A European monsoon-like climate in a warmhouse world

Domain: earth_science
Published: 2025-10-28
Editorial outcome: minor_revision

Abstract
The middle Eocene warmhouse period (45 million years ago) featured atmospheric carbon dioxide concentrations equivalent to those projected under high future emission scenarios. Seasonal-to-weather timescale climate reconstructions from this period can provide critical insight into the impact of Anthropogenic warming on intra-annual variability in temperature and precipitation. Here, we combine daily-scale reconstructions of the evolution of temperature and the water cycle in western Europe based on stable oxygen and clumped isotope analyses on the fastest-growing gastropod known in the fossil record: Campanile giganteum. Our dataset shows that the middle Eocene of western Europe featured monsoon-like conditions, with seawater temperatures of ~24 °C during mild and wet winters, >30 °C during hot and dry spring and autumn seasons, and ~28 °C during warm and comparatively wet summers. Coupled climate model simulations using the Community Earth System Model indicate these seasonal variations in temperature and precipitation were driven by shifting atmospheric and oceanic circulation regimes over Western Europe, with winds from different directions bringing distinct waters to the region and minimal wind during spring reducing cooling through diminished latent heat flux. Our results highlight that Europe may experience wetter summers with more frequent extreme rainfall events under future high emissions scenarios.

Introduction
Anthropogenic carbon emissions and land-use change are pushing Earth’s climate to a warmer state1. General Circulation Models (GCMs) project a significant increase in the intensity and frequency of extreme rainfall events in monsoon regions under warmer climate scenarios2. In Europe, more frequent and severe extreme weather events have been observed over the past years3,4. However, the large spread in climate model projections, and a lack of direct, seasonal-scale climate data from past warm periods hamper consistent and reliable projections of the impact of warming on the seasonal variability in temperature and precipitation2,5.

One of such warm periods is the Lutetian (middle Eocene; ~41–48 million years ago6). With atmospheric CO2 levels of ~1000 ppmV7, resembling projections for the year 2300 CE under Shared Socioeconomic Pathway (SSP) 5–8.51, and averaged deep-sea temperatures up to 10 °C warmer than today8, the Lutetian climate is referred to as a “Warmhouse period”9. Together with modelling of future climate scenarios10, the Lutetian analogue presents a way to understand the impact of high global mean temperatures on the seasonal structure of climate. Our knowledge about past warm time intervals such as the Lutetian is mostly based on geochemical proxy records from (micro) fossils in sedimentary archives, which generally yield information about past climate on long (>1000 year) timescales (e.g. ref. 9). While instrumental for our understanding of climate trends through the Cenozoic, these archives do not resolve information about fundamental aspects of climate such as short-term climate feedbacks, seasonality, and weather extremes11,12. This is problematic because the impact of extreme weather events on human society is generally higher than changes in climatic means13.

The occurrence of extreme events is intrinsically linked to the seasonal distribution of temperature and precipitation14. This seasonal impact on the distribution of extreme events is particularly strong in western Europe15. The Western European climate is heavily influenced by the strength of the Westerlies, which transport moisture from the Atlantic Ocean to the continent. In the current climate state, occasional seasonal variability in the strength of these westerly winds, caused by changing temperature differences between the continent and the North Atlantic Ocean16 can cause a phenomenon called the “European Monsoon”. It is characterized by a dry spring season and a wetter summer season brought about by a resurgence of the Westerlies around June16. It differs from the much stronger Indian Monsoon, which results from the seasonal migration of the Intertropical Convergence Zone (ITCZ; ref. 17). Such seasonally contrasting precipitation patterns are uncharacteristic for temperate latitudes in the present day. High-resolution models for European climate predict that Arctic Amplification of warming will result in a weakening of the Westerlies in the spring/summer season, which would counteract the European Monsoon pattern (e.g., 14, 15, 18) and cause an increase in prolonged dry spells in summer and intense precipitation events in winter in the mid-latitudes19. Yet, it has so far not been verified if the European Monsoon phenomenon indeed ceases under warmer climate states. Idealized simulations of seasonal temperature variability in a warmer world could help understand such monsoon-like climates in higher latitudes. Additionally, assessing the seasonal impact of global warming on European climate requires archives that reliably record seasonal variability during past warmhouse periods. Fossil mollusc shells are excellent archives for deep time palaeoclimatological data with sub-annual resolution, as they can preserve records with a resolution of hours to weeks20–22.

Here we present a unique ultra-high resolution δ18Oc record containing multiple years of weather-timescale variability in the Eocene in the giant marine gastropod Campanile giganteum (Lamarck, 1804) from the middle Lutetian deposits of Fleury-la-Rivière, in the shallow marine (2–20 m23,24) Paris Basin in France. Recent research has shown that with growth rates up to 60 cm/year along the helix25, far exceeding those of all other fossil molluscs, these giant gastropods have the unique potential to record weather-timescale variability in the Eocene greenhouse world25. Therefore, we generated a high-resolution δ18Oc record and used seasonal-scale clumped isotope analysis to separate the effects of temperature and the water cycle on the δ18Oc values. We use our proxy results as a benchmark against which to test middle Eocene seasonality outcomes from Community Earth System Model (CESM) version 1.0.5, which simulates middle Eocene climate with a similar palaeogeography and pCO2 (4x pre-industrial; 1120 ppmV) compared to the middle Lutetian26. To assess the variability in weather regimes, we extended the existing equilibrated simulations to generate 30 years of daily output, in addition to 100 years of monthly output. Based on this data-model comparison, we show that the Western European climate featured a strong European Monsoon-like climate during the Lutetian warmhouse.

Results
Seasonal variability recorded in the oxygen isotope composition of C. giganteum shell carbonate
The stable oxygen isotope (δ18Oc) values in the shell aragonite of C. giganteum vary periodically between −2.5‰ and +1.0‰ VPDB in ~4.5 cycles (Fig. 1; Supplementary Fig. 1). The cycles exhibit a platykurtic shape, defined by sharper maxima and more prolonged minima. Assuming a quasi-sinusoidal temperature progression through the year, these sharper peaks are a typical signature of winters, when the growth slows in modern molluscs27,28. This winter slow-down of growth is confirmed by the presence of visible growth breaks at locations in the shell with high δ18Oc values (Fig. 1). We used an internal age model based on the periodic δ18Oc record (following ref. 29), calibrated with growth increment counting (see Methods) to place our δ18Oc measurements on a chronology relative to the annual cycle, assuming ~365 days in a year and defining a year by one cycle in δ18Oc. Our record shows variability on a scale of days superimposed on this seasonal cycle, most notably in the summer (Fig. 1). The amplitude of these sub-seasonal δ18Oc variations (0.3-0.5‰) exceeds the variability observed within the same growth increment (see Supplementary Fig. 2), and thus reflects true variability in the growth environment of C. giganteum on a daily scale. Assuming the periodic δ18Oc variability observed in C. giganteum is seasonal, this specimen records roughly 4.5 years of near-daily environmental variability in its shell. Although it is difficult to determine how well the recorded 4.5 years reflect the broader middle Eocene climate of Western Europe, the consistent δ¹⁸Oc variability across these years suggests they are reasonably representative of typical climate conditions during that period.

Absolute seasonal temperature reconstructions using clumped isotope palaeothermometry
Since the δ18Oc proxy is sensitive to variations in the δ18O of the water (δ18Ow) from which the shell carbonate is precipitated and the temperature of the water30, the δ18Oc variability in Fig. 1 cannot directly be translated to temperature variability. Therefore, we have reconstructed palaeotemperatures independent from δ18Ow by using the carbonate clumped isotope thermometer31 on a selection of samples from each of the four seasons. To define these seasons, we assumed a priori that the maximum δ18Oc values, associated with growth breaks, represent winter, and the minimum δ18Oc values occur in the calendar summer, with spring and autumn seasons in between (see Fig. 2). This age model was independently corroborated by counting visible growth increments on the exterior of the shell (Methods; Supplementary Fig. 3; Supplementary Data file S1), previously established to reflect the semidiurnal tidal cycle25. While not necessarily perfect representatives of modern-defined meteorological seasons (e.g., summer as the three-month average of conditions between June 1st and August 31st), the sets of clumped isotope data cover the main seasonal variation in the middle Eocene climate.

Clumped isotope analyses yielded water temperatures of 33.2 ± 4.4 °C for spring, 27.9 ± 3.8 °C for summer, 30.3 ± 3.8 °C for autumn and 24.5 ± 3.8 °C for winter (see Fig. 2). These palaeotemperatures corroborate other annual mean temperature reconstructions from the same palaeolatitude, based on middle Eocene oysters and foraminifera (20–30 °C32; 23–32 °C33). However, the timing of maximum temperature here is in spring, whereas a maximum seawater temperature is expected in summer, where the δ18Oc record reaches the lowest values26,33. This finding casts strong doubts on the assumption that δ18Ow remains constant throughout the year, which is common in δ18Oc-based seasonality reconstructions.

Reconstructions of seasonal water stable isotope variability in the middle Eocene Paris Basin
We reconstructed the δ18Ow value for every season based on our clumped isotope-based temperature reconstructions, the seasonal δ18Oc measurements in C. giganteum, and the relationship between the δ18Oc value of aragonitic shells, δ18Ow and the temperature during shell formation34. Doing so yields δ18Ow values of +1.56 ± 1.00‰ VSMOW in spring, −0.27 ± 0.87‰ VSMOW in summer, +0.84 ± 0.87‰ VSMOW in autumn and +0.94 ± 0.85‰ VSMOW in winter (see Fig. 2). In modern shallow marine settings, shifts in δ18Ow values of this magnitude are predominantly caused by the balance between evaporation, which removes isotopically light water and raises δ18Ow values, and precipitation, which adds isotopically light freshwater and lowers δ18Ow values35,36. These reconstructions therefore suggest a comparatively dry spring season and a wet summer, with a more moderate autumn and winter season.

Reconstructions suggest a European Monsoon-like climate during the middle Eocene
The high variability observed in the δ18Oc record during the summer season coincides with a drop in temperature and a decrease in δ18Ow. To facilitate a drop in temperature and δ18Ow in the Paris Basin in summer, an influx of cooler water is needed that is lower in δ18Ow. We hypothesize that this decoupling of temperature and δ18Ow from the Lutetian spring season into the summer is the signature of a transition from the hot, dry spring to a warm, wet summer. Recently, seasonally variable fluvial discharge has been suggested for the Lutetian Paris Basin, based on strontium isotope data from bivalve shells37. The increased δ18Oc variability in the Lutetian summer observed in the C. giganteum record suggests that the low-δ18Ow freshwater influx in this season was likely concentrated in intense pulses, which we interpret to reflect an increase in the frequency of convective rainfall events. This suggests that, rather than drier summers and wetter winters, as predicted for a warmer-than-present European climate19, the Lutetian warmhouse climate seems to have featured a seasonal transition from a warm and dry spring to a summer with intense rainfall, akin to an extreme version of the present-day European Monsoon phenomenon. This is in stark contrast with the mild and moderately wet climate with equal distribution of precipitation throughout the year experienced in present-day western Europe38.

Data-model agreement on an intensified middle Eocene European Monsoon-like climate
CESM simulations for the late-middle Eocene (38 Ma) show annual mean air temperatures of 24.7 °C (23.0–26.3 °C) for the Paris Basin region, and 660 mm (440-810 mm) of annual precipitation (25/75 percentile range; Fig. 3). Our model palaeogeography lacks the spatial resolution to resolve the small marine embayment that constitutes the Paris Basin. As a result, no modelled seawater temperatures are available for this basin. Nevertheless, considering the shallow water depths in this embayment24, we regard near-surface air temperatures as the most appropriate analogue for local seawater temperatures. Overland, we see a pronounced seasonal cycle, with monthly mean temperatures ranging between 15.3 °C in January and 36.1 °C in July. The monthly precipitation distribution is relatively flat, with July being the wettest month. Daily precipitation statistics, however, show a pronounced dry period in late spring (May-June) followed by an abrupt shift towards much wetter conditions in early summer (Fig. 3a; Supplementary Fig. 4). During this peak, convective precipitation makes up nearly 100% of all summer precipitation (see Fig. 3b), suggesting a major contribution from short, intense precipitation events. A brief drier interval in autumn is followed by a steady increase in average precipitation as well as daily variability in winter. While the simulated mean annual air temperatures (24.7 ± 1.7 °C) agree with the shallow marine temperatures reconstructed by carbonate clumped thermometry from C. giganteum (28.9 ± 3.3 °C), modelled air temperatures do not replicate the seasonal seawater temperature pattern observed in the data with hot spring and autumn and milder summers (see Fig. 3a). The modelled surface air temperatures clearly reveal higher seasonal contrast than the data, but this may be caused by the fact that C. giganteum grew much slower during the winter and may not have recorded the coldest winter temperatures. Model simulations of past warm climates generally show high seasonal temperature contrast compared to proxy data from the same location and time period. It is a challenge to simulate low equator-to-pole temperature gradients and mild winter temperatures without unrealistically high (>50 °C) summer temperatures in climate models (e.g., ref. 39). While a recent proxy-model comparison during the mid-Piazentian Warm Period achieved better seasonal agreement between mollusc-based temperature records and model outcomes18, we note that mollusc-based reconstructions remain challenging to compare directly with model outcomes due to their sensitivity to local climate variability.

Over Eocene Northern Africa, we find a temperature seasonality similar to the proxy record, with an intense monsoonal precipitation pattern, but with a much higher annual temperature (Supplementary Fig. 4; see also Supplementary Fig. 5). Despite our model configuration using a 38 Ma palaeogeography, similar seasonal patterns can be recognized in DeepMIP simulations39 for the early Eocene (50 Ma; Supplementary Fig. 5 and 6). The latter shows an intensification of the hydrological cycle at middle latitudes and a poleward expansion of monsoonal conditions40. DeepMIP simulations generally show wetter conditions over Europe compared to our simulations, as well as cooler temperatures, accompanied by a more pronounced summer precipitation peak, especially over southwestern Europe. Cooler temperatures in the DeepMIP results can be explained by the standard 3xCO2 forcing compared to the 4xPIC (including CH4) used here, making Europe 3–5 °C warmer in our simulations. The lower latitude of our site in 55 Ma versus 38 Ma may also explain the tendency towards more pronounced summer wet seasons. Intense summer precipitation is more pronounced compared to the ensemble mean in the 55 Ma CESM1.2 simulations (ref. 41; see also Supplementary Fig. 7).

A comparison to distant future conditions over Europe is less intuitive, as precipitation changes in summer are dominated by drying over Southern Europe and little change over central Europe (CMIP6 SSP5.85; see e.g. ref. 42). These results also show a strengthening of westerly winds in winter and overall weaker circulation patterns in summer. In our own extended (2000 yr) pre-industrial 4xCO2 simulations, we see small changes in Central Western Europe precipitation as well (see also Supplementary Fig. 8). Despite a tendency towards a converging circulation pattern, the growing influence of upper ridging, elongated areas of relatively high atmospheric pressure, seems to have a more suppressive effect on summer precipitation as noted in CMIP6 simulations. That said, we note that middle Eocene conditions are still much warmer than any future references considered here (12–15 °C globally, versus 3–5 °C at 2100 or 6–8 °C under 4xCO2).

Within the context of middle Eocene conditions, we further test the sensitivity of the climate conditions shown here to (small; 30–38 Ma) changes in the palaeogeography, greenhouse gas levels, and the orbital configuration (Supplementary Fig. 9). None of these external forcings influences the results shown previously in a significant way. We see an overall cooling resulting from lower atmospheric carbon levels, little effect from the palaeogeography, and an increased seasonality with higher Northern Hemisphere summer insolation. While this means that our results are robust under this range of possible Eocene conditions, the role of these in comparison to the present day is likely still substantial, particularly that of the palaeogeography (see e.g. ref. 26, 39). While the annual proxy-based temperature is matched only by the deep tropics in the current climate, we find the best match at middle latitudes for the middle Eocene (Supplementary Fig. 10). In both cases, the best match to seasonality is found in the sub-tropics, which is not surprising as these experience the most pronounced monsoonal climates.

Seasonality in Westerly wind strength drives mild summers in the middle Eocene
A closer look at the circulation patterns around western Europe and the associated weather regimes shown in CESM simulations for the middle Eocene help to interpret the proxy record (Fig. 4). Through winter and early spring, we see persistent westerly to southwesterly winds across the region. These winds mostly disappear in late spring, transitioning into stronger northerly to northeasterly flow in summer to early autumn. A brief pause in prevailing winds is quickly followed by a return of the westerlies in late autumn toward winter, a pattern reminiscent of the modern European Monsoon16. A convergent circulation pattern over much of western central Europe (including the Paris Basin) provides the conditions needed to produce the convective rainfall events which drive variability in our daily climate record (Fig. 4f). This corresponds to an expansive region of lower surface pressures surrounded by high pressure over the Atlantic Ocean and Mediterranean/Paratethys.

A limitation of the model simulation is the absence of a shallow marine environment near the Paris Basin in the modelled palaeogeography. In addition, the horizontal model resolution prevents an adequate point-by-point comparison to the proxy site. This is a common limitation of model-proxy comparisons. We therefore only consider regional averages and larger-scale climatic conditions. We can argue which of the surrounding waters primarily influenced the region considered. Westerly to southwesterly winds likely brought mild waters from the Bay of Biscay region, which at 22.8 °C (December-March; 20.2–24.1 °C) closely match winter seawater temperatures in the proxy record. A quick temperature increase of the shallow waters of the Paris Basin in late spring is promoted by stable conditions and weak winds, with the simulated near-surface air temperatures in May (27.3 °C; 24.7–28.9 °C) and June (32.9 °C; 30.3–35.0 °C) providing the best match to clumped isotope-based late spring seawater temperature reconstructions. In summer, northerly winds bring relatively cool waters from the North Sea region, which by then have warmed to 28.6 °C (July–August; 27.0–30.7 °C) and again match the proxy record well. Stable conditions only briefly return in autumn, but can be matched to the proxy record. Both land-based temperatures of 28.6 °C (September–October; 27.2–30.3 °C) and sea surface temperatures in the Biscay region of 30.4 °C (September-October; 28.9–32.1 °C) fall well within the limits of the proxy-based estimate. In conclusion, we can state that the changing atmospheric circulation regimes are key to understand the temperature seasonality in the Paris Basin in the middle Eocene. Furthermore, the quick transition from dry, stable conditions in spring towards highly variable and much wetter conditions in summer makes a strong case for a European Monsoon-like weather regime in summer, on which both the proxy reconstruction and the model simulation agree.

European Monsoon-like climate under a high emissions scenario
Both proxy reconstructions and model simulations support the existence of a European Monsoon-like climate pattern with elevated precipitation in summer in Europe during the high-CO2 middle Eocene. These results may indicate that under higher CO2 conditions, such as those expected by 2300 CE under the SSP5-8.5 IPCC SSP1, the climate in Western Europe could shift towards a more seasonal precipitation regime, strongly controlled by seasonal variations in the strength of the Westerlies, challenging previous knowledge about a warm European climate.

Methods
The C. giganteum specimen is collected in the Banca Verrains of the Calcaire Grossier Formation in the subterranean galleries of La Cave aux Coquillages, a gallery/museum in Fleury-la-Rivière (France; 49°06’05”N; 3°52’54”E). The Banca Verrains, also known as the main Campanile horizon24, is dated to approximately 45 Ma, based on correlations by calcareous nannofossil biozonation (NP15) and magnetostratigraphy (Polarity Chron C20r43,44).

After careful removal of the specimen from the matrix using soft preparation tools, powdered samples were acquired along the entire height of the shell using a handheld DREMEL® 3000 rotary drill with a tungsten carbide drill bit with a diameter of 500 μm. Sampling was done on the outer shell along the most adapical (upper) spiral thread, and was carried out by drilling short transects parallel to the growth increments to gather enough powder while preventing time averaging.

Stable oxygen isotope ratios and age model
Stable oxygen isotope ratios were measured using a Thermo Fisher™ Delta V Advantage isotope ratio mass spectrometer coupled to a Thermo Finnigan™ GasBench II through a continuous flow interface at the Department of Earth and Environmental Sciences, KU Leuven. Aliquots of ~50 μg of aragonite powder were reacted with excess anhydrous orthophosphoric acid (H3PO4) in helium-flushed vials to produce CO2, which is then measured in the continuous flow mode. International and internal standards are measured to correct for instrumental drifts. They are calibrated to the Vienna Pee Dee Belemnite (VPDB) standard.

The growth model ShellChron is used to transform the isotope records from the distance domain into a chronology relative to the seasonal δ18Oc cycle. Assuming the δ18Oc variation in C. giganteum predominantly reflects seasonal variability, this model aligns δ18Oc measured along a sampling transect to a shell chronology, allowing the growth rate to vary seasonally (including potential growth cessations; ref. 29) To corroborate the seasons defined based on the δ18Oc profile and calibrate the ShellChron age model, visible growth lines were counted of the inferred 3rd year of growth (Supplementary Fig. 3), represented by the 20st to the 25th whorl, and compared to the a priori defined seasons and ShellChron-based ages. The total amount of visible growth increments in this year (704) is almost double the number of days per year (~365), suggesting the increments reflect a semidiurnal cycle with the winter growth cessations concealing several days, that are not reflected as increments. The interval between the growth cessation (assumed to coincide with the shortest day of the year, December 21st) and the midpoint of the intervals sampled for clumped isotopic analyses, respectively for the autumn, winter, spring and summer, cover approximately 138 growth increments before the growth cessation, 25 growth increments before the growth cessation, 284 growth increments after the growth cessation and 427 growth increments after the growth cessation. Based on the number of increments, it can be calculated that the mean of the winter season sample interval occurs around day 342 of the year (mid-December), the mean of the spring season sample interval occurs around day 132 of the year (mid-May), the mean of the summer season sample interval occurs around day 203 of the year (late July), while the mean of the autumn sample interval occurs around day 286 of the year (mid-October), corroborating the seasons defined based on the δ18Oc profile.

In the 3rd year of growth there is an average +33 day offset in the calculated day of year between the age model based on growth increment counting and the ShellChron age model. To correct for this, the output of the ShellChron age model was shifted by +33 days. (Supplementary Data file S1).

Carbonate clumped isotopes
Carbonate clumped isotope measurements (Δ47) were performed in the carbonate clumped isotope lab at the Earth Science Department at Utrecht University. A total of 168 replicates were analysed spread over the four seasons based on the shell chronology presented above. Small (75–95 μg) aliquots were reacted with orthophosphoric acid in a Kiel IV carbonate preparation device. The resultant CO2 was cryogenically purified using two liquid nitrogen-cooled cold fingers before being led through a Porapak trap45. The clumped isotope composition was analysed in a Thermo Finnigan MAT 254 PLUS Isotope Ratio Mass Spectrometer using the Long Integration Dual Inlet (LIDI) routine45,46. The results were corrected for intensity-based negative background effects47 and standardized using intensity-matched ETH-1, ETH-2 and ETH-3 community standards48, which were measured in a roughly 1:1 ratio with samples49. Two check standards (IAEA-C2 and Merck50;) were used to quantify long-term instrumental precision (typical standard deviation of 0.04‰).

For the palaeotemperature calculation from Δ47, the equation proposed by Anderson et al. (ref. 51) is used.

Δ47 = 0.0391 ± 0.0004 × 10^6 / T^2 + 0.154 ± 0.004 (1)

Here, T is temperature in Kelvin. This equation can then be transformed to temperature:

T = sqrt(0.0391 / (Δ47 - 0.154)) × 10^3 (2)

Calibrated stable isotope data were aligned with the ShellChron shell chronology and plotted using the open-source computational software R52. All scripts used for data processing along with raw data of all the analyses are provided in SI_data_supplement(https://doi.org/10.5281/zenodo.14140838).

CESM model runs and data processing
The proxy record presented here is compared to climate model simulations of the middle Eocene using the CESM 1.0.526,53. Using a 38 Ma palaeogegraphy reconstruction, the 4xPIC (i.e., pre-industrial carbon; CO2 and CH4) simulations were shown to be a good match with Bartonian (41.03–37.71 Ma) SST Proxies. The model configuration features CAM4 at ~2° horizontal resolution and 26 hybrid sigma levels and POP2 at ~1 deg resolution and 60 vertical levels for the atmosphere and ocean, respectively. Existing simulations are well equilibrated after ~3500 years, with the following 100 years considered for monthly climatologies used here. For this work, we continued this simulation by a further 30 years to generate the daily output for mean sea level pressure, near surface (2m) air temperature, and precipitation. Further information on the simulations, as well as additional spin-up and sensitivity experiments, can be found in refs. 26, 53. We also consider early Eocene simulations from the DeepMIP ensemble39 for a further comparison in Supplementary Fig. 5.

Using global output fields, we consider the European region in our analyses and three regions more specifically: Western Europe surrounding the Paris Basin region (37N-47N, 5W-15E), the Bay of Biscay (35N-43N, 7W-GM), and the North Sea (43N-51N, 4W-3E). Statistics are weighted using the surface area and only consider terrestrial cells (land fraction at least 0.5) for Western Europe and marine cells for the Bay of Biscay and North Sea regions, respectively. Sea surface temperatures are taken from the upper level of the ocean model and are therefore the upper 10m average. Wind speeds are interpolated from hybrid sigma levels onto the 925 hPa level over the Western Europe region, to represent boundary layer winds without too much interaction from the topography. Over the ocean, we use the 975 hPa level for near-surface winds in the absence of topography, while the atmospheric boundary layer is shallower here. For monthly climatologies, we only consider spatial variation within the considered regions in our analyses. For the daily model output, we also include temporal variation to represent synoptic-scale variability as well. Finally, our resulting daily statistics are smoothed using a local linear regression and a 15-day sliding window.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Van Horebeek et al. use a new proxy reconstruction of daily scale temperature and rainfall variability based on oxygen\nisotopes, combined with paleoclimate model simulations, to provide insight into middle Eocene European climate and by\nextension, far future European climate under an SSP585 climate change scenario. They assert that a European monsoon-\nlike climate existed in the middle Eocene (mild and wet winters, hot and dry should seasons, and warm and wet summers)\nand thus that such a climate will occur in the future.\nThe authors have put in a lot of effort which is commendable. I think the topic is of interest to a broad audience. However, a\nlot of extra work is needed to support the conclusion that future European climate will be monsoon-like, and several aspects\nof the methods and results need to be made substantially clearer. Whenever attempting to link paleoclimate (especially deep\ntime) to future climate extra care needs to be taken in considering all the differences between the two in order to support any\nclaims of an analagous climate. This is why I recommend rejection with encouragement to resubmit. Note I cannot comment\non the proxy aspects of this study as it is not my area of expertise.\nMajor comments\n1) Use of modelling to support conclusions: I see no fundamental issues with the paleoclimate modelling conducted to\ncompare against proxy data (though see point below on model-data comparison). However, the question that immediately\ncomes to mind when reading the paper is why not use climate projections to investigate future European climate.\nPaleoclimate simulations are fundamental to such as study for comparing against proxy records, but for relating this to the\nfuture there is assumedly a number of CMIP6 SSP585 overshoot models the authors could examine which would\nsignificantly support their claim for a future monsoon-like climate. Even if it was only for the CESM (assuming NCAR ran\novershoot simulations), why not get the daily and monthly data and see how that compares to PI climate? Otherwise, this\nreads like yet another study that attempts to link the past and the future based on somewhat loosely substantiated claims.\nThis may directly pertain to lines 64-69 that states it has not been verified whether the European monsoon exists in a warmer\nclimate (again, if this is so then why not examine projections and find out).\nIt could be argued that the PI 4xCO2 experiment (extended data figure 6) is a substitute for SSP585 and thus examining\nCMIP output isn’t necessary. However, this raises another issue with the results which is that according to the authors\nneither CO2, geography nor insolation affect the results significantly (lines 187-190). This then begs the further question of\nwhat is causing the simulated pattern in temperature and rainfall that the authors are trying to relate to the proxy record? Is\nthis just a characteristic of CESM climate (perhaps modern/PI simulations with CESM give similar results)? In which case it\nwould seem the middle Eocene simulations don’t actually support the proxy evidence. This needs investigation and/or\naddressing in the text.\nMy statement is not meant to shut down the authors’ study/conclusions; indeed the two ways to predict whether something\nwill happen in a warm future is through proxy investigation and climate projections, but I think both need to be done (at least\nfor a journal of this calibre), especially when the past climate is 40 Myrs ago and proxy evidence is from one location and for\n4.5 years. Which brings me to my next point.\n2) Proxy data: The proxy reconstruction seems very impressive. It’s amazing to get such high temporal resolution for 38\nmillion years ago. But the results from this reconstruction need to be tempered with the reality that this proxy represents ~4.5\nyears of data for one specific location. We have no idea (I assume) how representative this is of the general climate of the\nmiddle Eocene (modes of variability in the current climate can cause decent changes in weather) and we don’t know how\nrepresentative the proxy site is of the larger region or what kind of confirmation bias there is. These issues plague every\ncomparison of models to proxy data, but they still need discussing. The CESM grid cells are ~200 km wide. Integrating other\npaleoclimate evidence (even qualitative) describing the seasonality of Europe would go a long way in building the picture of\na monsoon-like climate in Europe.\nOther comments\nL27: please use “shifting atmospheric and oceanic circulation” to be more specific here.\nL43-46: We also gain a lot of knowledge from modelling. Include modelling and a sentence on the weaknesses/limitations of\nmodelling in this paragraph, like you have for proxy data.\nL53-56: Please include a sentence on the known or speculated causes of this variability in the westerlies.\nL58-59: Tautology, please correct/remove.\nL59-61: Does this mean a weakening in the mean westerlies? If so, isn’t this different to the seasonal variability in the\nwesterlies that we’re interested in RE the monsoon? Please clarify the text in this sentence.\nL63-67: It might be worth noting that this topic seems ripe for idealised simulations. I’m not suggesting it is needed for this\nstudy but it could be worth mentioning as potential future work for understanding how monsoon-like climates would operate\nat mid-high latitudes. Or if it has already been done please add a ref.\nL68-75: I’m not a proxy person, but the idea of a fossil providing such high temporal resolution is amazing to me. And it\ndeserves one or two sentences somewhere to introduce the reader. Who found this fossil? Why haven’t these been seen\nmore frequently in the geological record and/or literature? Or is this high resolution due to an improvement in\ninstruments/techniques? Normally the reader could be sent to a reference to get such details, but it seems such a step\nchange that it should be summarised briefly (especially given the high profile of this paper).\nL93: Can we actually assume 365 days per year? I know length of the year changes slowly back in time but I can’t recall the\napproximate rate. Please check and verify this doesn’t affect your interpretation.\nL176-179: It’s commonly known that climate models are generally more seasonal than proxies suggest for past warm\nperiods. They don’t get the equator-pole temperature gradient low enough. Thus, please include the limitations of models\nand of making model-data comparisons when explaining the model-data discrepancy (e.g. comparing 200 km grid cells to a\nspecific site).\nL181: Is this meant to reference Extended data figure 4 instead?\nL189-190: I’m a little surprised orbital configuration doesn’t have a significant impact since one assumes northern insolation\nis extremely influential on land-sea contrast and thus monsoon rainfall. Further, the caption for this figure says the orbital\nconfiguration represents a minimum in southern high latitude summer insolation, what does this mean for the northern\nhigh latitudes (is it particularly high, low or in between)?\nL191: You’ve compared to PI geography. Do you move the boxes you’re averaging over to account for continental drift when\nyou examine the PI simulation. Otheriwse northern Africa might be much closer to central Africa in the PI(?).\nL199: Figure 4 only shows data for January and July. So I don’t understand how you can refer to winter and early spring,\nplease include more figures (supp material if necessary) to support this and following statements.\nL211: modify to “...Paris Basin in late spring and early summer is promoted…”.\nL213: modify to “… In mid summer to early autumn, northerly…”.\nL225-230: “confirm” is definitely too strong a word here. This study shows supporting evidence for the proposed theory.\nSame with “These results suggest”; to make this assertion responsibly would also entail looking at actual climate\nprojections. It doesn’t make sense to talk about future climate without looking at climate projections.\nFigure 3:\n• Something doesn’t look right about the daily and monthly rainfall lines in this figure. If I’m interpreting it correctly the\nmonthly value of rainfall for May is ~1.5mm/day (green dashed line in panel b), but if you look at the daily values they all\nseem to be lower than 1.5 mm/day for that month… please check your plotting script, or explain this better if I’ve\nmisunderstood.\n• It’s not clear how the dashed line representing the Paris Basin in panel a is calculated. Please explain this more.\n• Please indicate whether the marine winds at 975 hPa are for the Paris Basin grid cell or are area averages over the purple\nbox, or something else.\n• Change y axis units for precipitation to “mm/day”.\n• You need to be more explicit when explaining the shading in panel b. I assume the two regions refer to 10/90th percentile\nand 25/75th percentiles. This makes sense for temperature but less so for rainfall, for which I think you could just show the\n75th and 90th percentile. This way you avoid the odd slivers of light green at the bottom left and bottom right of the panel.\nFigure 4: Need to include description of MSLP contours. Also please make continental outlines much thicker as it’s hard to\ndistinguish from the MSLP contours in a and c.\nExtended figure 5: If I understand correctly this means CESM1 is well outside the DeepMIP spread for almost the entire year\nfor rain and temperature in all 4 locations. Is that right? If so please comment on this.\nExtended figure 7: The caption for this figure needs more information as I’m not sure what\nI’m looking at. Panel a suggests you have gridded proxy reconstructions to compare against\nCESM output. Or did you take 4 seasonal values and apply them as constants globally? Is panel b PI compared to proxy data, why? Needs more explanation. I don’t understand\n“minimized at each grid point by adjusting the annual mean temperature”.", "reviewer_2": "Overall comments:\nThis manuscript addresses an important void in our knowledge of a future predicted CO2-induced warming – the role of\nseasonality. The authors analyze the seasonality of precipitation and temperature during the middle Eocene (41-48 Ma) in\nEurope, a time with ~1000 ppmV CO2 using stable oxygen and clumped isotopes from a fossil gastropod shell – Campanile\ngiganteum. Understanding the seasonality of the climate during this past time could help us understand seasonality in a\nwarming future and the extreme weather events that would be impactful in this future warmer world. The advantage of this\nstudy over others from this time period is the authors have used a proxy with high resolution which allows for seasonal- to\nweather-scale resolution. The work supports the conclusions and claims of the paper specifically that the middle Eocene, a\npotential analog for future warm conditions, was a time of high seasonality in temperature and precipitation with a European\nmonsoon similar to what is occasionally found today (i.e. dry spring and wetter summers due to convective storms).\nOverall, I think this paper is important and well done. I do not see any flaws that prohibit publication. Minor revisions are\nindicated below. The methodology is sound, and with a few minor edits, there is enough detail provided for the work to be\nreproduced.\nSpecific comments:\nLine ~100 – did you sample the entire shell or just a portion of it? I would recommend that you include some indication of\nhow much of the shell was sampled in Figure 1. How many years did the shell live? Could this reconstruction be expanded\nto include more samples from this same shell to determine if the extreme monsoonal behavior is picked up in other parts of\nthe shell?\nLine 150 – replace “depleted” with lower δ18O values or specify the isotope (16O or 18O) that is depleted\nLine 157 – dryer – replace with drier\nLine 180 – modern Africa? Or modeled Eocene Africa?\nMethods:\nLine 255 – How did you determine an age for this shell? Dating method?\nLine 303 – define Bartonian\nExtended data figure caption – “vertical error bars represent two standard deviations of uncertainty around δ18Oc and\nδ13Cc measurements” – carbon isotopes also have uncertainty shown.\nExtended data figure 3 caption – February spelled incorrectly\nExtended data figure 4 inset – can you put the proxy location on this map?\nExtended data figure 6 caption – what does the first pre-industrial in this phrase mean? “pre-industrial 4x pre-industrial”", "reviewer_3": "Review of the Manuscript: \"A European Monsoon-like Climate in a Warmhouse World\" by Van Horebeek et al.\nThis manuscript provides valuable insights into seasonal climate variability over Western Europe under a warming state\nfrom a paleoclimate perspective. The study presents an ultra-high resolution δ¹⁸O record to reconstruct intra-annual climate\ndynamics in the Eocene Paris Basin. By integrating proxy-based reconstructions with CESM model simulations, the authors\npropose that Western Europe experienced European monsoon-like conditions during the Lutetian warmhouse. The\ncombination of high-resolution geochemical proxies and climate modeling is a significant strength, offering a robust\nframework for understanding past warm climates and their implications for future climate change at a high emission\nscenario, in contrast to previous studies showing the ceasing of the European monsoon-like conditions. The results are\nnovel and interesting. However, several key areas require further clarification and improvement, and I suggest these major\npoints be addressed before the manuscript is considered for publication in Nature Communications, as follows.\nMajor comments\n1. The study finds that the highest temperatures occur in spring, and second highest in autumn, rather than summer. This\nanalysis uses the carbonate clumped isotope thermometer and is suggested independent of δ¹⁸Ow. However, this result\nneeds more verification and clarification. The authors should elaborate on how this unexpected warmest season may be due\nto seasonal variations in δ¹⁸Ow (which is treated as a constant in common practice). If this approach cannot even reproduce\na reasonable seasonal cycle, how can we trust the reconstructed temperature? Notably, this contradicts your simulation\nresults (Fig. 3a, black dashed line), which depict spring as the season with the lowest temperatures. The same also applies\nto your analysis of δ¹⁸Ow and its interpretation for the hydroclimate state.\n2. The manuscript would be strengthened by a more comprehensive analysis of the climate model output, particularly\nconcerning the simulated changes in the westerlies. An examination of these changes could provide valuable insights on\nhow the response might be different from previous studies (e.g. refs 13,14,17). The study also states that summer rainfall\nduring the Eocene was likely convective, and additional atmospheric dynamics from the modelling can be contributing.\nAnother valuable addition to this study would be to supplement the proxy data analysis with simulations from an isotope-\nenabled climate model of the same period (e.g. Zhu et al. 2020), providing a more comprehensive understanding of the\nisotope processes.\n3. Figures and figure captions should be significantly improved for clarity. For instance, in Fig 1, the colored dots and how\nthey are calculated are not described, not sure why they are not distributed over all four years of data, only part of it, why not\nerror bars are associated with these dots; in Fig 2, the citation of two refs in y-axis label is not fully explained, not description\non colored dots in (c); in Fig. 4, the meaning of contours, and ideally, inclusion of the key atmospheric variables associated\nwith westerlies driving precipitation patterns.\nSpecific comments\nLine 38-39: There is a lack of connection between this paragraph and the previous. It would be better to include a transition\nstatement here, rather than immediately introducing the concept of the “Warmhouse period.”\nLine 41: “the Lutetian climate resembles projections for the year 2300 CE under Shared Socioeconomic Pathway (SSP) 5-\n8.5” This may not be accurate and can be rephrased. As you discussed later, while CO₂ levels may be comparable, there\nare other fundamental differences, such as land-sea boundaries, ice sheet extent, and ocean circulation.\nLine 46: “trends trough the Cenozoic”, Should this be \"through the Cenozoic\" instead?\nLine 80: the length of the climate model output is quite short, and can be subjected to centennial variability (e.g. Askjær et al.\n2022) even in an equilibrium simulation. This serious limitation should be discussed.\nLine 107/126 Non-experts in water isotope reconstruction might find these two sections confusing. The text first establishes\nthe common practice of assuming a constant δ18Ow, but then immediately suggests that estimating its seasonal fluctuations\nis achievable, potentially leading to misinterpretations.\nLine 134: “These reconstructions therefore suggest a comparatively dry spring season and a wet summer, with a more\nmoderate autumn and winter season.” However, how do you account for non-local influences on δ18Ow? For example,\nδ18Ow values may also be affected by ocean circulation processes that transport seawater with different δ18Ow from other\nregions.\nLine 155: “the low-δ18Ow freshwater influx in this season was likely concentrated in intense pulses which we interpret to\nreflect an increase in the frequency of convective rainfall events.” While you attribute the low-δ¹⁸Ow freshwater influx to\nrainfall-driven river runoff, there is limited direct evidence supporting this claim. Additionally, is it possible that the low-δ¹⁸Ow\nfreshwater influx originates from Arctic waters transported via an eastern boundary current rather than local precipitation?\nLine 198: “shown in CESM simulations for the middle Eocene helps to interpret the proxy record (Fig 4).” The circulations\nshown in Figure 4 represent only winter and summer. Why is spring circulation not included? Adding the spring circulation\nwould provide a clearer picture of the atmospheric circulations associated with the dry spring and wet summer.\nLine 203: “The convergency of weather system”, it is not evident in the Fig. 4d.\nLine 227-228: “These results suggest that under higher CO2 conditions, such as those expected by 2300 CE under the\nSSP5-8.5 IPCC Shared Socioeconomic Pathway”. You can highlight that your results challenge established findings.\nRefs\nAskjær et al. (2022). Multi-centennial Holocene climate variability in proxy records and transient model simulations.\nQuaternary Science Reviews, 296, 107801.\nZhu et al. (2020). Simulation of early Eocene water isotopes using an Earth system model and its implication for past climate\nreconstruction. Earth and Planetary Science Letters, 537, 116164.", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature\nCommunications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career\nResearchers who co-review manuscripts."}, "author_response": "Rebuttal\nReviewer #1\n1) Use of modelling to support conclusions: I see no fundamental issues with the\npaleoclimate modelling conducted to compare against proxy data (though see point below\non model-data comparison). However, the question that immediately comes to mind when\nreading the paper is why not use climate projections to investigate future European climate.\nPaleoclimate simulations are fundamental to such as study for comparing against proxy\nrecords, but for relating this to the future there is assumedly a number of CMIP6 SSP585\novershoot models the authors could examine which would significantly support their claim for\na future monsoon-like climate. Even if it was only for the CESM (assuming NCAR ran\novershoot simulations), why not get the daily and monthly data and see how that compares\nto PI climate? Otherwise, this reads like yet another study that attempts to link the past and\nthe future based on somewhat loosely substantiated claims. This may directly pertain to lines\n64-69 that states it has not been verified whether the European monsoon exists in a warmer\nclimate (again, if this is so then why not examine projections and find out).\nIt could be argued that the PI 4xCO2 experiment (extended data figure 6) is a substitute for\nSSP585 and thus examining CMIP output isn’t necessary. However, this raises another\nissue with the results which is that according to the authors neither CO2, geography nor\ninsolation affect the results significantly (lines 187-190). This then begs the further question\nof what is causing the simulated pattern in temperature and rainfall that the authors are\ntrying to relate to the proxy record? Is this just a characteristic of CESM climate (perhaps\nmodern/PI simulations with CESM give similar results)? In which case it would seem the\nmiddle Eocene simulations don’t actually support the proxy evidence. This needs\ninvestigation and/or addressing in the text.\nMy statement is not meant to shut down the authors’ study/conclusions; indeed the two ways\nto predict whether something will happen in a warm future is through proxy investigation and\nclimate projections, but I think both need to be done (at least for a journal of this calibre),\nespecially when the past climate is 40 Myrs ago and proxy evidence is from one location and\nfor 4.5 years. Which brings me to my next point.\n-\nResponse:\nAs pointed out by the reviewer, the relevance and purpose of our simulations should\nbe explained better. This is mainly to support our conclusions from the proxy record,\nwhich in itself is novel and has some implications for warmer climates in general. We\nrephrased some of our statements and add further support and comparisons to\nCMIP6 studies and pre-industrial reference simulations, as further explained below.\nWe do consider pre-industrial and (2000yr) 4xCO2 experiments using the same\nmodel configuration, of which we added a comparison to the supplement as well as\nsome discussion. The 4xCO2 simulation shows a wetter winter over central/western\nEurope, but a slightly drier summer. This agrees with the CMIP6 ensemble, for the\nSSP5.85 scenario. There is no clear indication of a tendency towards a summer wet\nseason, but there is a clear trend towards more distinct seasonal circulation regimes.\nThese show more persistent westerly/southwesterly flow in winter, and more\nnortherly/easterly flow in summer in a warmer future (e.g. De Vries et al. 2022). This\nsuggests that the suppressive effect of upper level ridges is stronger than that of\nthermally lowering surface pressures over land. This comparison suggests that the\ncombined influence of Eocene conditions on European climate is much more\nprofound than that of warming alone, with potentially a large contribution from e.g.\ncontinental geometry, land surface properties, and ice sheets. Meanwhile, the\nmagnitude of Eocene warming (12-15C globally) is far greater than the average\nwarming shown in future high emission (3-5C) or 4xCO2 (6-8C) model simulations.\nWe will add this discussion to nuance and substantiate our claims on the implications\nfor future warming.\nThe point on the suggested insensitivity of the simulations is valid and is now\nexplained better. We aim to say that within different model configurations\nrepresenting the Eocene, we see no significant qualitative differences in climate\nregimes. This is a clear indication that the model results are not found for just one\nparticular configuration. There are relevant sensitivities to external forcing within the\nscenarios considered, while any of these scenarios are still very different from any\nclimate seen today.\nFinally, the model results shown here do not serve to prove that the simulations are a\nperfect representation of either the Eocene, present or future climate. They are\nmainly considered to interpret the novel and surprising proxy record found in the\nCampanile fossil. Within substantial limitations (e.g. detail of geography, time frame,\nand model resolution), the simulations do present a realistic scenario which helps to\nunderstand the Eocene climate regime suggested by the proxy record. We also\nadded further context and motivation to the use of model simulations in this study.\n--\nProxy data: The proxy reconstruction seems very impressive. It’s amazing to get such high\ntemporal resolution for 38 million years ago. But the results from this reconstruction need to\nbe tempered with the reality that this proxy represents ~4.5 years of data for one specific\nlocation. We have no idea (I assume) how representative this is of the general climate of the\nmiddle Eocene (modes of variability in the current climate can cause decent changes in\nweather) and we don’t know how representative the proxy site is of the larger region or what\nkind of confirmation bias there is. These issues plague every comparison of models to proxy\ndata, but they still need discussing. The CESM grid cells are ~200 km wide. Integrating other\npaleoclimate evidence (even qualitative) describing the seasonality of Europe would go a\nlong way in building the picture of a monsoon-like climate in Europe.\n--\nResponse:\nWe agree with the reviewer that the presented proxy record only covers 4.5 years of\ndata, and acknowledge that it is difficult to establish how representative these years\nwere for the general climate in the region. These issues indeed plague every\ncomparison of models to proxy data. Nevertheless, the consistent δ¹⁸Oc variability\nacross the recorded years suggests they are reasonably representative of typical\nclimate conditions in the region during the middle Eocene. In our revised manuscript\n(lines 104-107) we now briefly acknowledge the limitations of a 4.5 year\nsclerochronological record:\n“Although it is difficult to determine how well the recorded 4.5 years reflect the\nbroader middle Eocene climate of Western Europe, the consistent δ¹⁸Oc variability\nacross these years suggests they are reasonably representative of typical climate\nconditions during that period.”\nRegarding the final point on the CESM resolution, we acknowledge that the model is\nlimited in its capability to represent the conditions at a specific location. This is a\ncommon challenge comparing model to proxy data and is the main reason why we\nconsider large scale conditions (averages over the areas shown in figure 3) and\ncirculation patterns rather than a point-by-point comparison. This discussion was\nadded to the text.\n---\nOther comments\nL27: please use “shifting atmospheric and oceanic circulation” to be more specific here.\n--\nResponse: Added\n---\nL43-46: We also gain a lot of knowledge from modelling. Include modelling and a sentence\non the weaknesses/limitations of modelling in this paragraph, like you have for proxy data.\n--\nResponse: Done\n---\nL53-56: Please include a sentence on the known or speculated causes of this variability in\nthe westerlies.\n--\nResponse: Done\n---\nL58-59: Tautology, please correct/remove.\nResponse: Done\n---\nL59-61: Does this mean a weakening in the mean westerlies? If so, isn’t this different to the\nseasonal variability in the westerlies that we’re interested in RE the monsoon? Please clarify\nthe text in this sentence.\nResponse:\nHigh-resolution models for European climate predict that this weakening of the\nwesterlies in future climates mostly takes place in spring/summer, which would\ncounteract the typical European Monsoon pattern. Particularly over Europe,\nwintertime westerlies are actually expected to increase because of the cooling\nsubpolar North Atlantic. We have revised the text to indicate this more clearly.\n---\nL63-67: It might be worth noting that this topic seems ripe for idealised simulations. I’m not\nsuggesting it is needed for this study but it could be worth mentioning as potential future\nwork for understanding how monsoon-like climates would operate at mid-high latitudes. Or if\nit has already been done please add a ref.\nResponse: Good point, we added a sentence to suggest this as an avenue for\nfuture research: “Idealized simulations of seasonal temperature variability in a\nwarmer world could help understand such monsoon-like climates in higher latitudes.\nAdditionally, assessing the seasonal impact…”\n---\nL68-75: I’m not a proxy person, but the idea of a fossil providing such high temporal\nresolution is amazing to me. And it deserves one or two sentences somewhere to introduce\nthe reader. Who found this fossil? Why haven’t these been seen more frequently in the\ngeological record and/or literature? Or is this high resolution due to an improvement in\ninstruments/techniques? Normally the reader could be sent to a reference to get such\ndetails, but it seems such a step change that it should be summarised briefly (especially\ngiven the high profile of this paper).\nResponse:\nWe refer to previous studies demonstrating that mollusc shells can record climate\ninformation on the scale of hours to weeks. In addition, in the following paragraph, we\nexplain that is was only recently recognized that Campanile giganteum grew\nexceptionally fast: “Recent research has shown that with growth rates up to 60\ncm/year along the helix, far exceeding those of all other fossil molluscs, these giant\ngastropods have the unique potential to record weather-timescale variability in the\nEocene greenhouse world” (lines 75-55)\n---\nL93: Can we actually assume 365 days per year? I know length of the year changes slowly\nback in time but I can’t recall the approximate rate. Please check and verify this doesn’t\naffect your interpretation.\n--\nResponse:\nThe reviewer is correct that the gradual slowing of Earth’s rotation due to tidal\ninteractions with the Moon, days are becoming longer over geological time, resulting\nin gradually less days per year. Hence, the number of days will have been slightly\nhigher during the middle Eocene. Yet, estimating how much is challenging. A recent\nstudy by De Winter et al. 2020 (https://doi.org/10.1029/2019PA003723) has shown\nthat during the Campanian (approximately 80 million years ago), there were about\n372 days per year. A linear interpolation would suggest that during the Eocene, there\nwere around 369 days per year. Given the relatively larger uncertainly in e.g.\nincrement counting, we consider the number days per year still very close to the\nmodern day situation. The difference of 3-4 days will not affect our interpretation.\n---\nL176-179: It’s commonly known that climate models are generally more seasonal than\nproxies suggest for past warm periods. They don’t get the equator-pole temperature gradient\nlow enough. Thus, please include the limitations of models and of making model-data\ncomparisons when explaining the model-data discrepancy (e.g. comparing 200 km grid cells\nto a specific site).\nResponse:\nModel simulations of past warm climates generally show high seasonal temperature\ncontrasts compared to proxy data from the same location and time period, due in part\nto the challenge to simulate low equator-to-pole temperature gradients in climate\nmodels. Nevertheless, recent DeepMIP and PlioMIP2 papers show a more realistic\nmeridional gradient.\nWhile a recent proxy-model comparison during the mid-Piazentian Warm Period\nachieved better seasonal agreement between mollusc-based temperature records\nand model outcomes (de Winter et al., 2024), we note that mollusc-based\nreconstructions remain challenging to compare directly with model outcomes due to\ntheir sensitivity to local climate variability. At the same time the big strength of these\narchives is that they actually record a (full) seasonal cycle rather than indirect\nindications of seasonal range.\n---\nL181: Is this meant to reference Extended data figure 4 instead?\nResponse: correct. Adjusted.\n---\nL189-190: I’m a little surprised orbital configuration doesn’t have a significant impact since\none assumes northern insolation is extremely influential on land-sea contrast and thus\nmonsoon rainfall. Further, the caption for this figure says the orbital configuration represents\na minimum in southern high latitude summer insolation, what does this mean for the northern\nhigh latitudes (is it particularly high, low or in between)?\nResponse: It is indeed surprising to see such little effect of the orbital configuration\non precipitation seasonality, while there clearly is a substantial change in temperature\nseasonality over Europe. A minimum in southern high latitude summer insolation\nindeed means a maximum at northern high latitudes, we clarify this now. This figure\nmostly serves to show that the climatic regime considered here is not just the result\nof 1 specific model configuration. While the details of these different simulations are\nbeyond the scope of this study, they help support our comparison, particularly since\nthe stratigraphic age of the fossil is not known precisely enough to date it within the\nphase of orbital (e.g. precession) cycles.\n---\nL191: You’ve compared to PI geography. Do you move the boxes you’re averaging over to\naccount for continental drift when you examine the PI simulation. Otherwise northern Africa\nmight be much closer to central Africa in the PI(?).\nResponse: Yes, the boxes are moved to account for continental drift, following the\npaleomagnetic reference frame by van Hinsbergen et al. (2015)\n---\nL199: Figure 4 only shows data for January and July. So I don’t understand how you can\nrefer to winter and early spring, please include more figures (supp material if necessary) to\nsupport this and following statements.\nResponse: This is a good suggestion, as the hot and comparatively dry spring\nregime is as interesting as the other ones discussed. We added panels showing May\nto this figure and some additional interpretation.\n---\nL211: modify to “...Paris Basin in late spring and early summer is promoted…”.\nResponse: ok\n---\nL213: modify to “… In mid summer to early autumn, northerly…”.\nResponse: with our adjusted age model, the clumped interval sampled for the early\nsummer season approximately corresponds to the 160th day of the year, about mid-\nJune. This corresponds more closely to late spring/early summer than to mid-summer\nto early autumn.\n---\nL225-230: “confirm” is definitely too strong a word here. This study shows supporting\nevidence for the proposed theory. Same with “These results suggest”; to make this assertion\nresponsibly would also entail looking at actual climate projections. It doesn’t make sense to\ntalk about future climate without looking at climate projections.\nResponse: ok, we adjusted this to “…support the existence of a European\nMonsoon-like climate pattern…” and later “These results suggest may indicate\nthat…”\n---\n---\nFigure 3:\n• Something doesn’t look right about the daily and monthly rainfall lines in this figure. If I’m\ninterpreting it correctly the monthly value of rainfall for May is ~1.5mm/day (green dashed\nline in panel b), but if you look at the daily values they all seem to be lower than 1.5 mm/day\nfor that month… please check your plotting script, or explain this better if I’ve\nmisunderstood.\n• It’s not clear how the dashed line representing the Paris Basin in panel a is calculated.\nPlease explain this more.\n• Please indicate whether the marine winds at 975 hPa are for the Paris Basin grid cell or are\narea averages over the purple box, or something else.\n• Change y axis units for precipitation to “mm/day”.\n• You need to be more explicit when explaining the shading in panel b. I assume the two\nregions refer to 10/90th percentile and 25/75th percentiles. This makes sense for\ntemperature but less so for rainfall, for which I think you could just show the 75th and 90th\npercentile. This way you avoid the odd slivers of light green at the bottom left and bottom\nright of the panel.\nResponse:\nWe adjusted the figure design and caption to clarify these issues.\nAn important difference is that the daily model data is acquired from a 30-year\nextension of the simulation. The monthly climatology is acquired from the preceding\n200 model years. The latter thus also acts as a means to validate the relatively short\n30-year period and thus show some (minor) effects of longer term internal variability.\nThe dashed line representing the Paris Basin is a blend of the 3 areas considered,\nbased on the prevailing wind regime, using either SST or 2m temperature.\nFor winds, 975hPa is only used over the ocean, while we use 925hPa over land to\nlimit surface interaction. All wind data is averaged over the respective boxes (purple\nfor Paris Basin). We do not consider data at individual grid cells considering the\nlimitations on spatial detail in the simulations discussed above.\nWe updated the axes to consistently show mm/day (except the monthly climatologies\nin the supplement).\nWe indeed show those percentiles. Following this suggestion, we removed the 10/25\npercentiles for daily precipitation.\n---\nFigure 4: Need to include description of MSLP contours. Also please make continental\noutlines much thicker as it’s hard to distinguish from the MSLP contours in a and c.\nResponse: We followed both suggestions here to improve this figure.\n---\nExtended figure 5: If I understand correctly this means CESM1 is well outside the DeepMIP\nspread for almost the entire year for rain and temperature in all 4 locations. Is that right? If so\nplease comment on this.\nResponse: The discrepancy is perhaps not as dramatic as suggested here, but there\nare indeed some significant differences between the DeepMIP and our 38Ma\nsimulations. Important is to consider the different time frame (55 vs 38Ma) and limited\nset of simulations. Within these limitations, we aim to show that the general nature of\na European Eocene climate showing a distinct summer wet season is something\nsupported by other simulations as well. The cooler temperatures can mostly be\nexplained by the DeepMIP 3xCO2 standard versus our 4xPIC, causing much of\nEurope to be 3-5C warmer in the latter. We added some discussion on this, as well\nas a separate figure in the supplement showing the CESM1.2 simulations which are\nthe closest to our simulations in terms of model architecture.\n---\nExtended figure 7: The caption for this figure needs more information as I’m not sure what\nI’m looking at. Panel a suggests you have gridded proxy reconstructions to compare against\nCESM output. Or did you take 4 seasonal values and apply them as constants globally? Is\npanel b PI compared to proxy data, why? Needs more explanation. I don’t understand\n“minimized at each grid point by adjusting the annual mean temperature”.\nResponse: We improved the caption of this figure, including some interpretation, as\nit is indeed rather specific. We aim to show here how we can find a relatable climate\nin both the Eocene and PI simulated climate. By also considering a possible annual\ntemperature deviation, we also find possible analogues of the surprising temperature\nseasonality while showing the corresponding offset.\nThe left panels thus show the smallest possible mean absolute error of temperature\nseasonality, for any given annual temperature deviation, while the right panels show\nthe deviation for which this minimum is found.\nReviewer #2\nSpecific comments:\nLine ~100 – did you sample the entire shell or just a portion of it? I would recommend that\nyou include some indication of how much of the shell was sampled in Figure 1. How many\nyears did the shell live? Could this reconstruction be expanded to include more samples\nfrom this same shell to determine if the extreme monsoonal behavior is picked up in other\nparts of the shell?\nResponse: The entire shell was sampled. Based on our internal age model, we\nestimate that the shell lived for ~4.5 years. Hence, unfortunately this is the maximum\ntimespan we can extract from this individual shell. We added a statement to the\nMethods section to highlight that we sampled the entire height of the shell.\n---\nLine 150 – replace “depleted” with lower δ18O values or specify the isotope (16O or 18O)\nthat is depleted\nResponse: ok, adjusted\n---\nLine 157 – dryer – replace with drier\nResponse: Adjusted\nLine 180 – modern Africa? Or modeled Eocene Africa?\nResponse: Eocene. We indicated this in the revised manuscript.\n---\nMethods:\nLine 255 – How did you determine an age for this shell? Dating method?\nResponse: The Banc a Verrains, from where the specimen was extracted, is dated\nto approximately 45 Ma, based on correlations by calcareous nannofossil biozonation\n(NP15) and magnetostratigraphy. In our revised manuscript, this is now indicated in\nthe text.\n---\nLine 303 – define Bartonian\nResponse: Since the Bartonian is a geological stage that is officially defined by the\nInternational Commission on Stratigraphy (ICS), we feel that it is redundant to\nreproduce this definition in our manuscript. Nevertheless, we have added the\nestimated ages of the Bartonian stage, based on the ICS.\n---\nExtended data figure caption – “vertical error bars represent two standard deviations of\nuncertainty around δ18Oc and δ13Cc measurements” – carbon isotopes also have\nuncertainty shown.\nResponse: Adjusted\n---\nExtended data figure 3 caption – February spelled incorrectly\nResponse: Adjusted\n---\nExtended data figure 4 inset – can you put the proxy location on this map?\nResponse: Adjusted\n---\nExtended data figure 6 caption – what does the first pre-industrial in this phrase mean? “pre-\nindustrial 4x pre-industrial”\nResponse: Typo, adjusted\n---\nReviewer #3\n1. The study finds that the highest temperatures occur in spring, and second highest in\nautumn, rather than summer. This analysis uses the carbonate clumped isotope\nthermometer and is suggested independent of δ¹⁸Ow. However, this result needs more\nverification and clarification. The authors should elaborate on how this unexpected warmest\nseason may be due to seasonal variations in δ¹⁸Ow (which is treated as a constant in\ncommon practice). If this approach cannot even reproduce a reasonable seasonal cycle,\nhow can we trust the reconstructed temperature? Notably, this contradicts your simulation\nresults (Fig. 3a, black dashed line), which depict spring as the season with the lowest\ntemperatures. The same also applies to your analysis of δ¹⁸Ow and its interpretation for the\nhydroclimate state.\nResponse: The clumped isotope thermometer is independent from d18Osw. The\nunexpected warmest season is therefore not likely the result of seasonal variations in\nd18Osw. Instead, we consider the reconstructed temperatures to reflect actual water\ntemperatures. In our manuscript, we make the case that the warmest temperatures\nare reached in late spring, because wind speeds are reduced during this season,\nallowing for the shallow waters in the Paris Basin to warm up quickly. Our model\nresults show that during Summer, northerly winds can bring in cooler surface waters\nfrom the North Sea. We therefore argue that our seasonal cycle is in fact reasonable.\nIn our revised manuscript, we have updated our internal age model based on\nadditional increment counting, which suggests that the clumped-isotope interval with\nthe highest temperatures corresponds to early May. This aligns precisely with the\nperiod in which our model outcomes project the winds to reduce (see Figure 3). The\nsimulation results suggest that the lowest temperatures are reached in February-\nMarch, when the Paris Basin is flushed by cooler Atlantic waters, related to the strong\nWesterlies.\nConcerning the d18Osw and hydrology, we do not see a conflict between the proxy\ndata and the modelled data. In fact, our temperature reconstructions, which are\nindependent from assumptions about d18Ow and hydrology, highlight that the\ncommon assumption that d18Ow remains constant throughout the year is not valid in\nthis situation.\n2. The manuscript would be strengthened by a more comprehensive analysis of the climate\nmodel output, particularly concerning the simulated changes in the westerlies. An\nexamination of these changes could provide valuable insights on how the response might be\ndifferent from previous studies (e.g. refs 13,14,17). The study also states that summer rainfall\nduring the Eocene was likely convective, and additional atmospheric dynamics from the\nmodelling can be contributing. Another valuable addition to this study would be to\nsupplement the proxy data analysis with simulations from an isotope-enabled climate model\nof the same period (e.g. Zhu et al. 2020), providing a more comprehensive understanding of\nthe isotope processes.\nResponse: As the main focus of our study is to present and interpret this new proxy\nrecord, we chose to keep the comparison to model simulations (particularly outside\nthe ones presented here) limited. As suggested by the reviewer, a more elaborative\noverview would help the overall relevance so we expanded in this in the text and\nsupplement. We added an overview of DeepMIP climatologies and those from our\npre-industrial 4xCO2 simulation as well as some discussion. The latter are consistent\nwith the model trends shown in CMIP6 SSP5.85 simulations, which we now mention\nin the discussion. Thank you for the suggestion of isotope-enabled modelling, this is\na very valuable option for potential follow-up studies,\n----\n3. Figures and figure captions should be significantly improved for clarity. For instance, in Fig\n1, the colored dots and how they are calculated are not described, not sure why they are not\ndistributed over all four years of data, only part of it, why not error bars are associated with\nthese dots; in Fig 2, the citation of two refs in y-axis label is not fully explained, not\ndescription on colored dots in (c); in Fig. 4, the meaning of contours, and ideally, inclusion of\nthe key atmospheric variables associated with westerlies driving precipitation patterns.\nResponse: Black symbols reflect conventional δ18Oc measurements, colored\nsymbols represent δ18Oc measurements obtained during clumped isotope analyses.\nVertical error bars representing two standard deviations of measurement uncertainty.\nThis has now been indicated in the revised manuscript, as are the figure captions.\nWe also added more explicit references to the proxy calibration studies cited in the\nfigures in their captions.\n--\nSpecific comments\nLine 38-39: There is a lack of connection between this paragraph and the previous. It would\nbe better to include a transition statement here, rather than immediately introducing the\nconcept of the “Warmhouse period.”\nResponse: Adjusted, we now start the paragraph as follows: “One of such warm\nperiods is the Lutetian (middle Eocene; ~41-48 million years ago6). With atmospheric\nCO levels of ~1000 ppmV 8, resembling projections for the year 2300 CE under\nup to 10°C warmer than today 9, the Lutetian climate is referred to as a “Warmhouse\nperiod” 7. Together with modelling of future climate scenarios, the Lutetian analogue\npresents a way to understand the impact of high global mean temperatures on the\nseasonal structure of climate.”\n---\nLine 41: “the Lutetian climate resembles projections for the year 2300 CE under Shared\nSocioeconomic Pathway (SSP) 5-8.5” This may not be accurate and can be rephrased. As\nyou discussed later, while CO₂ levels may be comparable, there are other fundamental\ndifferences, such as land-sea boundaries, ice sheet extent, and ocean circulation.\nResponse: The resemblance is mainly in the ppmV CO . We have now adjusted the\n2\nphrasing to ” With atmospheric CO levels of ~1000 ppmV 8, resembling projections\n2\nfor the year 2300 CE under Shared Socioeconomic Pathway (SSP) 5-8.5 1, …”\n---\nLine 46: “trends trough the Cenozoic”, Should this be \"through the Cenozoic\" instead?\nResponse: Adjusted\n---\nLine 80: the length of the climate model output is quite short, and can be subjected to\ncentennial variability (e.g. Askjær et al. 2022) even in an equilibrium simulation. This serious\nlimitation should be discussed.\nResponse: We did consider this limitation. The monthly climatologies shown are\ntaken from 200 years of simulation data to also serve as a means to validate the 30\nyear daily statistics. We added some discussion on the limitation of the daily data.\n---\nLine 107/126 Non-experts in water isotope reconstruction might find these two sections\nconfusing. The text first establishes the common practice of assuming a constant δ18Ow,\nbut then immediately suggests that estimating its seasonal fluctuations is achievable,\npotentially leading to misinterpretations.\nResponse: We would like to point out that, while the δ¹⁸O proxy requires\nc\nassumptions on δ¹⁸O (explained in the first paragraph), the clumped isotope\nw\nthermometer is independent on d18Osw. Hence, no assumptions regarding d18Ow\nare made. The clumped isotope thermometer is based on the thermodynamic\npreference for heavy isotopes (¹³C and ¹⁸O) to bond, or \"clump,\" together within the\ncarbonate lattice at lower temperatures. This \"clumping\" is quantified using the\nparameter Δ₂₂, which measures the enrichment of the isotopologue ¹³C–¹⁸O–¹⁶O in\nCO₂ derived from acid digestion of carbonate, relative to a stochastic (random)\ndistribution. Since the extent of clumping is temperature-dependent and independent\nof the isotopic composition of the water from which the carbonate precipitated, Δ₂₂\nprovides a direct proxy for formation temperature (Ghosh et al., 2006; Eiler, 2007).\nBecause Δ₂₂ yields a temperature estimate without needing to assume a δ¹⁸O\nw\nvalue, it allows us to decouple temperature and water isotopic composition—two\nvariables that are convolved in traditional oxygen isotope thermometry. Once the\ntemperature is known from Δ₂₂, and the δ¹⁸O of the carbonate (δ¹⁸O ) is measured,\nc\none can use oxygen isotope fractionation equations (e.g., Kim and O’Neil, 1997) to\nback-calculate the δ¹⁸O of the water in which the carbonate formed, i.e., δ¹⁸O .\nw\nThis approach has become a powerful tool in paleoceanography and\npaleoclimatology for reconstructing both past temperatures and seawater δ¹⁸O, which\nis closely related to global ice volume and hydrological changes.\nOur aim with these two paragraphs is to first highlight this limitation in conventional\nδ¹⁸O proxy analysis before introducing the clumped isotope-based methodology we\nc\nuse to overcome this issue.\n---\nLine 134: “These reconstructions therefore suggest a comparatively dry spring season and a\nwet summer, with a more moderate autumn and winter season.” However, how do you\naccount for non-local influences on δ18Ow? For example, δ18Ow values may also be\naffected by ocean circulation processes that transport seawater with different δ18Ow from\nother regions.\nResponse: This is exactly the mechanism that we believe explains the warmer and\nmore enriched waters in spring, and cooler and more depleted waters in summer.\nOur modelling shows that, because of the seasonally shifting winds, the Paris Basin\nis under influence of different water currents, bringing in Atlantic waters during\nwinters (by the Westerlies), with no influx of water during spring, and with the influx of\nwater from the North Sea during summer. We would like to refer the reviewer to lines\n196-223 in our original manuscript, where this mechanism is explained.\n---\nLine 155: “the low-δ18Ow freshwater influx in this season was likely concentrated in intense\npulses which we interpret to reflect an increase in the frequency of convective rainfall\nevents.” While you attribute the low-δ¹⁸Ow freshwater influx to rainfall-driven river runoff,\nthere is limited direct evidence supporting this claim. Additionally, is it possible that the low-\nδ¹⁸Ow freshwater influx originates from Arctic waters transported via an eastern boundary\ncurrent rather than local precipitation?\nResponse: Our model runs suggest a summer precipitation peak over Western\nEurope, which makes it likely that low d18Osw values are rainfall driven. We believe\nthat precipitation is a more likely source of low-δ¹⁸O waters than Arctic seawater,\nw\nbecause the Arctic Ocean waters were probably much less isotopically light in the\nBartonian than today due to the absence of the Greenland Ice Sheet, which\nnowadays provides a source of highly isotopically depleted water to the Arctic Ocean.\n----\nLine 198: “shown in CESM simulations for the middle Eocene helps to interpret the proxy\nrecord (Fig 4).” The circulations shown in Figure 4 represent only winter and summer. Why is\nspring circulation not included? Adding the spring circulation would provide a clearer picture\nof the atmospheric circulations associated with the dry spring and wet summer.\nResponse: We agree with the reviewer, and added a panel for spring.\n----\nLine 203: “The convergency of weather system”, it is not evident in the Fig. 4d.\nResponse: There is a large-scale converging regime over Central Europe in autumn\nwinter where northerly winds over the North Sea come together with\nsoutherly/easterly winds from the Mediterranean. This is clearly visible in the updated\nFigure 4f, to which we refer specifically in the revised text.\n---\nLine 227-228: “These results suggest that under higher CO2 conditions, such as those\nexpected by 2300 CE under the SSP5-8.5 IPCC Shared Socioeconomic Pathway”. You can\nhighlight that your results challenge established findings.\nResponse: OK, we added “, challenging previous knowledge about warm European\nclimate.”\nReviewer #1\nI have a few more comments below that they should address (no need for further\nreview if the editor finds the responses satisfactory). Mainly this relates to making it\nclearer from the beginning of the manuscript that the temperature seasonality being\ndescribed relates to water temperature not air temperature.\nResponse:\nIn our revised manuscript we have now more clearly indicated that the proxy record\ninvolves sea water temperatures, by stating this explicitly in the abstract (line 24) and\nin the section on Data-model agreement (line 195)\n==\nI would also recommend they consider describing the mechanism explaining this\nseasonality in the abstract or intro (wind direction bringing different waters to the\nregion and minimal wind leading to reduced cooling through reduced latent heat flux).\nResponse:\nIn our revised manuscript we have added a sentence on this in the abstract (lines 28-\n29)\n==\nI may have missed this in my initial review, but why is air temperature used for Central\nWestern Europe in Figure 3b? You’re trying to explain shallow marine temperature\nseasonality and the other two boxed regions are using SST, so why use air\ntemperature in this region? I might have issed the explanation (in which case\ndisregard this comment) but if not – or even if I have – it’s possible the reason for this\nneeds to be made clearer.\nResponse:\nOur model palaeogeography lacks the spatial resolution to resolve the small marine\nembayment that constitutes the Paris Basin. As a result, no modelled sea water\ntemperatures are available for this basin. Nevertheless, considering the shallow\nwater depths in this embayment, we regard near-surface air temperatures as the\nmost appropriate analogue for local seawater temperatures, in particular during low\nwind conditions, in the spring. We have now explained this at lines 183-187.\n==\nRelated to the above point, it’s absolutely crucial that the following sentence in the\nabstract be made to explicitly refer to marine conditions. As it stands it would be\ninterpreted by most to be referring to air temperature. “Our dataset shows that the\nmiddle Eocene of western Europe featured monsoon-like conditions, with mild\n(~24°C) and wet winters, hot (>30°C) and dry spring and autumn seasons, and warm\n(~28°C) and comparatively wet summers.”.\nResponse:\nIn our revised manuscript we have now explicitly indicated that these temperatures\nrefer to sea water temperatures.\n==\nAs a follow up point, it would be worth stating that you don’t believe that air\ntemperature in the region would be hotter in Spring vs Summer (which is what I\nunderstood for the majority of the paper) and that this counter-intuitive result\nmanifests itself in the marine record due to the influence of the different water bodies\nyou’ve analysed.\nResponse:\nIn our revised manuscript we have now more clearly indicated that the temperature\ndifferences are related to sea water temperatures.\n==\n“While the simulated mean annual temperatures (24.7 ± 1.7°C) agree with those\nreconstructed by carbonate clumped thermometry from C. giganteum (28.9 ± 3.3°C),\nmodelled air temperatures do not replicate the seasonal temperature pattern observed\nin the data with hot spring and autumn and milder summers (see Fig. 3b).” Again,\nrelated to the above points, why would you expect air temperature output to match\nproxy water temperatures? Because it’s more representative than modelled SST?\nResponse:\nSee above.\n==\n• Figure 3 caption still mentions the 10th/25th percentiles even though they’ve been\nremoved from the fig.\n• Double period on line 275.\n• Should line 192 reference Fig 3a instead of 3b?\n• Extended figure 4 x axis has incorrect lettering for the months (e.g. last letter is “F”\neven though it is preceded by “D”).\nResponse:\nAll corrected.\n==\nReviewer #2\nThe authors have considered the changes suggested by the reviewers and have made\nthe necessary adjustments – thank you! I appreciate the novelty of the work\nespecially utilizing a shell that it is so old and yet in good enough condition to get\nthese high-resolution data. I think using ShellChron is another novel aspect of this\nwork as well as clumped isotopes to isolate the effects of d18Osw and temperature.\nI see no major issues in the revised manuscript and recommend it for publication. I\nhave only a few minor comments – see below.\nLine 270 – no comma needed after “both”\nLine 273 – SSP has already been defined so you can just use SSP\nLine 345 – extra .,s\nResponse:\nAll corrected."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have addressed my comments satisfactorily. I have a few more comments below that they should address (no need for further review if the editor finds the responses satisfactory). Mainly this relates to making it clearer from the beginning of the manuscript that the temperature seasonality being described relates to water temperature not air temperature. I would also recommend they consider describing the mechanism explaining this seasonality in the abstract or intro (wind direction bringing different waters to the region and minimal wind leading to reduced cooling through reduced latent heat flux).\n• I may have missed this in my initial review, but why is air temperature used for Central Western Europe in Figure 3b? You’re trying to explain shallow marine temperature seasonality and the other two boxed regions are using SST, so why use air temperature in this region? I might have missed the explanation (in which case disregard this comment) but if not – or even if I have – it’s possible the reason for this needs to be made clearer.\n• Related to the above point, it’s absolutely crucial that the following sentence in the abstract be made to explicitly refer to marine conditions. As it stands it would be interpreted by most to be referring to air temperature. “Our dataset shows that the middle Eocene of western Europe featured monsoon-like conditions, with mild (~24°C) and wet winters, hot (>30°C) and dry spring and autumn seasons, and warm (~28°C) and comparatively wet summers.”.\n◦ As a follow up point, it would be worth stating that you don’t believe that air temperature in the region would be hotter in Spring vs Summer (which is what I understood for the majority of the paper) and that this counter-intuitive result manifests itself in the marine record due to the influence of the different water bodies you’ve analysed.\n• “While the simulated mean annual temperatures (24.7 ± 1.7°C) agree with those reconstructed by carbonate clumped thermometry from C. giganteum (28.9 ± 3.3°C), modelled air temperatures do not replicate the seasonal temperature pattern observed in the data with hot spring and autumn and milder summers (see Fig. 3b).”\n◦ Again, related to the above points, why would you expect air temperature output to match proxy water temperatures? Because it’s more representative than modelled SST?\n• Figure 3 caption still mentions the 10th/25th percentiles even though they’ve been removed from the fig.\n• Double period on line 275.\n• Should line 192 reference Fig 3a instead of 3b?\n• Extended figure 4 x axis has incorrect lettering for the months (e.g. last letter is “F” even though it is preceded by “D”).", "reviewer_2": "The authors have considered the changes suggested by the reviewers and have made the necessary adjustments – thank you! I appreciate the novelty of the work especially utilizing a shell that it is so old and yet in good enough condition to get these high-resolution data. I think using ShellChron is another novel aspect of this work as well as clumped isotopes to isolate the effects of d18Osw and temperature.\nI see no major issues in the revised manuscript and recommend it for publication. I have only a few minor comments – see below.\nLine 270 – no comma needed after “both”\nLine 273 – SSP has already been defined so you can just use SSP\nLine 345 – extra .,s", "reviewer_3": "I appreciate the authors' efforts in addressing my previous comments. The manuscript has been significantly improved and clarified, and I recommend its publication in Nature Communications.", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "Response:\nIn our revised manuscript we have now more clearly indicated that the proxy record\ninvolves sea water temperatures, by stating this explicitly in the abstract (line 24) and\nin the section on Data-model agreement (line 195)\n==\nIn our revised manuscript we have added a sentence on this in the abstract (lines 28-\n29)\n==\nOur model palaeogeography lacks the spatial resolution to resolve the small marine\nembayment that constitutes the Paris Basin. As a result, no modelled sea water\ntemperatures are available for this basin. Nevertheless, considering the shallow\nwater depths in this embayment, we regard near-surface air temperatures as the\nmost appropriate analogue for local seawater temperatures, in particular during low\nwind conditions, in the spring. We have now explained this at lines 183-187.\n==\nIn our revised manuscript we have now explicitly indicated that these temperatures\nrefer to sea water temperatures.\n==\nIn our revised manuscript we have now more clearly indicated that the temperature\ndifferences are related to sea water temperatures.\n==\nSee above.\n==\nAll corrected.\n==\nAll corrected."}]

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