https://essd.copernicus.org/articles/ Combined list of the recent articles of the journal Earth System Science Data and the recent discussion forum Earth System Science Data Discussions en https://doi.org/10.5194/essd-18-2573-2026 Spatially distributed measurements of aerosols and stable isotopes in water vapour and precipitation in coastal Northern Norway during the ISLAS2021 campaign Alena Dekhtyareva, Harald Sodemann, Tim Carlsen, Iris Thurnherr, Aina Johannessen, Andrew Seidl, David M. Chandler, Daniele Zannoni, Alexandra Touzeau, Marvin Kähnert, Astrid B. Gjelsvik, Franziska Hellmuth, Britta Schäfer, and Robert O. David Earth Syst. Sci. Data, 18, 2573–2607, https://doi.org/10.5194/essd-18-2573-2026, 2026 During a recent field campaign from 15 to 30 March 2021 at Andenes, Norway, we collected a set of observations that allows to better constrain how clouds and precipitation processes work. Frequent alternations between mid-latitude and arctic weather systems were encountered during the campaign. Our dataset is unique in combining measurements in both vapour and precipitation, aerosols, ice nucleating particles, and was made simultaneously at different elevations at a high latitude location. Fri, 10 Apr 2026 23:09:31 +0200 https://doi.org/10.5194/essd-2026-232 OceanTACO: A Multi-Sensor Global Ocean Sea Surface State Dataset Nils Lehmann, Cesar Aybar, Ando Shah, Marcello Passaro, Jonathan L. Bamber, and Xiao Xiang Zhu Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-232,2026 Preprint under review for ESSD (discussion: open, 0 comments) We created a global ocean dataset that brings together satellite measurements, model outputs, and observations into one consistent system. We did this to reduce the time and effort needed to combine different data sources, to improve reproducibility, and enable new analyses. The result makes it easier to study ocean changes, compare methods, and support better understanding of climate processes and extreme events. Fri, 10 Apr 2026 23:09:31 +0200 https://doi.org/10.5194/essd-2026-99 The ICOS Ecosystem Station Loobos: a pine forest site exposed to atmospheric pollution Michiel K. van der Molen, Henk Snellen, Rupert Holzinger, Johannes G. M. Barten, Hong Zhao, Laurens Ganzeveld, Julie Fry, Wouter Peters, Maarten Krol, Jordi Vila-Guerau de Arrelano, and Bart Kruijt Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-99,2026 Preprint under review for ESSD (discussion: open, 0 comments) In 2021, a second tower was built in Loobos (NL-Loo) to measure carbon dioxide and water fluxes, as an Integrated Carbon Observing System (ICOS) Class 2 Ecosystem station. Instrumentation was installed to measure volatile organic compound and ozone fluxes. This paper describes the site’s geological and cultural history, ecosystem composition, instrumentation and ancillary ecosystem measurements. The paper goes into the quality of the measurements and continuity with respect to the first tower. Fri, 10 Apr 2026 23:09:31 +0200 https://doi.org/10.5194/essd-18-2549-2026 Differences in anthropogenic greenhouse gas emissions estimates explained William F. Lamb, Robbie M. Andrew, Matthew Jones, Zebedee Nicholls, Glen P. Peters, Chris Smith, Marielle Saunois, Giacomo Grassi, Julia Pongratz, Steven J. Smith, Francesco N. Tubiello, Monica Crippa, Matthew Gidden, Pierre Friedlingstein, Jan Minx, and Piers M. Forster Earth Syst. Sci. Data, 18, 2549–2572, https://doi.org/10.5194/essd-18-2549-2026, 2026 This study explores why global greenhouse gas (GHG) emissions estimates vary. Key reasons include different coverage of gases and sectors, varying definitions of anthropogenic land use change emissions, and the Paris Agreement not covering all emission sources. The study highlights three main ways emissions data is reported, each with different objectives and resulting in varying global emission totals. It emphasizes the need for transparency in choosing datasets and setting assessment scopes. Thu, 09 Apr 2026 23:09:31 +0200 https://doi.org/10.5194/essd-18-2507-2026 Soil information and soil property maps for the Kurdistan region, Dohuk governorate (Iraq) Mathias Bellat, Mjahid Zebari, Benjamin Glissmann, Tobias Rentschler, Paola Sconzo, Nafiseh Kakhani, Ruhollah Taghizadeh-Mehrjardi, Pegah Kohsravani, Bekas Brifkany, Peter Pfälzner, and Thomas Scholten Earth Syst. Sci. Data, 18, 2507–2548, https://doi.org/10.5194/essd-18-2507-2026, 2026 This dataset presents the first soil maps for the region produced using digital mapping techniques. It includes predictions for ten major physical and chemical soil properties at various depths, plus a map of total soil depth. For each property, we selected the most accurate models and key environmental drivers. In Southwestern Asia and many arid or semi-arid regions, detailed soil data are often missing. This dataset fills that gap, supporting agriculture, research, planning, and local policy. Thu, 09 Apr 2026 23:09:31 +0200 https://doi.org/10.5194/essd-2026-201 Towards a global database on building architecture and construction materials for urban climate models Lorena de Carvalho Araujo, Valéry Masson, Robert Schoetter, Jean Wurtz, Anouk Le Bihan, and Marion Bonhomme Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-201,2026 Preprint under review for ESSD (discussion: open, 0 comments) Urban populations are increasingly exposed to heat stress due to climate change and the urban heat island effect. Urban climate models require detailed data on building materials (e.g. roof cover material, insulation in walls) to simulate the meteorological impact on humans and infrastructure. This study presents an open database of residential building types by country that has been created based on a global survey of architects and urban climatologists. Wed, 08 Apr 2026 23:09:31 +0200 https://doi.org/10.5194/essd-2026-198 The Greenland GNSS Network (GNET): Geodetic Grade GNSS measurements of Greenland's 3D Bedrock Displacement from 1995–2025 Christian Solgaard, Finn Bo Madsen, Malte Winther-Dahl, Thomas Henry Nylen, Danjal Longfors Berg, Ole Bjerregaard, Javed Hassan, Per Knudsen, Michael Bevis, and Shfaqat Abbas Khan Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-198,2026 Preprint under review for ESSD (discussion: open, 0 comments) Greenland GNSS Network consist of more than 70 high grade GNSS (Global Navigation Satellite System) stations placed along the perimeter of Greenland. With this work, we present the processed position solution for the 20+ year record in a daily resolution. Along with the processed time series, we also publish the extensive metadata record for the network + all the raw data. A comparison with other subsets of the data showed an increased stability in the full processed dataset we here publish. Wed, 08 Apr 2026 23:09:31 +0200 https://doi.org/10.5194/essd-2025-841 Regional Oceanographic Database (BaRDO) for the Argentine Continental Shelf Ana G. Baldoni, Graciela N. Molinari, and Raul A. Guerrero Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-841,2026 Preprint under review for ESSD (discussion: open, 0 comments) This paper presents information on physical data collected over the past 47 years by INIDEP research vessels, primarily from the Argentine Continental Shelf. The main objective of this work is to provide access to this important dataset by describing the main characteristics of the instruments used over time, as well as the evolution of sampling, data processing, and quality-control procedures. Tue, 07 Apr 2026 23:09:31 +0200 https://doi.org/10.5194/essd-2025-811 Validation samples for the Land Cover Map of Europe 2017 Małgorzata Jenerowicz-Sanikowska, Elke Krätzschmar, Peter Schauer, Ewa Gromny, Radek Malinowski, Michał Krupiński, Stanisław Lewiński, Marcin Rybicki, and Cezary Wojtkowski Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-811,2026 Preprint under review for ESSD (discussion: open, 0 comments) We present the validation dataset created within the Sentinel-2 Global Land Cover project. Development of this dataset aimed at supporting accuracy assessment of pan-European database at both continental and country levels. The outcome was a large dataset composed of over 50,000 samples and 13 land cover/land use classes which represent different climatic regions and conditions. Tue, 07 Apr 2026 23:09:31 +0200 https://doi.org/10.5194/essd-2026-29 Fusing Local and Regional Datasets to Develop a Composite Land Cover Product Across High Latitudes Valeria Briones, Hélène Genet, Elchin Jafarov, Brendan Rogers, Jennifer Watts, Anna-Maria Virkkala, Annett Bartsch, Benjamin Maglio, Joshua Rady, and Susan Natali Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-29,2026 Preprint under review for ESSD (discussion: open, 0 comments) Rapid warming is reshaping Arctic landscapes as frozen ground thaws, affecting ecosystems and climate. To better understand these changes, we created a map showing the distribution of land types such as forests, shrubs, and wetlands across the Arctic and northern regions. We combined several existing maps using computer-based pattern recognition to develop a harmonized circumpolar land cover dataset that maps ecosystems across the Arctic–Boreal region at 1-km resolution for the period 2000–2023. Tue, 07 Apr 2026 23:09:31 +0200 https://doi.org/10.5194/essd-18-2469-2026 A first approach towards dual-hemisphere sea ice reference measurements from multiple data sources repurposed for evaluation and product intercomparison of satellite altimetry Ida Lundtorp Olsen, Henriette Skourup, Heidi Sallila, Stefan Hendricks, Renée Mie Fredensborg Hansen, Stefan Kern, Stephan Paul, Marion Bocquet, Sara Fleury, Dmitry Divine, and Eero Rinne Earth Syst. Sci. Data, 18, 2469–2505, https://doi.org/10.5194/essd-18-2469-2026, 2026 Discover the latest advancements in sea ice research with our comprehensive Climate Change Initiative (CCI) sea ice thickness (SIT) Round Robin Data Package (RRDP). This pioneering collection contains reference measurements from 1960 to 2024 from airborne sensors, buoys, visual observations and sonar and covers the polar regions from 1993 to 2024, providing crucial reference measurements for validating satellite-derived sea ice thickness. Thu, 02 Apr 2026 23:09:31 +0200 https://doi.org/10.5194/essd-18-2413-2026 NortheastChinaSoybeanYield20m: an annual soybean yield dataset at 20 m in Northeast China from 2019 to 2023 Jingyuan Xu, Xin Du, Taifeng Dong, Qiangzi Li, Yuan Zhang, Hongyan Wang, Jing Xiao, Jiashu Zhang, Yunqi Shen, and Yong Dong Earth Syst. Sci. Data, 18, 2413–2441, https://doi.org/10.5194/essd-18-2413-2026, 2026 This study proposed a 20 m soybean yield dataset in Northeast China (NortheastChinaSoybeanYield20m) from 2019 to 2023 using a hybrid framework coupling crop growth model with deep learning algorithm. Stable results were achieved through the years. The overall accuracy of the dataset was 287.44 and 272.36 kg ha–1 in the root mean squared error for field and regional scale, respectively. The study satisfied the urgent demands for precise control of crop yield information. Thu, 02 Apr 2026 23:09:31 +0200 https://doi.org/10.5194/essd-18-2179-2026 Australia's terrestrial industrial footprint and ecological intactness Ruben Venegas-Li, Scott Atkinson, Milton Aurelio Uba de Andrade Junior, Rachel Fletcher, Peter Owen, Lucia Morales-Barquero, Bora Aska, Miguel Arias-Patino, Hedley S. Grantham, Hugh Possingham, Oscar Venter, Michelle Ward, and James E. M. Watson Earth Syst. Sci. Data, 18, 2179–2201, https://doi.org/10.5194/essd-18-2179-2026, 2026 We developed two datasets representing human industrial pressures and ecological intactness across Australia´s landscapes. These datasets fill a long-standing gap in national-scale pressure mapping, providing key insights into human disturbance of the environment. They can support conservation planning, environmental policy, and restoration efforts, aligning with Australia’s Strategy for Nature and global biodiversity targets to protect intact ecosystems and promote sustainable development. Thu, 02 Apr 2026 23:09:31 +0200 https://doi.org/10.5194/essd-18-2443-2026 Reconstruction of δ13CDIC in the Atlantic Ocean: a probabilistic machine learning approach for filling historical data gaps Hui Gao, Zelun Wu, Zhentao Sun, Diana Cai, Meibing Jin, and Wei-Jun Cai Earth Syst. Sci. Data, 18, 2443–2467, https://doi.org/10.5194/essd-18-2443-2026, 2026 Observations of stable carbon isotopes in dissolved inorganic carbon are sparse, limiting their potential in carbon cycle studies. We compiled 51 cruises and used a machine learning method trained on 37 cruises that passed secondary quality control to reconstruct isotope values in the Atlantic. The reconstruction expands usable samples from 8,941 to 68,435, reducing noise, filling gaps, preserving decadal trend, and strengthening studies of carbon variability and model validation. Thu, 02 Apr 2026 23:09:31 +0200 https://doi.org/10.5194/essd-2026-215 PlanktoShare: A large (50k+) and FAIR learning set for the Plankton Imager (Pi-10) for the Greater North Sea and NE Atlantic, based on a new flexible classification protocol Lodewijk van Walraven, James Scott, Sophie Pitois, Joseph Ribeiro, Hayden Close, James Pettigrew, Cecilia M. Liszka, Elaine Fileman, Jeroen Hoekendijk, Pieter Hovenkamp, Robbert Jak, Joost van Dalen, and Dick van Oevelen Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-215,2026 Preprint under review for ESSD (discussion: open, 0 comments) PlanktoShare offers a large collection of carefully labelled plankton images collected using the Pi-10 Plankton Imager in the North-East Atlantic. It was created to overcome inconsistent naming across datasets and to support reliable classification. By standardizing taxonomic details and storing extra traits separately, the database enables sharing and combining learning sets. This helps expand global monitoring efforts and strengthens future plankton imaging research. Thu, 02 Apr 2026 23:09:31 +0200 https://doi.org/10.5194/essd-2026-107 Bridging the Data Gap: An Enhanced Global Inventory for Statistical Characterization and Hazard Assessment of Landslide Dams Xiangang Jiang, Guoqiang Xiao, Tao Wen, and Guang Yang Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-107,2026 Preprint under review for ESSD (discussion: open, 0 comments) Landslide dams pose serious flood risks, yet data on them remains scarce. To address this, we compiled a global database of 902 dams spanning the years 1800 to 2020. Our analysis reveals that the maximum water flow is strictly controlled by the width and depth of the breach channel. We found that deeper breaches drive significantly more intense floods than wider ones. This work aids in predicting floods and planning disaster relief. Thu, 02 Apr 2026 23:09:31 +0200 https://doi.org/10.5194/essd-2026-114 Extending the late 1963 to 1964 Mt Agung rescued searchlight aerosol profiles dataset at 32º N, from early 1963 to 1976 Juan Carlos Antuña-Marrero, Abel Calle, Juan Antonio Añel, Victoria E. Cachorro, Laura de la Torre, David Barriopedro, Ricardo García Herrera, and Javier Pacheco Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-114,2026 Preprint under review for ESSD (discussion: open, 1 comment) New rescued searchlight stratospheric aerosol profiles (SSAEP) at 32° N extent the recovered SAP from late 1963 to 1964 to early 1963 to 1976. It covers 1963 Agung and 1974 Fuego volcanic eruptions and background conditions in between. Early 1963 perturbed SSAEP challenges currently assumed northern hemisphere arrival in second half of 1963. The extended dataset will contribute to advance our limited knowledge and understanding of the Agung stratospheric aerosol transport. Thu, 02 Apr 2026 23:09:31 +0200 https://doi.org/10.5194/essd-18-2397-2026 A manually labeled contrail dataset from MSG/SEVIRI Vanessa Santos Gabriel, Luca Bugliaro, Mara Montag, Sabrina Ries, Ziming Wang, Kai Widmaier, Matteo Arico, Simon Unterstrasser, Johanna Mayer, Deniz Menekay, Andreas Marsing, Elena de la Torre Castro, Liam Megill, Monika Scheibe, and Christiane Voigt Earth Syst. Sci. Data, 18, 2397–2412, https://doi.org/10.5194/essd-18-2397-2026, 2026 We provide observations of the geostationary Meteosat satellite with contrails labeled by three people complemented with detailed cloud information. Contrails influence climate but are hard to identify in satellite imagery. With this study, we support contrail detection development and evaluation, stress the subjectivity of human labeling and reveal which meteorological conditions highlight or hide contrails. This dataset contributes to a better understanding of aviation’s climate impact. Wed, 01 Apr 2026 23:09:31 +0200 https://doi.org/10.5194/essd-2026-103 Daily Human Thermal Index Dataset for India (HiTIC-India) at 1-km Spatial Resolution (2003–2020) Subhransu Sekhar Gouda, Saket Dubey, Vrinda Kankanala, Jasinta Gera, and Sukeerthi Bharatha Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-103,2026 Preprint under review for ESSD (discussion: open, 0 comments) Extreme heat and cold affect health, work, and daily life across India, yet existing information on how people experience these conditions is often too coarse to reflect local variations. We created daily maps of 12 human thermal stress datasets for India from 2003 to 2020 using meteorological data and satellite information at 1 km resolution. The dataset reveals local patterns of heat and cold exposure and supports public health planning, urban design, and climate adaptation. Wed, 01 Apr 2026 23:09:31 +0200 https://doi.org/10.5194/essd-2026-179 Grounded Icebergs around Antarctica: A High-Resolution Dataset Derived from Deep Learning and Sentinel-1 Synthetic Aperture Radar Kaihong Jiao, Alexander D. Fraser, Johannes Lohse, Pat Wongpan, Caitlin Adams, and Alexander C. Bradley Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-179,2026 Preprint under review for ESSD (discussion: open, 0 comments) Grounded icebergs anchor Antarctic sea ice and support marine ecosystems, yet their continent-wide distribution was previously unknown. Using satellite radar imagery and an automated artificial intelligence tool, we mapped nearly 39,000 stationary icebergs. We discovered that tiny, frequently overlooked icebergs actually dominate both the total number and area. This public dataset offers a crucial new baseline for modelling coastal ice stability and understanding broader environmental changes. Wed, 01 Apr 2026 23:09:31 +0200