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15 results for “mid-Holocene”
Gridded depth and accumulation products from dated airborne radar stratigraphy over West Antarctica during the mid-Holocene, v.1.0.0
<p>This dataset comprises of codes (written in MATLAB) and gridded files (exported as GeoTIFF) presented in Bodart et al. (2023; The Crysophere; <a href="https://doi.org/10.5194/tc-2022-199">https://doi.org/10.5194/tc-2022-199</a>). A summary of the key findings from this study is provided as follows:</p> <p>"Using a spatially extensive IRH over Pine Island Glacier, Thwaites Glacier, and Institute and Möller Ice Streams (covering a total of 610 000 km2 or 30% of the WAIS), and a local layer approximation model, we infer mid-Holocene accumulation rates over the slow-flowing parts of these catchments for the past ~4700 years. By comparing our results with modern climate reanalysis models (1979 – 2019) and observational syntheses (1651 – 2010), we estimate that accumulation rates over the Amundsen-Weddell-Ross divide were on average 18% higher during the mid-Holocene than modern rates. However, no significant spatial changes in the accumulation pattern were observed."</p> <p>This dataset contains a series of files (5x .m files, 10x .tif files). The numbering of the figures in the description below refers to the order of the figures in the associated paper.</p> <ul> <li><strong> 5x MATLAB files:</strong> <ul> <li><strong>Calculate_accumulation_rates.m</strong>: calculates accumulation rates for the mid-Holocene-to-present, as well as uncertainties associated with the age and model structural uncertainty;</li> <li><strong>Calculate_D_parameter.m</strong>: calculates the D parameter (and associated L_path, L_H and L_b) to assess the feasability of the LLA over our grid;</li> <li><strong>Calculate_longitudinal_strain_rates.m</strong>: calculates the longitudinal strain rates over our grid from modern ice-flow velocities;</li> <li><strong>Calculate_vertical_strain_rates.m</strong>: calculates vertical strain rates for the mid-Holocene-to-present part of the ice column from accumulation estimates;</li> <li><strong>Resample_IRH_data.m</strong>: Re-samples the along-track IRH data into evenly distributed 500-m points for speeding up the gridding and calculations of accumulation rates;<br> </li> </ul> </li> <li><strong>10x GeoTIFF files:</strong> <ul> <li><strong>Holocene_IRH_depth_Fig2a.tif: </strong>Figure 2a;</li> <li><strong>Holocene_accumulation_rates_Fig3a.tif:</strong> Figure 3a;</li> <li><strong>Difference_Holocene_accumulation_RACMO2_Fig3c.tif:</strong> Figure 3c;</li> <li><strong>Relative_difference_Holocene_accumulation_RACMO2_Fig4.tif:</strong> Figure 4;</li> <li><strong>D_parameter_FigS1d.tif:</strong> Figure S1d;</li> <li><strong>Holocene_vertical_strain_rates_FigS2a.tif: </strong>Figure S2a;</li> <li><strong>Longitudinal_strain_rates_FigS2b.tif:</strong> Figure S2b;</li> <li><strong>Holocene_accumulation_lower_uncertainty_FigS4a.tif:</strong> Figure S4a;</li> <li><strong>Holocene_accumulation_upper_uncertainty_FigS4b.tif:</strong> Figure S4b;</li> <li><strong>Holocene_accumulation_relative_uncertainty_FigS4c.tif: </strong>Figure S4c;</li> </ul> </li> </ul> <p>Please also cite the associated paper when using this dataset.</p> <p>Any questions, please direct them to the corresponding author, Julien Bodart (julien.bodart@ed.ac.uk).</p>
Data provided in manuscript Mid-Holocene rainfall seasonality and ENSO dynamics over the southwestern Pacific
<p>Here we provide datasets of trace elements (LA-ICP-MS), carbon and oxygen stable isotopes, and greyscale values extracted from stalagmite C132 from Niue Island, covering the mid-Holocene (6.4 to 5.4 ka BP). The dataset includes the speleothem 230Th dates, and layer counting.</p>
Too hot for the devil? Did climate change cause the mid-Holocene extinction of the Tasmanian devil (Sarcophilus harrisii) from mainland Australia?
<p>The possible role of climate change in late Quaternary animal extinctions is hotly debated, yet few studies have investigated its direct effects on animal physiology to assess whether past climate changes might have had significant impacts on now-extinct species. Here we test whether climate change could have imposed physiological stress on the Tasmanian devil (Sarcophilus harrisii) during the mid-Holocene, when the species went extinct on mainland Australia. Physiological values for the devil were quantified using mechanistic niche models of energy and water requirements for thermoregulation, and soil-moisture-based indices of plant stress from drought to indirectly represent food and water availability. The spatial pervasiveness, extremity, and frequency of physiological stresses were compared between a period of known climatic and presumed demographic stability (8000-6010 BP) and the extinction period (5000-3010 BP). We found no evidence of widespread negative effects of climate on physiological parameters for the devil on the mainland during its extinction window. This leaves cultural and demographic changes in the human population or competition from the dingo (Canis dingo) as the main contending hypotheses to explain mainland loss of the devil in the mid-Holocene.</p>
Supplementary files for the article "Reconstruction of the surface temperature employing models with different complexity levels: a study for the mid-Holocene."
<p>Dear members of the scientific community,</p> <p>This dataset contains all data and scripts used to prepare the manuscript "Reconstruction of the Surface Temperature Employing Models with Different Complexity Levels: A Study for the Mid-Holocene." </p> <p>Notice that the compressed file contains folders for the mid-Holocene and pre-industrial scenarios and the climatologies of the scenarios' differences. To sum up, we provide each model output adopted in this study and their ensembles: high-complexity models (HCM), Reduced-complexity models (RCM), and All-complexity models (ACM). The statistics and plots can be generated by running the R scripts within the "R_script" folder.</p> <p><br>Best regards,</p> <p>Emerson D. Oliveira</p>
Supplementary Data for: Worldwide consequences of a mid-Holocene cold event in the Nordic Seas
<p>SupplementaryTable1.xlsx lists all the samples used to calculate the regional reservoir correction.</p> <p>SupplementaryTable2.xlsx lists all information on the individual radiocarbon dates of all the cores used in the study: LabID, Depth [cm], 14C age ± error, Calibrated age (95% confidence range and mean), and Dated species. Please note that the age-depth relationships have been modeled using a Bayesian approach so the Calibrated ages might differ from the ages that would be yielded by the calibration of individual radiocarbon ages.</p> <p>SupplementaryTable3.xlsx contains all the data used in the study:</p> <p>OCE2017-GR02:<br>- Depth [cm] <br>- Age [ka BP] (this study)<br>- <em>N. pachyderma </em>[%] (Telesiński et al. 2022)<br>- summer sSST 100m [°C] (this study)</p> <p>MSM5-5-723:<br>- Depth [cm]<br>- Age [ka BP] (this study)<br>- <em>N. pachyderma</em> [%] (Werner et al. 2015)<br>- summer sSST 100m [°C] (this study)<br>- P<sub>B</sub>IP<sub>25</sub> (Werner et al. 2015)<br>- Planktic foraminifera fragmentation [%] (Werner et al. 2003)</p> <p>JM10-330GC:<br>- Depth [cm]<br>- Age [ka BP] (this study)<br>- <em>N. pachyderma </em>[%] (Consolaro et al. 2018)<br>- summer sSST 100m [°C] (this study)<br>- Planktic foraminifera [ind./g] (Consolaro et al. 2018)</p> <p>MSM5-5-712:<br>- Depth [cm]<br>- Age [ka BP] (this study)<br>- <em>N. pachyderma </em>[%] (Werner et al. 2013)<br>- summer sSST 100m [°C] (this study)<br>- IRD flux [#/cm**2/kyr] (Werner et al. 2013, recalculated to the new age model)<br>- P<sub>B</sub>IP<sub>25 </sub>(Müller et al. 2012)</p> <p>M23258:<br>- Depth [cm]<br>- Age [ka BP] (this study)<br>- <em>N. pachyderma </em>[%] (Sarnthein et al. 2003)<br>- summer sSST 100m [°C] (this study)<br>- annual SST [°C] (Martrat et al. 2003)</p> <p>M17730-4<br>- Depth [cm]<br>- Age [ka BP] (this study)<br>- <em>N. pachyderma </em>[%] (Telesiński et al. 2015)<br>- summer sSST 100m [°C] (this study)<br>- Planktic foraminifera [ind./g] (Telesiński et al. 2015)</p> <p>MD95-2011<br>- Depth [cm]<br>- Age [ka BP] (this study)<br>- <em>N. pachyderma </em>[%] (Risebrobakken et al. 2003)<br>- summer sSST 100m [°C] (this study)<br>- Planktic foraminifera [ind./g] (Risebrobakken et al. 2003)</p> <p>MD99-2284<br>- Depth [cm]<br>- Age [ka BP] (this study)<br>- <em>N. pachyderma </em>[%] (Bakke et al. 2009, Eldevik et al. 2014)<br>- summer sSST 100m [°C] (this study)</p> <p>JM09-020<br>- Depth [cm]<br>- Age [ka BP] (this study)<br>- annual SST [°C] (Łącka et al. 2019)</p> <p>SupplementaryFigure1.pdf shows Age-depth relationships of cores used in the study as modeled using a Bayesian approach with the Bacon software (Blaauw and Christen, 2011). Dark shading indicates the more likely ages for a given depth, the grey dashed line indicates the 95% confidence range, and the red dashed line indicates the best-fit (mean) age model.</p> <p>SupplementaryFigure2.pdf shows Sea-ice concentration in (A) 6.83-6.85 ka BP and (B) 7.63-7.65 ka BP in the TraCE-21ka. Subsurface (92 m) temperature in (C) 6.81-6.83 ka BP and (D) 7.63-7.65 ka BP in the TraCE-21ka.</p>
Too hot for the devil? Did climate change cause the mid-Holocene extinction of the Tasmanian devil (Sarcophilus harrisii) from mainland Australia?
Open the record for dataset details and reuse information.
~550-year climate periodicity in the Yunnan-Guizhou plateau during the late mid-Holocene: Insights and implications
<p>This is the Supporting Information for Li et al. "550-Year Climate Periodicity in the Yunnan-Guizhou Plateau during the late Mid-Holocene: Insights and Implications" published in Geophysical Research Letters. The data comes from a stalagmite in southwestern China (27° 4' N, 105° 5' E). The dataset includes the speleothem 230Th dating data (Table S1 in Supporting Information S1), the speleothem 230Th dating, 13C, lamina thickness, 18O, Sr/Ca and Mg/Ca data (Table S2), the updated 14C database from archaeological sites in southwestern China (Table S3), the calculated minimal occupation events as the unit of analysis by combining more than one 14C date (Table S4) and the summed 14C probability (SCP) records (Table S5). The Supporting Information S1 includes a pdf file (available through Zenodo) provided also contains details on the methods of all the lab work, the results of the trace elements, the demonstration of annual lamina and application of least-squares fit, the practices of calculating summed 14C probability (SCP) distributions in southwestern China and a discussion on how ENSO and local precipitation can influence the proxies. Additionally, there are supporting figures (Figure S1-S8) for the main text in Supporting Information S1. The speleothem 230Th dating, 13C, lamina thickness, 18O, Sr/Ca and Mg/Ca data in this study are also available in the public paleoclimate database of the National Oceanic and Atmospheric Administration (NOAA) (https://www.ncei.noaa.gov/access/paleo-search/study/38059).</p>
~550-year climate periodicity in the Yunnan-Guizhou plateau during the late mid-Holocene: Insights and implications
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Data from: Dynamics of marsh-mangrove ecotone since the mid-Holocene: a palynological study of mangrove encroachment and sea level rise in the Shark River Estuary, Florida
Sea level rise and the associated inland shift of the marsh-mangrove ecotone in south Florida have raised many scientific and management concerns in recent years. Holocene paleoecological records can provide an important baseline to shed light on the long-term dynamics of vegetation changes across this ecotone in the past, which is needed to predict the future. In this study, we present palynological, X-ray fluorescence, and loss-on ignition data from four sedimentary cores recovered from a 20-km marine-to-freshwater transect along the Shark River Estuary, southwest Everglades, to document the patterns and processes of coastal vegetation changes in response to sea level rise since the mid-Holocene. Our record indicates that freshwater marsh progressively replaced marl prairies at the Shark River Estuary between 5700 and 4400 cal yr BP. As marine transgression continued, marine influence reached the threshold necessary for mangroves to establish at the current mouth of the Shark River Slough at 3800 cal yr BP. During the next 3000 years, although sea level rise in the Western North Atlantic slowed down to 0.4 mm/yr, a spatial and temporal gradient was evident as the marsh-mangrove ecotone shifted inland by 20 km from 3800 to 800 cal yr BP, accompanied by a gradual landward replacement of freshwater marsh by mangrove forest. If sea level continues to rise at 2.33 mm/yr in the 21st century in south Florida, it is possible that marine influence will reach the threshold for mangroves to establish in the central Everglades, and we could expect a much more aggressive mangrove encroachment toward the northern and interior parts of south Florida in the next few centuries.
The isotopic composition of the French Illimani ice core in the Bolivian Andes supports the east-west South American precipitation dipole from the last deglaciation to the mid-Holocene
<p>Isotopic composition (deuterium and deuterium excess) of the French Illimani ice core drilled in 1999 with a revised dating detailed in the following manuscript:</p> <p>Françoise Vimeux and Amaëlle Landais, 2025. The isotopic composition of the French Illimani ice core in the Bolivian Andes supports the east-west South American precipitation dipole from the last deglaciation to the mid-Holocene. Quaternary Science Reviews 347, https://doi.org/10.1016/j.quascirev.2024.109098.</p>
Mid-Holocene ENSO Variability reduced by northern African vegetation changes: a model intercomparison study
<p>This dataset contains model outputs from four climate models: EC-Earth, iCESM, UofT-CCSM4 and GISS. For each model, data is provided for three simulations: pre Industrial (PI), reference mid-Holocene without Green Sahara (MH_PMIP), and mid-Holocene with Green Sahara (MH_GS). For each simulation, data is provided for the variables: surface temperature, precipitation and zonal wind strength.</p>
AWI-CM3 output of mid-Holocene and pre-industrial experiments
<p>This repository contains the AWI-CM3 output of the pre-industrial (PI) and mid-Holocene (MH) experiments.</p> <p>Files description</p> <p>2t=> surface air temperature (2m)<br> a_ice=> sea ice concentration<br> radiation: radiation: components of Arctic surface energy budget</p> <p>PI and MH both contains 5 ensemble runs, which are labeled as 001-005.</p> <p>For more data details, please refer to the self-describing information of NetCDF files.</p>
Data from: Dynamics of marsh-mangrove ecotone since the mid-Holocene: a palynological study of mangrove encroachment and sea level rise in the Shark River Estuary, Florida
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Appendix to paper Mid-Holocene climate record in Santovka travertine (Slovakia) in context of regional discrepancies of climate shifts 8.2 and 7.4 ka BP
<p>Figures, data, and code are available in html file exported from RStudio. The html knit file contain the whole code with notes, used R libraries, data preparation, visualisation of plots, and data analyses. Zip file contain used LiPD data of Santovka-village and other sites.</p>
Climate simulations of impact of LULC on mid-Holocene climate
<p>Extracted data from climate simulations by Smith et al., 2016 with and without landuse-landcover changes at 6000 yr BP., used to construct Figure 8 in <strong>Harrison, S.P.</strong>, Gaillard, M-J., Stocker, B., Vander Linden, M., Klein Goldewijk, K., Boles, O., Braconnot, P., Dawson, A., Fluet-Chouinard, E., Kaplan, J.O., Kastner, T., Pausata, F.S.R., Robinson, E., Whitehouse, N., Madella, M., Morrison, K.D., 2019. Development and testing of scenarios for implementing Holocene LULC in Earth System Model Experiments. <em>Geoscientific Model Development</em> <em>Discussions, </em><strong><a href="https://doi.org/10.5194/gmd-2019-125%20%20%20%207">https://doi.org/10.5194/gmd-2019-125 7</a></strong></p>
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International Brain Laboratory public data
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OpenNeuro
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