The Gravity Recovery And Climate Experiment (GRACE) mission has greatly improved our understanding of changes in Earth's gravity field over time. A novel mass concentration (mascon) dataset, GCL-Mascon2024, was determined by leveraging the short-arc approach, advanced spatial constraints, a frequency-dependent noise processing strategy, and parameterization-integrating natural boundaries, aiming to enhance accuracy for monitoring mass transportation on Earth.

There is currently limited evidence about how land-based “natural flood management” measures affect soil properties. We therefore measured soil physical and hydraulic properties (n = 1300) at seven field sites (Thames catchment, UK). The sites cover a range of geologies, land use, and management. Dataset applications include hydrological and land surface modelling and validation of remote sensing observations. The dataset also provides a baseline against which future soil changes may be compared.

Climate change is deeply impacting mountain areas around the globe, especially in the Himalaya. Here, we present the Pyramid Meteorological Network, located in the Himalaya (Nepal) on the southern slopes of Mt. Everest. The network is composed of seven meteorological stations located between 2660 and 7986 m a.s.l., which collected continuous climatic data during 30 recent years (1994–2023). The dataset is freely accessible from https://zenodo.org/records/15211352 (Salerno et al., 2024).

We introduce the official ESA CCI Soil Moisture GAPFILLED climate data record. A univariate interpolation algorithm is applied to predict missing data points without relying on ancillary variables. The dataset includes gap-free uncertainty estimates for all predictions and was validated with independent in situ reference measurements. Our data record is recommended for applications which require global long-term gap-free satellite soil moisture data.

Surveys of global relief classes are important for understanding the morphology and land processes of Earth's surface. This study proposes a novel framework integrating the accumulated slope and a new surface relief index for global relief classification (GRC) with 1 arcsec resolution. This dataset can provide abundant and detailed land surface information for the field of Earth sciences.

Quantification of dust deposition into the broader Atlantic Ocean is provided, with the estimates established based on Earth observations. The dataset is considered unique with respect to a range of applications, including compensating for spatiotemporal gaps of sediment-trap measurements, assessments of model simulations, shedding light on physical processes related to the dust cycle, and improving the understanding of dust biogeochemical impacts on oceanic ecosystems, weather, and climate.

This study proposes a global-to-local approach for estimating forest height by fusing repeat-pass synthetic aperture radar interferometry and Global Ecosystem Dynamics Investigation (GEDI) data. Using Advanced Land Observing Satellite (ALOS-1) data and a twofold strategy to address temporal gaps, the method produced 30 m gridded forest height mosaics for the northeastern United States and China, demonstrating promising accuracies and offering potential for fusing data from future missions.

We created a new, publicly available, database of the top 50 most extreme European winter windstorms from each of four different meteorological input data sets covering the years 1995–2015. We found variability in all aspects of our database, from which storms were included in the top 50 storms for each input to the storms' spatial variability. We urge users of our database to consider the storms as identified from two or more input sources within our database where possible.

CLIMADAT-GRid is the first, publicly available, daily air temperature and precipitation gridded climate dataset for Greece at a high resolution of 1 km × 1 km and for the period 1981–2019. The dataset is based on quality-controlled station data, and various interpolation techniques were evaluated for generating the daily grids. CLIMADAT-GRid serves as a valuable resource for research and information in climate studies as well as in other areas such as hydrology, agriculture, energy, and health.

Site-level metadata from 328 paleoecological study sites in South Korea, compiled from 66 papers (2003–2023), address regional gaps in data availability in recent global syntheses. The dataset reflects various depositional environments studied over two decades with multi-proxy approaches and regional collaborations. The GeoEcoKorea online platform, developed alongside this dataset, aims to enhance the accessibility of Korean paleodata and promote FAIR (findable, accessible, interoperable, and reusable) data sharing among researchers.

This article presents the first open-access dataset of wild short-beaked common dolphin recordings. It was collected at sea in the Bay of Biscay (France) and comprises audio recordings of echolocation clicks, whistles, and other social sounds as well as visual observations of dolphin behaviour. This dataset could be used to improve the comprehension of dolphin communication by scientists, which could assist in the development of conservation strategies, particularly with regard to by-catches.

The objective of this study is to rescue and integrate historical data from eight pioneering geomagnetic observatories in China. Data quality is significantly improved through integration. The integrated dataset is now publicly available for easy access and use by the academic community and the public. These datasets are of great significance for optimizing historical geomagnetic field models and investigating changing magnetic fields, the main geomagnetic field.

Following a seismic crisis in May 2018 in Mayotte, an observation network has been created with the given objective of monitoring the volcanic phenomena. A SeaExplorer glider has been deployed to supplement the data obtained during a series of oceanographic surveys. The glider performed a continuous monitoring over 30 months of the water column from the sea surface to 1250 m water depth, with the objective of acquiring the hydrological properties, water currents and dissolved gas concentrations.

Methane and carbon dioxide emission rates were calculated for facilities across several sectors in New York State using aerial observations. Of the sampled facilities, landfills dominated the methane emission rates, while combustion facilities had the highest carbon dioxide emission rates, followed by landfills. The self-reported Environmental Protection Agency (EPA) inventory mostly underestimates landfill methane emissions, apart from a few facilities with comparable numbers.

Meteorological reanalyses are crucial datasets. Most reanalyses are Eulerian, providing data at specific, fixed points in space and time. When studying how air moves, it is more convenient to follow air masses through space and time, requiring a Lagrangian Reanalysis (LARA). We explain how the LARA dataset is organised and provide four examples of applications. These include studying the evolution of wind patterns, understanding weather systems, and measuring air mass travel time over land.

Our study created a high-resolution soil moisture dataset for the eastern US by integrating satellite data with a land surface model and advanced algorithms, achieving 1 km scale analyses. Validated against multiple in situ networks and analysis datasets, it demonstrated superior accuracy. This dataset is vital for understanding soil moisture dynamics, especially during droughts, and highlights the need to mitigate soil-type-dependent biases in the model.

Large-sample datasets are essential in hydrological science to support modelling studies and advance process understanding. Caravan is a community initiative to create a large-sample hydrology dataset of meteorological forcing data, catchment attributes and discharge data for catchments around the world. This dataset is a subset of hydrological discharge data and station-based watersheds from the Global Runoff Data Centre (GRDC), which are covered by an open data policy.

We developed a new global dataset of nitrogen dioxide (NO₂) levels in the lower atmosphere, using data from TROPOMI for 2018–2021. This dataset offers improved accuracy and detail compared to earlier versions, meeting high international standards for climate data. By refining how measurement errors are calculated and reduced over time and space, we provide clearer insights into pollution patterns. This work supports better air quality monitoring and informs actions to address pollution globally.

This study presents a climate data record (CDR) of atmospheric column water vapor and sea surface temperature using over two decades of stable-orbit satellite-based passive microwave imagery observations. The evaluation results show that the CDR has long-term consistency and continuity, and is more accurate than other similar products in climate covariability, suggesting that the CDR is suitable for climate change research and for constraining climate model simulations.

Karst phenomena arise through dissolution, and the resulting landscapes are characterised by caves which focus the transport of water underground. To better understand geometry of these conduits at various scales, we mapped caves with laser scanners and built models of the walls to constitute the KarstConduitCatalogue. These mapping techniques allow us to measure cave geometries accurately. This paper describes how we acquired and curated the dataset and explores possible geoscientific uses.

We introduce China's first de-aliasing computation platform, incorporating China's Atmospheric Reanalysis and an in-house ocean circulation model. This platform produces CRA-LICOM, a high-frequency atmospheric and oceanic gravity de-aliasing product with a 6-hourly, 50 km resolution covering 2002–2024 globally. This product is reliable for de-aliasing, signal separation in satellite gravity missions, and climate change studies.