This dataset contains extremal forecast of latitutude (lat), longitude (lon) and intensity of the geomagnetic dipole between 2019 and 2119. The geomagnetic dipole is evolved by a fluid flow at the core-mantle boundary that maximises the rate-of-change of the dipole latitude. The forecast is calculated from the year 2019 assuming that the geomagnetic field is described by the CHAOS-7 dataset. The optimisation procedure is described in https://doi.org/10.3390/geosciences11080318

This dataset includes weekly data from monitoring of stream, rainfall and groundwater hydrochemistry in the Vyrnwy research catchment between 1994 and 2001. Data for over 50 chemical determinands are presented alongside data for some in-situ measurements such as water temperature. Full descriptions of the analytical methods used for each determinand is included. Intensive and long-term monitoring within the catchments underpins a wealth of hydrological and hydro-chemical research; other linked datasets include river flow, meteorology and a variety of detailed spatial datasets representing the topography, soils and rivers of the catchments. Monitoring is funded by the Centre for Ecology & Hydrology. Full details about this dataset can be found at https://doi.org/10.5285/68f4a12f-740d-4705-9c27-6a7fb7127046

The dataset includes abundances of phosphorus redox species (phosphate, phosphite, pyrophosphate) and metal abundances for a collection of mafic and ultramafic rocks. These include peridotites, komatiites and basalts from a variety of locations and ages. The results show that reduced and polymerized phosphorus is present in unaltered mafic and ultramafic rocks, in addition to phosphate. Therefore, oceanic crust can serve as a source of reactive phosphorus species.

This dataset includes rainfall, river and stream hydro-chemistry data from the River Hafren (Severn). The dataset represents high-frequency (7 hourly) monitoring of stream hydrochemistry at both the Lower and Upper Hafren site from 2007-2009, as well as rainfall hydrochemistry near the Carreg Wen meteorological site. Data for over 50 chemical determinands are presented alongside data for some in-situ measurements such as water temperature. Full descriptions of the analytical methods used for each determinand is included. The Plynlimon research catchments lie within the headwaters of the River Severn in the uplands of mid-Wales. Intensive and long-term monitoring within the catchments underpins a wealth of hydrological and hydro-chemical research; other linked datasets include river flow, meteorology and a variety of detailed spatial datasets representing the topography, soils and rivers of the catchments. Monitoring is funded by the Centre for Ecology & Hydrology, and is ongoing since 1968. Full details about this dataset can be found at https://doi.org/10.5285/551a10ae-b8ed-4ebd-ab38-033dd597a374

This dataset includes rainfall, cloud, river and stream hydro-chemistry of the Plynlimon research catchments. The data is from weekly monitoring of stream hydrochemistry of the River Hafren (Severn) at both the Lower and Upper Hafren site from 1998, stream hydrochemistry of the River Hore at the Lower Hore site from 1983 and Upper Hore site from 1984 as well as rainfall hydrochemistry near the Carreg Wen meteorological site from 1983 and cloud hydrochemistry near the Carreg Wen meteorological site from 1990. Data for over 50 chemical determinands are presented alongside data for some in-situ measurements such as water temperature. Full descriptions of the analytical methods used for each determinand is included. The Plynlimon research catchments lie within the headwaters of the River Severn and the River Wye in the uplands of mid-Wales. Intensive and long-term monitoring within the catchments underpins a wealth of hydrological and hydro-chemical research; other linked datasets include river flow, meteorology and a variety of detailed spatial datasets representing the topography, soils and rivers of the catchments. Monitoring is funded by the Centre for Ecology & Hydrology, and is ongoing since 1968. Full details about this dataset can be found at https://doi.org/10.5285/44095e17-43b0-45d4-a781-aab4f72da025

Data are presented for Above ground Carbon Density (ACD) estimated from a series of forest census surveys which took place from 1992- 2016 in a mixture of logged and unlogged tropical lowland dipterocarp forest in the Ulu Segama Forest Reserve (USFR) and Danum Valley Conservation Area (DVCA), Sabah, Malaysia. Additional data on logging method, coupe and year of logging is also presented. The USFR comprises of forested land divided into coupes that were each logged once, between 1972 and 1993 using either "tractor" or "high-lead" methods. Between 1993 and 2004, forest restoration treatments were carried out, including climber cutting and tree planting, annually across logging coupes within the USFR. The data-set was compiled from census carried out in three independent plot networks. The first led by researchers from the Universities of Dundee, Aberdeen and Nottingham. The second led by researchers from the University of Aberdeen. The third through the INnoprise FAce PROject INFAPRO project. Between 1992 and 2016 a forest census survey was carried out on at least two occasions in 553 forest plots to determine the rate of ACD accumulation and understand the impact of forest restoration treatments on ACD accumulation. Tree stem diameter, height and identity measurements at each plot were collected by project members and research assistants employed by the SouthEast Asian Rainforest Research Partnership (SEARRP). The ACD carbon estimation and modelling was led by researchers from the Universities of Dundee, ETH Zurich and Aberdeen. The data were compiled and submitted by researchers from the University of Dundee and ETH Zurich. Funding for the establishment of the original plot networks was provided by the EU-funded INDFORSUS project (ER-BIC18T960102), from New England Electric Systems, National Geographic Society and the Garden Club of America, and from Face the Future Foundation. Funding for the repeated measurements was provided by the NERC "Spatio-TEmporal Dynamics of Forest Response to ENSO Drought (STEED)" (NERC grant reference NE/P004806/1) and the Carnegie Trust for the Universities of Scotland funded project"Changing species diversity and biomass accumulation in conserved and regenerating tropical forests: two decades on". Full details about this dataset can be found at https://doi.org/10.5285/a75e6371-a931-4676-9199-d1f5af565ab2

The dataset comprises of chronostratigraphic data from the Fildes Peninsula, King George Island, South Shetland Islands. The data consists of Radiocarbon (C-14) ages, which were obtained by Accelerator Mass Spectrometry (AMS) dating of marine mollusc shells, terrestrial mosses and seaweed layers embedded in sediments, and Cosmogenic Helium-3 (He-3) nuclide surface exposure dating (CSED). The data have been used to constrain deglaciation and climate-glacier dynamics on the Fildes Peninsula. Data collected in this study were funded by: Centro de Investigaciones en Ciencias de la Tierra (CICTERRA), the Direccion Nacional del Antartico/Instituto Antartico Argentino (DNA/IAA) in the framework of the Project PICTA, 2011 - 0102, IAA "Geomorfologia y Geologia Glaciar del Archipielago James Ross e Islas Shetland del Sur, Sector Norte de la Peninsula Antartica"; the Alfred Wegener Institute (AWI) research program Polar regions and Coasts in a changing Earth System (PACES II); IMCONet (FP7 IRSES, action no. 318718); the Natural Environment Research Council (NERC/BAS-CGS Grant no.81); the NERC/BAS science programmes CACHE-PEP: Natural climate variability - extending the Americas palaeoclimate transect through the Antarctic Peninsula to the pole and GRADES-QWAD: Quaternary West Antarctic Deglaciations. We thank the crews of the Argentine research station "Carlini'" and the adjoined German Dallmann-Labor (AWI) Laboratory, the Uruguayan research station "Artigas", the Russian Bellingshausen Station, the Chinese Great Wall Station, Base Presidente Eduardo Frei Montalva, the Brazilian Navy Almirante Maximiano, the UK Navy HMS Endurance and NERC/BAS James Clark Ross for logistical support during the 2006, 2011, 2014 and 2015 field seasons.

The dataset comprises of chronostratigraphic data from the Fildes Peninsula, King George Island, South Shetland Islands. The data have been used to constrain deglaciation and climate-glacier dynamics on the Fildes Peninsula. These data include C-14 density probability phases. Data was compiled with with Potter Peninsula and King George Island data and a non-parametric phase model applied. Data collected in this study were funded by: Centro de Investigaciones en Ciencias de la Tierra (CICTERRA), the Direccion Nacional del Antartico/Instituto Antartico Argentino (DNA/IAA) in the framework of the Project PICTA, 2011 - 0102, IAA "Geomorfologia y Geologia Glaciar del Archipielago James Ross e Islas Shetland del Sur, Sector Norte de la Peninsula Antartica"; the Alfred Wegener Institute (AWI) research program Polar regions and Coasts in a changing Earth System (PACES II); IMCONet (FP7 IRSES, action no. 318718); the Natural Environment Research Council (NERC/BAS-CGS Grant no.81); the NERC/BAS science programmes CACHE-PEP: Natural climate variability - extending the Americas palaeoclimate transect through the Antarctic Peninsula to the pole and GRADES-QWAD: Quaternary West Antarctic Deglaciations. We thank the crews of the Argentine research station "Carlini" and the adjoined German Dallmann-Labor (AWI) Laboratory, the Uruguayan research station "Artigas", the Russian Bellingshausen Station, the Chinese Great Wall Station, Base Presidente Eduardo Frei Montalva, the Brazilian Navy Almirante Maximiano, the UK Navy HMS Endurance and NERC/BAS James Clark Ross for logistical support during the 2006, 2011, 2014 and 2015 field seasons.

Biomarker data from marine sediments samples retrieved from the following sites: (i) Tanzania (TDP Site 14), (ii) New Jersey Margin (Site 174AX), (iii) Denmark (Fur) (iv) Tasman Sea (ODP Site 1172) and (v) the High Arctic (IODP Site 302). Sediments are ~56 million years old and span the Paleocene-Eocene Thermal Maximum. Biomarker data was compiled from previous publications (see ref. 1-5 below) or extracted and analysed via gas chromatography-mass spectrometry (GC-MS). Biomarker data was then apportioned into plant, soil, and algal organic carbon using a three-end member mixing model (https://github.com/FluvialSeds/petm_mixing_model). The dataset also includes climate variables from ocean-atmosphere climate model simulations. This was generated previously (see ref. 6) or obtained using the Hadley Centre model. The analysis was supported by Royal Society Dorothy Hodgkin Fellowship DHF/R1/191178 and NERC Pushing the Frontiers Grant UKRI1272. In total, 14 individual datasets are included: Sheet 1: Lipid biomarker data and OC burial fluxes from Tasman Sea (Source data; Fig. 1) Sheet 2: Lipid biomarker data and OC burial fluxes from New Jersey Margin (source data: Fig.1) Sheet 3: Lipid biomarker data and OC burial fluxes from the High Arctic (source data: Fig.1) Sheet 4: Lipid biomarker data and OC burial fluxes from Denmark (source data: Fig.1) Sheet 5: Lipid biomarker data and OC burial fluxes from Tanzania (source data: Fig.1) Sheet 6: Average mass accumulation rate (MAR) data for High Arctic, New Jersey Margin, Denmark, and Tasman Sea between the latest Paleocene and PETM (source data: Fig. 2a) Sheet 7: Average mass accumulation rate (MAR) data for High Arctic and New Jersey Margin during the pre-PETM, PETM body and PETM recovery (source data: Fig. 2b, 2c) Sheet 8: DeepMIP model ensemble-derived estimates of mean annual precipitation under different CO2 scenarios (source data; Figure 3) Sheet 9: HadCM3L-derived estimates of plant and soil OC stocks under different CO2 scenarios (Source data: fig.4) Sheet 10: Total organic carbon burial flux (in MtC/yr-1) in marine sediments during the PETM assuming 270kyr duration Sheet 11: MOSES2.1 soil parameters used within the HadCM3B palaeoclimate model. Sheet 12: Lipid biomarker data from Mississippi (Yedema et al., 2022) and proportion of plant, soil, and marine OC Sheet 13: #ringstetra data for Denmark Sheet 14: #ringstetra data for New Jersey Margin References: (1) Stokke, E.W., et al., (2020) Earth and Planetary Science Letters, 544 (2) Sluijs, A., et al., (2020) Climate of the Past, 16(6) (3) Sluijs, A., et al., (2011) Climate of the Past. 7(1) (4) Carmichael, M.J., et al., (2017) Global and Planetary Change. 157 (5) Elling, F.J., et al., (2019) Nature Communications. 10(1) (6) Lunt, D.J., et al., (2021) Climate of the Past. 17(1)