In this study, carbon flux and auxiliary meteorological data are post-processed to create an analysis-ready dataset for 34 sites across six ecosystems in the Heihe River basin. Overall, 18 sites have multi-year observations, while 16 were observed only during the 2012 growing season, totaling 1513 site months. This dataset can be used to explore carbon exchange, assess ecosystem responses to climate change, support upscaling studies, and evaluate carbon cycle models.

Leaf inclination angle (LIA) is a vital trait in radiative transfer, rainfall interception, evapotranspiration, photosynthesis, and hydrological processes. However, global LIA knowledge is still lacking. This study generated the first global 500 m LIA products by gap-filling LIA measurement data. The global LIA is 41.47° ± 9.55° and increases with latitude. LIA products could enhance our understanding of global LIA and assist remote sensing retrieval and land surface modeling studies.

EEAR-Clim is a new and unprecedented observational dataset gathering in situ daily measurements of air temperature and precipitation from a network of about 9000 weather stations covering the European Alps. Data collected, including time series from recordings up to 2020 and time series significantly enhancing data coverage at high elevations, were tested for quality and homogeneity. The dataset aims to serve as a powerful tool for better understanding climate change over the European Alpine region.

The electric field in the Earth's atmosphere reflects global planetary conditions. It is influenced by both atmospheric processes (such as thunderstorms, pollution, and aerosols) and space weather. Marine measurements of the electric field are rare. Here, we present a unique dataset of atmospheric electric field measurements taken over the Atlantic Ocean. This dataset is valuable not only for atmospheric electricity studies but also for research on climate and space–Earth interactions.

This paper presents the first comprehensive dataset of 528 large dams in Italy. It contains structural characteristics of the dams, such as coordinates, reservoir surface areas and volumes, together with a range of geomorphological, climatological, extreme rainfall, land cover and soil-related attributes of their upstream catchments. 

We generate a daily sunshine duration dataset in China at a spatial resolution of 5 km using Himawari AHI data from 2016 to 2023 fitted with an Ångström–Prescott model at different days of year (DOYs). These high-resolution sunshine duration data provide important support for accurate radiation resource assessments in China.

A new reprocessed altimeter coastal sea level dataset, International Altimetry Service 2024 (IAS2024), for monitoring sea level changes along the world’s coastlines is presented. The evaluation and validation results confirm the reliability of this dataset. The altimeter-based virtual stations along the world’s coastlines can be built using this dataset to monitor the coastal sea level changes where tide gauges are unavailable. Therefore, it is beneficial for both oceanographic communities and policymakers.

This dataset covers 654 rivers all flowing in France. The provided time series and catchment attributes will be of interest to those modelers wishing to analyze hydrological behavior and perform model assessments.

Snow is an essential water resource in the intermountain western United States, and predictions are made using models. We made observations to validate, constrain, and develop the models. The data are from the Study of Precipitation, the Lower Atmosphere and Surface for Hydrometeorology (SPLASH) campaign in Colorado's East River valley, 2021–2023. The measurements include meteorology and variables that quantify energy transfer between the atmosphere and surface. The data are available publicly.

It is hard to access long-time series and high-resolution meteorological data for past years. In this paper, we propose the Geopotential-guided Attention Network (GeoAN) for downscaling which can produce high-resolution data using given low-resolution data. Quantitative and visual comparisons reveal our GeoAN produces better results with regard to most metrics. Using GeoAN, a historical meteorological dataset called MDG625 has been produced daily for the period since 1940.

Groundwater dynamics depend on groundwater recharge, but daily benchmark data of recharge are scarce. Here we present a daily groundwater recharge per unit specified yield (RpSy) data at 485 US groundwater monitoring wells. RpSy can be used to validate the temporal consistency of recharge products from land surface and hydrologic models and facilitate assessment of recharge-driver functional relationships in them.

Fallout radionuclides (FRNs) such as ¹³⁷Cs and ^239+240Pu are considered to be critical tools in various environmental research. Here, we compiled reference soil data on these FRNs from the literature to build a comprehensive database. Using this database, we determined the distribution and sources of ¹³⁷Cs and ^239+240Pu. We also demonstrated how the database can be used to identify the environmental factors that influence their distribution using a machine learning algorithm.

We developed a CAMELS-style dataset in Denmark, which contains hydrometeorological time series and landscape attributes for 3330 catchments (304 gauged). Many catchments in CAMELS-DK are small and at low elevations. The dataset provides information on groundwater characteristics and dynamics, as well as quantities related to the human impact on the hydrological system in Denmark. The dataset is especially relevant for developing data-driven and hybrid physically informed modeling frameworks.

After reviewing 2519 literature and media reports, we compiled the first comprehensive global dataset of 555 debris flow barrier dams (DFBDs) from 1800 to 2023. Our dataset meticulously documents 38 attributes of DFBDs, and we have utilized Google Earth for validation. Additionally, we discussed the applicability of landslide dam stability and peak-discharge models to DFBDs. This dataset offers a rich foundation of data for future studies on DFBDs.

To address key gaps in data availability and homogeneity with regard to sunshine duration, we compiled raw data and made a homogenization protocol to produce a homogenized daily observational dataset of sunshine duration from 1961 to 2022 in China. The dataset avoids a sharp drop in zero-value frequency after 2019 as caused by the instrument upgrade but is also more continuous for various periods. This dataset is crucial for accurately assessing dimming and brightening and for supporting other applications.

The Deep-Time Marine Sedimentary Element Database (DM-SED) expands upon the Sedimentary Geochemistry and Paleoenvironments Project (SGP) database, totalling 63 627 entries and covering major and trace elements and some stable isotopes in ancient marine sediments. This database is not only a significant reference for reconstructing Earth's system evolution but is also a valuable resource for studying palaeo-environments, palaeo-climates, and geochemical cycles.

We present glenglat, a database that contains measurements of ice temperature from 213 glaciers measured in 788 boreholes between 1842 and 2023. Even though ice temperature is a defining characteristic of any glacier, such measurements have been conducted on less than 1 ‰ of all glaciers globally. Our database permits us, for the first time, to investigate glacier temperature distributions at global or regional scales.

The availability of data from two airborne gravity campaigns using sensors based on both classical and quantum technology is presented. Data are made available by the European Space Agency as raw, intermediate, and final data products. Here “raw” refers to the sensor output, while “final” refers to the along-track gravity estimates. This makes the data relevant for users interested in applications ranging from data processing and quantum studies to geophysical studies using gravity observations.

We compiled a dataset of reflectance measurements for a variety of benthic macrophyte species and substrate types occurring naturally in the Baltic Sea. This dataset provides insights into the spectral properties of macrophyte species characteristic of the temperate geographic region. Such information is often lacking in the data format, while it is essential for developing remote sensing algorithms, classifying images, and defining requirements for future remote sensing missions.

Moored time series data are crucial for detecting changes in the ocean. However, mooring losses or instrument failures often result in data gaps. A gap-filled time series dataset of a shelf mooring array off the Western Australian coast is created using a machine learning tool to fill the data gaps. The gap-filled data show consistency with observations and can be used to characterize marine heat waves and cold spells influenced by ocean boundary currents.