Temperature Reconstructions Research Articles

Reconstructing hydroclimate changes over the past 2500 years using speleothems from Pyrenean caves (NE Spain)

Abstract. Reconstructing of past hydroclimates at regional scales during the Common Era (CE) is necessary to place the current warming in the context of natural climate variability. Here we present a composite record of oxygen isotope variations during last 2500 years based on eight stalagmites from four caves in the central Pyrenees (NE Spain) dominated by temperature variations, with the amount of precipitation playing a minor role. The dataset is compared with other Iberian reconstructions that show a high degree of internal coherence with respect to variability at the centennial scale. The Roman Period (RP) (especially 0–200 CE), the Medieval Climate Anomaly (MCA), and part of the Little Ice Age (LIA) represent the warmest periods, while the coldest decades occurred during the Dark Ages (DA) and most of the LIA intervals (e.g., 520–550 CE and 1800–1850 CE). Importantly, the LIA cooling or the MCA warming were not continuous or uniform and exhibited high decadal variability. The Industrial Era (IE) shows an overall warming trend although with marked cycles and partial stabilization during the last 2 decades (1990–2010). The strong coherence between the speleothem data, European temperature reconstructions and global tree-ring data informs about the regional representativeness of this new record as Pyrenean past climate variations. Solar variability, likely through its impact on the North Atlantic Oscillation, and major volcanic eruptions appear to be the two main drivers of climate in southwestern Europe during the past 2.5 millennia.

A novel land surface temperature reconstruction method and its application for downscaling surface soil moisture with machine learning

Downscaling of soil moisture data is important for high resolution hydrological modeling. Most downscaling studies in the literature have used spatially discontinuous land surface temperature (LST) maps as the main auxiliary parameter, which limits the creation of continuous soil moisture maps. The number of studies on soil moisture downscaling with machine learning that use gapless LST maps is limited. With this motivation, a hybrid reconstruction method has been proposed in this study to practically obtain continuous LST maps, which are then used to produce high resolution surface soil moisture (SSM) datasets. The proposed method is shown to have high mean performance with R2 and RMSE values of 0.94 and 1.84°K, respectively, for the period between 2019 and 2022. The developed reconstructed LST maps were then used to downscale original 9 km spatial resolution soil moisture datasets of SMAP L3 and SMAP L4 with Random Forest (RF) machine learning algorithm. The RF model were run with four different rainfall datasets, and the MSWEP rainfall dataset was found to produce the best results. The use of antecedent rainfall values as input variables in machine learning models has been shown to improve the performance of the models R2 0.76 to 0.93. The accuracy of the downscaled data was later evaluated for Western Anatolia Basins (WAB) in Türkiye with 31 in-situ stations. The downscaled SMAP L4 had good average statistical indicators R (0.815 ± 0.1), RMSE (0.09 ± 0.047 cm3/cm3), and ubRMSE (0.058 ± 0.025 cm3/cm3). Downscaled SMAP L3 was also validated with in-situ observations with satisfactory R (0.79 ± 0.074), RMSE (0.09 ± 0.043 cm3/cm3), and ubRMSE (0.06 ± 0.026 cm3/cm3) statistics. Furthermore, the performance of the downscaled SMAP L3 was also cross validated with SMAP + Sentinel 1 (L2) dataset between 2019 and 2022. The mean statistics of R (0.761 ± 0.11) and Root Mean Squared Difference (RMSD) (0.05 ± 0.014 cm3/cm3) between downscaled SMAP L3 and L2 data revealed that the new reconstruction method of LST used in the RF model for downscaling of soil moisture performed well to obtain high resolution soil moisture datasets. The proposed technique also overcame the difficulties associated with coastal regions where data was masked for quality considerations, by not only enhancing overall spatial resolution but also filling these data gaps and giving a complete SSM coverage.

Assessment of Porites microatolls for paleothermometry: Calibration for French Polynesia

Massive dome-shaped coral Porites are the predominant choice for paleoclimate studies due to their consistent and reliable growth. When growing close to sea level, they become limited in their vertical growth and form so-called ‘microatolls’. Microatolls have not yet been extensively explored for paleoclimate reconstruction. Here, we investigate how reliable modern Porites microatolls are against empirical sea-surface temperature using Sr/Ca, δ18O, Li/Mg and SrU paleothermometry methods on samples from the Society Islands, French Polynesia. Our results show Sr/Ca ratios have the lowest Standard Error of the Inverse Prediction (SEIP) at 0.415 °C (N = 41) with a calibration of Sr/Ca (mmol mol−1) = −0.082 ± 0.006 SST (°C) + 11.256 ± 0.170 and with high reproducibility across multiple corals. The reproducibility of δ18O was less good, with SEIP increasing to 0.829 °C (N = 41). Considering methods directly from the literature, Li/Mg ratio empirically corrected for Sr/Ca had the best balance between bias and precision where no local calibration could be available. This study independently evaluates and confirms the suitability of Porites microatolls from well-flushed environments for paleoclimate studies. Fossil dome-shaped Porites grow anywhere between near-surface and roughly 20 m depths which inherently incorporates uncertainty into any sea surface temperature reconstruction. This uncertainty is significantly reduced for microatolls due to their well-constrained bathymetry. The study represents a fundamental step in paleoclimate research targeting consistently near the water-air interface bringing reliability and, especially when combined with their ability to reconstruct past sea-level changes, microatolls have the potential to be central for future paleoenvironmental studies.

A tree ring-based spring temperature reconstruction for the Hindu Kush region in northern Pakistan

Annually resolved and absolutely dated proxy archives are necessary for contextualizing the rate and amplitude of anthropogenic climate change. High-resolution climate reconstructions are particularly important for remote regions where instrumental meteorological observations are limited in space and time. Here, we develop a robust, 260-year-long tree-ring width chronology from 32 Himalayan cedars (Cedrus deodara D. Don), which grew around 3000 m asl in the Kumrat Valley of the Hindu Kush region in northern Pakistan. Growth-climate response analyses reveal a significant negative correlation of -0.631 between our new standard chronology and March-April minimum temperatures (p < 0.001, n = 51). This inverse relationship between radial tree growth and early spring temperatures, together with positive correlations against precipitation totals at the onset of the growing season, suggest that warming-induced drought is the most limiting factor of sub-alpine forest growth in the Kumrat Valley. We then use the inverse growth-temperature association to reconstruct March-April minimum temperatures from 1812 to 2018 CE. The reconstruction explains 40 % of the instrumental record back to 1967, and exhibits the coldest and warmest spring conditions in 1815–1864 (6.67 ± 0.21°C) and 1918–1927 (8.11 ± 0.43°C), respectively. This pioneering study is indicative of the dendroclimatological potential in the Hindu Kush, where samples from living and relict trees of different species and elevational bands should be collected for advanced temperature and hydroclimate reconstructions.

Fast reconstruction of boiler numerical physical field based on proper orthogonal decomposition and conditional deep convolutional generative adversarial networks

ABSTRACT Obtaining real-time physical field data inside the boiler furnace is crucial for combustion diagnostics and optimization. In this work, we propose a fast reconstruction technique for the physical fields in a tangentially-fired coal boiler. The method combines the Proper Orthogonal Decomposition (POD) and Conditional Deep Convolutional Generative Adversarial Networks (cDCGAN) based on the boiler physical field obtained by computational fluid dynamics (CFD). Firstly, CFD simulations are performed using data from the boiler Distributed Control System (DCS). After verifying the CFD results, we expanded the simulation to 105 operational condition cases sample sets. Then, the physical fields of the sample set undergo POD to determine the appropriate number of POD bases, thereby ensuring the accuracy of the reconstruction. Finally, the cDCGAN method is employed to establish the correlation between the POD bases and the operational conditions of the boiler. Results show that the POD-cDCGAN method achieves rapid and accurate reconstruction of temperature and velocity fields, with mean relative error (MRE) below 1.5% and root relative squared error (RRSE) below 5.7%. The reconstruction time is reduced to 10.57s, significantly faster than direct CFD methods. The POD-cDCGAN method offers an efficient approach for online operational diagnosis and digital twin construction of boiler equipment.

A deep-learning approach to the 3D reconstruction of dust density and temperature in star-forming regions

Aims. We introduce a new deep-learning approach for the reconstruction of 3D dust density and temperature distributions from multi-wavelength dust emission observations on the scale of individual star-forming cloud cores (&lt;0.2 pc). Methods. We constructed a training data set by processing cloud cores from the Cloud Factory simulations with the POLARIS radiative transfer code to produce synthetic dust emission observations at 23 wavelengths between 12 and 1300 µm. We simplified the task by reconstructing the cloud structure along individual lines of sight (LoSs) and trained a conditional invertible neural network (cINN) for this purpose. The cINN belongs to the group of normalising flow methods and it is able to predict full posterior distributions for the target dust properties. We tested different cINN setups, ranging from a scenario that includes all 23 wavelengths down to a more realistically limited case with observations at only seven wavelengths. We evaluated the predictive performance of these models on synthetic test data. Results. We report an excellent reconstruction performance for the 23-wavelength cINN model, achieving median absolute relative errors of about 1.8% in log(n/m−3) and 1% in log(Tdust/K), respectively. We identify trends towards an overestimation at the low end of the density range and towards an underestimation at the high end of both the density and temperature values, which may be related to a bias in the training data. After limiting our coverage to a combination of only seven wavelengths, we still find a satisfactory performance with average absolute relative errors of about 2.8% and 1.7% in log(n/m−3) and log(Tdust/K). Conclusions. This proof-of-concept study shows that the cINN-based approach for 3D reconstruction of dust density and temperature is very promising and it is even compatible with a more realistically constrained wavelength coverage.

North Atlantic Temperature Change Across the Eocene‐Oligocene Transition From Clumped Isotopes

AbstractThe Eocene‐Oligocene transition (EOT) (∼34 Ma) is marked by the rapid development of a semi‐permanent Antarctic ice‐sheet, as indicated by ice‐rafted debris and a 1–1.5‰ increase in deep sea δ18O. Proxy reconstructions indicate a drop in atmospheric CO2 and global cooling. How these changes affected surface ocean temperatures in the North Atlantic and ocean water stratification remains poorly constrained. In this study, we apply clumped‐isotope thermometry to well‐preserved planktonic foraminifera, that are associated with lower mixed‐layer to subthermocline dwelling depths from the drift sediments at international ocean discovery program Site 1411, Newfoundland, across four intervals bracketing the EOT. The thermocline/lower mixed‐layer dwelling foraminifera record a cooling of 1.9 ± 3.5 K (mean ± 95% CI) across the EOT. While the cooling amplitude is similar to previous sea surface temperature (SST) reconstructions, absolute temperatures (Eocene 20.0 ± 2.9°C, Oligocene 18.0 ± 2.2°C) appear colder than previous organic proxy reconstructions for the northernmost Atlantic extrapolated to this location. We discuss seasonal bias, recording depth, and appropriate consideration of paleolatitudes, all of which complicate the comparison between SST reconstructions and model output. Our subthermocline dwelling foraminifera record a larger cooling across the EOT (Eocene 19.0 ± 3.5°C, Oligocene 13.0 ± 3.2°C, cooling of 5.5 ± 4.6 K) than foraminifera from the thermocline/lower mixed‐layer, consistent with global cooling and an increase in ocean stratification which may be related to the onset or intensification of the Atlantic meridional overturning circulation.

Anti-phase glacier fluctuations on the millennial-scale on the southern Tibetan Plateau and New Zealand during the last glacial period

The sparsity of high-resolution 10Be chronologies in the Northern Hemisphere makes it difficult to determine whether the global fluctuations in glacier extent during the last glacial occurred simultaneously. This limits our understanding of the past mechanisms driving global climate changes. We compiled and reanalyzed 476 10Be exposure ages from the southern Tibetan Plateau for the last glacial and compared them with coeval 10Be ages from the Southern Alps. The results indicate an anti-phase relationship between the glacier expansions in these two regions on the millennial-scale during the last glacial period. Comparison with a glacier-derived temperature reconstruction suggests that maintaining a stable glacier state in both regions required a similar cooling magnitude. We speculate that variability of the Atlantic Meridional Overturning Circulation, which induced poleward/equatorward shifts in atmospheric and oceanic circulation, was the primary driving mechanism of this anti-phase relationship. Our findings provide glacial geological evidence to support the bipolar seesaw hypothesis.

Summer warming during Heinrich Stadial 1 in Northeast China

Abstract The last deglaciation is considered a key period for exploring the underlying dynamics of temperature changes because it was characterized by multiple millennial-scale abrupt climatic events. However, the limited number of quantitative temperature records in Northeast (NE) China covering the last deglaciation hampers a complete understanding of the mechanisms and processes behind the temperature changes that occurred in that region. Here, we present a quantitative reconstruction of summer temperature over the last deglaciation based on bacterial branched glycerol dialkyl glycerol tetraethers (brGDGTs) analyzed from the sediment sequence of Lake Kielguo, a small volcanic lake in NE China. The results show that summer temperature was lowest during the interval ca. 20–18.2 calibrated (cal.) k.y. B.P. with a value of ~11.1 °C and increased by ~1.9 °C during Heinrich Stadial 1 (HS1) and by ~2.7 °C during the transition to the Bølling-Allerød (B-A). The summer temperatures during the B-A warm interval and Younger Dryas cold interval were ~14.1 °C and ~12.0 °C, respectively. The summer temperature record from the Lake Kielguo sediment sequence indicates that summer warming dominated the climate change state during HS1 in East Asia, which is different from the cooling pattern controlled by winter temperatures in the North Atlantic and Greenland realms. This distinction can be explained by weakened winter cooling signals triggered by the collapse of Atlantic Meridional Overturning Circulation when these signals propagated to East Asia, and increased summer temperature warming controlled by orbital and greenhouse gases during HS1 in East Asia.

Climate change drove the route shift of the ancient Silk Road in two distinct ways

Although climate change has convincingly been linked to the evolution of human civilization on different temporal scales, its role in influencing the spatial patterns of ancient civilizations has rarely been investigated. The northward shift of the ancient Silk Road (SR) route from the Tarim Basin (TB) to the Junggar Basin during ∼420–850 CE provides the opportunity to investigate the relationship between climate change and the spatial evolution of human societies. Here, we use a new high-resolution chironomid-based temperature reconstruction from arid China, combined with hydroclimatic and historical datasets, to assess the possible effects of climate fluctuations on the shift of the ancient SR route. We found that a cooling/drying climate in the TB triggered the SR route shift during ∼420–600 CE. However, a warming/wetting climate during ∼600–850 CE did not inhibit this shift, but instead promoted it, because of the favorable climate-induced geopolitical conflicts between the Tubo Kingdom and the Tang Dynasty in the TB. Our findings reveal two distinct ways in which climate change drove the spatial evolution of human civilization, and they demonstrate the flexibility of societal responses to climate change.

Bayesian multi-proxy reconstruction of early Eocene latitudinal temperature gradients

Abstract. Accurately reconstructing large-scale palaeoclimatic patterns from sparse local records is critical for understanding the evolution of Earth's climate. Particular challenges arise from the patchiness, uneven spatial distribution, and disparate nature of palaeoclimatic proxy records. Geochemical data typically provide temperature estimates via transfer functions derived from experiments. Similarly, transfer functions based on the climatic requirements of modern taxa exist for some fossil groups, such as pollen assemblages. In contrast, most ecological and lithological data (e.g. coral reefs and evaporites) only convey information on broad climatic requirements. Historically, most large-scale proxy-based reconstructions have used either geochemical or ecological data, but few studies have combined multiple proxy types into a single quantitative reconstruction. Large spatial gaps in existing proxy records have often been bridged by simple averaging, without taking into account the spatial distribution of samples, leading to biased temperature reconstructions. Here, we present a Bayesian hierarchical model to integrate ecological data with established geochemical proxies into a unified quantitative framework, bridging gaps in the latitudinal coverage of proxy data. We apply this approach to the early Eocene climatic optimum (EECO), the interval with the warmest sustained temperatures of the Cenozoic. Assuming the conservation of thermal tolerances of modern coral reefs and mangrove taxa, we establish broad sea surface temperature ranges for EECO coral reef and mangrove sites. We integrate these temperature estimates with the EECO geochemical shallow marine proxy record to model the latitudinal sea surface temperature gradient and global average temperatures of the EECO. Our results confirm the presence of a flattened latitudinal temperature gradient and unusually high polar temperatures during the EECO, which is supported by high-latitude ecological data. We show that integrating multiple types of proxy data, and adequate prior information, has the potential to enhance quantitative palaeoclimatic reconstructions, improving temperature estimates from datasets with limited spatial sampling.

The Ostracod Clumped‐Isotope Thermometer: A Novel Tool to Accurately Quantify Continental Climate Changes

AbstractThis study presents a methodological advancement in the field of clumped‐isotope (∆47) thermometry, specifically tailored for application to freshwater ostracods. The novel ostracod clumped isotope approach enables quantitative temperature and hydrological reconstruction in lacustrine records. The relationship between ∆47 and the temperature at which ostracod shell mineralized is determined by measuring ∆47 on different species grown under controlled temperatures, ranging from 4 ± 0.8 to 23 ± 0.5ºC. The excellent agreement between the presented ∆47 ostracod data and the monitored temperatures confirms that ∆47 can be applied to ostracod shells and that a vital effect is absent outside the uncertainty of measurements. Results are consistent with the carbonate clumped‐isotope unified calibration (Anderson et al., 2021, https://doi.org/10.1029/2020gl092069), therefore, an ostracod‐specific calibration is not needed. The ostracod clumped‐isotope thermometer represents a powerful tool for terrestrial paleoclimate studies all around the world, as lakes and ostracods are found in all climatic belts.

Charcoal analysis for temperature reconstruction with infrared spectroscopy

The duration and maximum combustion temperature of vegetation fires are important fire properties with implications for ecology, hydrology, hazard potential, and many other processes. Directly measuring maximum combustion temperature during vegetation fires is difficult. However, chemical transformations associated with temperature are reflected in the chemical properties of charcoals (a by-product of fire). Therefore, charcoal could be used indirectly to determine the maximum combustion temperature of vegetation fires with application to palaeoecological charcoal records. To evaluate the reliability of charcoal chemistry as an indicator of maximum combustion temperature, we studied the chemical properties of charcoal formed through two laboratory methods at measured temperatures. Using a muffle furnace, we generated charcoal from the woody material of ten different tree and shrub species at seven distinct peak temperatures (from 200°C to 800°C in 100°C increments). Additionally, we simulated more natural combustion conditions by burning woody material and leaves of four tree species in a combustion facility instrumented with thermocouples, including thermocouples inside and outside of tree branches. Charcoal samples generated in these controlled settings were analyzed using Fourier Transform Infrared (FTIR) spectroscopy to characterize their chemical properties. The Modern Analogue Technique (MAT) was employed on FTIR spectra of muffle furnace charcoal to assess the accuracy of inferring maximum pyrolysis temperature. The MAT model temperature matching accuracy improved from 46% for all analogues to 81% when including ±100°C. Furthermore, we used MAT to compare charcoal created in the combustion facility with muffle furnace charcoal. Our findings indicate that the spectra of charcoals generated in a combustion facility can be accurately matched with muffle furnace-created charcoals of similar temperatures using MAT, and the accuracy improved when comparing the maximum pyrolysis temperature from muffle furnace charcoal with the maximum inner temperature of the combustion facility charcoal. This suggests that charcoal produced in a muffle furnace may be representative of the inner maximum temperatures for vegetation fire-produced charcoals.

Reconstructed seasonality during the Mid Piacenzian Warm Interval and early Pleistocene cooling as recorded by growth temperatures from Mercenaria shells

The Mid Piacenzian Warm Interval (MPWI) has been identified as an analogue for future global warming because it had warmer temperatures and higher atmospheric CO2 levels than today, while subsequent early Pleistocene cooling is more similar to modern climate. However, reconstructions of these intervals lack seasonal-scale temperature reconstructions. Seasonal sea surface temperature (SST) reconstructions from deep-time archives can potentially provide insight into the nature of the climate system on sub-annual scales during critical climate states. Here we compared seasonal variability in growth temperatures during the MPWI and subsequent early Pleistocene cooling to modern climate reconstructed from oxygen isotope ratios recorded by the bivalve Mercenaria. Modern shells were collected from the University of North Carolina's Marine Sanctuary. Fossil shells from the Mid-Atlantic Coastal Plain (North Carolina) were collected from the Duplin Formation (MPWI) and the Waccamaw Formation (early Pleistocene). Oxygen isotope ratios range from −1 to 2.4 ‰ during the MPWI, −1–2.4 ‰ during the early Pleistocene, and −2.2 to 2.3 ‰ in modern shells. Stable carbon isotope ratios ranged from −0.91 to 1.67 ‰ during the MPWI, 0.19–1.87 ‰ during the early Pleistocene, and −2.46 to 0.60 ‰ in modern shells. Average seasonal growth temperature variations for the MPWI (∼11 ± 3 °C) are reduced compared to modern instrument records (∼16 ± 3 °C), while the early Pleistocene (∼14 ± 2 °C) was more similar to today. Modern Mercenaria record dark increment formation during the summer while fossil Mercenaria record dark increment formation during the winter. We hypothesize that this difference is timing of dark increment formation may be due in part to differences in water depth (∼1m for modern shells and ∼20m for fossil shells) or a shift in the location of the boundary between biogeographic zones. A −1.6 ‰ shift in mean stable carbon isotope ratios between fossil (0.92 ± 0.66 ‰) and modern (−0.65 ± 0.44 ‰) shells has been observed and may be a result of the “Suess Effect” and/or influences of estuarine/freshwater relative to marine settings.

BrGDGT-based seasonal paleotemperature reconstruction for the last 15 000 years from a shallow lake on the eastern Tibetan Plateau

Abstract. Understanding Holocene temperature changes is vital for resolving discrepancies between proxy reconstructions and climate models. The intricate temperature variations across the Tibetan Plateau (TP) add complexity to studying continental climate change during this period. Discrepancies between model-based and proxy-based reconstructions might stem from seasonal biases and environmental uncertainties in the proxies. Employing multiple proxies from a single sediment core for quantitative temperature reconstructions offers an effective method for cross-validation in terrestrial environments. Here, we present an ice-free-season temperature record for the past 15 kyr from a shallow, freshwater lake on the eastern TP, based on brGDGTs (branched glycerol dialkyl glycerol tetraethers). This record shows that the Holocene Thermal Maximum lags the pollen-based July temperature recorded in the same sediment core. We conclude that the mismatch between the brGDGT-based and pollen-based temperatures is primarily the result of seasonal variations in solar irradiance. The overall pattern of temperature changes is supported by other summer temperature records, and the Younger Dryas cold event and the Bølling–Allerød warm period are also detected. A generally warm period occurred during 8–3.5 ka, followed by a cooling trend in the late Holocene. Our findings have implications for understanding the seasonal signal of brGDGTs in shallow lakes and provide critical data for confirming the occurrence of seasonal biases in different proxies from high-elevation lakes. To further investigate the significance of the brGDGTs and temperature patterns on the TP, we examined existing brGDGT-based Holocene temperature records, which interpret these compounds as indicators of mean annual or growing season temperatures. The existing and available temperature records show complicated patterns of variation, some with general warming trends throughout the Holocene, some with cooling trends, and some with a warm middle Holocene. We analyzed the possible reasons for the diverse brGDGTs records on the TP and emphasize the importance of considering lake conditions and modern investigations of brGDGTs in lacustrine systems when using brGDGTs to reconstruct paleoenvironmental conditions.

Southern Ocean High‐Resolution (SOhi) Modeling Along the Antarctic Ice Sheet Periphery

AbstractThe Southern Ocean plays a major role in controlling the evolution of Antarctic glaciers and in turn their impact on sea level rise. We present the Southern Ocean high‐resolution (SOhi) simulation of the MITgcm ocean model to reproduce ice‐ocean interaction at 1/24° around Antarctica, including all ice shelf cavities and oceanic tides. We evaluate the model accuracy on the continental shelf using Marine Mammals Exploring the Oceans Pole to Pole data and compare the results with three other MITgcm ocean models (ECCO4, SOSE, and LLC4320) and the ISMIP6 temperature reconstruction. Below 400 m, all the models exhibit a warm bias on the continental shelf, but the bias is reduced in the high‐resolution simulations. We hypothesize some of the bias is due to an overestimation of sea ice cover, which reduces heat loss to the atmosphere. Both high‐resolution and accurate bathymetry are required to improve model accuracy around Antarctica.

Sea surface temperature reconstruction in the Pacific Ocean using multi-elemental proxy in Porites and Diploastrea corals: Application to Palau Archipelago

Massive reef-building Porites corals are commonly studied to obtain long-term reconstructions of past sea surface temperature (SST) using temperature-sensitive elemental proxies, such as Sr/Ca or Li/Mg ratios. Most recently, a multi-proxy approach combining these two ratios (e.g. D'Olivo et al., 2018) and the SrU method (DeCarlo et al., 2016) have proved to be more robust to reconstruct paleo-temperatures. To date, no study has been carried out on the application of these new approaches on the Diploastrea heliopora coral, another massive reef-building genus that can potentially provide longer temperature records. Moreover, only a few studies have assessed coral SST calibrations at the scale of the Indo-Pacific basin and compared SST reconstructions obtained from two massive coral genera from the same site.In this study, we investigated the elemental composition of the topmost portion of 34 modern tropical Porites and 6 Diploastrea colonies collected during the Tara Pacific expedition (2016–2018) from various hydrological contexts in the Pacific Ocean. We derived and discussed annual Sr/Ca, Li/Mg, combined Sr/Ca-Li/Mg and Sr/Ca-Li/Ca-Mg/Ca and SrU vs. SST calibrations as well as potential intra-colonial and genus specific effects and evaluated the use of these basin-wide calibration equations. Overall, multi-ratio and multi-genera SST calibrations perform better than single-ratio calibrations and seem to improve temperature reconstructions.These new SST calibrations were applied to two colonies of Porites and Diploastrea collected from the same site in the North-West of the Palau archipelago located in the western Pacific Ocean to evaluate the applicability of universal calibrations based on different proxies and their combination. Coral-based SST records spanning the last 141 years show decadal changes and recent warming episodes that are related to major El Niño Southern Oscillation events. However, differences in reconstruction remain between both genera in the long-term trends, amplitudes, and absolute temperatures, depending on which genus or temperature proxy is considered.

First Pediastrum–temperature transfer function and its application to mid-to-late Holocene reconstruction in Central Asia

The green alga Pediastrum is an ecologically significant component of freshwater ecosystems, but its potential as an independent proxy for quantitative paleoenvironmental reconstruction is relatively unexplored. Here we use multivariate statistical analysis to explore the relationship between the Pediastrum composition of lake surface sediments and environmental variables. The findings highlight the mean growing season air temperature between March and October (TMar-Oct) as the most important factor determining the Pediastrum composition. We then establish the first transfer function between the Pediastrum taxa and TMar-Oct, which enables us to provide a quantitative temperature reconstruction for the past ∼8.2 kyr based on sedimentary subfossil Pediastrum records from Bosten Lake in Xinjiang, China. Our findings reveal an exceptionally warm climate during ∼4.8–3.6 kyr, with temperatures ∼4 °C higher compared to those during ∼8.2–4.8 kyr. This unusually warm climate is verified by the carbonate clumped isotopes record of the same core and other paleoclimate records. These findings contribute to our understanding of past temperature changes in Central Asia and provide a basis for future research on long-term lake ecosystem dynamics under past climatic warming.

Increasing prevalence of hot drought across western North America since the 16th century.

Across western North America (WNA), 20th-21st century anthropogenic warming has increased the prevalence and severity of concurrent drought and heat events, also termed hot droughts. However, the lack of independent spatial reconstructions of both soil moisture and temperature limits the potential to identify these events in the past and to place them in a long-term context. We develop the Western North American Temperature Atlas (WNATA), a data-independent 0.5° gridded reconstruction of summer maximum temperatures back to the 16th century. Our evaluation of the WNATA with existing hydroclimate reconstructions reveals an increasing association between maximum temperature and drought severity in recent decades, relative to the past five centuries. The synthesis of these paleo-reconstructions indicates that the amplification of the modern WNA megadrought by increased temperatures and the frequency and spatial extent of compound hot and dry conditions in the 21st century are likely unprecedented since at least the 16th century.

Climate change, society, and pandemic disease in Roman Italy between 200 BCE and 600 CE.

Records of past societies confronted with natural climate change can illuminate social responses to environmental stress and environment-disease connections, especially when locally constrained high-temporal resolution paleoclimate reconstructions are available. We present a temperature and precipitation reconstruction for ~200 BCE to ~600 CE, from a southern Italian marine sedimentary archive-the first high-resolution (~3 years) climate record from the heartland of the Roman Empire, stretching from the so-called Roman Climate Optimum to the Late Antique Little Ice Age. We document phases of instability and cooling from ~100 CE onward but more notably after ~130 CE. Pronounced cold phases between ~160 to 180 CE, ~245 to 275 CE, and after ~530 CE associate with pandemic disease, suggesting that climate stress interacted with social and biological variables. The importance of environment-disease dynamics in past civilizations underscores the need to incorporate health in risk assessments of climate change.