Regionally aggregated, stitched and de‐drifted CMIP‐climate data, processed with netCDF‐SCM v2.0.0

The world's most complex climate models are currently running a range of experiments as part of the Sixth Coupled Model Intercomparison Project (CMIP6). Added to the output from the Fifth Coupled Model Intercomparison Project (CMIP5), the total data volume will be in the order of 20PB. Here, we present a dataset of annual, monthly, global, hemispheric and land/ocean means derived from a selection of experiments of key interest to climate data analysts and reduced complexity climate modellers. The derived dataset is a key part of validating, calibrating and developing reduced complexity climate models against the behaviour of more physically complete models. In addition to its use for reduced complexity climate modellers, we aim to make our data accessible to other research communities. We facilitate this in a number of ways. Firstly, given the focus on annual, monthly, global, hemispheric and land/ocean mean quantities, our dataset is orders of magnitude smaller than the source data and hence does not require specialized ‘big data’ expertise. Secondly, again because of its smaller size, we are able to offer our dataset in a text-based format, greatly reducing the computational expertise required to work with CMIP output. Thirdly, we enable data provenance and integrity control by tracking all source metadata and providing tools which check whether a dataset has been retracted, that is identified as erroneous. The resulting dataset is updated as new CMIP6 results become available and we provide a stable access point to allow automated downloads. Along with our accompanying website (cmip6.science.unimelb.edu.au), we believe this dataset provides a unique community resource, as well as allowing non-specialists to access CMIP data in a new, user-friendly way

mmrefpoints: Projecting long-term marine mammal abundance with bycatch

An R package that generates marine mammal population projections based on starting abundance, life history, and bycatch rates, based on the BALEEN II population dynamics model

AgMIP Wheat Pilot Data 4 release

This dataset contains the underlaying data for the study: Benchmark data set for wheat growth models: field experiments and AgMIP multi-model simulations. Open Data Journal for Agricultural Research : ODjAR The data set includes a current representative management treatment from detailed, quality-tested sentinel field experiments with wheat from four contrasting environments including Australia, The Netherlands, India and Argentina. Measurements include local daily climate data (solar radiation, maximum and minimum temperature, precipitation, surface wind, dew point temperature, relative humidity, and vapor pressure), soil characteristics, frequent growth, nitrogen in crop and soil, crop and soil water and yield components. Simulations include results from 27 wheat models and a sensitivity analysis with 26 models and 30 years (1981-2010) for each location, for elevated atmospheric CO2 and temperature changes, a heat stress sensitivity analysis at anthesis, and a sensitivity analysis with soil and crop management variations and a Global Climate Model end-century scenario

Marine microbial metagenomes sampled across space and time

Recent advances in understanding the ecology of marine systems have been greatly facilitated by the growing availability of metagenomic data, which provide information on the identity, diversity and functional potential of the microbial community in a particular place and time. Here we present a dataset comprising over 5 terabases of metagenomic data from 610 samples spanning diverse regions of the Atlantic and Pacific Oceans. One set of metagenomes, collected on GEOTRACES cruises, captures large geographic transects at multiple depths per station. The second set represents two years of time-series data, collected at roughly monthly intervals from 3 depths at two long-term ocean sampling sites, Station ALOHA and BATS. These metagenomes contain genomic information from a diverse range of bacteria, archaea, eukaryotes and viruses. The data’s utility is strengthened by the availability of extensive physical, chemical, and biological measurements associated with each sample. We expect that these metagenomes will facilitate a wide range of comparative studies that seek to illuminate new aspects of marine microbial ecosystems.© The Author(s) 201

Database: Tidal Marsh Soil Organic Carbon (MarSOC) Dataset

The repository is formatted in the following structure: - README.md: markdown file with repository description - MarSOC-Dataset.Rproj: R project file - useful when using RStudio - Maxwell_MarSOC_dataset.csv: .csv file containing the final dataset. The data structure is described in the metadata file. It contains 17,454 records distributed amongst 29 countries. - Maxwell_MarSOC_dataset_metadata.csv: .csv file containing the main data file metadata (equivalent to Table 1). - data_paper/: folder containing the list of studies included in the dataset, as well as figures for this data paper (generated from the following R script: ‘reports/04_data_process/scripts/04_data-paper_data_clean.R’). - reports/01_litsearchr/: folder containing .bib files with references from the original naive search, a .Rmd document describing the litsearchr analysis using nodes to go from the naive search to the final search string, and the .bib files from this final search, which were then imported into sysrev for abstract screening. - reports/02_sysrev/: folder with .csv files exported from sysrev after abstract screening. These files contain the included studies with their various labels. - reports/03_data_format/: folder containing all original data, associated scripts, and exported data. - reports/04_data_process/: folder containing data processing scripts to bind and clean the exported data, as well as a script testing the different models for predicting soil organic carbon from organic matter and finalising the equation using all available data. A script testing and removing outliers is also included

Surface Ocean CO2 Atlas (SOCAT) V6

The Surface Ocean CO2 Atlas (SOCAT) is a synthesis activity by the international marine carbon research community (>100 contributors). SOCAT version 6 has 23.4 million quality-controlled, surface ocean fCO2 (fugacity of carbon dioxide) observations from 1957 to 2017 for the global oceans and coastal seas. Calibrated sensor data are also available. Automation allows annual, public releases. SOCAT data is discoverable, accessible and citable. SOCAT enables quantification of the ocean carbon sink and ocean acidification and evaluation of ocean biogeochemical models. SOCAT represents a milestone in biogeochemical and climate research and in informing policy. 424 datasets Version 5: https://doi.pangaea.de/10.1594/PANGAEA.877863 Version 4: https://doi.pangaea.de/10.1594/PANGAEA.866856 Version 3: https://doi.pangaea.de/10.1594/PANGAEA.849770 Version 2: https://doi.org/10.1594/PANGAEA.81515