The Coastal Atmosphere and Sea Time Series (CoASTS) and Bio-Optical mapping of Marine Properties (BiOMaP) programs produced bio-optical data supporting satellite ocean color applications across European seas for almost 2 decades. CoASTS and BiOMaP applied equal standardized instruments, measurement methods, quality control schemes and processing codes to ensure temporal and spatial consistency with data products.

High-quality observations are crucial to understanding ocean oxygen changes and their impact on marine biota. We developed a quality control procedure to ensure the high quality of the heterogeneous ocean oxygen data archive and to prove data consistency. Oxygen data obtained by means of oxygen sensors on autonomous Argo floats were compared with reference data based on the chemical analysis, and estimates of the residual offsets were obtained.

This data review is about the reprocessing of historical eXpendable BathyThermograp (XBT) profiles from the Ligurian and Tyrrhenian seas over the time period 1999–2019. A new automated quality control analysis has been performed starting from the original raw data and operational log sheets. The data have been formatted and standardized according to the latest community best practices, and all available metadata have been inserted, including calibration information and uncertainty specification.

Gas exchange is fundamental to many biogeochemical processes in streams and depends on the degree of gas saturation and the gas transfer velocity (k). Currently, k is harder to measure than concentration. Here, we present a processing pipeline to estimate k from tracer-gas experiments conducted in 22 streams by the National Ecological Observatory Network. The processed dataset (n = 339) represents the largest compilation of standardized k estimates available.

We present a dataset of water vapor mixing ratio profiles acquired during the Water Vapor Lidar Network Assimilation campaign in fall and winter 2022 and summer 2023, using three lidar systems deployed on the western Mediterranean coastline. This innovative campaign provides access to lower-tropospheric water vapor variability to constrain meteorological forecasting models. The scientific objective is to improve forecasting of heavy-precipation events that lead to flash floods and landslides.

Quantifying water and CO₂ exchanges through transpiration, evaporation, net photosynthesis, and soil respiration is essential for understanding how ecosystems function. We implemented five methods to estimate these fluxes over a 5-year period across 47 sites. This is the first dataset representing such large spatial and temporal coverage of soil and plant exchanges, and it has many potential applications, such as examining the response of ecosystems to weather extremes and climate change.

The CAMELS-DE dataset features data from 1582 streamflow gauges across Germany, with records spanning from 1951 to 2020. This comprehensive dataset, which includes time series of up to 70 years (median 46 years), enables advanced research on water flow and environmental trends and supports the development of hydrological models.

This dataset provides, for the first time, combined observations of clouds and precipitation with coincident retrievals of atmospheric thermodynamics obtained from the same space-based instrument. Furthermore, it provides the locations of the ray trajectories of the observations along various precipitation-related products interpolated into them with the aim of fostering the use of such dataset in scientific and operational applications.

This paper provides a cross-shaped moored array dataset (MASCS 1.0) of observations that consist of five buoys and four moorings in the northern South China Sea from 2014 to 2015. The moored array is influenced by atmospheric forcings such as tropical cyclones and monsoon as well as oceanic tides and flows. The data reveal variations of the air–sea interface and the ocean itself, which are valuable for studies of air–sea interactions and ocean dynamics in the northern South China Sea.

Growing concern arises in the Arctic Ocean as toxic and harmful phytoplankton emerge due to climate change. The potential surge in these occurrences threatens both human health and the Arctic ecosystem. Our ongoing research yields insights into spatial patterns and biodiversity, challenging the belief that the Arctic is unsuitable for toxic and harmful algal events. This work underscores the need to comprehend and address the ecological impact of these emerging species in the Arctic environment.