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There has been considerable debate about the degree to which climate has driven societal changes in the eastern Mediterranean region, partly through reliance on a limited number of qualitative records of climate changes and partly reflecting the need to disentangle the joint impact of changes in different aspects of climate. Here, we use tolerance-weighted, weighted-averaging partial least squares to derive reconstructions of the mean temperature of the coldest month (MTCO), mean temperature of the warmest month (MTWA), growing degree days above a threshold of 0 ∘ C (GDD0), and plant-available moisture, which is represented by the ratio of modelled actual to equilibrium evapotranspiration (α) and corrected for past CO 2 changes. This is done for 71 individual pollen records from the eastern Mediterranean region covering part or all of the interval from 12.3 ka to the present. We use these reconstructions to create regional composites that illustrate the long-term trends in each variable. We compare these composites with transient climate model simulations to explore potential causes of the observed trends. We show that the glacial–Holocene transition and the early part of the Holocene was characterised by conditions colder than the present. Rapid increases in temperature occurred between ca. 10.3 and 9.3 ka, considerably after the end of the Younger Dryas. Although the time series are characterised by centennial to millennial oscillations, the MTCO showed a gradual increase from 9 ka to the present, consistent with the expectation that winter temperatures were forced by orbitally induced increases in insolation during the Holocene. The MTWA also showed an increasing trend from 9 ka and reached a maximum of ca. 1.5 ∘ C greater than the present at ca. 4.5 and 5 ka, followed by a gradual decline towards present-day conditions. A delayed response to summer insolation changes is likely a reflection of the persistence of the Laurentide and Fennoscandian ice sheets; subsequent summer cooling is consistent with the expected response to insolation changes. Plant-available moisture increased rapidly after 11 ka, and conditions were wetter than today between 10 and 6 ka, but thereafter, α declined gradually. These trends likely reflect changes in atmospheric circulation and moisture advection into the region and were probably too small to influence summer temperature through land–surface feedbacks. Differences in the simulated trajectory of α in different models highlight the difficulties in reproducing circulation-driven moisture advection into the eastern Mediterranean. [ABSTRACT FROM AUTHOR]

Vegetation regulates land‐atmosphere, water, and energy exchanges and is an essential component of land‐surface models (LSMs). However, LSMs have been handicapped by assumptions that equate acclimated photosynthetic responses to the environment with the fast responses observable in the laboratory. The effects of acclimation can be taken into account by including PFT‐specific values of photosynthetic parameters, but at the cost of increasing parameter requirements. Here, we develop an alternative approach for including acclimation in LSMs by adopting the P model, an existing light‐use efficiency model for gross primary production (GPP) that implicitly predicts the acclimation of photosynthetic parameters on a weekly to monthly timescale via optimality principles. We demonstrate that it is possible to explicitly separate the fast and slow photosynthetic responses to environmental conditions, allowing the simulation of GPP at the sub‐daily timesteps required for coupling in an LSM. The resulting model reproduces the diurnal cycles of GPP recorded by eddy‐covariance flux towers in a temperate grassland and boreal, temperate and tropical forests. The best performance is achieved when biochemical capacities are adjusted to match recent midday conditions. Comparison between this model and the operational LSM in the European Centre for Medium‐range Weather Forecasts climate model shows that the new model has better predictive power in most of the sites and years analyzed, particularly in summer and autumn. Our analyses suggest a simple and parameter‐sparse method to include both instantaneous and acclimated responses within an LSM framework, with potential applications in weather, climate, and carbon‐cycle modeling. Plain Language Summary: Vegetation regulates the exchanges of energy, water, and carbon dioxide between the land and the atmosphere. Numerical climate models represent these processes, focusing mainly on their rapid variations in response to changes in the environment (including temperature and light) on timescales of seconds to hours. However, plants also adjust their physiology to environmental changes over longer periods within the season. Here, we have adapted a simple model that formulates plant behavior in terms of optimal trade‐offs between different processes, so it simulates processes on both timescales. This model correctly reproduces the daily cycle of carbon dioxide uptake by plants, as recorded in different kinds of vegetation. We show that plants optimize their behavior for midday conditions, when the light is greatest, and adjust to longer‐term environmental variations on a timescale of a week to a month. The model conveniently avoids the need to give specific, fixed values to physiological variables (such as photosynthetic capacity) for different types of plants. The optimality assumptions mean that the model gives equally good results in tropical, temperate, and boreal forests, and in grasslands, using the same equations, and a very small number of input variables. Key Points: Optimality theory is used to develop a model incorporating fast and acclimated responses of photosynthesis and stomatal conductanceBiogeochemical photosynthetic capacities adjust to midday light conditionsThe new parameter‐sparse model simulates gross primary production on sub‐daily timesteps across a range of vegetation types and climates [ABSTRACT FROM AUTHOR]

The Last Glacial Maximum (LGM, ∼ 21 000 years ago) has been a major focus for evaluating how well state-of-the-art climate models simulate climate changes as large as those expected in the future using paleoclimate reconstructions. A new generation of climate models has been used to generate LGM simulations as part of the Paleoclimate Modelling Intercomparison Project (PMIP) contribution to the Coupled Model Intercomparison Project (CMIP). Here, we provide a preliminary analysis and evaluation of the results of these LGM experiments (PMIP4, most of which are PMIP4-CMIP6) and compare them with the previous generation of simulations (PMIP3, most of which are PMIP3-CMIP5). We show that the global averages of the PMIP4 simulations span a larger range in terms of mean annual surface air temperature and mean annual precipitation compared to the PMIP3-CMIP5 simulations, with some PMIP4 simulations reaching a globally colder and drier state. However, the multi-model global cooling average is similar for the PMIP4 and PMIP3 ensembles, while the multi-model PMIP4 mean annual precipitation average is drier than the PMIP3 one. There are important differences in both atmospheric and oceanic circulations between the two sets of experiments, with the northern and southern jet streams being more poleward and the changes in the Atlantic Meridional Overturning Circulation being less pronounced in the PMIP4-CMIP6 simulations than in the PMIP3-CMIP5 simulations. Changes in simulated precipitation patterns are influenced by both temperature and circulation changes. Differences in simulated climate between individual models remain large. Therefore, although there are differences in the average behaviour across the two ensembles, the new simulation results are not fundamentally different from the PMIP3-CMIP5 results. Evaluation of large-scale climate features, such as land–sea contrast and polar amplification, confirms that the models capture these well and within the uncertainty of the paleoclimate reconstructions. Nevertheless, regional climate changes are less well simulated: the models underestimate extratropical cooling, particularly in winter, and precipitation changes. These results point to the utility of using paleoclimate simulations to understand the mechanisms of climate change and evaluate model performance. [ABSTRACT FROM AUTHOR]

Reconstruction of past changes in monsoon climate from speleothem oxygen isotope (δ18O) records is complex because δ18O signals can be influenced by multiple factors including changes in precipitation, precipitation recycling over land, temperature at the moisture source, and changes in the moisture source region and transport pathway. Here, we analyse >150 speleothem records of the Speleothem Isotopes Synthesis and AnaLysis (SISAL) database to produce composite regional trends in δ18O in monsoon regions; compositing minimises the influence of site-specific karst and cave processes that can influence individual site records. We compare speleothem δ18O observations with isotope-enabled climate model simulations to investigate the specific climatic factors causing these regional trends. We focus on differences in δ18O signals between the mid-Holocene, the peak of the Last Interglacial (Marine Isotope Stage 5e) and the Last Glacial Maximum as well as on δ18O evolution through the Holocene. Differences in speleothem δ18O between the mid-Holocene and the Last Interglacial in the East Asian and Indian monsoons are small, despite the larger summer insolation values during the Last Interglacial. Last Glacial Maximum δ18O values are significantly less negative than interglacial values. Comparison with simulated glacial–interglacial δ18O shows that changes are principally driven by global shifts in temperature and regional precipitation. Holocene speleothem δ18O records show distinct and coherent regional trends. Trends are similar to summer insolation in India, China and southwestern South America, but they are different in the Indonesian–Australian region. Redundancy analysis shows that 37 % of Holocene variability can be accounted for by latitude and longitude, supporting the differentiation of records into individual monsoon regions. Regression analysis of simulated precipitation δ18O and climate variables show significant relationships between global Holocene monsoon δ18O trends and changes in precipitation, atmospheric circulation and (to a lesser extent) source area temperature, whereas precipitation recycling is non-significant. However, there are differences in regional-scale mechanisms: there are clear relationships between changes in precipitation and δ18O for India, southwestern South America and the Indonesian–Australian regions but not for the East Asian monsoon. Changes in atmospheric circulation contribute to δ18O trends in the East Asian, Indian and Indonesian–Australian monsoons, and a weak source area temperature effect is observed over southern and central America and Asia. Precipitation recycling is influential in southwestern South America and southern Africa. Overall, our analyses show that it is possible to differentiate the impacts of specific climatic mechanisms influencing precipitation δ18O and use this analysis to interpret changes in speleothem δ18O. [ABSTRACT FROM AUTHOR]

Quantitative reconstructions of past climates are an important resource for evaluating how well climate models reproduce climate changes. One widely used statistical approach for making such reconstructions from fossil biotic assemblages is weighted averaging partial least-squares regression (WA-PLS). There is however a known tendency for WA-PLS to yield reconstructions compressed towards the centre of the climate range used for calibration, potentially biasing the reconstructed past climates. We present an improvement of WA-PLS by assuming that: (i) the theoretical abundance of each taxon is unimodal with respect to the climate variable considered; (ii) observed taxon abundances follow a multinomial distribution in which the total abundance of a sample is climatically uninformative; and (iii) the estimate of the climate value at a given site and time makes the observation most probable, i.e. it maximizes the log-likelihood function. This climate estimate is approximated by weighting taxon abundances in WA-PLS by the inverse square of their climate tolerances. We further improve the approach by considering the frequency (fx) of the climate variable in the training dataset. Tolerance-weighted WA-PLS with fx correction greatly reduces the compression bias, compared with WA-PLS, and improves model performance in reconstructions based on an extensive modern pollen dataset. [ABSTRACT FROM AUTHOR]

Characterizing the temporal uncertainty in palaeoclimate records is crucial for analysing past climate change, correlating climate events between records, assessing climate periodicities, identifying potential triggers and evaluating climate model simulations. The first global compilation of speleothem isotope records by the SISAL (Speleothem Isotope Synthesis and Analysis) working group showed that age model uncertainties are not systematically reported in the published literature, and these are only available for a limited number of records (ca. 15 %, n=107/691). To improve the usefulness of the SISAL database, we have (i) improved the database's spatio-temporal coverage and (ii) created new chronologies using seven different approaches for age–depth modelling. We have applied these alternative chronologies to the records from the first version of the SISAL database (SISALv1) and to new records compiled since the release of SISALv1. This paper documents the necessary changes in the structure of the SISAL database to accommodate the inclusion of the new age models and their uncertainties as well as the expansion of the database to include new records and the quality-control measures applied. This paper also documents the age–depth model approaches used to calculate the new chronologies. The updated version of the SISAL database (SISALv2) contains isotopic data from 691 speleothem records from 294 cave sites and new age–depth models, including age–depth temporal uncertainties for 512 speleothems. SISALv2 is available at 10.17864/1947.256 (Comas-Bru et al., 2020a). [ABSTRACT FROM AUTHOR]

This paper is the first of a series of four GMD papers on the PMIP4-CMIP6 experiments. Part 2 (Otto-Bliesner et al., 2017) gives details about the two PMIP4-CMIP6 interglacial experiments, Part 3 (Jungclaus et al., 2017) about the last millennium experiment, and Part 4 (Kageyama et al., 2017) about the Last Glacial Maximum experiment. The mid-Pliocene Warm Period experiment is part of the Pliocene Model Intercomparison Project (PlioMIP) - Phase 2, detailed in Haywood et al. (2016). The goal of the Paleoclimate Modelling Intercomparison Project (PMIP) is to understand the response of the climate system to different climate forcings for documented climatic states very different from the present and historical climates. Through comparison with observations of the environmental impact of these climate changes, or with climate reconstructions based on physical, chemical, or biological records, PMIP also addresses the issue of how well state-of-the-art numerical models simulate climate change. Climate models are usually developed using the present and historical climates as references, but climate projections show that future climates will lie well outside these conditions. Palaeoclimates very different from these reference states therefore provide stringent tests for state-of-the-art models and a way to assess whether their sensitivity to forcings is compatible with palaeoclimatic evidence. Simulations of five different periods have been designed to address the objectives of the sixth phase of the Coupled Model Intercomparison Project (CMIP6): the millennium prior to the industrial epoch (CMIP6 name: past1000); the mid-Holocene, 6000 years ago (midHolocene); the Last Glacial Maximum, 21 000 years ago (lgm); the Last Interglacial, 127 000 years ago (lig127k); and the mid-Pliocene Warm Period, 3.2 million years ago (midPliocene-eoi400). These climatic periods are well documented by palaeoclimatic and palaeoenvironmental records, with climate and environmental changes relevant for the study and projection of future climate changes. This paper describes the motivation for the choice of these periods and the design of the numerical experiments and database requests, with a focus on their novel features compared to the experiments performed in previous phases of PMIP and CMIP. It also outlines the analysis plan that takes advantage of the comparisons of the results across periods and across CMIP6 in collaboration with other MIPs. [ABSTRACT FROM AUTHOR]

ABSTRACT There has been a gradual evolution in the way that palaeoclimate modelling and palaeoenvironmental data are used together to understand how the Earth System works, from an initial and largely descriptive phase through explicit hypothesis testing to diagnosis of underlying mechanisms. Analyses of past climate states are now regarded as integral to the evaluation of climate models, and have become part of the toolkit used to assess the likely realism of future projections. Palaeoclimate assessment has demonstrated that changes in large-scale features of climate that are governed by the energy and water balance show consistent responses to changes in forcing in different climate states, and these consistent responses are reproduced by climate models. However, state-of-the-art models are still largely unable to reproduce observed changes in climate at a regional scale reliably. While palaeoclimate analyses of state-of-the-art climate models suggest an urgent need for model improvement, much work is also needed on extending and improving palaeoclimate reconstructions and quantifying and reducing both numerical and interpretative uncertainties. [ABSTRACT FROM AUTHOR]

The goal of the Palaeoclimate Modelling Intercomparison Project (PMIP) is to understand the response of the climate system to changes in different climate forcings and to feedbacks. Through comparison with observations of the environmental impacts of these climate changes, or with climate reconstructions based on physical, chemical or biological records, PMIP also addresses the issue of how well state-of-the-art models simulate climate changes. Palaeoclimate states are radically different from those of the recent past documented by the instrumental record and thus provide an out-of-sample test of the models used for future climate projections and a way to assess whether they have the correct sensitivity to forcings and feedbacks. Five distinctly different periods have been selected as focus for the core palaeoclimate experiments that are designed to contribute to the objectives of the sixth phase of the Coupled Model Intercomparison Project (CMIP6). This manuscript describes the motivation for the choice of these periods and the design of the numerical experiments, with a focus upon their novel features compared to the experiments performed in previous phases of PMIP and CMIP as well as the benefits of common analyses of the models across multiple climate states. It also describes the information needed to document each experiment and the model outputs required for analysis and benchmarking. [ABSTRACT FROM AUTHOR]

Quantitative palaeoclimate reconstructions are widely used to evaluate climate model performance. Here, as part of an effort to provide such a data set for Australia, we examine the impact of analytical decisions and sampling assumptions on modern-analogue reconstructions using a continent-wide pollen data set. There is a high degree of correlation between temperature variables in the modern climate of Australia, but there is sufficient orthogonality in the variations of precipitation, summer and winter temperature and plant–available moisture to allow independent reconstructions of these four variables to be made. The method of analogue selection does not affect the reconstructions, although bootstrap resampling provides a more reliable technique for obtaining robust measures of uncertainty. The number of analogues used affects the quality of the reconstructions: the most robust reconstructions are obtained using 5 analogues. The quality of reconstructions based on post-1850 CE pollen samples differ little from those using samples from between 1450 and 1849 CE, showing that European post-settlement modification of vegetation has no impact on the fidelity of the reconstructions although it substantially increases the availability of potential analogues. Reconstructions based on core top samples are more realistic than those using surface samples, but only using core top samples would substantially reduce the number of available analogues and therefore increases the uncertainty of the reconstructions. Spatial and/or temporal averaging of pollen assemblages prior to analysis negatively affects the subsequent reconstructions for some variables and increases the associated uncertainties. In addition, the quality of the reconstructions is affected by the degree of spatial smoothing of the original climate data, with the best reconstructions obtained using climate data from a 0.5° resolution grid, which corresponds to the typical size of the pollen catchment. This study provides a methodology that can be used to provide reliable palaeoclimate reconstructions for Australia, which will fill in a major gap in the data sets used to evaluate climate models. [ABSTRACT FROM AUTHOR]

Lack of constraint on spatial and long-term temporal variability of the El Niño southern Oscillation (ENSO) and its sensitivity to external forcing limit our ability to evaluate climate models and ENSO future projections. Current knowledge of Holocene ENSO variability derived from paleoclimate reconstructions does not separate the role of insolation forcing from internal climate variability. Using an updated synthesis of coral and bivalve monthly resolved records, we build composite records of seasonality and interannual variability in four regions of the tropical Pacific: Eastern Pacific (EP), Central Pacific (CP), Western Pacific (WP) and South West Pacific (SWP). An analysis of the uncertainties due to the sampling of chaotic multidecadal to centennial variability by short records allows for an objective comparison with transient simulations (mid-Holocene to present) performed using four different Earth System models. Sea surface temperature and pseudo-δ18O are used in model-data comparisons to assess the potential influence of hydroclimate change on records. We confirm the significance of the Holocene ENSO minimum (HEM) 3-6ka compared to low frequency unforced modulation of ENSO, with a reduction of ENSO variance of ∼50 % in EP and ∼80 % in CP. The approach suggests that the increasing trend of ENSO since 6ka can be attributed to insolation, while models underestimate ENSO sensitivity to orbital forcing by a factor of 4.7 compared to data, even when accounting for the large multidecadal variability. Precession-induced change in seasonal temperature range is positively linked to ENSO variance in EP and to a lesser extent in other regions, in both models and observations. Our regional approach yields insights into the past spatial expression of ENSO across the tropical Pacific. In the SWP, today under the influence of the South Pacific Convergence Zone (SPCZ), interannual variability was increased by ∼200 % during the HEM, indicating that SPCZ variability is independent from ENSO on millennial time scales. • Composite paleo-ENSO records compared to transient simulations in 4 Pacific regions. • Holocene ENSO minimum (HEM) 3-6ka is significant compared to centennial variability. • Trend in ENSO since 6ka is robustly attributed to insolation forcing. • Seasonal range and ENSO are positively linked in both models and observations. • The interannual variability in the SPCZ was strongly increased during the HEM. [ABSTRACT FROM AUTHOR]

Changes in lake status are often interpreted as palaeoclimate indicators due to their dependence on precipitation and evaporation. The Global Lake Status Database (GLSDB) has since long provided a standardised synopsis of qualitative lake status over the last 30,000 14C years. Potential sources of uncertainty however are not recorded in the GLSDB. Here we present an updated and improved relational-database framework that incorporates uncertainty in both chronology and the interpretation of palaeoenvironmental data. The database uses peer-reviewed palaeolimnological studies to produce a consensus on qualitative lake-status histories, whose chronologies are revised and standardized through the recalibration of radiocarbon dates and the application of Bayesian age-depth modelling for stratigraphic archives. Quantitative information on absolute water-level elevation is preserved if available from geomorphological sources. We also propose a new probabilistic analytical framework that accounts for these uncertainties to reconstruct synoptic, integrated environmental signals. The process is based on a Monte Carlo algorithm that iteratively samples individual lake-status histories within the limits of their uncertainties to produce many possible scenarios. We then use Recursively-Subtracted Empirical Orthogonal Function analysis to extract dominant patterns of lake-status variability from these scenarios. As a proof of concept, we apply this framework to 67 sites in eastern and southern Africa whose lake-status histories cover part of the late Pleistocene and/or Holocene. We show that, despite the sometimes large temporal and interpretation uncertainties, and the inclusion of highly discontinuous lake-status time series, identifying the major known millennial-scale climatic phases during the last 20,000 years is possible. Our framework was also able to identify an antiphased response between the lake basins in eastern and interior southern Africa to these changes. We propose that our new database and methodology framework serves as a template for efficient lake-status data synthesis, encourages the incorporation of lake-status data in palaeoclimate syntheses, and expands the possibilities for the use of such data in the evaluation of climate models. • A new database format synthesises lake-status histories, conserving data uncertainty in chronology and lake status. • Monte Carlo sampling and recursively-subtracted empirical orthogonal function analysis extract dominant lake-status patterns. • The method highlights millennial-scale palaeoclimatic trends of eastern and southern Africa of the last 20,000 year. [ABSTRACT FROM AUTHOR]