Here we describe LegacyClimate 1.0, a dataset of the reconstruction of the mean July temperature (T_July), mean annual temperature (T_ann), and annual precipitation (P_ann) from 2594 fossil pollen records from the Northern Hemisphere, spanning the entire Holocene, with some records reaching back to the Last Glacial Period. Two reconstruction methods, the modern analog technique (MAT) and weighted averaging partial least squares regression (WA-PLS), reveal similar results regarding spatial and temporal patterns. To reduce the impact of precipitation on temperature reconstruction, and vice versa, we also provide reconstructions using tailored modern pollen data, limiting the range of the corresponding other climate variables. We assess the reliability of the reconstructions, using information from the spatial distributions of the root mean squared error in the prediction and reconstruction significance tests. The dataset is beneficial for synthesis studies of proxy-based reconstructions and to evaluate the output of climate models and thus help to improve the models themselves. We provide our compilation of reconstructed T_July, T_ann, and P_ann as open-access datasets at PANGAEA (https://doi.org/10.1594/PANGAEA.930512; Herzschuh et al., 2023a). The R code for the reconstructions is provided at Zenodo (https://doi.org/10.5281/zenodo.7887565; Herzschuh et al., 2023b), including the harmonized open-access modern and fossil datasets used for the reconstructions, so that customized reconstructions can be easily established.

We collected the available relative pollen productivity estimates (PPEs) for 27 major pollen taxa from Eurasia and applied them to estimate plant abundances during the last 40 ka cal BP (calibrated thousand years before present) using pollen counts from 203 fossil pollen records in northern Asia (north of 40∘ N). These pollen records were organized into 42 site groups and regional mean plant abundances calculated using the REVEALS (Regional Estimates of Vegetation Abundance from Large Sites) model. Time-series clustering, constrained hierarchical clustering, and detrended canonical correspondence analysis were performed to investigate the regional pattern, time, and strength of vegetation changes, respectively. Reconstructed regional plant functional type (PFT) components for each site group are generally consistent with modern vegetation in that vegetation changes within the regions are characterized by minor changes in the abundance of PFTs rather than by an increase in new PFTs, particularly during the Holocene. We argue that pollen-based REVEALS estimates of plant abundances should be a more reliable reflection of the vegetation as pollen may overestimate the turnover, particularly when a high pollen producer invades areas dominated by low pollen producers. Comparisons with vegetation-independent climate records show that climate change is the primary factor driving land-cover changes at broad spatial and temporal scales. Vegetation changes in certain regions or periods, however, could not be explained by direct climate change, e.g. inland Siberia, where a sharp increase in evergreen conifer tree abundance occurred at ca. 7–8 ka cal BP despite an unchanging climate, potentially reflecting their response to complex climate–permafrost–fire–vegetation interactions and thus a possible long-term lagged climate response.

A mismatch between model- and proxy-based Holocene climate change, known as the “Holocene conundrum”, may partially originate from the poor spatial coverage of climate reconstructions in, for example, Asia, limiting the number of grid cells for model–data comparisons. Here we investigate hemispheric, latitudinal, and regional mean time series and time-slice anomaly maps of pollen-based reconstructions of mean annual temperature, mean July temperature, and annual precipitation from 1908 records in the Northern Hemisphere extratropics. Temperature trends show strong latitudinal patterns and differ between (sub-)continents. While the circum-Atlantic regions in Europe and eastern North America show a pronounced Middle Holocene temperature maximum, western North America shows only weak changes, and Asia mostly shows a continuous Holocene temperature increase. Likewise, precipitation trends show certain regional peculiarities such as the pronounced Middle Holocene precipitation maximum between 40 and 50^∘ N in Asia and Holocene increasing trends in Europe and western North America, which can all be linked with Holocene changes in the regional circulation pattern responding to temperature change. Given a background of strong regional heterogeneity, we conclude that the calculation of global or hemispheric means, which initiated the Holocene conundrum debate, should focus more on understanding the spatiotemporal patterns and their regional drivers.

A modern pollen dataset with an even distribution of sites is essential for pollen-based past vegetation and climate estimations. As there were geographical gaps in previous datasets covering the central and eastern Tibetan Plateau, lake surface sediment samples (n=117) were collected from the alpine meadow region on the Tibetan Plateau between elevations of 3720 and 5170 m a.s.l. Pollen identification and counting were based on standard approaches, and modern climate data were interpolated from a robust modern meteorological dataset. A series of numerical analyses revealed that precipitation is the main climatic determinant of pollen spatial distribution: Cyperaceae, Ranunculaceae, Rosaceae, and Salix indicate wet climatic conditions, while Poaceae, Artemisia, and Chenopodiaceae represent drought. Model performance of both weighted-averaging partial least squares (WA-PLS) and the random forest (RF) algorithm suggest that this modern pollen dataset has good predictive power in estimating the past precipitation from pollen spectra from the eastern Tibetan Plateau. In addition, a comprehensive modern pollen dataset can be established by combining our modern pollen dataset with previous datasets, which will be essential for the reconstruction of vegetation and climatic signals for fossil pollen spectra on the Tibetan Plateau. Pollen datasets including both pollen counts and percentages for each sample, together with their site location and climatic data, are available at the National Tibetan Plateau Data Center (TPDC; Cao et al., 2021; https://doi.org/10.11888/Paleoenv.tpdc.271191).

Here we describe the LegacyPollen 1.0, a dataset of 2831 fossil pollen records with metadata, a harmonized taxonomy, and standardized chronologies. A total of 1032 records originate from North America, 1075 from Europe, 488 from Asia, 150 from Latin America, 54 from Africa, and 32 from the Indo-Pacific. The pollen data cover the late Quaternary (mostly the Holocene). The original 10 110 pollen taxa names (including variations in the notations) were harmonized to 1002 terrestrial taxa (including Cyperaceae), with woody taxa and major herbaceous taxa harmonized to genus level and other herbaceous taxa to family level. The dataset is valuable for synthesis studies of, for example, taxa areal changes, vegetation dynamics, human impacts (e.g., deforestation), and climate change at global or continental scales. The harmonized pollen and metadata as well as the harmonization table are available from PANGAEA (https://doi.org/10.1594/PANGAEA.929773; Herzschuh et al., 2021). R code for the harmonization is provided at Zenodo (https://doi.org/10.5281/zenodo.5910972; Herzschuh et al., 2022) so that datasets at a customized harmonization level can be easily established.