated extremes than projected by climate models. This aligns with recent findings that climate models may underestimate dynamical changes driven by global warming19,50.

Methods
Proxy records
Varve thickness measurements from Nautajärvi and Diss Mere are available at https://doi.org/10.1594/PANGAEA.968802 and https://doi.org/10.1594/PANGAEA.94441. Details of the methods applied are explained in the Supplementary Information. Varve data were detrended to remove the effects of non-stationarity in the proxy records, such as sediment compaction and other long-term non-climate-related catchment processes. We linearly detrend each time-series using the pracmaR package. The season-to-annual ratios were calculated as the percentage of the summer and winter lamina thickness contributing to the total varve thickness. The proxy record has an annual temporal resolution. The summer (winter)-to-annual ratio of the Nautajärvi varve record was calibrated using values of summer (winter) days calculated from NOAA 20-CR reanalysis1 during the period 1900-1940 CE by applying a linear regression model.

Palaeo-simulations
The TraCE-21ka transient climate simulation uses the fully coupled CCSM3 general circulation model with a horizontal grid resolution of 3.25°51. The full simulation is forced by different transient boundary conditions, including orbital parameters (ORB), greenhouse gases (GHG), ice sheet height (ICE) and finally freshwater flow forcings (MWF). Simulations were also completed for each of the forcings independently. We use anomalies for each of the model outputs, taking a reference period between 1950–1990 CE to overlap with the historical data available. The latitudinal temperature gradient was calculated using a longitudinal grid of 30°W-30°E and a create two latitudinal bands from 0–10°N for the low latitudes and 80–90°N for the high and subtract the low latitude from the high to get the gradient. We then convert the LTG to anomalies between 1950–1990 CE. To identify the potential drivers of variability in the LTG, we use the attribution experiments from the TraCE-21ka simulation for the same grid boxes mentioned above. These simulations apply only single attribution forcings (GHG, ICE, ORB, MWF) and can be compared to the full simulations where all the forcings are applied. We assess the linear response of the forcings to the LTG by comparing the sum of all the individual attribution experiments and the full simulation.

Solar insolation data used to compute the latitudinal insolation gradient is the LA04 data52 downloaded for the past 11,000 years using the Rpalinsol package. An annual mean was taken at 0°N and 90°N, and the gradient was calculated by subtracting the high latitude mean from the low.

Data-model Comparison
Correlation coefficients and p-values between the proxy data and TraCE-21ka outputs were created using the corrplot R package. All the correlations shown in the main text are done at 10-year resolution, using original temporal resolution for TraCE-21ka simulations and resampling every 10 years for the varve proxy data. For scaling the simulated LTG and reconstructed European summer days, the time series were normalised using their mean and standard deviation. The scaling factor was calculated by dividing the standard deviations of the original time series.

Historical data: combination of monthly instrumental and reanalysis data. We use four sources of gridded temperature data from HadCRUT5, NASA GISTemp, NOAA GlobalTemp, the Berkeley Earth interpolated data and the ERA5 reanalysis data, which combines both instrumental data and models to fill in the missing spatial and temporal gaps (Supplementary Table 1). Data had been extracted and the LTG has been calculated using the same approach as the palaeosimulation and converted to anomalies from the 1950 to 1990 mean.

Historical simulations: we also use an ensemble of 23 historical CMIP6 experiments between 1850 and 2014 for the LTG grid (Supplementary Table 2). Anomalies were calculated using the CMIP6 historical simulation between 1950–1990 CE, and an ensemble mean and standard deviation were calculated at an annual resolution.

Future projections: to investigate the role of future scenarios on the LTG, we use 23 CMIP6 models (Supplementary Table 3) for the Shared Socioeconomic Pathway simulations for 1–2.6, 2–4.5 and 5–8.5 (SSP1-2.6, SSP2-4.5, SSP5-8.5), corresponding to different levels of socio-economic adaptations to anthropogenic climate change53. Anomalies were calculated using the historical simulation between 1950–1990 CE for the corresponding model.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This is an interesting paper that leverages high-quality varved lake sediments from two European lakes. The varves at each lake record changes in winter and summer conditions, allowing for seasonality to be distinguished through the Holocene. This information was used to investigate changes in the relative dominance of winter and summer conditions during the Holocene and their relationship with model-derived changes in latitudinal temperature gradients. Overall, the relationship between model-derived LTGs and inferred changes in the number of summer days shows a good correspondence. It is only during the last ca. 1500 years that the relationship is less robust. The generally good relationship over the Holocene is then combined with future estimates of LTGs to make statements about the paleoclimate context for potentially longer summers in the future under different emission scenarios.\nThe study is generally compelling and I do have major concerns with the (significantly revised) manuscript as presented. I think the work is original, novel, and appears to use sound methodology. I believe the work would be well received by the broader climate and scientific community. A few minor comments are given below.\n1) The writing could/should be smoothed out. There are numerous instances of incomplete sentences, missing articles, etc… in both the main text and supplemental information. I also suggest using the past tense when describing trends, such as of the LTG, that occurred in the past instead of describing them as though they were happening today.\n2) Define the Holocene at first use – line 74\n3) The calibration period is short, but I suppose there’s nothing to do about this. Are there any other seasonally specific paleoclimate records that the seasonal specific varve records could be compared with on longer timescales to see how the calibration holds up?\n4) The overall correspondence between the LTG and inferred European summer days is pretty good. But what might explain the disconnect during the last 1500 years? Is this an artifact of human influence?\n5) Break up the sentence from line 232 – 236.", "reviewer_2": "The manuscript has been apparently evaluated for another NPG journal. The previous reviewers had already summarised the study and identified the main weak points of that previous version. In my opinion, the submitted version addresses most of the the concerns raised by the reviewers, although some issues still remain, as I explain below.\nForm the technical point of view, I think that the study is now essentially sound. The proxy records and the Holocene climate simulations are correctly analysed. However, I have a more fundamental worry about the main hypothesis of the study. This main hypothesis is that the Latitudinal Temperature Gradient over Europe is connected with the length of the summer and winter seasons in Europe at long temporal scales. This connection is established from the analysis of the paleoclimate records, together with current observations and the climate simulations. Therefore, the changes in the LTG projected for the future can be used as an indicator of the duration of the summer and winter seasons in this region. The duration of the seasons is defined through the impact of the atmospheric circulation on surface temperatures: as the continents are colder (warmer) in winter (summer), the impact of the winds on temperatures is opposite in summer or winter.\nI have tow main comments. One is short , and relates to the title. The second is more substantive. All in all, I think that both concerns can be addressed, and it is also possible that my main concern is caused by my fundamental misunderstanding of the study, but then it would also mean that other readers may also misunderstand it.\n1) I found the title not really informative. What does 'to provide context ' mean ? I could not really make sense of the title. Perhaps this is already indicating a deeper problem, as the authors seem to struggle to find a title that really summarised their findings\n2) My more substantive concern is whether there is a circularity in the chain of thought. The study seems top posit the LGT as an independent 'driver' of the season duration, but the definition of the LGT entails the difference between the temperature in the tropics and at midlatitudes. Therefore, there is an automatic correlation between the LGT and the mean temperature at midlatitudes, independently of which factor is the driver. Further, the mean temperature at midlatitudes should also be clearly correlated with the seasonality. For instance, warmer mean summer temperatures will be linked with longer summers in general in an stationary climate, since in a stationary climate with the external drivers (greenhouse gas, insolation, etc) are constant, the only source of variability is the atmospheric circulation. The authors establish this link by linking the length of the seasons and the mean seasonal temperature (or the LTG, which as I mentioned are automatically related).\nThe problem arises when trying to extrapolate this link to other climates (past or future), for which the external drivers have changed or are continuously changing. For instance, when greenhouse gases are increasing and rising the mean temperatures, they do more so over the continents than over the ocean. Therefore, the link between atmospheric circulation and temperatures becomes automatically more summerlike, lengthening the summers and shortening the winters They do so not because the LTG has changed per se, but because the mean temperatures have risen. Since greenhouse-gas forcing also causes a stronger rise of mid-latitudes temperatures than tropical temperatures, its effect is also reflected on the LTG. Thus, an alternative explanation could leave the LTG entirely out of the reasoning, and just focus on the effect of greenhouse gas forcing.\nThe orbital forcing during the midHolocene shares this characteristics with greenhouse gas forcing: summer continental temperatures would rise more strongly than ocean temperatures, and mid-latitude temperatures in the Northern Hemisphere also more strongly than tropical temperatures.\nThus, my concern can be summarized as follows: is the LTG really a driver of the seasonality or is this link just an artefact due to the very definition of the LTG ?", "reviewer_3": "The manuscript by Martin-Puertas et al. submitted to Nature Communications represents an important scientific achievement, obtained through a well-structured approach and detailed investigation. The manuscript is written in a manner that more submissions should strive to achieve in terms of language and care. There are some minor issues that I will outline in the specific comments. It addresses a crucial paleoenvironmental issue, which the authors accurately describe as a lack of “seasonal clock” investigations using natural archives. However, even though it is indeed an interesting approach, somewhat unique, I am not entirely convinced that it is suitable for Nature Communications. Base on the quality of the ms I'm suggesting minor revisions, with the asterisk of being unsure about the journal choice.\nYet, I must stress that the use of the \"simple” varve parameter, which is its fundamental characteristic, such as varve thickness, is something that more investigators should aim for and take care of. This shows that it is not always necessary to work with a multiproxy dataset based on numerous analytical techniques and extremely complex statistics. This study demonstrates that a well-structured and constructed hypothesis, paired with a well-adjusted analytical process, can answer some pressing questions. This was also possible thanks to the extensive study of the sites selected by the authors. This leaves me impressed.\nI abstain from delving into circulation patterns, as I find it too far removed from my expertise. I can only hope that through the review, the Editors will find it easier to reach their conclusions. Given that due to the manuscript transfer, previous reviews and the rebuttal were available, I feel obligated to say that some of the responses to the questions raised are not satisfactory. This is especially true at times when reviewers raised concerns, which were met with “part of the text/figure is removed now\" without addressing the underlying problem. Despite that, I’m treating this review as a standalone, new submission.\nTo summarize, I do not find any specific or major flaws in the submitted manuscript; however, I’m unsure if NComms is the appropriate outlet.\nGeneral comments\nAs Nature Communications is an outlet for a broad range of investigations and therefore for numerous readers outside of “our” field, I’d suggest that the authors take more care in communicating the significance of their research (and in general, the paleosciences), as well as the current and future climate state. For example, is the mentioned change of summer season by 6 days (line 26) a substantial change? Please consider this from the perspective of a non-expert reader outside the (paleo)climate field. Why should we care? Strengthen your point.\nThe climate seasonal clock: frankly, while I have no other choice but to accept the definition provided in the literature, I find this term/wording throws the reader off balance. This reads like an easy concept with unnecessary steps and verbosity.\nSummer and weather extremes' persistence is mentioned in 48-49, but later on, persistence refers to what I understand as the total number of summer-like season days, which for me is not the same as persistence.\nBe consistent; compound words with the “palaeo” prefix are written in three different ways: as one, hyphenated, and with a space. Stick with one.\nThe first time early/mid/late Holocene are mentioned, it should be immediately followed by the ages, which are provided later in the text. Also, what about current and formal Holocene subdivisions?\nAround 110-111, if there is still room in the literature, there are other examples of such behavior and studies using longer and shorter time frames. Do the authors argue that if varves do not strictly follow the simplest pattern, they become useless for such an approach? Because in that case, it might not be about the other researchers’ willingness to share the data or even count it; it might be inherently impossible to produce similar records.\nDespite previous comments, not all r values are reported with p values.\nFigure 2 and the referencing text: are the authors satisfied with the relatively small sample size of the calibration and, hence, the regression equation? n = 40 barely meets the minimum and could be a source of bias. On the other hand, I’m concerned about the other issues that “plague” the varved sequences. The authors suggest that human impact has affected the sedimentation processes and thus signal formation; however, only varve thickness detrending is reported as a means of dealing with changing sediment properties. Furthermore, figures whenever results of applied regression are used should provide uncertainty bands.\nThe figure caption for panel 2C is confusing, in my opinion. On the other hand, panel D presents a clever approach.\nDid you correct for autocorrelation in the time series, as suggested by earlier reviews?\nFigure S2’s shade is too deep."}, "author_response": "Point by point response to reviewers’ comments on the manuscript\n\"Persistent summers in the mid-Holocene provide context for changing\nseasons\" by Martin-Puertas et al. submitted to Nature Communications.\nReviewer #1 (Remarks to the Author):\nThis is an interesting paper that leverages high-quality varved lake sediments\nfrom two European lakes. The varves at each lake record changes in winter and\nsummer conditions, allowing for seasonality to be distinguished through the\nHolocene. This information was used to investigate changes in the relative\ndominance of winter and summer conditions during the Holocene and their\nrelationship with model-derived changes in latitudinal temperature gradients.\nOverall, the relationship between model-derived LTGs and inferred changes in\nthe number of summer days shows a good correspondence. It is only during the\nlast ca. 1500 years that the relationship is less robust. The generally good\nrelationship over the Holocene is then combined with future estimates of LTGs to\nmake statements about the paleoclimate context for potentially longer summers\nin the future under different emission scenarios.\nThe study is generally compelling and I do not have major concerns with the\n(significantly revised) manuscript as presented. I think the work is original, novel,\nand appears to use sound methodology. I believe the work would be well\nreceived by the broader climate and scientific community. A few minor comments\nare given below.\nWe thank the reviewer for the positive feedback, and we are pleased that this\nnew revised version is well received. We have accepted the suggestions 1,2 and\n5 below and have revised the manuscript accordingly. We reply to comments 3\nand 4 below.\n1) The writing could/should be smoothed out. There are numerous instances of\nincomplete sentences, missing articles, etc… in both the main text and\nsupplemental information. I also suggest using the past tense when describing\ntrends, such as of the LTG, that occurred in the past instead of describing them\nas though they were happening today.\nDone\n2) Define the Holocene at first use – line 74\nDone. Line 133 in the revised manuscript.\n3) The calibration period is short, but I suppose there’s nothing to do about this.\nAre there any other seasonally specific paleoclimate records that the seasonal\nspecific varve records could be compared with on longer timescales to see how\nthe calibration holds up?\nDegree Days (GDD) is the only proxy that could potentially be compared here,\nbut it does not align perfectly with our approach. Our proxy reflects a\nsummer:winter ratio, whereas GDD is a temperature-based threshold metric for\nplant and insect development during a specific part of the year, and not a direct\nindicator of climatic seasons. That said, the correlation with GDD from the pollen\nrecord at Nautajärvi (Ojala et al., 2008) is very strong, as shown in Fig. 2c,\nparticularly during the early and mid-Holocene.\nWe agree that thinking of the summer season naturally brings temperature to\nmind, but we aim to avoid direct comparison with summer temperature\nreconstructions (e.g., tree rings, GDGTs, chironomids), since our proxy does not\nrespond solely to summer temperature. We provide a more detailed response to\nthis issue in our reply to Reviewer #2.\nIn our case, the seasonality recorded in the varves (couplets) reflects a\nwinter:summer ratio defined by the lake’s annual cycle and limnological seasons.\nThis ratio corresponds well with the two main climate seasons described by\nCassou and Cattiaux (2016), which are based on large-scale climate dynamics.\nAccording to lake monitoring data, the timing of these limnological seasons\nbroadly coincides with the timing of European climate seasons (based on\naveraged data for western Europe). For calibration, we used the NOAA\nreanalysis dataset (the longest available), kindly provided by Cassou and\nCattiaux, which includes NOAA (1900–1994), ERA (1916–1994), and NCEP\n(1964–1994). We acknowledge that 41 data points is close to the lower limit for\nstatistical significance; nevertheless, this calibration supports the climate–proxy\nrelationship (r2=0.56) already established in the detailed paleolimnological study\nof the varves, including modern monitoring. Finally, comparison between two\nindependent lakes situated in distinct geological settings shows a consistent\nsignal throughout the Holocene, further reinforcing the robustness of our\ninterpretation.\nWe have added further clarification on why we use this particular definition of\nseasonality, and why other palaeoclimate records reconstructing summer\ntemperature or temperature seasonality are not the most appropriate for\ncomparison in this study. We hope this addition clarifies our reasoning (see lines\n137–203).\n4) The overall correspondence between the LTG and inferred European summer\ndays is pretty good. But what might explain the disconnect during the last 1500\nyears? Is this an artifact of human influence?\nWe agree with the reviewer that this is likely related to human impact. Diss Mere\nis not varved during the last two millennia, and Nautajärvi began to experience\nminor human influence around that time. However, varve deposition and\nseasonal sedimentation at Nautajärvi remain largely unaffected (i.e., no changes\nin varve structure, sediment composition, or preservation) until much later,\naround 1940 CE. Over the past 1500 years, the correlation with simulated LTG at\nboth 10- and 50-year resolution remains strong and significant (Fig. 4; Extended\nData Fig. 1), suggesting that the climate signal is still preserved. What changes in\nthe last 1500 years period is the scaling factor between the two variables, likely\ndue to superimposed human impacts. For this reason, the proportionality\nbetween the two variables reported in the manuscript for potential use in climate\nmodels is based only on the 10–2 ka BP interval.\n5) Break up the sentence from line 232 – 236.\nDone\nReviewer #2 (Remarks to the Author):\nThe manuscript has been apparently evaluated for another NPG journal. The\nprevious reviewers had already summarised the study and identified the main\nweak points of that previous version. In my opinion, the submitted version\naddresses most of the concerns raised by the reviewers, although some issues\nstill remain, as I explain below.\nForm the technical point of view, I think that the study is now essentially sound.\nThe proxy records and the Holocene climate simulations are correctly analysed.\nHowever, I have a more fundamental worry about the main hypothesis of the\nstudy. This main hypothesis is that the Latitudinal Temperature Gradient over\nEurope is connected with the length of the summer and winter seasons in Europe\nat long temporal scales. This connection is established from the analysis of the\npaleoclimate records, together with current observations and the climate\nsimulations. Therefore, the changes in the LTG projected for the future can be\nused as an indicator of the duration of the summer and winter seasons in this\nregion. The duration of the seasons is defined through the impact of the\natmospheric circulation on surface temperatures: as the continents are colder\n(warmer) in winter (summer), the impact of the winds on temperatures is opposite\nin summer or winter.\nWe would like to thank the reviewer for such constructive feedback, which has\nhelped to improve and clarify the revised version of the manuscript.\nI have two main comments. One is short , and relates to the title. The second is\nmore substantive. All in all, I think that both concerns can be addressed, and it is\nalso possible that my main concern is caused by my fundamental\nmisunderstanding of the study, but then it would also mean that other readers\nmay also misunderstand it.\nWe also believe the two concerns can be addressed and we provide point-by-\npoint response below. After reading the main concern, we think that we should\nhave explained the rationale of our study in another way providing more details of\nthe current discussion about how Arctic Amplification can impact mid-latitude\nclimate and the potential key role of dynamical processes. We have modified the\nintroduction, hopefully with a satisfactory result. Line 44-214\n1) I found the title not really informative. What does 'to provide context ' mean ? I\ncould not really make sense of the title. Perhaps this is already indicating a\ndeeper problem, as the authors seem to struggle to find a title that really\nsummarised their findings\nBy ‘to provide context,’ we mean that the study offers a long-term perspective on\nhow seasons have changed in the past. When choosing the original title, we were\nconstrained by the character limit, as the manuscript was transferred from\nNature. Since Nature Communications allows longer titles, and in line with the\nreviewer’s suggestion, we now propose the following revised title:\nConsistent response of European summers to the latitudinal temperature\ngradient over the Holocene\n2) My more substantive concern is whether there is a circularity in the chain of\nthought. The study seems top posit the LGT as an independent 'driver' of the\nseason duration, but the definition of the LGT entails the difference between the\ntemperature in the tropics and at midlatitudes. Therefore, there is an automatic\ncorrelation between the LGT and the mean temperature at midlatitudes, independently of which factor is the driver.\nWe thank the reviewer for bringing attention to this issue. We think this is a very\nsensible comment that we should have clarified more explicitly in the text.\nFirst, we would like to clarify that we have calculated the North Atlantic LTG as\nthe temperature difference between the Equator and the North Pole and not from\nthe equator to mid-latitude as the reviewer states. We have used the equator-to-\npole LTG according to state-of-the-art research on the impact of AA on mid-\nlatitude summer weather (Coumou et al., 2015, 2018). This was explained in\nMethods, line 6594-662: “the latitudinal temperature gradient was calculated\nusing a longitudinal grid of 30°W-30°E and a create two latitudinal bands from 0-\n10°N for the low latitudes and 80-90°N for the high and subtract the low latitude\nfrom the high to get the gradient. We then convert the LTG to anomalies between\n1950-1990 CE”. Therefore, there is no automatic correlation to midlatitude\ntemperatures.\nAccording to the current literature, there is a recent trend towards longer summer\nin the last two decades, which is associated with the Arctic Amplification (AA)\nrelated to dramatic melting of Arctic sea ice and spring snow cover (chicken and\negg situation). This has triggered an early start of the summer making summer\nlonger. These profound changes in the Arctic system have coincided with a\nperiod of ostensibly more frequent extreme weather events (atmospheric\nblockings) across the Northern Hemisphere mid-latitudes in the last two decades\n(Cohen et al., 2014). The possibility of a link between Arctic change and mid-\nlatitude weather has spurred growing research interest, particularly into potential\ndynamical pathways through which AA may influence mid-latitude summer\nweather, specifically, via a weakening of the equator-to-pole temperature gradient\nand alteration of atmospheric circulation patterns (Coumou et al., 2015, 2018).\nScientists are generally confident in the thermodynamic drivers of longer and\nmore extreme summers (in agreement with the reviewer’s comment) but are less\nso in the dynamical aspects (Coumou et al., 2012, 2018). However, through\nthese dynamical processes, it is possible, in principle, for sea ice and snow cover\nto jointly influence mid-latitude weather, and to explain the link between longer\nsummer and long-lasting weather extremes. We want to highlight that both\nphenomena are investigated independently in the current literature; nevertheless,\nit is reasonable to expect that if summers begin earlier, the likelihood of summer\nweather extremes will increase, since the period of summer-type atmospheric\ncirculation is extended. There is still an incomplete knowledge of how high-\nlatitude climate change influences these mid-latitude phenomena, notably due to\nsparse and short data records, and imperfect models, which explain the large\nuncertainty regarding the magnitude of such an influence (Cohen et al., 2014).\nThe main goal of our manuscript is, therefore, to provide significant statistical\nevidence to support that the link between LTG and seasonal weather existed in\nthe past on a decadal to millennial scales to support further research into the\ndynamical aspect of more persistent summers. From the proxy data, it is difficult\nto define whether the contribution of the summer season to the annual signal (i.e.\nour proxy record represents a winter:summer ratio) is responding to either the\nduration of the summer or number of extreme hot days, or most likely to both.\nIn the manuscript, we have calibrated the proxy data with the duration of the\nEuropean summer season from reanalysis data according to the definition of\nsummer provided by Cassou and Cautiaux (2016). This is because the division of\na calendar year in two main seasons agrees with the seasonal pattern of the\nlakes included in this study (please note that the link between climate seasons\nand lake seasonality is also supported by lake monitoring data and the\nlimnological interpretation of the varves. Unfortunately the duration of the lake\nmonitoring is not long enough to support significant statistical correlations).\nIn response to the reviewer’s concern about the automatic correlation between\ntemperature and LTG, we did not find such correlation in the TraCE simulation.\nDuring the Holocene, the correlation between the simulated LTG and the\nsimulated mid-latitude temperature (grid used in the manuscript) and local\ntemperature (at the lake locations) is not as correlated as the reviewer suggests.\nWe use TraCE-21ka data to compute the following correlations. We have also\nincluded the proxy data as this information will be used below. Please note that\nthe sample size n = 988, which leads to low p-values, so we rather interpret the\nmagnitude of r.\nTable 1. Correlation coefficients (r) and p-values\nThe highest correlation between LTG (equator to pole) and Temperature is at the\nlocation of Nautajarvi (the northernmost location closer to the Arctic circle, which\ncould be expected as the LTG is calculated using pole’s temperature) but still it is\nlower than r = 0.5. At the location of Diss, which is 10 degrees further south, the\ncorrelation goes down to 0.08. For the averaged European mid-latitudes, the\ncorrelation between these two variables is poor, therefore contradicting the strong\nlink between LTG and regional temperature suggested by the reviewer.\nFurther, the mean temperature at midlatitudes should also be clearly correlated\nwith the seasonality. For instance, warmer mean summer temperatures will be\nlinked with longer summers in general in an stationary climate, since in a\nstationary climate with the external drivers (greenhouse gas, insolation, etc) are\nconstant, the only source of variability is the atmospheric circulation. The authors\nestablish this link by linking the length of the seasons and the mean seasonal\ntemperature (or the LTG, which as I mentioned are automatically related).\nAs mentioned above, we calibrated our proxy data using the summer duration\ndefined by Cassou and Cattiaux (2016), which is not solely based on temperature\nseasonality. To verify that the varves do not directly record temperature, we\ncorrelated the proxy data during the instrumental period with local temperature\nmeasurements compiled by the Finnish Geological Survey (GTK). This approach\nis similar to the analysis shown in Fig. 2a, but here we use local instrumental\ntemperature. Please note that monthly data are not available, as the instrumental\ndataset combines multiple meteorological stations, and homogenization was only\npossible at annual resolution. As shown in the plot below, this calibration does\nnot produce a meaningful correlation (r = 0.07, p = 0.53). These results have\nbeen included in the revised manuscript (lines 273–278).”\nFig.1. Scatter plot of the relationship between normalised summer thickness from\nthe Nautajarvi varved record expressed in percentage of the total varve thickness\n(proxy) and instrumental annual mean temperature from meteorological stations\nnear to lake Nautajarvi linear regression line of best fit for the period 1882-\n1940CE\nFor the Holocene period and using TraCE-21k data for the simulation of the\nclimate variables (Table 1), the correlation between the European summer\ntemperature (50-70N) and our proxy for European summer days is r=0.45\n(r=0.43 at Nautajarvi 61N and r=0.31 at Diss Mere 51N) a bit lower than the\ncorrelation between the proxy data and the annual LTG (r=0.60) (Table1).\nThis indicates that longer summers tend to coincide with higher mean summer\ntemperatures, particularly in northern Europe, as the reviewer suggests, though\nthe correlation is weaker in central Europe. The stronger correlation with LTG\nimplies that additional factors contribute to the number of summer days\nthroughout the calendar year: about 36% of the variability in reconstructed\nEuropean summer days is explained by LTG, compared with only 20% explained\nby simulated summer temperature. This supports the idea that the LTG plays a\nmore dynamic role in shaping seasonality via its influence on atmospheric\ncirculation. In particular, the link between equator-to-pole LTG and summer\nweather may be mediated by the occurrence of more frequent and persistent\nextreme events, which increase the number of hot days and, consequently, the\nmean summer temperature.\nWe would also like to clarify that, in our study, we have used the annual mean\nLTG rather than summer LTG because the correlation with the proxy record is\nhigher, r = 0.6 (10-yr resolution) and r = 0.49, respectively. We believe it is\nbecause 1) our proxy record responds to the winter:summer ratio and not to the\nsummer season only and 2) the TraCE data has a 10-yr resolution and the\ncorrelation with the annual mean might include the cumulative impact of previous\nseasons / years on a decadal scale. The correlation between annual mean LTG\nand summer LTG is r = 0.82 (Table 1), suggesting that both have a similar\nHolocene trend (see plot below). Major differences are observed during the early\nHolocene when the large ice sheet had a major impact on the annual mean\nrather than the summer LTG. Our proxy records change at 8ka BP with a similar\namplitude as simulated by the annual LTG (Fig. 3a in the manuscript). The\nscaling factor between the annual LTG and the proxy data is constant throughout\nthe Holocene (except from the last 1500 years likely due to human impact as\nexplained to Reviewer#1).\n3 1.5\n1\n2\n0.5\n1 0\n-0.5\n0\n-2000 0 2000 4000 6000 8000 10000 1200-01\n-1 -1.5\n-2\n-2\n-2.5\n-3 -3\nLTG Anom Annual Mean summer LTG_pole_equator\nFigure 2: Comparison of the Annual mean equator to pole LTG and summer LTG\nover the North Atlantic-European region during the Holocene.\nThis is debated in the literature how the excess heat in summer affects the\nfollowing autumn and winter season (Coumou et al., 2015; Park et al., 2019), so\nthe fact that the reconstructed summer days is better correlated to the annual\nLTG than the summer LTG on decadal timescales might suggest the impact of\nthe cumulative effect of the previous summer (i.e. the excess heat absorbed\nduring summer is transferred from the ocean to the atmosphere via radiative and\nturbulent fluxes during autumn and winter (Cohen et al., 2014), so a summer with\nmore extreme hot days might influence on an earlier start of the next summer,\nand a longer summer also increases the likelihood of more extremes, and so on).\nThis also helps to explain the link between summer length, persistence and LTG\non multiannual timescales.\nThe problem arises when trying to extrapolate this link to other climates (past or\nfuture), for which the external drivers have changed or are continuously\nchanging. For instance, when greenhouse gases are increasing and rising the\nmean temperatures, they do more so over the continents than over the ocean.\nTherefore, the link between atmospheric circulation and temperatures becomes\nautomatically more summerlike, lengthening the summers and shortening the\nwinters They do so not because the LTG has changed per se, but because the\nmean temperatures have risen. Since greenhouse-gas forcing also causes a\nstronger rise of mid-latitudes temperatures than tropical temperatures, its effect is\nalso reflected on the LTG. Thus, an alternative explanation could leave the LTG\nentirely out of the reasoning, and just focus on the effect of greenhouse gas\nforcing.\nThe orbital forcing during the mid-Holocene shares this characteristics with\ngreenhouse gas forcing: summer continental temperatures would rise more\nstrongly than ocean temperatures, and mid-latitude temperatures in the Northern\nHemisphere also more strongly than tropical temperatures.\nWe are not entirely certain about the reviewer’s concern, and we hope it has\nalready been addressed. Nevertheless, we provide some additional evidence that\nmay help clarify the point. We also note that Cassou & Cattiaux (2016) used a\nsophisticated dynamical framework to evaluate seasonal length, indicating that\nseasonal timing is not determined solely by mean temperature changes, but\ninvolves more complex processes. Indeed, they suggest that seasonal length\nexhibits strong inter-decadal variability that does not appear to be directly related\nto mean temperature changes across Europe. This suggests that additional\ndynamical factors may be influencing seasonal length, as discussed in their\nstudy.”\nIn Fig. 3 (main text) we show an attribution experiment to evaluate the different\ndrivers changing the annual mean LTG during the Holocene. The experiment\nreveals that the external drivers were not constant and melt water flux (MWF)\nduring the early and mid-Holocene is the main driver for the LTG. Orbital forcing\nplays a major role but only after 5 cal kyr BP. This evolution is not directly\nproportional to greenhouse gas concentrations, reinforcing the idea that the LTG\nreflects more than just external temperature forcing.\nIn response to the reviewer’s comment, we have explored the attribution on the\nHolocene mid-latitude temperature over Europe from TraCE-21k using the same\napproach as in the main text (individual forcing, combined sum of the forcings\nand then a simulation where all the forcings were applied).\nFigure 3. Attribution experiment for simulated mid-latitude annual mean\ntemperature for the North-Atlantic European region.\nFull GHG ICE ORB MWF Combined\nFull 1\nGHG 0.23314867 1\nICE 0.35262319 0.16833867 1\nORB 0.06130117 -0.5514183 -0.0659992 1\nMWF 0.62199011 0.18432744 0.26427453 0.03222126 1\nCombined 0.63561422 0.19647567 0.71137286 0.25599542 0.79177942 1\nTable 2. Correlation coefficients (r) for the Holocene period\nThis revealed a weak correlation between the full simulated temperature\nincluding all forcing and the orbitally-induced temperature is r=0.06 during the\nHolocene and r=0.14 during the mid-Holocene (8-4ka BP) when we observe the\nlongest summers. Thus, European temperature is not well related to orbitally\nforced signal but rather with meltwater fluxes. On the other hand, this attribution\nexperiment, together with the correlation between the full simulated temperature\nand the combined forcing temperature, suggest that internal variability also play\nan important role explaining temperature variability at European mid-latitudes.\nFor the last 100 years, the correlation between temperature and GHGs increases\nconsiderably though.\nFull GHG ICE ORB MWF Combined\nFull 1\nGHG 0.57308839 1\nICE -0.2400985 -0.0725495 1\nORB 0.17377924 0.35775299 -0.4789424 1\nMWF -0.0316104 0.28978215 -0.2162769 0.06934983 1\nCombined 0.07685382 0.62004144 0.56085667 0.14693927 0.42217188 1\nTable 3. Correlation coefficients (r) for the last 100 years (industrial period)\nAdditional evidence that the LTG is not directly responding to the orbital forcing is\nthat the latitudinal insolation gradient alone does not explain the LTG as shown in\nthe plots below (and Fig. S3).\nFigure 4. Left: Scatter plot of the relationship between the equator-to-pole LTG\nand the latitudinal insolation gradient (LIG); Right: Holocene evolution of the LTG\nand the LIG.\nThus, my concern can be summarized as follows: is the LTG really a driver of the\nseasonality or is this link just an artefact due to the very definition of the LTG ?\nWe agree with the reviewer that this is an intriguing question and, according to\nthe literature, the LTG can be both the response and the driver. The mechanisms\nbehind these links are not fully understood yet. Providing past evidence could\nhelp and the climate community is already asking for this support. This is an\nexample from a quote from Coumou et al. 2018: “high-resolution paleo-climate\nrecords over the Holocene period can provide further insights into the circulation\nresponse to temperature gradient changes and put recent trends into a long-term\nperspective. The mid-Holocene provides a possible paleo analogue with\nenhanced high-latitude warming”.\nThis is exactly the main goal of our study. Our study shows that simulated LTG is\nexplaining more variability of the proxy records than summer temperature,\nsuggesting that it might add additional mechanisms to better explain this\nvariability.\nReviewer #3 (Remarks to the Author):\nThe manuscript by Martin-Puertas et al. submitted to Nature Communications\nrepresents an important scientific achievement, obtained through a well-\nstructured approach and detailed investigation. The manuscript is written in a\nmanner that more submissions should strive to achieve in terms of language and\ncare. There are some minor issues that I will outline in the specific comments. It\naddresses a crucial paleoenvironmental issue, which the authors accurately\ndescribe as a lack of “seasonal clock” investigations using natural archives.\nHowever, even though it is indeed an interesting approach, somewhat unique, I\nam not entirely convinced that it is suitable for Nature Communications. Base on\nthe quality of the ms I'm suggesting minor revisions, with the asterisk of being\nunsure about the journal choice.\nYet, I must stress that the use of the \"simple” varve parameter, which is its\nfundamental characteristic, such as varve thickness, is something that more\ninvestigators should aim for and take care of. This shows that it is not always\nnecessary to work with a multiproxy dataset based on numerous analytical\ntechniques and extremely complex statistics. This study demonstrates that a\nwell-structured and constructed hypothesis, paired with a well-adjusted analytical\nprocess, can answer some pressing questions. This was also possible thanks to\nthe extensive study of the sites selected by the authors. This leaves me\nimpressed.\nI abstain from delving into circulation patterns, as I find it too far removed from\nmy expertise. I can only hope that through the review, the Editors will find it\neasier to reach their conclusions. Given that due to the manuscript transfer,\nprevious reviews and the rebuttal were available, I feel obligated to say that some\nof the responses to the questions raised are not satisfactory. This is especially\ntrue at times when reviewers raised concerns, which were met with “part of the\ntext/figure is removed now\" without addressing the underlying problem. Despite\nthat, I’m treating this review as a standalone, new submission.\nTo summarize, I do not find any specific or major flaws in the submitted\nmanuscript; however, I’m unsure if NComms is the appropriate outlet.\nWe thank the reviewer for their feedback and reply to their comments below.\nGeneral comments\nAs Nature Communications is an outlet for a broad range of investigations and\ntherefore for numerous readers outside of “our” field, I’d suggest that the authors\ntake more care in communicating the significance of their research (and in\ngeneral, the paleosciences), as well as the current and future climate state. For\nexample, is the mentioned change of summer season by 6 days (line 26) a\nsubstantial change? Please consider this from the perspective of a non-expert\nreader outside the (paleo)climate field. Why should we care? Strengthen your\npoint.\nThanks for this comment. We have edited to abstract to send a clearer message.\nThe change of summer season by 6 days is for every 1C decrease in the LTG.\nDepending on the emission scenario, our estimation by 2100 is an addition of 13\n- 42 summer days to current summers. Line 23-31: “Our results indicate that\nsummer weather dominated during the mid-Holocene, with an average of 195\nsummer days per year—falling within the extreme upper tail of summer\ndistributions in the early- and late-Holocene. The Holocene variability in summer\ndays aligns closely with simulated past changes in the LTG, supporting the\nhypothesis that dynamical processes influence mid-latitude seasonal weather. A\n1°C decrease in LTG would extend the summer season by ~6 days, potentially\nadding up to 42 summer days by 2100 under a business-as-usual scenario.\nThese findings provide key observational constraints for understanding and\nprojecting seasonal impacts on ecosystems and society.”\nThe climate seasonal clock: frankly, while I have no other choice but to accept\nthe definition provided in the literature, I find this term/wording throws the reader\noff balance. This reads like an easy concept with unnecessary steps and\nverbosity.\nWe agree with the reviewer that this term might be confusing. In the new revised\nversion, we have avoided it as much as possible. However, we believe that the\nsplit of a calendar year in two main seasons that explain the link between\ntemperature and mid-latitude atmospheric circulation is the one that agrees best\nwith the varve seasonality of our lakes (see response to Reviewer#2’s\ncomments), so we still keep it for the calibration of our proxy data but reporting it\nas number of summer days instead of climate seasonal clock. We have also\nchanged figure 2d and have replaced the Holocene climate seasonal clock by\nhistograms displaying the distribution of summer days in the early-, mid- and late-\nHolocene. We believe this new panel highlights the differences between the three\nperiods rather than the averaged values previously shown in the seasonal clock.\nThis allow to see that these distributions are not necessarily Gaussian, and also\nto better highlight the quite large differences that we find along the Holocene. In\nline 302-312, we explain these results: “The range of variability of summer days a\nyear during the Holocene goes from 164 to 202 (Fig. 2d; Extended Data Fig. 1e).\nThe reconstruction reveals that the longest summers occurred during the mid-\nHolocene (3.5 – 8 cal kyr BP; Fig. 3a). The histograms displayed in Fig. 2d show\nthe frequency and distribution of the summer days during the early-, mid- and\nlate-Holocene. Mid-Holocene’s distribution is bell-shaped and centred around\n195 days with most years between 192 and 199 of summer days. In contrast,\nearly- and late-Holocene’s distributions are wider and skewed to the right (early-\nHolocene) and to the left (late-Holocene) but both with a peak around 189\nsummer days. Although there is some overlap with the mid-Holocene distribution,\naveraged summers in this period can be considered extreme in the early- and\nmid-Holocene and happened less than 100 times (Fig. 2d)”\nSummer and weather extremes' persistence is mentioned in 48-49, but later on,\npersistence refers to what I understand as the total number of summer-like\nseason days, which for me is not the same as persistence.\nWe agree that the term persistence may be ambiguous and we agree with the\nreviewer that the use of persistence in climatology is more related to extreme\nevents and atmospheric blockings. In the revised version we have avoided the\nuse of this term to explain our results.\nBe consistent; compound words with the “palaeo” prefix are written in three\ndifferent ways: as one, hyphenated, and with a space. Stick with one.\nDone\nThe first time early/mid/late Holocene are mentioned, it should be immediately\nfollowed by the ages, which are provided later in the text.\nDone\nAlso, what about current and formal Holocene subdivisions?\nWe thank the reviewer for this comment. While we acknowledge the point, we\nbelieve it may not be critical in this context. The terms early, mid, and late\nHolocene are widely used in palaeoclimatology by both proxy-based and\nmodelling communities. For a broad-audience journal such as Nature\nCommunications, we feel it is preferable to retain this commonly used\nterminology, while providing the corresponding calibrated age intervals (cal. yr\nBP) for clarity.\nAround 110-111, if there is still room in the literature, there are other examples of\nsuch behavior and studies using longer and shorter time frames.\nYes, there are indeed many other examples, such as Tiefer See in Germany, as\nwell as varved lakes in Poland and Finland. However, due to limitations on the\nnumber of references, we would need to remove an existing citation to include a\nnew one, which we believe would not significantly change the study’s\nconclusions. Montcortes and Żabińskie likely are the most relevant examples as\nthey have been monitored for a very long time and there are several publications\non the multi-event layers of their varves. In line 224-227, we have added that\nthese examples are the most well-known varved records in Europe.\nDo the authors argue that if varves do not strictly follow the simplest pattern, they\nbecome useless for such an approach? Because in that case, it might not be\nabout the other researchers’ willingness to share the data or even count it; it\nmight be inherently impossible to produce similar records.\nWe rather argue that, for reconstructing the evolution of the seasons / seasonal\nclock, the seasonality recorded by the varves should coincide with the climate\nseasons (i.e. continuing sedimentation during the season) and does not respond\nto phenological event such as a diatom bloom that happens in days or weeks\n(one layer) and the other layer representing sedimentation during the rest of the\nyear (e.g. Meerfelder Maar varves). These varves (and the thickness of the\ndiatom bloom lamina), however, might be useful to reconstruct spring wind\nevents (Martin-Puertas et al., 2012) or any other seasonal characteristics\ndepending on the environmental-climate interpretation of the varve seasonality\nfor each specific lake.\nThe main message here is the huge potential of the thickness of the varve sub-\nlayers, which is a proxy that is not fully exploited yet by the varve community.\nThere are potentially many varved records across Europe and other parts of the\nworld, which the varve pattern might work to reproduce a similar reconstruction\nthat the one presented in this study. Traditionally, the thickness of the seasonal\nlayers is not reported or measured as varved records have been used as a\nchronological tool. Things are changing and varve thickness is more and more\nused as an environmental and climate record. The potential of reporting seasonal\nvariability is also increasing with the development of high-resolution analysis.\nMeasuring and reporting the thickness of the seasonal layers is time consuming\nbut can be very helpful not only for this specific study of the length of the season\nbut applied to other matters. Hopefully this study can inspire others to publish\nseasonal layer thickness.\nDespite previous comments, not all r values are reported with p values.\nDone. We have provided p-values for every r value mentioned in the revised\nmauscript.\nFigure 2 and the referencing text: are the authors satisfied with the relatively\nsmall sample size of the calibration and, hence, the regression equation? n = 40\nbarely meets the minimum and could be a source of bias.\nWe would have liked to have a larger sample size but unfortunately, this is the\nbest we could make given the short overlapping between the reanalysis\ntimeseries and the varved data. There is a strong human impact on the\nNautajarvi catchment from 1940 to 1980, which is discussed in the\nSupplementary Information. This issue is also mentioned by Reviewer 1 and we\nhave replied to it.\nOn the other hand, I’m concerned about the other issues that “plague” the varved\nsequences. The authors suggest that human impact has affected the\nsedimentation processes and thus signal formation; however, only varve\nthickness detrending is reported as a means of dealing with changing sediment\nproperties.\nBased on previous palaeolimnological and lake monitoring studies, we know that\nhuman impact did not significantly hamper the climate signal within the preserved\nvarves.\nIn Nautajarvi, the only exception is the period AD1940-1980, when human impact\nchanged sediment composition (i.e. this is unrelated to the previous 1500 years,\nwhich is discussed in the response to reviewer 1. Just to make that really clear).\nFor the rest of the record, varves kept the same pattern. Sediment compaction is\naffecting the varve thickness, hence the detrending approach as a preventing\nmeasurement. This should be a common practice indeed. As mentioned above in\nthe response to Reviewer#2 the scaling factor of the relationship between the\nproxy and the LTG change, but as shown in Extended Data Figure 1d, the\nvariability pattern at 10yr resolution is very similar in both timeseries suggesting\nthat climate is still the main driver. We think that the change in the scaling factor\nmight be a consequence of human impact and the fact that only the Nautajarvi\nrecord is contributing to the signal as Diss Mere is not laminated for the last 2k.\nHowever, we are not aware of an approach to correct the human impact and we\nare unsure if any correction would be appropriate at all.\nIn Diss Mere, human impact affects varve preservation in the last 2 kyr, so we\ncan’t have varve thickness data for this period. Compaction is not an issue in this\nrecord (i.e. non-detrending and detrending varve thickness data show similar\nvariability during the Holocene)\nFurthermore, figures whenever results of applied regression are used should\nprovide uncertainty bands.\nWe have edited Fig. 3 and Fig. 4 to show the uncertainty bands calculated as the\nstandard error provided by the regression model.\nRegression Statistics\nMultiple R 0.75089038\nR Square 0.56383637\nAdjusted R Square 0.55265268\nStandard Error 2.49383616\nObservations 41\nThe figure caption for panel 2C is confusing, in my opinion. On the other hand,\npanel D presents a clever approach.\nDid you correct for autocorrelation in the time series, as suggested by earlier\nreviews?\nYes, we did.\nFigure S2’s shade is too deep.\nWe have reduced the opacity"}, {"round": 2, "reviewer_comments": {"reviewer_1": "I previously reviewed this manuscript and felt that the science of the paper was generally good, but in my rereading some additional questions have been raised. These issues have more to do with the front half of the paper that established the climatic context of the study and varve calibration. I believe the second half of the paper is still scientifically strong and reasonable, but the establishment of the varve record as a proxy for summer and winter days needs some additional explanation. The paper also needs to consider additional climate system components that respond to orbital insolation, like the Polar Front Jet Stream and North Atlantic ocean-atmosphere pressure systems.\n1) It is not clear to me how the summer and winter days were calculated based on the reanalysis data. According to Cassou, the seasonal clock is defined by specific atmospheric circulation patterns. What atmospheric circulation patterns were used to define a summer day vs. a winder day? These should be described in the main text of the paper prior to the use of the generic summer and winter day terminology.\n2) The climatological description of European weather also seems to be a little shy of the mark. The westerlies and SB are described, but no mention is made of the position or configuration of the Polar Front Jet Stream. The PFJS is shown in the conceptual diagram in Figure 1, but no specific reference is made to it or its influence on storm tracks, etc… The PFJS also responded to changes in orbital insolation over the course of the Holocene, which would have impacted European weather. A more thoughtful consideration of the PFJS and the literature surrounding its influence on European weather is warrented in this manuscript.\n3) The PFJS and westerlies are also influenced by more than simply the latitudinal temperature gradient. Upstream ocean-atmosphere processes in the Atlantic, like the NAO and NAO-like variability on longer timescales can also influence the westerlies and position and intensity of regional pressure systems. These ideas my be integrated in the thinking of this paper, but they could be more explicitly considered.\n4) Temperature is shown to not be a major influence on varve thickness, but I find this confusing because temperature is an important component of summer or winter mean climates. Immediately following the statement that temperature is not a major driver, the varve records are compared to a pollen record of growing degree days, which is a temperature related variable. The supplemental data also indicates that calcite in Dis Mere is related to summer temperature. Why is temperature not more influential? If it’s not temperature, what exactly is it about summer or winter climate that is causing thicker or thinner varves? Storminess is indicated in the supplemental materials as a factor for Dis Mere, but this is not indicated in the main text. It is important to at least state in the main text what the mechanisms/processes are that relates “summer days” and “winter days” to their respective seasonal varve thicknesses.\n5) Lastly, the paper still requires additional editing for language. I understand that English is not the first author’s first language and I am sympathetic to writing in a non-native language – I would struggle to author a high-level paper such as this in a language other than my native English. That said I still suggest that the paper undergoes a thorough editing to smooth out the syntax and improve the narrative flow. For example, many of the sentences are quite long and complex and would benefit from being broken up. I also suggest editing for conciseness. There are many instances where something is said with five words that could easily be said with two. I have made edits in an annotated pdf to illustrate my take on ways the writing could be smoothed out to improve the flow and readability – and thus understanding – of the paper, but I strongly urge the co-authors that are native English speakers to contribute to this effort.", "reviewer_2": "I thank the authors for considering my comments on the previous version. I think this version addresses my suggestions, and I am happy to recommend the manuscript for publication.", "reviewer_3": "The revised manuscript by Martin-Puertas et al. addresses the questions raised by the reviewers and represents a clear improvement over what a sound submission already was. I’m satisfied with the Authors’ responses and appreciate the modified title of the manuscript. If not indicated otherwise, questions raised in this review are left for the Authors to consider as an improvement direction, but don’t need an answer. This is a sound manuscript befitting NComms.\n21: European … seasonality – maybe you can be more specific, seasonality of what?\n22: summer understood as…, or in reference to…?\n35: Is it the high-pressure center called SB, or is the effect of its presence causing SB?\n184: Maybe add that it means “since the LGM”? Brings a nice context window.\n192: Generally, the ice cap influenced and displaced the zonal winds, didn’t it?\n451: I’m not sure, probably omitted it in the previous review – any reasoning for using Laskar over other orbital resolutions available in palinsol? Furthermore, do you mean you’ve calculated isolation for each day of a 365-day year and averaged it? Or are the four seasons meant (solstice, etc.), or something else (palinsol manual suggests that annual averages are computed, but be clear about it)."}, "author_response": "REVIEWER COMMENTS\nReviewer #1 (Remarks to the Author):\nI previously reviewed this manuscript and felt that the science of the paper was\ngenerally good, but in my rereading some additional questions have been raised.\nThese issues have more to do with the front half of the paper that established the\nclimatic context of the study and varve calibration. I believe the second half of the\npaper is still scientifically strong and reasonable, but the establishment of the\nvarve record as a proxy for summer and winter days needs some additional\nexplanation. The paper also needs to consider additional climate system components\nthat respond to orbital insolation, like the Polar Front Jet Stream and\nNorth Atlantic ocean-atmosphere pressure systems.\n1) It is not clear to me how the summer and winter days were calculated based\non the reanalysis data. According to Cassou, the seasonal clock is defined by\nspecific atmospheric circulation patterns. What atmospheric circulation patterns\nwere used to define a summer day vs. a winder day? These should be described\nin the main text of the paper prior to the use of the generic summer and winter\nday terminology.\nWe did not calculate the number of summer and winter days ourselves. The\ndataset was provided by Cassou and Cattiaux, and follows the definition outlined\nin their paper. This is described in lines 30-51 of our manuscript. The definition of\nthe seasons is based on the sign of the relationship (regression coefficients)\nbetween daily sea level pressure and temperature. This is explicitly said in lines\n39-42.\n2) The climatological description of European weather also seems to be a little\nshy of the mark. The westerlies and SB are described, but no mention is made of\nthe position or configuration of the Polar Front Jet Stream. The PFJS is shown in\nthe conceptual diagram in Figure 1, but no specific reference is made to it or its\ninfluence on storm tracks, etc… The PFJS also responded to changes in orbital\ninsolation over the course of the Holocene, which would have impacted\nEuropean weather. A more thoughtful consideration of the PFJS and the\nliterature surrounding its influence on European weather is warrented in this\nmanuscript.\nThe role of the PFJS is implicitly included in line 49 (see comment inserted in the\nrevised version of the manuscript) and lines. This is shown in Fig. 1 to illustrate\nthe impact of the LTG on the main westerlies circulation (with increased\nmeandering when the LTG is weak). Nevertheless, to follow the reviewer’s\nsuggestion, we have edited the sentence where we define the Scandinavian\nBlocking to explicitly mention the polar jet (line 37). However, we believe that an\nextended introduction and discussion of modes of climate variability and potential\nmigration of the PFJS over time would not add a relevant contribution to this\nmanuscript and would divert attention from its main objective, which is to test the\nexisting hypothesis of the LTG. We therefore prefer to present the context of\nour study at the level of drivers rather than feedback mechanisms, which\nintroduce a large uncertainty.\nWe acknowledge that the climate system is highly complex, and addressing all\npotential physical mechanisms lies beyond the scope of this proxy-based study.\nHere, we focus on a specific aspect of this complexity by providing statistical\nsupport for the hypothesis that the LTG influences the summer season, which we\nsee as a valuable contribution to current climate science rather than an attempt\nto resolve the underlying physics and feedback mechanisms, which are currently\nassociated with a large uncertainty. Based on our results, the LTG accounts for\npart of the observed variability (r = 0.6), but not all of it. Other factors—such as\nthe PFJS, directly as a response of the radiative forcing or through the LTG\n(Cohen et al., 2014)—may also play a role, as the reviewer suggests, but there is\nstill a large uncertainty about how these feedbacks and links work. We are\nconfident that the current introduction of the manuscript together with the\nliterature review summarise the main hypotheses, the relevant atmospheric\ndynamics and lack of knowledge to understand the relevance of the study and\nsupport the discussion of the results.\n3) The PFJS and westerlies are also influenced by more than simply the\nlatitudinal temperature gradient. Upstream ocean-atmosphere processes in the\nAtlantic, like the NAO and NAO-like variability on longer timescales can also\ninfluence the westerlies and position and intensity of regional pressure systems.\nThese ideas may be integrated in the thinking of this paper, but they could be\nmore explicitly considered.\nWe agree with the reviewer that the PFJS and westerlies are not solely\ninfluenced by the LTG. However, we insist that this topic is outside the scope of\nthis paper. Our proxy data do not provide sufficient evidence to meaningfully\ncontribute to the complex discussion, due to the large uncertainty in climate\nmodels, of the physical mechanisms underlying recent changes in seasonality.\nThe strongest evidence we can offer from the proxy records is the robust\nstatistical correlation between one potential driver (i.e. LG) and the climate\nresponse (i.e. changing seasons). Indeed, demonstrating that the LTG played a\nconsistent role in the past—the main goal of this paper—should help encourage\nfurther research on potential feedback mechanisms linked to the LTG and\ncontribute to reducing existing uncertainties.\nThere is a supplementary figure to illustrate the potential relationship between the\nLTG and zonal winds, based on what has been suggested from some modelling\nstudies. However, we recognise that this remains a highly debated topic in\nclimate science (many of these studies are cited in our manuscript) and there is a\nlarge uncertainty about it, so we prefer not to based our discussion on it,\nin addition to the reasons mentioned above. We fully agree with the reviewer\nthat this is an interesting and relevant topic, but a focus for future research.\n4) Temperature is shown to not be a major influence on varve thickness, but I\nfind this confusing because temperature is an important component of summer or\nwinter mean climates. Immediately following the statement that temperature is\nnot a major driver, the varve records are compared to a pollen record of growing\ndegree days, which is a temperature related variable. The supplemental data\nindicates that calcite in Dis Mere is related to summer temperature. Why is\ntemperature not more influential? If it’s not temperature, what exactly is it about\nsummer or winter climate that is causing thicker or thinner varves? Storminess is\nindicated in the supplemental materials as a factor for Dis Mere, but this is not\nindicated in the main text. It is important to at least state in the main text what the\nmechanisms/processes are that relates “summer days” and “winter days” to their\nrespective seasonal varve thicknesses.\nWe appreciate the reviewer’s continued engagement with this issue, which has\nbeen discussed extensively throughout the review process. We would like to\nclarify that our proxy is the contribution of the season to the annual variability\n(season-to-annual ratio) rather than the seasonal varve thicknesses themselves.\nAs stated in the manuscript and in our previous responses (particularly to\nReviewer #2), our results indicate that temperature is not the primary driver\nof variability for this ratio (i.e. interplay between the summer and winter)\nand the LTG can explain more variability. However, it does not mean that\ntemperature is not contributing to the variability of seasonal deposition in\nthe lake, as the reviewer interprets.\nNonetheless, we have added a new chapter to the supplementary information that\nexpands on the interpretation and calibration of the varves. Due to space\nlimitations, this material could not be included in the main text. However, since the\nproxy records have already been interpreted and published, citing this work in the\nmain text alongside a detailed explanation in the supplementary information should\nbe sufficient. While some of the content of this new section overlaps with material\npresented elsewhere in the main text and supplementary sections, we believe this\naddition strengthens and clarifies the paper.\n“4. Proxy calibration\nLake Nautajärvi still forms varves today, enabling the calibration of proxy data with\ninstrumental data. According to Ojala and Alenius (2005)10, variability of the varve\nthickness and thickness of the seasonal layers during 1881-1993 CE significantly\ncorrelate with annual, winter and summer precitation and spring temperature\n(Table S1), suggesting a combined response to different variables.\nIn this study, we are interested in the summer to winter ratio in order to reconstruct\nthe European seasonal clock, and we introduce a new varve proxy that consists in\nthe percentage of the annual signal represented by the summer and winter layers\n(i.e. % summer thickness and % winter thickness). For the proxy calibration, we\nuse the original dataset of number of summer days created by Cassaou and\nCattiaux (2016)7, which is based computations from several combinations of data\nsets (EOBS high-resolution gridded product, NCEP and NOAA-20CR reanalyses).\nFor this study we have used the NOAA-20CR dataset because is the longest one\nand overlaps with the proxy dataset.\nPrior to the calibration, a detailed investigation of potential human impact\ninfluencing lake sedimentation in Nautajarvi during the calibration period covered\nby NOAA-20CR reanalysis data has been carried out. The land use history of the\n20th century in the Nautajärvi catchment area can be traced from historical maps\nand aerial photographs (Maanmittaushallituksen uudistusarkisto 1914, 1925,\nNational Land Survey of Finland 1958, 1977, 1986) (Figure S1). The earliest maps\nfrom 1910–1920 CE show two natural inflow streams, one from Ristijärvi\n(northwest) and the other from northeast, but also indicate cultivated fields\nupstream and along these stream systems. However, peatland areas in the\nNautajärvi catchment were still untouched and only these two natural inlet streams\nexisted. The first ditches were excavated between 1920–1955 CE, which cover ca.\n14% of current artificial streams network. These excavations focus on pristine\npeatlands 1-3 km northeast of Nautajärvi. In general, the forest drainage improved\nforest growth on pristine peatlands and the most intense ditching period in Finland\nwas in the 1950s and 1960s. The forest peatland drainage has been reported to\nincrease the sediment and nutrient load23–25. The nutrient load is reduced gradually\nand depends on the mire and catchment properties26. The increase in the\ndischarge volume and materials is usually short-lived (few years) and forest\ndrainage can also level the discharge with reducing peak runoffs and increase the\nrunoff during low-flow periods23,24. The Nautajärvi catchment area experienced\nmultiple ditching events between 1955–1975 CE, and one of these was an\nexcavation of a new stream inlet into Nautajärvi from southeast (Figure S1). Ca.\n65% of the artificial ditches in the Nautajärvi catchment area were excavated\nbetween 1955–1975 CE. Between years 1975–1985 CE no artificial ditches were\nexcavated in the Nautajärvi catchment area and most of the fields were reforested\ndue to termination of agricultural activities. After 1985 CE ditching activities related\nonly to maintenance of existing drainage network.\nThe comparison and correlation of the proxy data with the reanalysis were\nconducted at annual resolution from 1900 to 2000 CE (Supplementary Information,\nFig. S2). During the period of intensified human impact due to ditching activities,\nthe climate signal in the sediment decreases from r = 0.76 to r = 0.41(Fig. S2).\nAlthough the number of datapoint is reduced to n = 41, we run the calibration from\n1900 to 1940 CE only, when both, the summer and winter layers respond best to the\nduration of the climate seasons defined by Cassou and Cattiaux, 20167.\nTo assess potential temperature bias in this calibration (i.e., whether the proxy\nreflects only temperature seasonality), a similar analysis was conducted using\nlocal temperature measurements from meteorological stations near the lake. As\nanticipated by Ojala and Alenius (2005)¹⁰ (Table S1), the correlation is weak (r =\n0.07, p = 0.53, n = 41). This finding supports the interpretation that the seasonal\nvariability recorded in the lake does not directly track local temperature, but instead\nreflects the combined influence of multiple meteorological factors shaping summer\nweather conditions.\nUnfortunately, Diss Mere no longer preserves varves, preventing calibration. The\npalaeoenvironmental interpretation of the varves3,4 together with the lake\nmonitoring1, support that the seasonal layers are a consequence of continue\ndeposition during the lake seasons, instead of punctual events, and the duration\nof the lake seasons broadly coincide with the European climate seasons (not that\nlake monitoring data cover four year only preventing significant statistical\ncorrelations). Nevertheless, the Holocene evolution of the summer-to-annual ratio\nrecorded in both varved records is comparable, varying within the same range.\nThis suggests that both sites capture the same variability and respond to the same\nClimate variable Varve thickness Winter layer Summer layer\nAnnual Temp. 0.187* 0.153 0.189\nWinter Temp. 0.129 0.078 0.139\nSpring Temp. 0.331* 0.305* 0.324*\nSummer Temp. -0.130 -0.099 -0.134\nAnnual Prec. 0.420* 0.398* 0.408*\nWinter Prec. 0.367* 0.300* 0.372*\nSpring Prec. 0.124 0.162 0.107\nSummer Prec. 0.320* 0.339* 0.299*\ndriving factors. To perform the Holocene reconstruction of the number of summer\ndays shown in the main text, we averaged the summer-to-annual ratio from both\nrecords and applied the calibration derived from Nautajärvi (Extended Data Figure\n1).”\nTable S1. Pearson’s correlation coefficients (r) for Lake Nautajärvi varve data and\ninstrumental meteorological measurements of the Jyväskylä weather station between 1881-1993 CE. Modified from Ojala and Alenius (2005)10. * Marked correlations are significant\nat p < 0.05.\nWe agree with the Riviewer#1 that the statement in line 213 (now removed from\nthe revised version) “ To identify potential temperature-bias on this calibration,\nsimilar analysis has been performed with data from meteorological stations near\nthe lake to identify the relationship between the proxy data and local temperature.\nThe correlation is poor (r = 0.07, p-value = 0.53), which shows that the seasonal\nvariability recorded in the lake is not directly responding to local temperature but\nrather to summer weather conditions” leads to misunderstanding. These\nsentences originally addressed a Reviewer #2’s comment. The correlation\ncoefficient is only based on the calibration period and is in agreement with\nresults shown in the table above. Considering Reviewer #1’s recent feedback, we\nagree they were somewhat out of context in the main manuscript and have\nmoved them to the Supplementary Information (copied section above), where the\nrelationship between the proxy data, temperature, and season length is\ndescribed, addressing both reviewers’ concerns.\nHowever, we want to ensure that the manuscript addresses Reviewer #2’s point\nregarding the potential autocorrelation between LTG, temperature, and summer\nlength, and the possibility that radiative forcing alone could explain changes in\nthe season without considering the role of the LTG. This is an important concern\nthat has been highlighted throughout the review process by different reviewers.\nAccordingly, we have added the following lines (342–356) to address it “We\nconducted a similar analysis using TraCE-21ka-simulated summer mean\ntemperature for the European grid between 50–70°N. While the correlation is\nlower, it remains significant (r = 0.45, p < 0.001), indicating that longer summers\ngenerally coincide with higher mean summer temperatures. The stronger\ncorrelation with the LTG suggests that additional factors influence the number of\nsummer days over the calendar year: approximately 36% of the variability in\nreconstructed European summer days is explained by the LTG, compared with\nonly 20% explained by simulated summer temperature. This supports the notion\nthat the LTG exerts a more dynamic influence on seasonality through its impact\non atmospheric circulation. In particular, the relationship between the equator-to-\npole LTG and summer weather may be mediated by the occurrence of more\nfrequent and persistent extreme events, which increase the number of hot days\nand, consequently, raise the mean summer temperature.” This refers to the\nintroduction, where we present the three main hypotheses proposed to explain\nrecent changes in summer weather: radiative forcing, the LTG, and aerosols. Our\ndata indicate that, at decadal to millennial scales, the impact of the\nmodeled LTG is remarkably consistent with the proxy data, without\nexcluding additional contributors. This represents a key finding itself, as\nclimate reconstructions more commonly reveal discrepancies with\ntransient climate model simulations over the Holocene (e.g., the Holocene\ntemperature conundrum).\nRegarding the comparison of our proxy record with the GGD: while the GGD is\nnot considered an indicator of summer length in climatology, within palaeoclimate\nresearch it represents the closest available metric for comparison. The two\ncurves show similarities but are not identical, even though they derive from the\nsame record. This supports the interpretation that they do not fully reflect the\nsame climate signal—GGD primarily represents the evolution of the growing\nseason, which is temperature-driven, and a given value may correspond to either\na hot, short summer or a mild, long one. We think it is good to show the\ncomparison of two different proxies representing “summer duration” even when\nthe summer is defined by different criteria (much like in meteorology where the\nparameters to define the summer differ across studies). We have added\nadditional clarification in lines 335-339.\n5) Lastly, the paper still requires additional editing for language. I understand that\nEnglish is not the first author’s first language and I am sympathetic to writing in a\nnon-native language – I would struggle to author a high-level paper such as this\nin a language other than my native English. That said I still suggest that the\npaper undergoes a thorough editing to smooth out the syntax and improve the\nnarrative flow. For example, many of the sentences are quite long and complex\nand would benefit from being broken up. I also suggest editing for conciseness.\nThere are many instances where something is said with five words that could\neasily be said with two. I have made edits in an annotated pdf to illustrate my\ntake on ways the writing could be smoothed out to improve the flow and\nreadability – and thus understanding – of the paper, but I strongly urge the co-\nauthors that are native English speakers to contribute to this effort.\nWe sincerely appreciate the reviewer’s effort in editing the manuscript. We have\naccepted some of the suggested changes and carefully revised sentences where\nedits slightly altered the original meaning. Additionally, we have provided\ncomments explaining our perspective in cases where we respectfully disagreed\nwith the reviewer’s suggestions (referring to general comments 2 and 3, lines 50\nand 256).\nReviewer #2 (Remarks to the Author):\nI thank the authors for considering my comments on the previous version. I think\nthis version addresses my suggestions, and I am happy to recommend the\nmanuscript for publication.\nMany thanks. We are pleased to hear so. The feedback was very constructive\nand helped us to shape and polish the main message of the manuscript.\nReviewer #3 (Remarks to the Author):\nThe revised manuscript by Martin-Puertas et al. addresses the questions raised\nby the reviewers and represents a clear improvement over what a sound\nsubmission already was. I’m satisfied with the Authors’ responses and appreciate\nthe modified title of the manuscript. If not indicated otherwise, questions raised in\nthis review are left for the Authors to consider as an improvement direction, but\ndon’t need an answer. This is a sound manuscript befitting NComms.\n21: European … seasonality – maybe you can be more specific, seasonality of\nwhat?\n22: summer understood as…, or in reference to…?\n35: Is it the high-pressure center called SB, or is the effect of its presence\ncausing SB?\n184: Maybe add that it means “since the LGM”? Brings a nice context window.\n192: Generally, the ice cap influenced and displaced the zonal winds, didn’t it?\n451: I’m not sure, probably omitted it in the previous review – any reasoning for\nusing Laskar over other orbital resolutions available in palinsol? Furthermore, do\nyou mean you’ve calculated isolation for each day of a 365-day year and\naveraged it? Or are the four seasons meant (solstice, etc.), or something else\n(palinsol manual suggests that annual averages are computed, but be clear\nabout it).\nThanks, we have changed / clarified the points above in the main text and\nmethods.\nPoint-by-point response to reviewer’s comments\nREVIEWERS' COMMENTS\nReviewer #1 (Remarks to the Author):\nThe authors have adequately addressed the issues I have raised and I do not have\nfurther comments or issues to raise. This is an interesting paper that makes an\nimportant contribution and I believe it will be well received. I appreciate the\nauthors' cooperation with and engagement in the review process.\nWe are pleased to hear that the reviewer is satisfied with the current version of the\nmanuscript. We sincerely thank them for their time, effort, and valuable contribution to\nimproving this paper and supporting its publication."}, {"round": 3, "reviewer_comments": {"reviewer_1": "The authors have adequately addressed the issues I have raised and I do not have further comments or issues to raise. This is an interesting paper that makes an important contribution and I believe it will be well received. I appreciate the authors' cooperation with and engagement in the review process."}, "author_response": ""}]

Decision letter