Description: The ²³⁴Th-²³⁸U radioactive pair has been extensively used to evaluate the efficiency with which photosyntetically fixed carbon is exported from the surface ocean by means of the biological pump since the 90's. The seminal work of Buesseler et al. (1992) proposed that particulate organic carbon (POC) flux can be indirectly calculated from ²³⁴Th distributions if the ratio of POC to ²³⁴Th measured on sinking particles (POC:²³⁴Th) at the desired export depth is known. Since then, a huge amount of ²³⁴Th depth profiles have been collected using a variety of sampling instruments and strategies that have changed along years. This is a global oceanic compilation of ²³⁴Th measurements, that collects results from innumerable researchers and laboratories over a period exceeding 50 years. The present compilation is made of a total 223 datasets: 214 from studies published either in articles in referred journals, PhD thesis or repositories, and 9 unpublished datasets. Including measurements from JGOFS, VERTIGO and GEOTRACES programs, with sampling from approximately 5000 locations spanning all the oceans. The compilation includes total ²³⁴Th profiles, dissolved and particulate ²³⁴Th concentrations, and POC:²³⁴Th ratios (both from pumps and sediment traps) for two sizes classes (1-53 μm and 〈 53 μm) when available. Appropriate metadata have been included, including geographic location, date, and sample depth, among others. When available, we also include water temperature, salinity, ²³⁸U data and particulate organic nitrogen data. Data sources and methods information (including ²³⁸U and ²³⁴Th) are also detailed along with valuable information for future data analysis such as bloom stage and steady/non-steady state conditions at the sampling moment. This undertaking is a treasure of data to understand and quantify how oceanic carbon cycle functions and how it will change in future. The compilation can be downloaded in three different ways: 1) A single merged file including all the individual excel files. This option can be accessed under "Other version: More than 50 years of Th-234 data: a comprehensive global oceanic compilation (single xlsx file)". 2) A summary table that includes details from cruise, sampling dates, techniques applied, authors and DOI of the compiled ²³⁴Th data, among others, each line corresponds to a specific dataset. The table can be accessed by clicking ""View dataset as HTML" and downloaded in "Download dataset as tab-delimited text". 3) Individual Excel files for each dataset can be manually chosen from the summary table, corresponding to the complete ²³⁴Th dataset and metadata from a specific publication or program. This option is available by clicking "View dataset as HTML". Furthermore, all files referred to can be downloaded in one go as ZIP or TAR.

Description: This paper provides a comprehensive description of the newest version of the Dynamic Global Vegetation Model with managed Land, LPJmL4. This model simulates – internally consistently – the growth and productivity of both natural and agricultural vegetation as coherently linked through their water, carbon, and energy fluxes. These features render LPJmL4 suitable for assessing a broad range of feedbacks within and impacts upon the terrestrial biosphere as increasingly shaped by human activities such as climate change and land use change. Here we describe the core model structure, including recently developed modules now unified in LPJmL4. Thereby, we also review LPJmL model developments and evaluations in the field of permafrost, human and ecological water demand, and improved representation of crop types. We summarize and discuss LPJmL model applications dealing with the impacts of historical and future environmental change on the terrestrial biosphere at regional and global scale and provide a comprehensive overview of LPJmL publications since the first model description in 2007. To demonstrate the main features of the LPJmL4 model, we display reference simulation results for key processes such as the current global distribution of natural and managed ecosystems, their productivities, and associated water fluxes. A thorough evaluation of the model is provided in a companion paper. By making the model source code freely available at https://gitlab.pik-potsdam.de/lpjml/LPJmL, we hope to stimulate the application and further development of LPJmL4 across scientific communities in support of major activities such as the IPCC and SDG process.

Description: The dynamic global vegetation model LPJmL4 is a process-based model that simulates climate and land use change impacts on the terrestrial biosphere, agricultural production, and the water and carbon cycle. Different versions of the model have been developed and applied to evaluate the role of natural and managed ecosystems in the Earth system and the potential impacts of global environmental change. A comprehensive model description of the new model version, LPJmL4, is provided in a companion paper (Schaphoff et al., 2018c). Here, we provide a full picture of the model performance, going beyond standard benchmark procedures and give hints on the strengths and shortcomings of the model to identify the need for further model improvement. Specifically, we evaluate LPJmL4 against various datasets from in situ measurement sites, satellite observations, and agricultural yield statistics. We apply a range of metrics to evaluate the quality of the model to simulate stocks and flows of carbon and water in natural and managed ecosystems at different temporal and spatial scales. We show that an advanced phenology scheme improves the simulation of seasonal fluctuations in the atmospheric CO2 concentration, while the permafrost scheme improves estimates of carbon stocks. The full LPJmL4 code including the new developments will be supplied open source through https://gitlab.pik-potsdam.de/lpjml/LPJmL. We hope that this will lead to new model developments and applications that improve the model performance and possibly build up a new understanding of the terrestrial biosphere.

Description: Present day system Earth research utilizes the tool ‘Scientific Drilling’ to access samples and to monitor deep Earth processes that cannot be tackled by other scientific means. Unlike most laboratory experiments or computer modelling, drilling projects are massive field endeavours requiring intense collaboration of researchers with engineers and service providers. In the framework of the International Continental Scientific Drilling Program, ICDP, more than seventy drilling projects have been conducted, from multiyear big research programs to short, smallscale deployments such as lake drilling projects. ICDP has supported these projects not only through grants covering field-related costs, but also through a variety of scientific-technical services and support, as well as active help in data management, outreach and publication. These services are described in this booklet. Due to its instructional character, we call it the ICDP Primer.

Description: This brochure is designed for scientists and engineers of upcoming drilling projects and explains the key steps and important challenges in planning and executing continental scientific drilling.

Description: There is a growing need for past weather and climate data to support science and decision-making. This paper describes the compilation and the construction of a global multivariable (air temperature, pressure, precipitation sum, number of precipitation days) monthly instrumental climate database that encompasses a substantial body of the known early instrumental time series. The dataset contains series compiled from existing databases that start before 1890 (though continuing to the present) as well as a large amount of newly rescued data. All series underwent a quality control procedure and subdaily series were processed to monthly mean values. An inventory was compiled, and the collection was deduplicated based on coordinates and mutual correlations. The data are provided in a common format accompanied by the inventory. The collection totals 12452 meteorological records in 118 countries. The data has been merged from 18250 original data files. The data can be used for climate reconstructions and analyses. It is the most comprehensive global monthly climate data set for the preindustrial period.

Description: Reconstructions of global hydroclimate during the Common Era (CE; the past ∼2000 years) are important for providing context for current and future global environmental change. Stable isotope ratios in water are quantitative indicators of hydroclimate on regional to global scales, and these signals are encoded in a wide range of natural geologic archives. Here we present the Iso2k database, a global compilation of previously published datasets from a variety of natural archives that record the stable oxygen (δ18O) or hydrogen (δ2H) isotopic compositions of environmental waters, which reflect hydroclimate changes over the CE. The Iso2k database contains 759 isotope records from the terrestrial and marine realms, including glacier and ground ice (210); speleothems (68); corals, sclerosponges, and mollusks (143); wood (81); lake sediments and other terrestrial sediments (e.g., loess) (158); and marine sediments (99). Individual datasets have temporal resolutions ranging from sub-annual to centennial and include chronological data where available. A fundamental feature of the database is its comprehensive metadata, which will assist both experts and nonexperts in the interpretation of each record and in data synthesis. Key metadata fields have standardized vocabularies to facilitate comparisons across diverse archives and with climate-model-simulated fields. This is the first global-scale collection of water isotope proxy records from multiple types of geological and biological archives. It is suitable for evaluating hydroclimate processes through time and space using large-scale synthesis, model–data intercomparison and (paleo)data assimilation. The Iso2k database is available for download at https://doi.org/10.25921/57j8-vs18 (Konecky and McKay, 2020) and is also accessible via the NOAA/WDS Paleo Data landing page: https://www.ncdc.noaa.gov/paleo/study/29593 (last access: 30 July 2020).

Description: Riverine nutrient export is an important process in marine coastal biogeochemistry and also impacts global marine biology. The nitrogen cycle is a key player here. Internal feedbacks regulate not only nitrogen distribution, but also primary production and thereby oxygen concentrations. Phosphorus is another essential nutrient and interacts with the nitrogen cycle via different feedback mechanisms. After a previous study of the marine nitrogen cycle response to riverine nitrogen supply, we here additionally include phosphorus from river export with different phosphorus burial scenarios and study the impact of phosphorus alone and in combination with nitrogen in a global 3-D ocean biogeochemistry model. Again, we analyse the effects on near coastal and open ocean biogeochemistry. We find that the addition of bio-available riverine phosphorus alone or together with nitrogen affects marine biology on millennial timescales more than riverine nitrogen alone. Biogeochemical feedbacks in the marine nitrogen cycle are strongly influenced by the additional phosphorus. Where bio-available phosphorus is increased by river input, nitrogen concentrations increase as well, except for regions with high denitrification rates. High phosphorus burial rates decrease biological production significantly. Globally, riverine phosphorus leads to elevated primary production rates in the coastal and open oceans.

Description: Spatial predictions of total organic carbon (TOC) concentrations and stocks are crucial for understanding marine sediments’ role as a significant carbon sink in the global carbon cycle. In this study, we present a geospatial prediction of TOC concentrations and stocks at a 5 x 5 arc minute grid scale, using a deep learning model — a novel machine learning approach based on a new compilation of over 22,000 global TOC measurements and a new set of predictors, such as seafloor lithologies, grain size distribution, and an alpha-chlorophyll satellite data. In our study, we compared the predictions and discuss the limitations from various machine learning methods. Our findings reveal that the neural network approach outperforms methods such as k Nearest Neighbors and random forests, which tend to overfit to the training data, especially in highly heterogeneous and complex geological settings. We provide estimates of mean TOC concentrations and total carbon stock in both continental shelves and deep sea settings across various marine regions and oceans. Our model suggests that the upper 10 cm of oceanic sediments harbors approximately 171 Pg of TOC stock and has a mean TOC concentration of 0.68 %. Furthermore, we introduce a standardized methodology for quantifying predictive uncertainty using Monte Carlo dropout and present a map of information gain, that measures the expected increase in model knowledge achieved through in-situ sampling at specific locations which is pivotal for sampling strategy planning.