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The number of studies investigating the effects of ocean acidification on marine organisms and communities increases every year. Results are not easily comparable since the carbonate chemistry and ancillary data are not always reported in similar units and scales and are not calculated using similar sets of constants. To facilitate data comparison, a data compilation hosted by the PANGAEA Data Publisher was initiated in 2008 and is updated on a regular basis (10.1594/PANGAEA.962556; Ocean Acidification International Coordination Centre (OA-ICC), 2023). By November 2023, a total of 1501 datasets (over 25 million data points) from 1554 papers had been archived. To easily filter and access relevant biological response data from this compilation, a user-friendly portal (https://oa-icc.ipsl.fr , last access: 9 November 2023) was launched in 2018. Here, we present an update of this data compilation since its second description by Yang et al. (2016) and provide an overview of the OA-ICC portal for ocean acidification biological response data, launched in 2018. Most of the study sites from which data have been archived are in the North Atlantic Ocean, North Pacific Ocean, South Pacific Ocean, and Mediterranean Sea, while polar oceans are still relatively poorly represented. Mollusca and Cnidaria are still the best-represented taxonomic groups. The biological processes most reported in the datasets are growth and morphology. Other variables that can potentially be affected by ocean acidification and are often reported include calcification/dissolution, primary production/photosynthesis, and biomass/abundance. The majority of the compiled datasets have considered ocean acidification as a single stressor, but their relative contribution has decreased from 68 % before 2015 to 57 % today, showing a clear tendency towards more data archived from multifactorial studies. [ABSTRACT FROM AUTHOR]

We present an ice-penetrating radar data set acquired over the Greenland ice sheet by aircraft during the years 1971, 1972, 1974, 1978, and 1979. The data set comprises over 177 000 km of flight lines and contains a wealth of information on the state of the Greenland ice sheet, including information on ice thickness and englacial properties. During data collection in the 1970s, the data were recorded on optical film rolls, and in this paper, we document the digitization of these film rolls and their associated geographical information. Our data digitization enables interaction with and analysis of the data and facilitates comparison with modern-day radar observations. The complete data set in full resolution is available in the Stanford Digital Repository (10.25740/wm135gp2721;), with the associated technical reports. Part of the data set is available as low-resolution JPG files at the Technical University of Denmark's data repository (10.6084/m9.figshare.c.7235299.v1;), with associated technical reports and digitized geographical information. The Stanford Digital Repository serves as long-term storage, providing archival historic preservation in perpetuity, and is not intended as a primary data access point. The Technical University of Denmark (DTU) data repository serves as a primary entry point for data access, with files organized according to acquisition year and flight line in a simple folder structure. Here, we release the full data sets to enable the larger community to access and interact with the data. [ABSTRACT FROM AUTHOR]

The climatic response of mountain permafrost and glaciers located in high-elevation mountain areas has major implications for the stability of mountain slopes and related geomorphological hazards, water storage and supply, and preservation of palaeoclimatic archives. Despite a good knowledge of physical processes that govern the climatic response of mountain permafrost and glaciers, there is a lack of observational datasets from summit areas. This represents a crucial gap in knowledge and a serious limit for model-based projections of future behaviour of permafrost and glaciers. A new observational dataset is available for the summit area of Mt Ortles, which is the highest summit of South Tyrol, Italy. This paper presents a series of air, englacial, soil surface and rock wall temperatures collected between 2010 and 2016. Details are provided regarding instrument types and characteristics, field methods, and data quality control and assessment. The obtained data series are available through an open data repository (10.5281/zenodo.8330289, Carturan et al., 2023). In the observed period, the mean annual air temperature at 3830 m a.s.l. was between -7.8 and -8.6 ∘ C. The most shallow layers of snow and firn (down to a depth of about 10 m) froze during winter. However, melt water percolation restored isothermal conditions during the ablation season, and the entire firn layer was found at the melting pressure point. Glacier ice is cold, but only from about 30 m depth. Englacial temperature decreases with depth, reaching a minimum of almost -3 ∘ C close to the bedrock, at 75 m depth. A small glacier located at 3470 m a.s.l., close to the summit of Mt Ortles, was also found in cold conditions down to a depth of 9.5 m. The mean annual ground surface temperature was negative for all but one monitored sites, indicating cold ground conditions and the existence of permafrost in nearly all debris-mantled slopes of the summit. Similarly, the mean annual rock wall temperature was negative at most monitored sites, except the lowest one at 3030 m a.s.l. This suggests that the rock faces of the summit are affected by permafrost at all exposures. [ABSTRACT FROM AUTHOR]

Integrating mineralogy with data science is critical to modernizing Earth materials research and its applications to geosciences. Data were compiled on 95 650 garnet sample analyses from a variety of sources, ranging from large repositories (EarthChem, RRUFF, MetPetDB) to individual peer-reviewed literature. An important feature is the inclusion of mineralogical "dark data" from papers published prior to 1990. Garnets are commonly used as indicators of formation environments, which directly correlate with their geochemical properties; thus, they are an ideal subject for the creation of an extensive data resource that incorporates composition, locality information, paragenetic mode, age, temperature, pressure, and geochemistry. For the data extracted from existing databases and literature, we increased the resolution of several key aspects, including petrogenetic and paragenetic attributes, which we extended from generic material type (e.g., igneous, metamorphic) to more specific rock-type names (e.g., diorite, eclogite, skarn) and locality information, increasing specificity by examining the continent, country, area, geological context, longitude, and latitude. Likewise, we utilized end-member and quality index calculations to help assess the garnet sample analysis quality. This comprehensive dataset of garnet information is an open-access resource available in the Evolutionary System of Mineralogy Database (ESMD) for future mineralogical studies, paving the way for characterizing correlations between chemical composition and paragenesis through natural kind clustering (Chiama et al., 2022; 10.48484/camh-xy98). We encourage scientists to contribute their own unpublished and unarchived analyses to the growing data repositories of mineralogical information that are increasingly valuable for advancing scientific discovery. [ABSTRACT FROM AUTHOR]

The Multi-angle Imaging SpectroRadiometer (MISR) instrument on NASA's Terra platform has been acquiring global measurements of the spectrodirectional reflectance of the Earth since 24 February 2000 and is still operational as of this writing. The primary radiometric data product generated by this instrument is known as the Level 1B2 (L1B2) Georectified Radiance Product (GRP): it contains the 36 radiometric measurements acquired by the instrument's nine cameras, each observing the planet in four spectral bands. The product version described here is projected on a digital elevation model and is available from the NASA Langley Atmospheric Science Data Center (ASDC; http://doi.org/10.5067/Terra/MISR/MI1B2T%5fL1.003 ;). The MISR instrument is highly reliable. Nevertheless, its onboard computer occasionally becomes overwhelmed by the number of raw observations coming from the cameras' focal planes, especially when switching into or out of Local Mode acquisitions that are often requested in conjunction with field campaigns. Whenever this occurs, one or more lines of data are dropped while the computer resets and readies itself for accepting new data. Although this type of data loss is minuscule compared to the total number of measurements acquired and is marginal for atmospheric studies dealing with large areas and long periods of time, this outcome can be crippling for land surface studies that focus on the detailed analysis of particular scenes at specific times. This paper describes the problem, reports on the prevalence of missing data, proposes a practical solution to optimally estimate the values of the missing data and provides evidence of the performance of the algorithm through specific examples in southern Africa. The software to process MISRL1B2GRP data products as described here is openly available to the community from the GitHub website (https://github.com/mmverstraete or 10.5281/zenodo.3519988). Two additional sets of resources are also made available on the research data repository of GFZ Data Services in conjunction with this paper. The first set (A; Verstraete et al., 2020, 10.5880/fidgeo.2020.012) includes five items: (A1) a compressed archive (L1B2_Out.zip) containing all intermediary, final and ancillary outputs created while generating the figures of this paper; (A2) a user manual (L1B2_Out.pdf) describing how to install, uncompress and explore those files; (A3) an additional compressed archive (L1B2_Suppl.zip) containing a similar set of results, only for eight other sites, spanning a much wider range of geographical, climatic and ecological conditions; (A4) a companion user manual (L1B2_Suppl.pdf) describing how to install, uncompress and explore those additional files; and (A5) a separate input MISR data archive (L1B2_input_68050.zip) for Path 168, Orbit 68050. This latter archive is usable with the second set (B; Verstraete and Vogt, 2020; 10.5880/fidgeo.2020.011), which includes (B1) a stand-alone, self-contained, executable version of the L1B2 correction codes (L1B2_Soft_Win.zip) that uses the IDL Virtual Machine technology and does not require a paid IDL license as well as (B2) a user manual (L1B2_Soft_Win.pdf) that explains how to install, uncompress and use this software. [ABSTRACT FROM AUTHOR]

The Multi-angle Imaging SpectroRadiometer (MISR) is one of the five instruments hosted on board the NASA Terra platform, launched on 18 December 1999. This instrument has been operational since 24 February 2000 and is still acquiring Earth observation data as of this writing. The primary mission of the MISR is to document the state and properties of the atmosphere, in particular the clouds and aerosols it contains, as well as the planetary surface, on the basis of 36 data channels collectively gathered by its nine cameras (pointing in different directions along the orbital track) in four spectral bands (blue, green, red and near-infrared). The radiometric camera-by-camera cloud mask (RCCM) is derived from the calibrated measurements at the nominal top of the atmosphere and is provided separately for each of the nine cameras. This RCCM data product is permanently archived at the NASA Atmospheric Science Data Center (ASDC) in Hampton, VA, USA, and is openly accessible (, and 10.5067/Terra/MISR/MIRCCM_L2.004). For various technical reasons described in this paper, this RCCM product exhibits missing data, even though an estimate of the clear or cloudy status of the environment at each individual observed location can be deduced from the available measurements. The aims of this paper are (1) to describe how to replace over 99 % of the missing values by estimates and (2) to briefly describe the software to replace missing RCCM values, which is openly available to the community from the GitHub website, https://github.com/mmverstraete/MISR\ RCCM/ (last access: 12 March 2020), or 10.5281/ZENODO.3240017. Two additional sets of resources are also made available on the research data repository of GFZ Data Services in conjunction with this paper. The first set (A; ; 10.5880/fidgeo.2020.004) includes three items: (A1) a compressed archive, RCCM_Out.zip, containing all intermediary, final and ancillary outputs created while generating the figures of this paper; (A2) a user manual, RCCM_Out.pdf, describing how to install, uncompress and explore those files; and (A3) a separate input MISR data archive, RCCM_input_68050.zip, for Path 168, Orbit 68050. This latter archive is usable with (B), the second set (; 10.5880/fidgeo.2020.008), which includes (B1), a stand-alone, self-contained, executable version of the RCCM correction codes, RCCM_Soft_Win.zip, using the IDL Virtual Machine technology that does not require a paid IDL license, as well as (B2), a user manual, RCCM_Soft_Win.pdf, to explain how to install, uncompress and use this software. [ABSTRACT FROM AUTHOR]

The NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) produced a unique dataset for research into aerosol–cloud–meteorology interactions, with applications extending from process-based studies to multi-scale model intercomparison and improvement as well as to remote-sensing algorithm assessments and advancements. ACTIVATE used two NASA Langley Research Center aircraft, a HU-25 Falcon and King Air, to conduct systematic and spatially coordinated flights over the northwest Atlantic Ocean, resulting in 162 joint flights and 17 other single-aircraft flights between 2020 and 2022 across all seasons. Data cover 574 and 592 cumulative flights hours for the HU-25 Falcon and King Air, respectively. The HU-25 Falcon conducted profiling at different level legs below, in, and just above boundary layer clouds (< 3 km) and obtained in situ measurements of trace gases, aerosol particles, clouds, and atmospheric state parameters. Under cloud-free conditions, the HU-25 Falcon similarly conducted profiling at different level legs within and immediately above the boundary layer. The King Air (the high-flying aircraft) flew at approximately ∼ 9 km and conducted remote sensing with a lidar and polarimeter while also launching dropsondes (785 in total). Collectively, simultaneous data from both aircraft help to characterize the same vertical column of the atmosphere. In addition to individual instrument files, data from the HU-25 Falcon aircraft are combined into "merge files" on the publicly available data archive that are created at different time resolutions of interest (e.g., 1, 5, 10, 15, 30, 60 s, or matching an individual data product's start and stop times). This paper describes the ACTIVATE flight strategy, instrument and complementary dataset products, data access and usage details, and data application notes. The data are publicly accessible through 10.5067/SUBORBITAL/ACTIVATE/DATA001 (ACTIVATE Science Team, 2020). [ABSTRACT FROM AUTHOR]

Nineteen years of atmospheric composition measurements made at the University of Toronto Atmospheric Observatory (TAO; 43.66 ∘ N, 79.40 ∘ W; 174 m a.s.l.) are presented. These are retrieved from Fourier transform infrared (FTIR) solar absorption spectra recorded with an ABB Bomem DA8 spectrometer from May 2002 to December 2020. The retrievals have been performed for 14 species: O3 , HCl, HF, HNO3 , CH4 , C2H6 , CO, HCN, N2O , C2H2 , H2CO , CH3OH , HCOOH, and NH3 using the SFIT4 algorithm. The measurements have been archived in the Network for the Detection of Atmospheric Composition Change (NDACC) data repository in Hierarchical Data Format version 4 (HDF4) files following the Generic Earth Observation Metadata Standard (GEOMS) and are also publicly available on Borealis, the Canadian Dataverse Repository (10.5683/SP2/VC8JMC, Yamanouchi et al., 2022). In this paper, we describe the instrumentation, the retrieval strategy, the vertical sensitivity of the retrievals, the quality assurance process, and the error analysis of the TAO FTIR measurements and present the current version of the time series. [ABSTRACT FROM AUTHOR]

The European Space Agency SnowSAR instrument is a side-looking, dual-polarised (VV/VH), X/Ku band synthetic aperture radar (SAR), operable from various sizes of aircraft. Between 2010 and 2013, the instrument was deployed at several sites in Northern Finland, Austrian Alps and northern Canada. The purpose of the airborne campaigns was to measure the backscattering properties of snow-covered terrain to support the development of snow water equivalent retrieval techniques using SAR. SnowSAR was deployed in Sodankylä, Northern Finland, for a single flight mission in March 2011 and 12 missions at two sites (tundra and boreal forest) in the winter of 2011–2012. Over the Austrian Alps, three flight missions were performed between November 2012 and February 2013 over three sites located in different elevation zones representing a montane valley, Alpine tundra and a glacier environment. In Canada, a total of two missions were flown in March and April 2013 over sites in the Trail Valley Creek watershed, Northwest Territories, representative of the tundra snow regime. This paper introduces the airborne SAR data and coincident in situ information on land cover, vegetation and snow properties. To facilitate easy access to the data record, the datasets described here are deposited in a permanent data repository (10.1594/PANGAEA.933255, Lemmetyinen et al., 2021). [ABSTRACT FROM AUTHOR]

We present here a global oceanic compilation of 234 Th measurements that collects results from researchers and laboratories over a period exceeding 50 years. The origin of the 234 Th sampling in the ocean goes back to 1967, when Bhat et al. (1969) initially studied 234 Th distribution relative to its parent 238 U in the Indian Ocean. However, it was the seminal work of Buesseler et al. (1992) – which proposed an empirical method to estimate export fluxes from 234 Th distributions – that drove the extensive use of the 234 Th– 238 U radioactive pair to evaluate the organic carbon export out of the surface ocean by means of the biological carbon pump. Since then, a large number of 234 Th depth profiles have been collected using a variety of sampling instruments and strategies that have changed during the past 50 years. The present compilation is made of a total 223 data sets: 214 from studies published in either articles in refereed journals, PhD theses, or repositories, as well as 9 unpublished data sets. The data were compiled from over 5000 locations spanning all the oceans for total 234 Th profiles, dissolved and particulate 234 Th activity concentrations (in dpm L -1), and POC:234Th ratios (in µmoldpm-1) from both sediment traps and filtration methods. A total of 379 oceanographic expeditions and more than 56 600 234 Th data points have been gathered in a single open-access, long-term, and dynamic repository. This paper introduces the dataset along with informative and descriptive graphics. Appropriate metadata have been compiled, including geographic location, date, and sample depth, among others. When available, we also include water temperature, salinity, 238 U data (over 18 200 data points), and particulate organic nitrogen data. Data source and method information (including 238 U and 234 Th) is also detailed along with valuable information for future data analysis such as bloom stage and steady-/non-steady-state conditions at the sampling moment. The data are archived on the PANGAEA repository, with the dataset DOI 10.1594/PANGAEA.918125 (Ceballos-Romero et al., 2021). This provides a valuable resource to better understand and quantify how the contemporary oceanic carbon uptake functions and how it will change in future. [ABSTRACT FROM AUTHOR]

Between 14 and 20 July 2018, small unmanned aircraft systems (UASs) were deployed to the San Luis Valley of Colorado (USA) alongside surface-based remote sensors, in situ sensors, and radiosonde systems as part of the Lower Atmospheric Profiling Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE). The measurements collected as part of LAPSE-RATE targeted quantities related to enhancing our understanding of boundary layer structure, cloud and aerosol properties and surface–atmosphere exchange and provide detailed information to support model evaluation and improvement work. Additionally, intensive intercomparison between the different unmanned aircraft platforms was completed. The current paper describes the observations obtained using three different types of surface-based mobile observing vehicles. These included the University of Colorado Mobile UAS Research Collaboratory (MURC), the National Oceanic and Atmospheric Administration National Severe Storms Laboratory Mobile Mesonet, and two University of Nebraska Combined Mesonet and Tracker (CoMeT) vehicles. Over the 1-week campaign, a total of 143 h of data were collected using this combination of vehicles. The data from these coordinated activities provide detailed perspectives on the spatial variability of atmospheric state parameters (air temperature, humidity, pressure, and wind) throughout the northern half of the San Luis Valley. These datasets have been checked for quality and published to the Zenodo data archive under a specific "community" setup for LAPSE-RATE (https://zenodo.org/communities/lapse-rate/ , last access: 21 January 2021) and are accessible at no cost by all registered users. The primary dataset DOIs are 10.5281/zenodo.3814765 (CU MURC measurements; de Boer et al., 2020d), 10.5281/zenodo.3738175 (NSSL MM measurements; Waugh, 2020), and 10.5281/zenodo.3838724 (UNL CoMeT measurements; Houston and Erwin, 2020). [ABSTRACT FROM AUTHOR]

There are international recommendations that the environment (i.e. wildlife) is assessed for the potential impact of releases of ionizing radiation. The transfer of radionuclides to wildlife from media (e.g. soil, water) is usually described using the whole-organism concentration ratio (CR wo-media), and a number of assessment models use these values to estimate radiation exposure and risk to wildlife; however, there are many gaps in knowledge. This paper describes a study conducted in 2015–2016 to sample terrestrial wildlife, soil and water from two forests in north-eastern England. Sampling was targeted towards species representative of the International Commission on Radiological Protection's (ICRP) terrestrial Reference Animals and Plants (RAPs): Wild Grass (Poaceae family), Pine Tree (Pinaceae family), Earthworm (Lumbricidae family), Bee (Apidae family), Rat (Muridae family), Deer (Cervidae family) and Frog (Ranidae family); opportunistic sampling of plant and fungi species was also conducted. The dataset comprises stable-element concentrations for 30 elements, radionuclide activity concentrations for K-40 and Cs-137, and radionuclide and stable-element concentration ratios. These data have significantly increased the number of CR wo-media values available for the ICRP RAPs and will contribute to the development of the databases underpinning the ICRP's environmental protection framework. Data will be included in the international database of wildlife transfer parameters for radioecological models and hence are likely to contribute to model developments in the future. All data and supporting documentation are freely available from the Environmental Information Data Centre (EIDC; https://eidc.ac.uk/ , last access: 13 November 2020) under the terms and conditions of the Open Government Licence (Barnett et al., 2020 https://doi.org/10.5285/8f85c188-a915-46ac-966a-95fcb1491be6). [ABSTRACT FROM AUTHOR]

The data set "Spatial radionuclide deposition data from the 60 radial km area around the Chernobyl nuclear power plant: results from a sampling survey in 1987" is the latest in a series of data to be published by the Environmental Information Data Centre (EIDC) describing samples collected and analysed following the Chernobyl Nuclear Power Plant accident in 1986. The data result from a survey carried out by the Ukrainian Institute of Agricultural Radiology (UIAR) in April and May 1987 and includes sample site information, dose rate, radionuclide (zirconium-95, niobium-95, ruthenium-106, caesium-134, caesium-137 and cerium-144) deposition, and exchangeable (determined following 1M NH4Ac extraction of soils) caesium-134 and 137. The purpose of this paper is to describe the available data and methodology used for sample collection, sample preparation and analysis. The data will be useful in reconstructing doses to human and wildlife populations, answering the current lack of scientific consensus on the effects of radiation on wildlife in the Chernobyl Exclusion Zone and evaluating future management options for the Chernobyl-impacted areas of Ukraine and Belarus. The data and supporting documentation are freely available from the EIDC under the terms and conditions of the Open Government Licence (Kashparov et al., 2019; 10.5285/a408ac9d-763e-4f4c-ba72-73bc2d1f596d). [ABSTRACT FROM AUTHOR]

Direct observations of marine microbial metabolism are sparse in the Arctic, particularly under sea ice during winter. This paper presents the first observations of Arctic winter microbial activity under sea ice in a west Greenland fjord (Lillefjord, ∼ 70 ∘ N). Here, measured changes in dissolved oxygen (DO) content in light and dark in situ incubations were used to calculate net community productivity, respiration and photosynthesis rates. Data were collected at two fully ice covered sites during February 2013, shortly after the end of the polar night. Averaged over the full study period, dark incubations showed statistically significant decreases in DO of -0.36±0.24 (near shore) and -0.09±0.07 g O2 m -3 d -1 (fjord centre), indicating respiration rates that were 2–20 times greater than rates previously reported under sea ice in the Arctic. Meanwhile, a lack of significant evidence for photosynthesis suggests that the rate of photosynthesis – if it was occurring – was much lower than that of respiration. The data also show no significant evidence of a temporal trend in metabolism rates over the study period; however, ambient seawater DO increased significantly at the fjord centre (0.023±0.013 g O2 m -3 d -1), possibly attributable to processes not occurring in the incubations (such as sea ice algal photosynthesis). These data may improve our understanding of microbial activity in the fjord during winter, and its contribution to Arctic ecosystems under present and future conditions. The data are archived at PANGAEA (10.1594/PANGAEA.906332, Chandler and Mackie, 2019; 10.1594/PANGAEA.912677, Chandler and Mackie, 2020). [ABSTRACT FROM AUTHOR]

We present Sval_Imp, a high-resolution gridded dataset designed for forcing models of terrestrial surface processes on Svalbard. The dataset is defined on a 1 km grid covering the archipelago of Svalbard, located in the Norwegian Arctic (74–82 ∘ N). Using a hybrid methodology, combining multidimensional interpolation with simple dynamical modeling, the atmospheric reanalyses ERA-40 and ERA-Interim by the European Centre for Medium-Range Weather Forecasting have been downscaled to cover the period 1957–2017 at steps of 6 h. The dataset is publicly available from a data repository. In this paper, we describe the methodology used to construct the dataset, present the organization of the data in the repository and discuss the performance of the downscaling procedure. In doing so, the dataset is compared to a wealth of data available from operational and project-based measurements. The quality of the downscaled dataset is found to vary in space and time, but it generally represents an improvement compared to unscaled values, especially for precipitation. Whereas operational records are biased to low elevations around the fringes, we stress the hitherto underused potential of project-based measurements at higher elevation and in the interior of the archipelago for evaluating atmospheric models. For instance, records of snow accumulation on large ice masses may represent measures of seasonally integrated precipitation in regions sensitive to the downscaling procedure and thus providing added value. Sval_Imp is publicly available from the Norwegian Research Data Archive NIRD, a data repository (10.11582/2018.00006). [ABSTRACT FROM AUTHOR]

The air at the surface of the high Antarctic Plateau is very cold, dry and clean. Under such conditions, the atmospheric moisture can significantly deviate from thermodynamic equilibrium, and supersaturation with respect to ice can occur. Most conventional humidity sensors for meteorological applications cannot report supersaturation in this environment. A simple approach for measuring supersaturation using conventional instruments, with one being operated in a heated airflow, is presented. Since 2018, this instrumental setup has been deployed at three levels in the lower ∼40 m above the surface at Dome C on the high Antarctic Plateau. A resulting 3-year (2018–2020) record (Genthon et al., 2021a) is presented and analyzed for features such as the frequency of supersaturation with respect to ice, diurnal and seasonal variability, and vertical distribution. As supercooled liquid water droplets are frequently observed in clouds at the temperatures experienced on the high Antarctic Plateau, the distribution of relative humidity with respect to liquid water at Dome C is also discussed. It is suggested that, while not strictly mimicking the conditions of the high troposphere, the surface atmosphere on the Antarctic Plateau is a convenient natural laboratory to test parametrizations of cold microphysics predominantly developed to handle the genesis of high tropospheric clouds. Data are available from the PANGAEA data repository at 10.1594/PANGAEA.939425 (Genthon et al., 2021a). [ABSTRACT FROM AUTHOR]

This publication presents a comprehensive hydrometeorological data set for three research sites in the upper Rofental (1891–3772 m a.s.l., Ötztal Alps, Austria) and is a companion publication to a data collection published in 2018. The time series presented here comprise data from 2017 to 2023 and originate from three meteorological and snow hydrological stations at 2737, 2805, and 2919 m a.s.l. The fully equipped automatic weather stations include a specific set of sensors to continuously record snow cover properties. These are automatic measurements of snow depth, snow water equivalent, volumetric solid and liquid water contents, snow density, layered snow temperature profiles, and snow surface temperature. One station is extended by a particular arrangement of two snow depth and water equivalent recording devices to observe and quantify wind-driven snow transport. These devices are installed at nearby wind-exposed and sheltered locations and are complemented by an acoustic-based snow drift sensor. We present data for temperature, precipitation, humidity, wind speed, and radiation fluxes and explore the continuous snow measurements by combined analyses of meteorological and snow data to show typical seasonal snow cover characteristics. The potential of the snow drift observations is demonstrated with examples of measured wind speeds, snow drift rates, and redistributed snow amounts during several blowing snow events. The data complement the scientific monitoring infrastructure in the research catchment and represent a unique time series of high-altitude mountain weather and snow observations. They enable comprehensive insights into the dynamics of high-altitude meteorological and snow processes and are collected to support the scientific community, local stakeholders, and the interested public, as well as operational warning and forecasting services. The data are publicly available from the GFZ Data Services repository: 10.5880/fidgeo.2023.037 (Department of Geography, University of Innsbruck, 2024). [ABSTRACT FROM AUTHOR]

The Total Carbon Column Observing Network (TCCON) measures column-average mole fractions of several greenhouse gases (GHGs), beginning in 2004, from over 30 current or past measurement sites around the world using solar absorption spectroscopy in the near-infrared (near-IR) region. TCCON GHG data have been used extensively for multiple purposes, including in studies of the carbon cycle and anthropogenic emissions, as well as to validate and improve observations from space-based sensors. Here, we describe an update to the retrieval algorithm used to process the TCCON near-IR solar spectra and to generate the associated data products. This version, called GGG2020, was initially released in April 2022. It includes updates and improvements to all steps of the retrieval, including but not limited to the conversion of the original interferograms into spectra, the spectroscopic information used in the column retrieval, post hoc air mass dependence correction, and scaling to align with the calibration scales of in situ GHG measurements. All TCCON data are available through https://tccondata.org/ (last access: 22 April 2024) and are hosted on CaltechDATA (https://data.caltech.edu/ , last access: 22 April 2024). Each TCCON site has a unique DOI for its data record. An archive of all the sites' data is also available with the DOI 10.14291/TCCON.GGG2020. The hosted files are updated approximately monthly, and TCCON sites are required to deliver data to the archive no later than 1 year after acquisition. Full details of data locations are provided in the "Code and data availability" section. [ABSTRACT FROM AUTHOR]

We present a seismic catalog (, https://doi.org/10.5880/GFZ.2.6.2023.010) including energy magnitude Me estimated from P waves recorded at teleseismic distances in the range 20°≤Δ≤98° and for depths shorter than 80 km. The catalog is built starting from the event catalog disseminated by GEOFON (GEOFOrschungsNetz), considering 6349 earthquakes with moment magnitude Mw≥5 occurring between 2011 and 2023. Magnitudes are computed using 1 031 396 freely available waveforms archived in EIDA (European Integrated Data Archive) and IRIS (Incorporated Research Institutions for Seismology) repositories, retrieved through the standard International Federation of Digital Seismograph Networks (FDSN) web services (https://www.fdsn.org/webservices/ , last access: March 2024). A reduced, high-quality catalog for events with Mw≥5.8 and from which stations and events with only few recordings were removed forms the basis of a detailed analysis of the residuals of individual station measurements, which are decomposed into station- and event-specific terms and a term accounting for remaining variability. The derived Me values are compared to Mw computed by GEOFON and with the Me values calculated by IRIS. Software and tools developed for downloading and processing waveforms for bulk analysis and an add-on for SeisComP for real-time assessment of Me in a monitoring context are also provided alongside the catalog. The SeisComP add-on has been part of the GEOFON routine processing since December 2021 to compute and disseminate Me for major events via the existing services. [ABSTRACT FROM AUTHOR]

The amount and the phase of cold-season precipitation accumulating in the upper Saint John River (SJR) basin are critical factors in determining spring runoff, ice jams, and flooding. To study the impact of winter and spring storms on the snowpack in the upper SJR basin, the Saint John River Experiment on Cold Season Storms (SAJESS) was conducted during winter–spring 2020–2021. Here, we provide an overview of the SAJESS study area, field campaign, and data collected. The upper SJR basin represents 41 % of the entire SJR watershed and encompasses parts of the US state of Maine and the Canadian provinces of Quebec and New Brunswick. In early December 2020, meteorological instruments were co-located with an Environment and Climate Change Canada station near Edmundston, New Brunswick. This included a separate weather station for measuring standard meteorological variables, an optical disdrometer, and a micro rain radar. This instrumentation was augmented during an intensive observation period that also included upper-air soundings, surface weather observations, a multi-angle snowflake camera, and macrophotography of solid hydrometeors throughout March and April 2021. During the study, the region experienced a lower-than-average snowpack that peaked at ∼ 65 cm, with a total of 287 mm of precipitation (liquid-equivalent) falling between December 2020 and April 2021, a 21 % lower amount of precipitation than the climatological normal. Observers were present for 13 storms during which they conducted 183 h of precipitation observations and took more than 4000 images of hydrometeors. The inclusion of local volunteers and schools provided an additional 1700 measurements of precipitation amounts across the area. The resulting datasets are publicly available from the Federated Research Data Repository at 10.20383/103.0591 (Thompson et al., 2023). We also include a synopsis of the data management plan and a brief assessment of the rewards and challenges of conducting the field campaign and utilizing community volunteers for citizen science. [ABSTRACT FROM AUTHOR]

The Western Channel Observatory (WCO) comprises a series of pelagic, benthic and atmospheric sampling sites within 40 km of Plymouth, UK, that have been sampled by the Plymouth institutes on a regular basis since 1903. This longevity of recording and the high frequency of observations provide a unique combination of data; for example temperature data were first collected in 1903, and the reference station L4, where nearly 400 planktonic taxa have been enumerated, has been sampled on a weekly basis since 1988. While the component datasets have been archived, here we provide the first summary database bringing together a wide suite of the observations. This provides monthly average values of some of the key pelagic and benthic measurements for the inshore site L4 (50 ∘ 15.00 ′ N, 4 ∘ 13.02 ′ W; approx. depth 55 m), the offshore site E1 (50 ∘ 02.00 ′ N, 4 ∘ 22.00 ′ W; approx. depth 75 m) and the intermediate L5 site (50 ∘ 10.80 ′ N, 4 ∘ 18.00 ′ W; approx. depth 58 m). In brief, these data include the following: water temperature (from 1903); macronutrients (from 1934); dissolved inorganic carbon and total alkalinity (from 2008); methane and nitrous oxide (from 2011); chlorophyll a (from 1992); high-performance liquid chromatography (HPLC)-derived pigments (from 1999); <20 µm plankton by flow cytometry, including bacteria (8 functional groups from 2007); phytoplankton by microscopy (6 functional groups from 1992); microplankton and mesozooplankton from FlowCam (6 groups from 2012); Noctiluca sp. dinoflagellate (from 1997); mesozooplankton by microscopy (8 groups from 1988); Calanus helgolandicus egg production rates (from 1992); fish larvae from the Young Fish Trawl survey (4 groups from 1924); benthic macrofauna (4 groups from 2008); demersal fish (19 families from 2008); blue shark, Prionace glauca (from 1958); and 16S alpha diversity for sediment and water column (from 2012). These data have varying coverage with respect to time and depth resolution. The metadata tables describe each dataset and provide pointers to the source data and other related Western Channel Observatory datasets and outputs not compiled here. We provide summaries of the main trends in seasonality and some major climate-related shifts that have been revealed over the last century. The data are available from the Data Archive for Seabed Species and Habitats (DASSH): 10.17031/645110fb81749 (McEvoy and Atkinson, 2023). Making these data fully accessible and including units of both abundance and biomass will stimulate a variety of uptakes. These may include uses as an educational resource for projects, for models and budgets, for the analysis of seasonality and long-term change in a coupled benthic–pelagic system, or for supporting UK and north-eastern Atlantic policy and management. [ABSTRACT FROM AUTHOR]

Two buoys equipped with Doppler lidars owned by the US Department of Energy (DOE) were deployed off the coast of California in autumn of 2020 by Pacific Northwest National Laboratory. The buoys collected data for an entire annual cycle at two offshore locations proposed for offshore wind development by the Bureau of Ocean Energy Management. One of the buoys was deployed approximately 50 km off the coast near Morro Bay in central California in 1100 m of water. The second buoy was deployed approximately 40 km off Humboldt County in northern California in 625 m of water. The buoys provided the first-ever continuous measurements of the air–sea transition zone off the coast of California. The atmospheric and oceanographic characteristics of the area and estimates of annual energy production at both the Morro Bay and Humboldt wind energy areas show that both locations have a high wind energy yield and are prime locations for future floating offshore wind turbines. This article provides a description and comprehensive analysis of the data collected by the buoys, and a final post-processed dataset is uploaded to a data archive maintained by the DOE. Additional analysis was conducted to show the value of the data collected by the DOE buoys. All post-processed data from this study are available on the Wind Data Hub website: https://a2e.energy.gov/data# (last access: 14 September 2023). Near-surface, wave, current, and cloud datasets for Humboldt and Morro Bay are provided at 10.21947/1783807 (Krishnamurthy and Sheridan, 2023b) and 10.21947/1959715 (Krishnamurthy and Sheridan, 2023a), respectively. Lidar datasets for Humboldt and Morro Bay are provided at 10.21947/1783809 (Krishnamurthy and Sheridan, 2023d) and 10.21947/1959721 (Krishnamurthy and Sheridan, 2023c), respectively. [ABSTRACT FROM AUTHOR]

The Atlantic Zone Monitoring Program (AZMP) was established by Fisheries and Oceans Canada (DFO) in 1998 with the aim of monitoring physical and biological ocean conditions in Atlantic Canada in support of fisheries management. Since 2014, at least two of the carbonate parameters (pH; total alkalinity, TA; and dissolved inorganic carbon, DIC) have also been systematically measured as part of the AZMP, enabling the calculation of derived parameters (e.g., carbonate saturation states, Ω , and partial pressure of CO2 , p CO2). The present study gives an overview of the spatiotemporal variability in these parameters between 2014 and 2022. Results show that the variability in the carbonate system reflects changes in both physical (e.g., temperature and salinity) and biological (e.g., plankton photosynthesis and respiration) parameters. For example, most of the region undergoes a seasonal warming and freshening. While the former will tend to increase Ω , the latter will decrease both TA and Ω. Spring and summer plankton blooms decrease DIC near the surface and then remineralize and increase DIC at depth in the fall. The lowest p CO2 values (down to ∼ 200 µ atm) are located in the cold coastal Labrador Current, whereas the highest values (>1500 µ atm) are found in the fresh waters of the Gulf of St. Lawrence and the St. Lawrence Estuary. The latter is also host to the lowest pH values of the zone (7.48 in the fall of 2022). Finally, most of the bottom waters of the Gulf of St. Lawrence (>90 %) are undersaturated with respect to aragonite (Ωarg<1). In addition to providing a baseline of carbonate parameters for the Atlantic Zone as a whole, this comprehensive overview is a necessary and useful contribution for the modelling community and for more in-depth studies. The full dataset of measured and derived parameters is available from the Federated Research Data Repository: 10.20383/102.0673. [ABSTRACT FROM AUTHOR]

Despite their small spatial extent, fluvial ecosystems play a significant role in processing and transporting carbon in aquatic networks, which results in substantial emission of methane (CH4) into the atmosphere. For this reason, considerable effort has been put into identifying patterns and drivers of CH4 concentrations in streams and rivers and estimating fluxes to the atmosphere across broad spatial scales. However, progress toward these ends has been slow because of pronounced spatial and temporal variability of lotic CH4 concentrations and fluxes and by limited data availability across diverse habitats and physicochemical conditions. To address these challenges, we present a comprehensive database of CH4 concentrations and fluxes for fluvial ecosystems along with broadly relevant and concurrent physical and chemical data. The Global River Methane Database (GriMeDB; 10.6073/pasta/f48cdb77282598052349e969920356ef, Stanley et al., 2023) includes 24 024 records of CH4 concentration and 8205 flux measurements from 5029 unique sites derived from publications, reports, data repositories, unpublished data sets, and other outlets that became available between 1973 and 2021. Flux observations are reported as diffusive, ebullitive, and total CH4 fluxes, and GriMeDB also includes 17 655 and 8409 concurrent measurements of concentrations and 4444 and 1521 fluxes for carbon dioxide (CO2) and nitrous oxide (N2O), respectively. Most observations are date-specific (i.e., not site averages), and many are supported by data for 1 or more of 12 physicochemical variables and 6 site variables. Site variables include codes to characterize marginal channel types (e.g., springs, ditches) and/or the presence of human disturbance (e.g., point source inputs, upstream dams). Overall, observations in GRiMeDB encompass the broad range of the climatic, biological, and physical conditions that occur among world river basins, although some geographic gaps remain (arid regions, tropical regions, high-latitude and high-altitude systems). The global median CH4 concentration (0.20 µmolL-1) and diffusive flux (0.44 mmolm-2d-1) in GRiMeDB are lower than estimates from prior site-averaged compilations, although ranges (0 to 456 µmolL-1 and - 136 to 4057 mmolm-2d-1) and standard deviations (10.69 and 86.4) are greater for this larger and more temporally resolved database. Available flux data are dominated by diffusive measurements despite the recognized importance of ebullitive and plant-mediated CH4 fluxes. Nonetheless, GriMeDB provides a comprehensive and cohesive resource for examining relationships between CH4 and environmental drivers, estimating the contribution of fluvial ecosystems to CH4 emissions, and contextualizing site-based investigations. [ABSTRACT FROM AUTHOR]

The response of the hydrological cycle to anthropogenic climate change, especially across the tropical oceans, remains poorly understood due to the scarcity of long instrumental temperature and hydrological records. Massive shallow-water corals are ideally suited to reconstructing past oceanic variability as they are widely distributed across the tropics, rapidly deposit calcium carbonate skeletons that continuously record ambient environmental conditions, and can be sampled at monthly to annual resolution. Climate reconstructions based on corals primarily use the stable oxygen isotope composition (δ18 O), which acts as a proxy for sea surface temperature (SST), and the oxygen isotope composition of seawater (δ18 O sw), a measure of hydrological variability. Increasingly, coral δ18 O time series are paired with time series of strontium-to-calcium ratios (Sr/Ca), a proxy for SST, from the same coral to quantify temperature and δ18 O sw variability through time. To increase the utility of such reconstructions, we present the CoralHydro2k database, a compilation of published, peer-reviewed coral Sr/Ca and δ18 O records from the Common Era (CE). The database contains 54 paired Sr/Ca – δ18 O records and 125 unpaired Sr/Ca or δ18 O records, with 88 % of these records providing data coverage from 1800 CE to the present. A quality-controlled set of metadata with standardized vocabulary and units accompanies each record, informing the use of the database. The CoralHydro2k database tracks large-scale temperature and hydrological variability. As such, it is well-suited for investigations of past climate variability, comparisons with climate model simulations including isotope-enabled models, and application in paleodata-assimilation projects. The CoralHydro2k database is available in Linked Paleo Data (LiPD) format with serializations in MATLAB, R, and Python and can be downloaded from the NOAA National Center for Environmental Information's Paleoclimate Data Archive at 10.25921/yp94-v135 (Walter et al., 2022). [ABSTRACT FROM AUTHOR]

Rice is the most important staple food in Asia. However, high-spatiotemporal-resolution rice yield datasets are limited over this large region. The lack of such products greatly hinders studies that are aimed at accurately assessing the impacts of climate change and simulating agricultural production. Based on annual rice maps in Asia, we incorporated multisource predictors into three machine learning (ML) models to generate a high-spatial-resolution (4 km) seasonal rice yield dataset (AsiaRiceYield4km) for the 1995–2015 period. Predictors were divided into four categories that considered the most comprehensive rice growth conditions, and the optimal ML model was determined based on an inverse probability weighting method. The results showed that AsiaRiceYield4km achieves good accuracy for seasonal rice yield estimation (single rice: R2=0.88 , RMSE = 920 kg ha -1 ; double rice: R2=0.91 , RMSE = 554 kg ha -1 ; and triple rice: R2=0.93 , RMSE = 588 kg ha -1). Compared with single rice from the Spatial Production Allocation Model (SPAM), the R2 of AsiaRiceYield4km was improved by 0.20, and the RMSE was reduced by 618 kg ha -1 on average. In particular, constant environmental conditions, including longitude, latitude, elevation and soil properties, contributed the most (∼ 45 %) to rice yield estimation. For different rice growth periods, we found that the predictors of the reproductive period had greater impacts on rice yield prediction than those of the vegetative period and the whole growing period. AsiaRiceYield4km is a novel long-term gridded rice yield dataset that can fill the unavailability of high-spatial-resolution seasonal yield products across major rice production areas and promote more relevant studies on agricultural sustainability worldwide. AsiaRiceYield4km can be downloaded from the following open-access data repository: https://doi.org/10.5281/zenodo.6901968 (Wu et al., 2022). [ABSTRACT FROM AUTHOR]

Benthic foraminifera are important components of the ocean benthos and play a major role in ocean biogeochemistry and ecosystem functioning. Generating ecological baselines for ocean monitoring or biogeographical distributions requires a reference dataset of recent census data. Moreover, the information from their modern biogeography can be used to interpret past environmental changes on the seafloor. In this study, we provide the first comprehensive quantitative benthic foraminifera database from surface sediments of the eastern Pacific (BENFEP). Through the collation of archival quantitative data on species abundance and their homogenization according to the most recent taxonomic standards, we are able to provide a database with 3077 sediment samples, corresponding to 2509 georeferenced stations of wide geographical (60 ∘ N–54 ∘ S) and water depth (0–7280 m) coverage. The quantitative data include living, dead, and living plus dead assemblages obtained from 50 published and unpublished documents. As well as describing the data collection and subsequent harmonization steps, we provide summarized information on metadata, examples of species' distributions, potential applications of the database, and recommendations for data archiving and publication of benthic foraminiferal data. The database is enriched with meaningful metadata for accessible data management and exploration with R software and geographical information systems. The first version of the database (BENFEP_v1, Diz et al., 2022a, 10.1594/PANGAEA.947086) is provided in short and long format, and it will be upgraded with new entries and when changes are needed to accommodate taxonomic revisions. [ABSTRACT FROM AUTHOR]

This work presents a hyperspectral reflectance dataset of macroplastic samples acquired using Analytical Spectral Devices (ASD) FieldSpec 4. Samples analyzed consisted of pristine, artificially weathered, and biofouled plastic items and plastic debris samples collected in the docks of the Port of Antwerp and in the river Scheldt near Temse Bridge (Belgium). The hyperspectral signal of each sample was measured in controlled dry conditions in an optical calibration facility at the Vlaamse Instelling voor Technologisch Onderzoek (VITO; Flemish Institute for Technological Research) and, for a subset of plastics, under wet and submerged conditions in a silo tank at Flanders Hydraulics. The wet and submerged hyperspectral signals were measured in a mesocosm setting that mimicked environmentally relevant concentrations of freshwater microalgae and suspended sediment. The ASD was equipped with an 8 ∘ field of view at the calibration facility, and a 1 ∘ field of view was used in the mesocosm setting. The dataset obtained complies with the FAIR (Findable, Accessible, Interoperable, Reusable) principles and is available in the open-access repository Marine Data Archive (10.14284/530, Leone et al., 2021). [ABSTRACT FROM AUTHOR]

Seagrass meadows provide valuable socio-ecological ecosystem services, including a key role in climate change mitigation and adaption. Understanding the natural history of seagrass meadows across environmental gradients is crucial to deciphering the role of seagrasses in the global ocean. In this data collation, spatial and temporal patterns in seagrass meadow structure, biomass and production data are presented as a function of biotic and abiotic habitat characteristics. The biological traits compiled include measures of meadow structure (e.g. percent cover and shoot density), biomass (e.g. above-ground biomass) and production (e.g. shoot production). Categorical factors include bioregion, geotype (coastal or estuarine), genera and year of sampling. This dataset contains data extracted from peer-reviewed publications published between 1975 and 2020 based on a Web of Science search and includes 11 data variables across 12 seagrass genera. The dataset excludes data from mesocosm and field experiments, contains 14 271 data points extracted from 390 publications and is publicly available on the PANGAEA® data repository (10.1594/PANGAEA.929968; Strydom et al., 2021). The top five most studied genera are Zostera, Thalassia, Cymodocea, Halodule and Halophila (84 % of data), and the least studied genera are Phyllospadix, Amphibolis and Thalassodendron (2.3 % of data). The data hotspot bioregion is the Tropical Indo-Pacific (25 % of data) followed by the Tropical Atlantic (21 %), whereas data for the other four bioregions are evenly spread (ranging between 13 and 15 % of total data within each bioregion). From the data compiled, 57 % related to seagrass biomass and 33 % to seagrass structure, while the least number of data were related to seagrass production (11 % of data). This data collation can inform several research fields beyond seagrass ecology, such as the development of nature-based solutions for climate change mitigation, which include readership interested in blue carbon, engineering, fisheries, global change, conservation and policy. [ABSTRACT FROM AUTHOR]

China ranks in the highest position for nitrogen (N) fertilizer consumption in the world. Although N fertilizer use has greatly contributed to the China's food production, this has also caused an unprecedented alteration in the biogeochemical cycles and endangered terrestrial and aquatic ecosystems. Existing use of N fertilizers in China, as shown by digital maps, is usually coarse in resolution and intermittently covered with a biased gridded dataset. Here, we have reconstructed a historical, annual N fertilizer use dataset in China and resampled it to 5km×5km resolution, covering the period from 1952 to 2018 by integrating improved cropland maps. Results showed that most of the N input was directly applied as N-only fertilizer, while the contribution from compound fertilizers has ranged between 16 % and 24 % since 1980. The national total N fertilizer input increased from 0.06 Tg N yr -1 (0.05 g N m -2 yr -1) in 1952 to 31.15 Tg N yr -1 (18.83 g N m -2 yr -1) in 2014 and then decreased to 28.31 Tg N yr -1 (17.06 g N m -2 yr -1) in 2018. Despite the total N input decreasing by 9.1 % (2.84 Tg N yr -1) from 2014 to 2018, the N input from compound fertilizers has increased by 6 % (0.43 Tg N yr -1) during the corresponding period. The previous Food and Agriculture Organization (FAO) data-based N fertilizer products in China overestimated N use in low cropland coverage areas but underestimated N use in high cropland coverage areas. However, our newly reconstructed data have not only corrected the existing biases and improved the spatial distribution but have also shown that vegetable and other crops (e.g., orchards), but not grain crops, are the most intensively fertilized crops in China, implying the importance of quantifying greenhouse gas (GHG) emissions from these croplands. We argue that the reconstructed, spatially explicit N fertilizer use data in this study are expected to contribute to better understanding of biogeochemical cycles, including the simulations of GHG emissions and food production in China. The spatially explicit N fertilizer use and the crop-specific N fertilizer use datasets are available via an open data repository (10.6084/m9.figshare.21371469.v1; Yu, 2022). [ABSTRACT FROM AUTHOR]

Lakes are key ecosystems within the global biogeosphere. However, the environmental controls on the biological productivity of lakes – including surface temperature, ice phenology, nutrient loads, and mixing regime – are increasingly altered by climate warming and land-use changes. To better characterize global trends in lake productivity, we assembled a dataset on chlorophyll- a concentrations as well as associated water quality parameters and surface solar radiation for temperate and cold-temperate lakes experiencing seasonal ice cover. We developed a method to identify periods of rapid net increase of in situ chlorophyll- a concentrations from time series data and applied it to data collected between 1964 and 2019 across 343 lakes located north of 40 ∘. The data show that the spring chlorophyll- a increase periods have been occurring earlier in the year, potentially extending the growing season and increasing the annual productivity of northern lakes. The dataset on chlorophyll- a increase rates and timing can be used to analyze trends and patterns in lake productivity across the northern hemisphere or at smaller, regional scales. We illustrate some trends extracted from the dataset and encourage other researchers to use the open dataset for their own research questions. The PCI dataset and additional data files can be openly accessed at the Federated Research Data Repository at 10.20383/102.0488 (Adams et al., 2021). [ABSTRACT FROM AUTHOR]

Since the beginning of this century, Europe has been experiencing severe drought events (2003, 2007, 2010, 2018 and 2019) which have had adverse impacts on various sectors, such as agriculture, forestry, water management, health and ecosystems. During the last few decades, projections of the impact of climate change on hydroclimatic extremes have often been used for quantification of changes in the characteristics of these extremes. Recently, the research interest has been extended to include reconstructions of hydroclimatic conditions to provide historical context for present and future extremes. While there are available reconstructions of temperature, precipitation, drought indicators, or the 20th century runoff for Europe, multi-century annual runoff reconstructions are still lacking. In this study, we have used reconstructed precipitation and temperature data, Palmer Drought Severity Index and available observed runoff across 14 European catchments in order to develop annual runoff reconstructions for the period 1500–2000 using two data-driven and one conceptual lumped hydrological model. The comparison to observed runoff data has shown a good match between the reconstructed and observed runoff and their characteristics, particularly deficit volumes. On the other hand, the validation of input precipitation fields revealed an underestimation of the variance across most of Europe, which is propagated into the reconstructed runoff series. The reconstructed runoff is available via Figshare, an open-source scientific data repository, under the DOI 10.6084/m9.figshare.15178107,. [ABSTRACT FROM AUTHOR]

Arctic river deltas and deltaic near-shore zones represent important land–ocean transition zones influencing sediment dynamics and nutrient fluxes from permafrost-affected terrestrial ecosystems into the coastal Arctic Ocean. To accurately model fluvial carbon and freshwater export from rapidly changing river catchments as well as assess impacts of future change on the Arctic shelf and coastal ecosystems, we need to understand the sea floor characteristics and topographic variety of the coastal zones. To date, digital bathymetrical data from the poorly accessible, shallow, and large areas of the eastern Siberian Arctic shelves are sparse. We have digitized bathymetrical information for nearly 75 000 locations from large-scale (1:25000 – 1:500000) current and historical nautical maps of the Lena Delta and the Kolyma Gulf region in northeastern Siberia. We present the first detailed and seamless digital models of coastal zone bathymetry for both delta and gulf regions in 50 and 200 m spatial resolution. We validated the resulting bathymetry layers using a combination of our own water depth measurements and a collection of available depth measurements, which showed a strong correlation (r>0.9). Our bathymetrical models will serve as an input for a high-resolution coupled hydrodynamic–ecosystem model to better quantify fluvial and coastal carbon fluxes to the Arctic Ocean, but they may be useful for a range of other studies related to Arctic delta and near-shore dynamics such as modeling of submarine permafrost, near-shore sea ice, or shelf sediment transport. The new digital high-resolution bathymetry products are available on the PANGAEA data set repository for the Lena Delta (10.1594/PANGAEA.934045; Fuchs et al., 2021a) and Kolyma Gulf region (10.1594/PANGAEA.934049; Fuchs et al., 2021b), respectively. Likewise, the depth validation data are available on PANGAEA as well (10.1594/PANGAEA.933187; Fuchs et al., 2021c). [ABSTRACT FROM AUTHOR]

Long-term global monitoring of terrestrial gross primary production (GPP) is crucial for assessing ecosystem responses to global climate change. In recent decades, great advances have been made in estimating GPP and many global GPP datasets have been published. These datasets are based on observations from optical remote sensing, are upscaled from in situ measurements, or rely on process-based models. Although these approaches are well established within the scientific community, datasets nevertheless differ significantly. Here, we introduce the new VODCA2GPP dataset, which utilizes microwave remote sensing estimates of vegetation optical depth (VOD) to estimate GPP at the global scale for the period 1988–2020. VODCA2GPP applies a previously developed carbon-sink-driven approach (Teubner et al., 2019, 2021) to estimate GPP from the Vegetation Optical Depth Climate Archive (Moesinger et al., 2020; Zotta et al., 2022​​​​​​​), which merges VOD observations from multiple sensors into one long-running, coherent data record. VODCA2GPP was trained and evaluated against FLUXNET in situ observations of GPP and compared against largely independent state-of-the-art GPP datasets from the Moderate Resolution Imaging Spectroradiometer (MODIS), FLUXCOM, and the TRENDY-v7 process-based model ensemble. The site-level evaluation with FLUXNET GPP indicates an overall robust performance of VODCA2GPP with only a small bias and good temporal agreement. The comparisons with MODIS, FLUXCOM, and TRENDY-v7 show that VODCA2GPP exhibits very similar spatial patterns across all biomes but with a consistent positive bias. In terms of temporal dynamics, a high agreement was found for regions outside the humid tropics, with median correlations around 0.75. Concerning anomalies from the long-term climatology, VODCA2GPP correlates well with MODIS and TRENDY-v7 (Pearson's r 0.53 and 0.61) but less well with FLUXCOM (Pearson's r 0.29). A trend analysis for the period 1988–2019 did not exhibit a significant trend in VODCA2GPP at the global scale but rather suggests regionally different long-term changes in GPP. For the shorter overlapping observation period (2003–2015) of VODCA2GPP, MODIS, and the TRENDY-v7 ensemble, significant increases in global GPP were found. VODCA2GPP can complement existing GPP products and is a valuable dataset for the assessment of large-scale and long-term changes in GPP for global vegetation and carbon cycle studies. The VODCA2GPP dataset is available at the TU Data Repository of TU Wien (10.48436/1k7aj-bdz35, Wild et al., 2021). [ABSTRACT FROM AUTHOR]

Continuous, semi-long-term, ground-based in situ cloud measurements were conducted during eight Pallas Cloud Experiments (PaCEs) held in autumn between 2004 and 2019. Those campaigns were carried out in the Finnish sub-Arctic region at the Sammaltunturi station (67 ∘ 58 ′ 24 ′′ N, 24 ∘ 06 ′ 58 ′′ E; 560 m a.m.s.l.), the part of the Pallas Atmosphere–Ecosystem Supersite and Global Atmosphere Watch (GAW) program. Two cloud spectrometer ground setups and a weather station were installed on the roof of the station to measure in situ cloud properties and several meteorological variables. Thus, the obtained data sets include the size distribution of cloud droplets as a measured cloud parameter along with the air temperature, dew point temperature, humidity, pressure, horizontal wind speed and direction, (global solar) sun radiation, and visibility at the station. Additionally, the number concentration, effective diameter, median volume diameter, and liquid water content from each instrument were derived. The presented data sets provide a insight into microphysics of low-level clouds in sub-Arctic conditions over a wide range of temperatures (-25.8 to 8.8 ∘ C). The data are available in the Finnish Meteorological Institute (FMI) open data repository for each campaign and each cloud spectrometer ground setup individually: https://doi.org/10.23728/FMI-B2SHARE.988739D21B824C709084E88ED6C6D54B (Doulgeris et al., 2021). [ABSTRACT FROM AUTHOR]

The Stratosphere-troposphere Processes and their Role in Climate (SPARC) Data Initiative (SPARC, 2017) performed the first comprehensive assessment of currently available stratospheric composition measurements obtained from an international suite of space-based limb sounders. The initiative's main objectives were (1) to assess the state of data availability, (2) to compile time series of vertically resolved, zonal monthly mean trace gas and aerosol fields, and (3) to perform a detailed intercomparison of these time series, summarizing useful information and highlighting differences among datasets. The datasets extend over the region from the upper troposphere to the lower mesosphere (300–0.1 hPa) and are provided on a common latitude–pressure grid. They cover 26 different atmospheric constituents including the stratospheric trace gases of primary interest, ozone (O3) and water vapor (H2O), major long-lived trace gases (SF6 , N2O , HF , CCl3F , CCl2F2 , NOy), trace gases with intermediate lifetimes (HCl , CH4 , CO , HNO3), and shorter-lived trace gases important to stratospheric chemistry including nitrogen-containing species (NO , NO2 , NOx , N2O5 , HNO4), halogens (BrO , ClO , ClONO2 , HOCl), and other minor species (OH , HO2 , CH2O , CH3CN), and aerosol. This overview of the SPARC Data Initiative introduces the updated versions of the SPARC Data Initiative time series for the extended time period 1979–2018 and provides information on the satellite instruments included in the assessment: LIMS, SAGE I/II/III, HALOE, UARS-MLS, POAM II/III, OSIRIS, SMR, MIPAS, GOMOS, SCIAMACHY, ACE-FTS, ACE-MAESTRO, Aura-MLS, HIRDLS, SMILES, and OMPS-LP. It describes the Data Initiative's top-down climatological validation approach to compare stratospheric composition measurements based on zonal monthly mean fields, which provides upper bounds to relative inter-instrument biases and an assessment of how well the instruments are able to capture geophysical features of the stratosphere. An update to previously published evaluations of O3 and H2O monthly mean time series is provided. In addition, example trace gas evaluations of methane (CH4), carbon monoxide (CO), a set of nitrogen species (NO , NO2 , and HNO3), the reactive nitrogen family (NOy), and hydroperoxyl (HO2) are presented. The results highlight the quality, strengths and weaknesses, and representativeness of the different datasets. As a summary, the current state of our knowledge of stratospheric composition and variability is provided based on the overall consistency between the datasets. As such, the SPARC Data Initiative datasets and evaluations can serve as an atlas or reference of stratospheric composition and variability during the "golden age" of atmospheric limb sounding. The updated SPARC Data Initiative zonal monthly mean time series for each instrument are publicly available and accessible via the Zenodo data archive (Hegglin et al., 2020). [ABSTRACT FROM AUTHOR]

Space and time analyses of channel changes, especially within large rivers subject to high levels of human impact, are critical to address multiple questions about rivers in the Anthropocene era. The reconstruction of long-term (> 150 year) evolutionary trajectories permits an understanding of how natural and anthropogenic factors impact hydromorphological and ecological processes in rivers, helps with the design of sustainable management and restoration options, and may also help in the assessment of future changes. However, the reconstruction of channel changes can be challenging: historical data are often scattered across many archives, and the quantity and accuracy of information generally decreases as one goes back in time. This data article provides a historical database of 350 cartographic and topo-bathymetric resources on the French Rhône River (530 km in length) compiled from the 17th to mid-20th century, with a temporal focus prior to extensive river training (1860s). The data were collected in 14 national, regional, and departmental archive services. A table describes the properties of each archived data item and its associated iconographic files. Some of the historical maps are available in a georeferenced format. A GIS layer enables one-click identification of all archive data available for a given reach of the French Rhône River. This database provides substantial new material for deeper analyses of channel changes over a longer time period and at a finer time step compared with previously available data. The database has several potential applications in geomorphology, retrospective hydraulic modelling, historical ecology, and river restoration, as well as permitting comparisons with other multi-impacted rivers worldwide. The dataset is available at 10.1594/PANGAEA.922437 (Arnaud et al., 2020a). Iconographic extracts of the 350 archived items are available at http://photo.driihm.fr/index.php/category/52 (last access: 2 May 2021). [ABSTRACT FROM AUTHOR]

The Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign (ATOMIC) took place from 7 January to 11 July 2020 in the tropical North Atlantic between the eastern edge of Barbados and 51 ∘ W, the longitude of the Northwest Tropical Atlantic Station (NTAS) mooring. Measurements were made to gather information on shallow atmospheric convection, the effects of aerosols and clouds on the ocean surface energy budget, and mesoscale oceanic processes. Multiple platforms were deployed during ATOMIC including the NOAA RV Ronald H. Brown (RHB) (7 January to 13 February) and WP-3D Orion (P-3) aircraft (17 January to 10 February), the University of Colorado's Robust Autonomous Aerial Vehicle-Endurant Nimble (RAAVEN) uncrewed aerial system (UAS) (24 January to 15 February), NOAA- and NASA-sponsored Saildrones (12 January to 11 July), and Surface Velocity Program Salinity (SVPS) surface ocean drifters (23 January to 29 April). The RV Ronald H. Brown conducted in situ and remote sensing measurements of oceanic and atmospheric properties with an emphasis on mesoscale oceanic–atmospheric coupling and aerosol–cloud interactions. In addition, the ship served as a launching pad for Wave Gliders, Surface Wave Instrument Floats with Tracking (SWIFTs), and radiosondes. Details of measurements made from the RV Ronald H. Brown , ship-deployed assets, and other platforms closely coordinated with the ship during ATOMIC are provided here. These platforms include Saildrone 1064 and the RAAVEN UAS as well as the Barbados Cloud Observatory (BCO) and Barbados Atmospheric Chemistry Observatory (BACO). Inter-platform comparisons are presented to assess consistency in the data sets. Data sets from the RV Ronald H. Brown and deployed assets have been quality controlled and are publicly available at NOAA's National Centers for Environmental Information (NCEI) data archive (https://www.ncei.noaa.gov/archive/accession/ATOMIC-2020 , last access: 2 April 2021). Point-of-contact information and links to individual data sets with digital object identifiers (DOIs) are provided herein. [ABSTRACT FROM AUTHOR]

Within the framework of the UV-Indien network, nine ground stations have been equipped with ultraviolet broadband radiometers, five of them have also been equipped with an all-sky camera, and the main station in Saint-Denis de la Réunion is also equipped with a spectroradiometer. These stations are spatially distributed to cover a wide range of latitudes, longitudes, altitudes, and environmental conditions in five countries of the western Indian Ocean region (Comoros, France, Madagascar, Mauritius, and Seychelles), a part of the world where almost no measurements have been made so far. The distribution of the stations is based on the scientific interest of studying ultraviolet radiation not only in relation to atmospheric processes but also in order to provide data relevant to fields such as biology, health (prevention of skin cancer), and agriculture. The main scientific objectives of this network are to study the annual and inter-annual variability in the ultraviolet (UV) radiation in this area, to validate the output of numerical models and satellite estimates of ground-based UV measurements, and to monitor UV radiation in the context of climate change and projected ozone depletion in this region. A calibration procedure including three types of calibrations responding to the various constraints of sustaining the network has been put in place, and a data processing chain has been set up to control the quality and the format of the files sent to the various data centres. A method of clear-sky filtering of the data is also applied. Here, we present an intercomparison with other datasets, as well as several daily or monthly representations of the UV index (UVI) and cloud fraction data, to discuss the quality of the data and their range of values for the older stations (Antananarivo, Anse Quitor, Mahé, and Saint-Denis). Ground-based measurements of the UVI are used to validate satellite estimates – Ozone Monitoring Instrument (OMI), the TROPOspheric Monitoring Instrument (TROPOMI), and the Global Ozone Monitoring Experiment (GOME) – and model forecasts of UVI – Tropospheric Emission Monitoring Internet Service (TEMIS) and Copernicus Atmospheric Monitoring Service (CAMS). The median relative differences between satellite or model estimates and ground-based measurements of clear-sky UVI range between - 34.5 % and 15.8 %. Under clear skies, the smallest UVI median difference between the satellite or model estimates and the measurements made by ground-based instruments is found to be 0.02 (TROPOMI), 0.04 (OMI), - 0.1 (CAMS), and - 0.4 (CAMS) at Saint-Denis, Antananarivo, Anse Quitor, and Mahé, respectively. The diurnal variability in UVI and cloud fraction, as well as the monthly variability in UVI, is evaluated to ensure the quality of the dataset. The data used in this study are available at 10.5281/zenodo.4811488. [ABSTRACT FROM AUTHOR]

The simulation dataset described herein provides a high-resolution depiction of the four-dimensional variability of weather conditions across the northern half of the San Luis Valley, Colorado, during the 14–20 July 2018 Lower Atmospheric Profiling Studies at Elevation-A Remotely-Piloted Aircraft Team Experiment (LAPSE-RATE) field program. The simulations explicitly resolved phenomena (e.g., wind shift boundaries, vertical shear, strong thermals, turbulence in the boundary layer, fog, low ceilings and thunderstorms) that are potentially hazardous to small uncrewed aircraft system (UAS) operations. Details of the model configuration used to perform the simulations and the data-processing steps used to produce the final grids of state variables and other sensible weather products (e.g., ceiling and visibility, turbulence) are given. A nested (WRF) model configuration was used in which the innermost domain featured large-eddy-permitting 111 m grid spacing. The simulations, which were executed twice per day, were completed in under 6 h on the National Center for Atmospheric Research (NCAR) Cheyenne supercomputer using 59 cores (2124 processors). A few examples are provided to illustrate model skill at predicting fine-scale boundary layer structures and turbulence associated with drainage winds, up-valley flows and convective storm outflows. A subset of the data is available at the Zenodo data archive (https://zenodo.org/record/3706365#.X8VwZrd7mpo , Pinto et al., 2020b) while the full dataset is archived on the NCAR Digital Asset Services Hub (DASH) and may be obtained at 10.5065/83r2-0579 (Pinto et al., 2020a). [ABSTRACT FROM AUTHOR]

This dataset contains input parameters for 12 703 locations around the world to parameterize a stochastic weather generator called CLIGEN. The parameters are essentially monthly statistics relating to daily precipitation, temperature, and solar radiation. The dataset is separated into three sub-datasets differentiated by having monthly statistics determined from 30-, 20-, and 10-year record lengths. Input parameters related to precipitation were calculated primarily from the NOAA GHCN-Daily network. The remaining input parameters were calculated from various sources including global meteorological and land-surface models that are informed by remote sensing and other methods. The new CLIGEN dataset includes inputs for locations in the US, which were compared to a selection of stations from an existing US CLIGEN dataset representing 2648 locations. This validation showed reasonable agreement between the two datasets, with the majority of parameters showing less than 20 % discrepancy relative to the existing dataset. For the three new datasets, differentiated by the minimum record lengths used for calculations, the validation showed only a small increase in discrepancy going towards shorter record lengths, such that the average discrepancy for all parameters was greater by 5 % for the 10-year dataset. The new CLIGEN dataset has the potential to improve the spatial coverage of analysis for a variety of CLIGEN applications and reduce the effort needed in preparing climate inputs. The dataset is available at the National Agriculture Library Data Commons website at https://data.nal.usda.gov/dataset/international-climate-benchmarks-and-input-parameters-stochastic-weather-generator-cligen (last access: 20 November 2020) and 10.15482/USDA.ADC/1518706 (Fullhart et al., 2020a). [ABSTRACT FROM AUTHOR]

Unmanned aircraft systems (UASs) offer innovative capabilities for providing new perspectives on the atmosphere, and therefore atmospheric scientists are rapidly expanding their use, particularly for studying the planetary boundary layer. In support of this expansion, from 14 to 20 July 2018 the International Society for Atmospheric Research using Remotely piloted Aircraft (ISARRA) hosted a community flight week, dubbed the Lower Atmospheric Profiling Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE; de Boer et al., 2020a). This field campaign spanned a 1-week deployment to Colorado's San Luis Valley, involving over 100 students, scientists, engineers, pilots, and outreach coordinators. These groups conducted intensive field operations using unmanned aircraft and ground-based assets to develop comprehensive datasets spanning a variety of scientific objectives, including a total of nearly 1300 research flights totaling over 250 flight hours. This article introduces this campaign and lays the groundwork for a special issue on the LAPSE-RATE project. The remainder of the special issue provides detailed overviews of the datasets collected and the platforms used to collect them. All of the datasets covered by this special issue have been uploaded to a LAPSE-RATE community set up at the Zenodo data archive (https://zenodo.org/communities/lapse-rate/ , last access: 3 December 2020). [ABSTRACT FROM AUTHOR]

Model simulations of the Last Glacial Maximum (LGM; ∼ 21 000 years before present) can aid the interpretation of proxy records, can help to gain an improved mechanistic understanding of the LGM climate system, and are valuable for the evaluation of model performance in a different climate state. Ocean-ice only model configurations forced by prescribed atmospheric data (referred to as "forced ocean models") drastically reduce the computational cost of palaeoclimate modelling compared to fully coupled model frameworks. While feedbacks between the atmosphere and ocean and sea-ice compartments of the Earth system are not present in such model configurations, many scientific questions can be addressed with models of this type. Our dataset supports simulations of the LGM in a forced ocean model set-up while still taking advantage of the complexity of fully coupled model set-ups. The data presented here are derived from fully coupled palaeoclimate simulations of the Palaeoclimate Modelling Intercomparison Project phase 3 (PMIP3). The data are publicly accessible at the National Infrastructure for Research Data (NIRD) Research Data Archive at 10.11582/2020.00052 (Morée and Schwinger, 2020). They consist of 2-D anomaly forcing fields suitable for use in ocean models that employ a bulk forcing approach and are optimized for use with CORE forcing fields. The data include specific humidity, downwelling long-wave and short-wave radiation, precipitation, wind (v and u components), temperature, and sea surface salinity (SSS). All fields are provided as climatological mean anomalies between LGM and pre-industrial (PI) simulations. These anomaly data can therefore be added to any pre-industrial ocean forcing dataset in order to obtain forcing fields representative of LGM conditions as simulated by PMIP3 models. Furthermore, the dataset can be easily updated to reflect results from upcoming and future palaeo-model intercomparison activities. [ABSTRACT FROM AUTHOR]

Between 6 September 2016 and 15 October 2017, meteorological measurement flights were conducted above the German Bight in the framework of the project WIPAFF (Wind Park Far Field). The scope of the measurements was to study long-range wakes with an extent larger than 10 km behind entire wind parks, and to investigate the interaction of wind parks and the marine atmospheric boundary layer. The research aircraft Dornier 128 of the Technische Universität (TU) Braunschweig performed in total 41 measurement flights during different seasons and different stability conditions. The instrumentation consisted of a nose boom with sensors for measuring the wind vector, temperature and humidity, and additionally sensors for characterizing the water surface, a surface temperature sensor, a laser scanner and two cameras in the visible and infrared wavelength range. A detailed overview of the aircraft, sensors, data post-processing and flight patterns is provided here. Further, averaged profiles of atmospheric parameters illustrate the range of conditions. The potential use of the data set has been shown already by first publications. The data are publicly available in the world data centre PANGAEA (10.1594/PANGAEA.902845; Bärfuss et al., 2019a). [ABSTRACT FROM AUTHOR]

One of the challenges in globally consistent assessments of physical climate risks is the fact that asset exposure data are either unavailable or restricted to single countries or regions. We introduce a global high-resolution asset exposure dataset responding to this challenge. The data are produced using "lit population" (LitPop), a globally consistent methodology to disaggregate asset value data proportional to a combination of nightlight intensity and geographical population data. By combining nightlight and population data, unwanted artefacts such as blooming, saturation, and lack of detail are mitigated. Thus, the combination of both data types improves the spatial distribution of macroeconomic indicators. Due to the lack of reported subnational asset data, the disaggregation methodology cannot be validated for asset values. Therefore, we compare disaggregated gross domestic product (GDP) per subnational administrative region to reported gross regional product (GRP) values for evaluation. The comparison for 14 industrialized and newly industrialized countries shows that the disaggregation skill for GDP using nightlights or population data alone is not as high as using a combination of both data types. The advantages of LitPop are global consistency, scalability, openness, replicability, and low entry threshold. The open-source LitPop methodology and the publicly available asset exposure data offer value for manifold use cases, including globally consistent economic disaster risk assessments and climate change adaptation studies, especially for larger regions, yet at considerably high resolution. The code is published on GitHub as part of the open-source software CLIMADA (CLIMate ADAptation) and archived in the ETH Data Archive with the link 10.5905/ethz-1007-226 (Bresch et al., 2019b). The resulting asset exposure dataset for 224 countries is archived in the ETH Research Repository with the link 10.3929/ethz-b-000331316 (Eberenz et al., 2019). [ABSTRACT FROM AUTHOR]

Palaeoclimate data hold the unique promise of providing a long-term perspective on climate change and as such can serve as an important benchmark for climate models. However, palaeoclimate data have generally been archived with insufficient standardisation and metadata to allow for transparent and consistent uncertainty assessment in an automated way. Thanks to improved computation capacity, transient palaeoclimate simulations are now possible, calling for data products containing multi-parameter time series rather than information on a single parameter for a single time slice. Efforts are underway to simulate a complete glacial–interglacial cycle using general circulation models (https://www.palmod.de/ , last access: 6 May 2020), and to confront these simulations with palaeoclimate data, we have compiled a multi-parameter marine palaeoclimate data synthesis that contains time series spanning 0 to 130 000 years ago. We present the first version of the data product that focuses exclusively on time series for which a robust chronology based on benthic foraminifera δ18O and radiocarbon dating is available. The product contains 896 time series of eight palaeoclimate parameters from 143 individual sites, each associated with rich metadata, age–depth model ensembles, and information to refine and update the chronologies. This version contains 205 time series of benthic foraminifera δ18O ; 169 of benthic foraminifera δ13C ; 131 of seawater temperature; 174 and 119 of planktonic foraminifera δ18O and δ13C ; and 44, 38 and 16 of carbonate, organic carbon and biogenic silica content, respectively. The data product is available in three formats (R, LiPD and netCDF) facilitating use across different software and operating systems and can be downloaded at 10.1594/PANGAEA.908831 (Jonkers et al., 2019). This data descriptor presents our data synthesis strategy and describes the contents and format of the data product in detail. It ends with a set of recommendations for data archiving. [ABSTRACT FROM AUTHOR]