In this work, we describe WALIS, the World Atlas of Last Interglacial Shorelines. WALIS is a sea-level database that includes sea-level proxies and samples dated to marine isotope stage 5 (~ 80 to 130 ka). The database was built through topical data compilations included in a special issue in this journal.

The TiP-Leaf dataset was compiled from direct field measurements and included 11 leaf traits from 468 species of 1692 individuals, covering a great proportion of species and vegetation types on the highest plateau in the world. This work is the first plant trait dataset that represents all of the alpine vegetation on the TP, which is not only an update of the Chinese plant trait database, but also a great contribution to the global trait database.

Antiarch placoderms, the most basal jawed vertebrates, have the potential to enlighten the origin of the last common ancestor of jawed vertebrates during the Paleozoic. This dataset, which was extracted manually from 142 published papers or books from 1939 to 2021, consists of 60 genera of 6025 specimens from the Ludfordian to the Famennian, covering all antiarch lineages. We transferred the unstructured data from the literature to structured data for further detailed research.

This paper reports on the main findings of a large measurement campaign aiming to better understand how an exposed estuary (the Ems Estuary on the Dutch–German border) interacts with a tidal river (the lower Ems River). Eight simultaneously deployed ships measuring a tidal cycle and 10 moorings collecting data throughout a spring–neap tidal cycle have produced a dataset providing valuable insight into processes determining exchange of water and sediment between the two systems.

Sulfur dioxide (SO₂) measurements from three satellite instruments were used to update and extend the previously developed global catalogue of large SO₂ emission sources. This version 2 of the global catalogue covers the period of 2005–2021 and includes a total of 759 continuously emitting point sources. The catalogue data show an approximate 50 % decline in global SO₂ emissions between 2005 and 2021, although emissions were relatively stable during the last 3 years.

The objective of this study is present the first gridded and temporally continuous quantitative plant-cover reconstruction for temperate and northern subtropical China over the last 12 millennia. The reconstructions are based on 94 pollen records and include estimates for 27 plant taxa, 10 plant functional types, and 3 land-cover types. The dataset is suitable for palaeoclimate modelling and the evaluation of simulated past vegetation cover and anthropogenic land-cover change from models.

Multimodal data fusion is an intuitive strategy to break the limitation of individual data in Earth observation. Here, we present a multimodal data set, named MDAS, consisting of synthetic aperture radar (SAR), multispectral, hyperspectral, digital surface model (DSM), and geographic information system (GIS) data for the city of Augsburg, Germany, along with baseline models for resolution enhancement, spectral unmixing, and land cover classification, three typical remote sensing applications.

Rapid Arctic changes are increasingly influencing human society, both locally and globally. Land cover offers a basis for characterizing the terrestrial world, yet spatially detailed information on Arctic land cover is lacking. We employ multi-source data to develop a new land cover map for the circumpolar Arctic. Our product reveals regionally contrasting biome distributions not fully documented in existing studies and thus enhances our understanding of the Arctic’s terrestrial system.

The mean sea surface (MSS) is a relative steady-state sea level within a finite period with important applications in geodesy, oceanography, and other disciplines. In this study, the Shandong University of Science and Technology 2020 (SDUST2020), a new global MSS model, was established with a 19-year moving average method from multi-satellite altimetry data. Its global coverage is from 80 °S to 84 °N, the grid size is 1'×1', and the reference period is from January 1993 to December 2019.

Much effort is made to project monsoon changes by reconstructing the past. The stable oxygen isotopic ratio of marine calcareous organisms is frequently used to reconstruct past monsoons. Here, we use the published and new stable oxygen isotopic data to demonstrate a diagenetic effect and a strong salinity influence on the oxygen isotopic ratio of foraminifera in the northern Indian Ocean. We also provide updated calibration equations to deduce monsoons from the oxygen isotopic ratio.

We explored the performance of the random forest algorithm to predict CO, NO_x, PM₁₀, SO₂, and O₃ air quality concentrations and comparatively assessed the monitored and modeled concentrations during the COVID-19 lockdown phases. We provide the first long-term O₃ and SO₂ observational dataset for an urban–residential area of Buenos Aires in more than a decade and study the responses of O₃ to the reduction in the emissions of its precursors because of its relevance regarding emission control.

We present a database of Southern Ocean macronutrient, temperature and salinity measurements collected on 20 oceanographic cruises between 1980 and 2009. Vertical profiles and underway surface measurements were collected year-round as part of an integrated ecosystem study. Our data provide a novel view of biogeochemical cycling in biologically productive regions across a critical period in recent climate history and will contribute to a better understanding of the drivers of primary production.

This paper presents a new satellite-derived gridded dataset, including 10 years of sea surface height and geostrophic velocity at monthly resolution, over the Arctic ice-covered and ice-free regions, up to 88° N. We assess the dataset by comparison to independent satellite and mooring data. Results correlate well with independent satellite data at monthly timescales, and the geostrophic velocity fields can resolve seasonal to interannual variability of boundary currents wider than about 50 km.

An accurate global 30 m wetland dataset that can simultaneously cover inland and coastal zones is lacking. This study proposes a novel method for wetland mapping and generates the first global 30 m wetland map with a fine classification system (GWL_FCS30), including five inland wetland sub-categories (permanent water, swamp, marsh, flooded flat and saline) and three coastal wetland sub-categories (mangrove, salt marsh and tidal flats).

We present a new gridded sea surface height and current dataset produced by combining observations from nadir altimeters and drifting buoys. This product is based on a multiscale and multivariate mapping approach that offers the possibility to improve the physical content of gridded products by combining the data from various platforms and resolving a broader spectrum of ocean surface dynamic than in the current operational mapping system. A quality assessment of this new product is presented.

AI4boundaries is an open AI-ready data set to map field boundaries with Sentinel-2 and aerial photography provided with harmonised labels covering seven countries and 2.5 M parcels in Europe.

To enrich a glacial surface air temperature (SAT) product of a long time series, an ensemble learning model is constructed to estimate monthly SATs from satellite land surface temperatures at a spatial resolution of 1 km, and long-term glacial SATs from 1961 to 2020 are reconstructed using a Bayesian linear regression. This product reveals the overall warming trend and the spatial heterogeneity of warming on TP glaciers and helps to monitor glacier warming, analyze glacier evolution, etc.

The AnisoVeg dataset brings 22 years of monthly satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor for South America at 1 km resolution aimed at vegetation applications. It has nadir-normalized data, which is the most traditional approach to correct satellite data but also unique anisotropy data with strong biophysical meaning, explaining 55 % of Amazon forest height. We expect this dataset to help large-scale estimates of vegetation biomass and carbon.

We generate the first monthly high-resolution (1 km) human thermal index collection (HiTIC-Monthly) in China over 2003–2020, in which 12 human-perceived temperature indices are generated by LightGBM. The HiTIC-Monthly dataset has a high accuracy (R² = 0.996, RMSE = 0.693 °C, MAE = 0.512 °C) and describes explicit spatial variations for fine-scale studies. It is freely available at https://zenodo.org/record/6895533 and https://data.tpdc.ac.cn/disallow/036e67b7-7a3a-4229-956f-40b8cd11871d.

This article describes the instrument bias in the raw Argo salinity data from 2000 to 2021. The main cause of this bias is sensor drift. Using Argo data without filtering out this instrument bias has been shown to lead to spurious results in various scientific applications. We describe the Argo delayed-mode process that evaluates and adjusts such instrument bias, and we estimate the uncertainty of the Argo delayed-mode salinity dataset. The best ways to use Argo data are illustrated.

We generated a 1 km daily soil moisture dataset for dryland wheat and maize across China (ChinaCropSM1 km) over 1993–2018 through random forest regression, based on in situ observations. Our improved products have a remarkably better quality compared with the public global products in terms of both spatial and time dimensions by integrating an irrigation module (crop type, phenology, soil depth). The dataset may be useful for agriculture drought monitoring and crop yield forecasting studies.

Here we construct a new database of Antarctic automatic weather station (AWS) meteorological records, which is quality-controlled by restrictive criteria. This dataset compiled all available Antarctic AWS observations, and its resolutions are 3-hourly, daily and monthly, which is very useful for quantifying spatiotemporal variability in weather conditions. Furthermore, this compilation will be used to estimate the performance of the regional climate models or meteorological reanalysis products.

The global need for updated soil datasets has increased. Our main objective was to synthesize and harmonize soil profile information collected by two different projects in Ecuador between 2009 and 2015.The main result was the development of the Harmonized Soil Database of Ecuador (HESD) that includes information from 13 542 soil profiles with over 51 713 measured soil horizons, including 92 different edaphic variables, and follows international standards for archiving and sharing soil data.

Thaw slumps and thermo-erosion gullies are cryospheric hazards that are widely encountered in Nordenskiöld Land, the largest and most compact ice-free area of the Svalbard Archipelago. By statistically analysing the landscape characteristics of locations where these processes occurred, we can estimate where they may occur in the future. We mapped 562 thaw slumps and 908 thermo-erosion gullies and used them to create the first multi-hazard susceptibility map in a high-Arctic environment.

One of the novel ways EUREC⁴A set out to investigate trade wind clouds and their coupling to the large-scale circulation was through an extensive network of isotopic measurements in water vapor, precipitation, and seawater. Samples were taken from the island of Barbados, from aboard two aircraft, and from aboard four ships. This paper describes the full collection of EUREC4A isotopic in situ data and guides readers to complementary remotely sensed water vapor isotope ratios.

We produced a reanalysis of GNSS data near tide gauges worldwide within the International GNSS Service. It implements advances in data modelling and corrections, extending the record length by about 7 years. A 28 % reduction in station velocity uncertainties is achieved over the previous solution. These estimates of vertical land motion at the coast supplement data from satellite altimetry or tide gauges for an improved understanding of sea level changes and their impacts along coastal areas.

Seagrasses are important underwater plants that provide valuable ecosystem services to humans, including mitigating climate change. Understanding the natural history of seagrass meadows across different types of environments is crucial to conserving seagrasses in the global ocean. This dataset contains data extracted from peer-reviewed publications and highlights which seagrasses have been studied and in which locations and is useful for pointing out which need further investigation.