We investigate how mapping sea level in the Arctic Ocean can benefit from combining data from three satellite radar altimeters: CryoSat-2, Sentinel-3A and SARAL/AltiKa. A dedicated processing for SARAL/AltiKa provides a baseline for the cross-referencing of CryoSat-2 and Sentinel-3A before mapping. We show that by combining measurements coming from three missions, we are able to increase the resolution of gridded sea level fields in the ice-covered Arctic Ocean.

Water quality modeling is essential for understanding and mitigating water quality deterioration in river networks due to agricultural and industrial pollution. Improving the availability and usability of open data is vital to support global water quality modeling efforts. The GRQA extends the spatial and temporal coverage of previously available water quality data and provides a reproducible workflow for combining multi-source water quality datasets.

We present a dataset consisting of seismic waveforms and associated metadata to be used primarily for seismologically oriented machine-learning (ML) studies. The dataset includes about 1.3 M three-component seismograms of fixed 120 s length, sampled at 100 Hz and recorded by more than 600 stations in Italy. The dataset is subdivided into seismograms deriving from earthquakes (~ 1.2 M) and from seismic noise (~ 130 000). The ~ 54 000 earthquakes range in magnitude from 0 to 6.5 from 2005 to 2020.

The German research aircraft HALO took part in the research campaign EUREC⁴A in January and February 2020. The focus area was the tropical Atlantic east of the island of Barbados. We describe the characteristics of the 15 research flights, provide auxiliary information, derive combined cloud mask products from all instruments that observe clouds on board the aircraft, and provide code examples that help new users of the data to get started.

GLODAP is a data product for ocean inorganic carbon and related biogeochemical variables measured by the chemical analysis of water bottle samples from scientific cruises. GLODAPv2.2021 is the third update of GLODAPv2 from 2016. The data that are included have been subjected to extensive quality control, including systematic evaluation of measurement biases. This version contains data from 989 hydrographic cruises covering the world's oceans from 1972 to 2020.

CCAM is proposed to promote large-sample hydrological research in China. The first catchment attribute dataset and catchment-scale meteorological time series dataset in China are built. We also built HydroMLYR, a hydrological dataset with standardized streamflow observations supporting machine learning modeling. The open-source code producing CCAM supports the calculation of custom watersheds.

Plankton form the base of the marine food web and are sensitive indicators of environmental change. The Plankton Lifeform Extraction Tool brings together disparate plankton datasets into a central database from which it extracts abundance time series of plankton functional groups, called lifeforms, according to shared biological traits. This tool has been designed to make complex plankton datasets accessible and meaningful for policy, public interest, and scientific discovery.

Based on the gradient balance wind theory and the SABER observations, a dataset of monthly mean zonal wind has been developed at heights of 18–100 km and latitudes of 50° Sndash;50° N from 2002 to 2019. The dataset agrees with the zonal wind from models (MERRA2, UARP, HWM14) and observations by meteor radar and lidar at seven stations. The dataset can be used to study seasonal and interannual variations and can serve as a background for wave studies of tides and planetary waves.

BRAN2020 is a dynamical reconstruction of the ocean, combining observations with a high-resolution global ocean model. BRAN2020 currently spans January 1993 to December 2019, assimilating in situ temperature and salinity, as well as satellite-based sea level and sea surface temperature. A new multiscale approach to data assimilation constrains the broad-scale ocean properties and turbulent mesoscale dynamics in two steps, showing closer agreement to observations than all previous versions.

We created 30 m resolution annual irrigation maps covering the conterminous US for the period of 1997–2017, together with derivative products and ground reference data. The products have several improvements over other data, including field-level details of change and frequency, an annual time step, a collection of ~ 10 000 ground reference locations for the eastern US, and improved mapping accuracy of over 90 %, especially in the east compared to others of 50 % to 80 %.

High-quality long-term ozone profile data sets are key to estimating short- and long-term ozone variability. Almost all the satellite (and chemical model) data sets show some kind of bias with respect to each other. This is because of differences in measurement methodologies as well as simplified processes in the models. We use satellite data sets and chemical model output to generate 42 years of ozone profile data sets using a random-forest machine-learning algorithm that is named ML-TOMCAT.

A 10-year dataset of observation in the atmospheric boundary layer at Dome C on the high Antarctic plateau is presented. This is obtained with sensors at six levels along a tower higher than 40 m. The temperature inversion can reach more than 25 °C along the tower in winter, while full mixing by convection can occur in summer. Different amplitudes of variability for wind and temperature at the different levels reflect different signatures of solar vs. synoptic forcing of the boundary layer.

New estimates of population and land area by settlement types within low-elevation coastal zones (LECZs) based on four sources of population data, four sources of settlement data and four sources of elevation data for the years 1990, 2000 and 2015. The paper describes the sensitivity of these estimates and discusses the fitness of use guiding user decisions. Data choices impact the number of people estimated within LECZs, but across all sources the LECZs are predominantly urban and growing.

The Antarctic Precipitation System project deployed and maintained four sites across Antarctica from November 2017 to November 2019. The goals for the project included the collection of in situ observations of precipitation in Antarctica, an improvement in the understanding of precipitation in Antarctica, and the ability to validate precipitation data from atmospheric numerical models. The collected dataset represents some of the first year-round observations of precipitation in Antarctica.

High-frequency observatory data (50 Hz 3D wind velocity, 50 Hz temperature and 1 Hz PM₁₀) for studying the features of the fluid and dust field during sand and dust storms were presented. It is anticipated that data collected in this work will be of utility not only specifically for the boundary layer community in building a model for sand and dust storms but also broadly for communities studying the exchange of the dust and fluid field and energy transfer for the particle-laden two-phase flow.

Our database of globally distributed natural soil total P (STP) concentration showed concentration ranged from 1.4 to 9630.0 (mean 570.0) mg kg⁻¹. Global predictions of STP concentration increased with latitude. Global STP stocks (excluding Antarctica) were estimated to be 26.8 and 62.2 Pg in the topsoil and subsoil, respectively. Our global map of STP concentration can be used to constrain Earth system models representing the P cycle and to inform quantification of global soil P availability.

We present synthetic maps of continuous properties of seabed sediments in the Firth of Clyde, SW Scotland. The data include proportions of mud, sand, and gravel fractions; whole-sediment median grain size; permeability; porosity; organic carbon and nitrogen content; and rates of natural disturbance by tidal currents. We show that the firth stores 3.42 and 0.33 million tonnes of organic carbon and nitrogen, respectively, in the upper 10 cm of sediment.

Management of marine fisheries and ecosystems is limited by knowledge based on datasets which are short and recent. We recovered new long-term catch and size data for swordfish in the Mediterranean Sea. Our new data series cover the period 1896–2010, which predates most other Mediterranean swordfish datasets. The data allow scientists to investigate long-term effects of fishing and ocean–climate conditions on swordfish ecology in the Mediterranean Sea.

This study has combined three existing land evaporation (ET) products to obtain a single framework of a long-term (1980–2017) daily ET product at a spatial resolution of 0.25° to define the global proxy ET with lower uncertainties. The merged product is the best at capturing dynamics over different locations and times among all data sets. The merged product performed well over a range of vegetation cover scenarios and also captured the trend of land evaporation over different areas well.

The German polarimetric weather radar Poldirad was deployed for the international campaign EUREC⁴A on Barbados. The focus was monitoring clouds and precipitation in the trade wind region east of Barbados. Observations were with a temporal sequence of 5 min and a maximum range of 375 km. Examples of mesoscale precipitation patterns, rain rate accumulation, diurnal cycle, and vertical distribution show the potential for further studies on the life cycle of precipitating shallow cumulus clouds.

The Mediterranean Sea exhibits an anti-estuarine circulation, responsible for its low productivity. Understanding this peculiar character is still a challenge since there is no exact quantification of nutrient sinks and sources. Because nutrient in situ observations are generally infrequent and scattered in space and time, climatological mapping is often applied to sparse data in order to understand the biogeochemical state of the ocean. The dataset presented here partly addresses these issues.

This paper presents nine standardized crop type reference datasets collected between 2013 and 2020 in seven tropical countries. It aims at participating in the difficult exercise of mapping agricultural land use through satellite image classification in those complex areas where few ground truth or census data are available. These quality-controlled datasets were collected in the framework of the international JECAM initiative and contain 27 074 polygons documented by detailed keywords.

The accurate planting area and spatial distribution information is the basis for ensuring food security at continental scales. We constructed a paddy rice map database in Southeast and Northeast Asia for 3 years (2017–2019) at a 10 m spatial resolution. There are fewer mixed pixels in our paddy rice map. The large-scale and high-resolution maps of paddy rice are useful for water resource management and yield monitoring.