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Brazilian Atmospheric Inventories – BRAIN: a comprehensive database of air quality in Brazil Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-05-16 Leonardo Hoinaski, Robson Will, Camilo Bastos Ribeiro
Abstract. Developing air quality management systems to control the impacts of air pollution requires reliable data. However, current initiatives do not provide datasets with large spatial and temporal resolutions for developing air pollution policies in Brazil. Here, we introduce the Brazilian Atmospheric Inventories (BRAIN), the first comprehensive database of air quality and its drivers in Brazil
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European topsoil bulk density and organic carbon stock database (0–20 cm) using machine-learning-based pedotransfer functions Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-05-16 Songchao Chen, Zhongxing Chen, Xianglin Zhang, Zhongkui Luo, Calogero Schillaci, Dominique Arrouays, Anne Christine Richer-de-Forges, Zhou Shi
Abstract. Soil bulk density (BD) serves as a fundamental indicator of soil health and quality, exerting a significant influence on critical factors such as plant growth, nutrient availability, and water retention. Due to its limited availability in soil databases, the application of pedotransfer functions (PTFs) has emerged as a potent tool for predicting BD using other easily measurable soil properties
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Two sets of bias-corrected regional UK Climate Projections 2018 (UKCP18) of temperature, precipitation and potential evapotranspiration for Great Britain Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-05-16 Nele Reyniers, Qianyu Zha, Nans Addor, Timothy J. Osborn, Nicole Forstenhäusler, Yi He
Abstract. The United Kingdom Climate Projections 2018 (UKCP18) regional climate model (RCM) 12 km regional perturbed physics ensemble (UKCP18-RCM-PPE) is one of the three strands of the latest set of UK national climate projections produced by the UK Met Office. It has been widely adopted in climate impact assessment. In this study, we report biases in the raw UKCP18-RCM simulations that are significant
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Evapotranspiration evaluation using three different protocols on a large green roof in the greater Paris area Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-05-15 Pierre-Antoine Versini, Leydy Alejandra Castellanos-Diaz, David Ramier, Ioulia Tchiguirinskaia
Abstract. Nature-based solutions have appeared as relevant solutions to mitigate urban heat islands. To improve our knowledge of the assessment of this ecosystem service and the related physical processes (evapotranspiration), monitoring campaigns are required. This was the objective of several experiments carried out on the Blue Green Wave, a large green roof located in Champs-sur-Marne (France).
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Water vapor Raman-lidar observations from multiple sites in the framework of WaLiNeAs Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-05-15 Frédéric Laly, Patrick Chazette, Julien Totems, Jérémy Lagarrigue, Laurent Forges, Cyrille Flamant
Abstract. During the Water Vapor Lidar Network Assimilation (WaLiNeAs) campaign, 8 lidars specifically designed to measure water vapor mixing ratio (WVMR) profiles were deployed on the western Mediterranean coast. The main objectives were to investigate the water vapor content during case studies of heavy precipitation events in the coastal Western Mediterranean and assess the impact of high spatio-temporal
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A global monthly field of seawater pH over 3 decades: a machine learning approach Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-05-15 Guorong Zhong, Xuegang Li, Jinming Song, Baoxiao Qu, Fan Wang, Yanjun Wang, Bin Zhang, Lijing Cheng, Jun Ma, Huamao Yuan, Liqin Duan, Ning Li, Qidong Wang, Jianwei Xing, Jiajia Dai
Abstract. The continuous uptake of anthropogenic CO2 by the ocean leads to ocean acidification, which is an ongoing threat to the marine ecosystem. The ocean acidification rate was globally documented in the surface ocean but limited below the surface. Here, we present a monthly four-dimensional 1°×1° gridded product of global seawater pH, derived from a machine learning algorithm trained on pH observations
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A 10 km daily-level ultraviolet radiation predicting dataset based on machine learning models in China from 2005 to 2020 Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-05-15 Yichen Jiang, Su Shi, Xinyue Li, Chang Xu, Haidong Kan, Bo Hu, Xia Meng
Abstract. Ultraviolet (UV) radiation is closely related to health, but limited measurements hindered further investigation of its health effects in China. Machine learning algorithm has been widely used in predicting environmental factors with high accuracy, but limited studies have done for UV radiation. This study aimed to develop UV radiation prediction model based on random forest method, and predict
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Retrieving Ground-Level PM2.5 Concentrations in China (2013–2021) with a Numerical Model-Informed Testbed to Mitigate Sample Imbalance-Induced Biases Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-05-15 Siwei Li, Yu Ding, Jia Xing, Joshua S. Fu
Abstract. Ground-level PM2.5 data derived from satellites with machine learning are crucial for health and climate assessments, however, uncertainties persist due to the absence of spatially covered observations. To address this, we propose a novel testbed using untraditional numerical simulations to evaluate PM2.5 estimation across the entire spatial domain. The testbed emulates the general machine-learning
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Global mapping of oil palm planting year from 1990 to 2021 Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-05-15 Adrià Descals, David L. A. Gaveau, Serge Wich, Zoltan Szantoi, Erik Meijaard
Abstract. Oil palm is a controversial crop, primarily because it is associated with negative environmental impacts such as tropical deforestation. Mapping the crop and its characteristics, such as age, is crucial for informing public and policy discussions regarding these impacts. Oil palm has received substantial mapping efforts, but up-to-date accurate oil palm maps for both extent and age are essential
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A consistent dataset for the net income distribution for 190 countries and aggregated to 32 geographical regions from 1958 to 2015 Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-05-14 Kanishka B. Narayan, Brian C. O'Neill, Stephanie Waldhoff, Claudia Tebaldi
Abstract. Data on income distributions within and across countries are becoming increasingly important for informing analysis of income inequality and understanding the distributional consequences of climate change. While datasets on income distribution collected from household surveys are available for multiple countries, these datasets often do not represent the same concept of inequality (or income
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Multiwavelength, aerosol lidars at Maïdo supersite, Reunion Island, France: instruments description, data processing chain and quality assessment Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-05-14 Dominique Gantois, Guillaume Payen, Michaël Sicard, Valentin Duflot, Nicolas Marquestaut, Thierry Portafaix, Sophie Godin-Beekmann, Patrick Hernandez, Eric Golubic
Abstract. Understanding optical and radiative properties of aerosols and clouds is critical to reduce uncertainties in climate models. For over 10 years, the Observatory of Atmospheric Physics of La Réunion (OPAR) has been operating three active lidar instruments (named Li1200, LiO3S and LiO3T) providing time-series of vertical profiles from 3 to 45 km of the aerosol extinction and backscatter coefficients
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A Global Daily High Spatial-temporal Coverage Merged Tropospheric NO2 dataset (HSTCM-NO2) from 2007 to 2022 based on OMI and GOME-2 Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-05-14 Kai Qin, Hongrui Gao, Xuancen Liu, Qin He, Jason Blake Cohen
Abstract. Remote sensing based on satellites can provide long-term, consistent, and global coverage of NO2 (an important atmospheric air pollutant) as well as other trace gases. However, satellite data often miss data due to factors including but not limited to clouds, surface features, and aerosols. Moreover, one of the longest continuous observational platforms of NO2 observations from space, OMI
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Spatio-Temporal Changes in China’s Mainland Shorelines Over 30 Years Using Landsat Time Series Data (1990–2019) Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-05-14 Gang Yang, Ke Huang, Lin Zhu, Weiwei Sun, Chao Chen, Xiangchao Meng, Lihua Wang, Yong Ge
Abstract. Continuous monitoring of shoreline dynamics is essential to understanding the drivers of shoreline changes and evolution. A long-term shoreline dataset can describe the dynamic changes in the spatio-temporal dimension and provide information on the influence of anthropogenic activities and natural factors on coastal areas. This study, conducted on the Google Earth Engine platform, analyzed
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Predictive mapping of organic carbon stocks in surficial sediments of the Canadian continental margin Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-05-13 Graham Epstein, Susanna D. Fuller, Dipti Hingmire, Paul G. Myers, Angelica Peña, Clark Pennelly, Julia K. Baum
Abstract. Quantification and mapping of surficial seabed sediment organic carbon have wide-scale relevance for marine ecology, geology and environmental resource management, with carbon densities and accumulation rates being a major indicator of geological history, ecological function and ecosystem service provisioning, including the potential to contribute to nature-based climate change mitigation
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The SDUST2022GRA global marine gravity anomalies recovered from radar and laser altimeter data: Contribution of ICESat-2 laser altimetry Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-05-13 Zhen Li, Jinyun Guo, Chengcheng Zhu, Xin Liu, Cheinway Hwang, Sergey Lebedev, Xiaotao Chang, Anatoly Soloviev, Heping Sun
Abstract. Global marine gravity anomaly models are predominantly recovered from along-track radar altimeter data. While remarkable advancements has been achieved in gravity anomaly modelling, the quality of gravity anomaly model remains constrained by the absence of across-track geoid gradients and the reduction of radar altimeter data, particularly in coastal and high-latitudes regions. ICESat-2 laser
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Indicators of Global Climate Change 2023: annual update of key indicators of the state of the climate system and human influence Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-05-08 Piers M. Forster, Chris Smith, Tristram Walsh, William Lamb, Robin Lamboll, Bradley Hall, Mathias Hauser, Aurélien Ribes, Debbie Rosen, Nathan Gillett, Matthew D. Palmer, Joeri Rogelj, Karina von Schuckmann, Blair Trewin, Myles Allen, Robbie Andrew, Richard Betts, Tim Boyer, Carlo Buontempo, Samantha Burgess, Chiara Cagnazzo, Lijing Cheng, Pierre Friedlingstein, Andrew Gettelman, Johannes Gütschow
Abstract. Intergovernmental Panel on Climate Change (IPCC) assessments are the trusted source of scientific evidence for climate negotiations taking place under the United Nations Framework Convention on Climate Change (UNFCCC). Evidence-based decision-making needs to be informed by up-to-date and timely information on key indicators of the state of the climate system and of the human influence on
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Oceanographic monitoring in Hornsund fjord, Svalbard Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-05-08 Meri Korhonen, Mateusz Moskalik, Oskar Głowacki, Vineet Jain
Abstract. Several climate-driven processes take place in the Arctic fjords. These include ice-ocean interactions, changes in biodiversity and ocean circulation patterns, as well as coastal erosion phenomena. Conducting long-term oceanographic monitoring in the Arctic fjords is, therefore, essential for better understanding and predicting global environmental shifts. Here we address this issue by introducing
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Reanalysis of multi-year high-resolution X-band weather radar observations in Hamburg Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-05-07 Finn Burgemeister, Marco Clemens, Felix Ament
Abstract. This paper presents an open-access data set of reanalysed radar reflectivities and rainfall rates at sub-kilometre spatial and minute temporal scales. Variability at these scales is a blind spot for both operational rain gauge networks and operational radar networks. In the urban area of Hamburg, precipitation measurements of a single-polarized X-band weather radar operating at high temporal
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Multi-year high time resolution measurements of fine PM at 13 sites of the French Operational Network (CARA program): Data processing and chemical composition Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-05-07 Hasna Chebaicheb, Joel F. de Brito, Tanguy Amodeo, Florian Couvidat, Jean-Eudes Petit, Emmanuel Tison, Gregory Abbou, Alexia Baudic, Mélodie Chatain, Benjamin Chazeau, Nicolas Marchand, Raphaele Falhun, Florie Francony, Cyril Ratier, Didier Grenier, Romain Vidaud, Shouwen Zhang, Gregory Gille, Laurent Meunier, Caroline Marchand, Véronique Riffault, Olivier Favez
Abstract. This paper presents a first comprehensive analysis of long-term measurements of atmospheric aerosol components from Aerosol Chemical Speciation Monitor (ACSM) and multi-wavelength Aethalometer (AE33) instruments collected between 2015 and 2021 at 13 (sub)urban sites as part of the French CARA program. The datasets contain the mass concentrations of major chemical species within PM1, namely
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Coral Skeletal Proxy Records Database for the Great Barrier Reef, Australia Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-05-07 Ariella Kathleen Arzey, Helen V. McGregor, Tara R. Clark, Jody M. Webster, Stephen E. Lewis, Jennie Mallela, Nicholas P. McKay, Hugo W. Fahey, Supriyo Chakraborty, Tries B. Razak, Matt J. Fischer
Abstract. The Great Barrier Reef (GBR), Australia has a long history of palaeoenvironmental coral research. However, it can be logistically difficult to find the relevant research and records, which are often unpublished or exist as ‘grey literature’. This hinders researchers’ ability to efficiently assess the current state of coral core studies on the GBR and thus identify any key knowledge gaps.
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A 30 m annual cropland dataset of China from 1986 to 2021 Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-05-06 Ying Tu, Shengbiao Wu, Bin Chen, Qihao Weng, Yuqi Bai, Jun Yang, Le Yu, Bing Xu
Abstract. Accurate, detailed, and up-to-date information on cropland extent is crucial for provisioning food security and environmental sustainability. However, because of the complexity of agricultural landscapes and lack of sufficient training samples, it remains challenging to monitor cropland dynamics at high spatial and temporal resolutions across large geographical extents, especially for regions
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The Total Carbon Column Observing Network's GGG2020 data version Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-05-06 Joshua L. Laughner, Geoffrey C. Toon, Joseph Mendonca, Christof Petri, Sébastien Roche, Debra Wunch, Jean-Francois Blavier, David W. T. Griffith, Pauli Heikkinen, Ralph F. Keeling, Matthäus Kiel, Rigel Kivi, Coleen M. Roehl, Britton B. Stephens, Bianca C. Baier, Huilin Chen, Yonghoon Choi, Nicholas M. Deutscher, Joshua P. DiGangi, Jochen Gross, Benedikt Herkommer, Pascal Jeseck, Thomas Laemmel, Xin
Abstract. The Total Carbon Column Observing Network (TCCON) measures column-average mole fractions of several greenhouse gases (GHGs), beginning in 2004, from over 30 current or past measurement sites around the world using solar absorption spectroscopy in the near-infrared (near-IR) region. TCCON GHG data have been used extensively for multiple purposes, including in studies of the carbon cycle and
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Global anthropogenic emissions (CAMS-GLOB-ANT) for the Copernicus Atmosphere Monitoring Service simulations of air quality forecasts and reanalyses Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-05-06 Antonin Soulie, Claire Granier, Sabine Darras, Nicolas Zilbermann, Thierno Doumbia, Marc Guevara, Jukka-Pekka Jalkanen, Sekou Keita, Cathy Liousse, Monica Crippa, Diego Guizzardi, Rachel Hoesly, Steven J. Smith
Abstract. Anthropogenic emissions are the result of many different economic sectors, including transportation, power generation, industrial, residential and commercial activities, waste treatment and agricultural practices. Air quality models are used to forecast the atmospheric composition, analyze observations and reconstruct the chemical composition of the atmosphere during the previous decades
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SDUST2020MGCR: a global marine gravity change rate model determined from multi-satellite altimeter data Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-05-06 Fengshun Zhu, Jinyun Guo, Huiying Zhang, Lingyong Huang, Heping Sun, Xin Liu
Abstract. Investigating the global time-varying gravity field mainly depends on GRACE/GRACE-FO gravity data. However, satellite gravity data exhibit low spatial resolution and signal distortion. Satellite altimetry is an important technique for observing the global ocean and provides many consecutive years of data, which enables the study of high-resolution marine gravity variations. This study aims
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AIGD-PFT: The first AI-driven Global Daily gap-free 4 km Phytoplankton Functional Type products from 1998 to 2023 Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-05-06 Yuan Zhang, Fang Shen, Renhu Li, Mengyu Li, Zhaoxin Li, Songyu Chen, Xuerong Sun
Abstract. Long time series of spatiotemporally continuous phytoplankton functional type (PFT) products are essential for understanding marine ecosystems, global biogeochemical cycles, and effective marine management. In this study, by integrating artificial intelligence (AI) technology with multi-source marine big data, we have developed a Spatial–Temporal–Ecological Ensemble model based on Deep Learning
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Weekly Green Tide Mapping in the Yellow Sea with Deep Learning: Integrating Optical and SAR Ocean Imagery Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-05-06 Le Gao, Yuan Guo, Xiaofeng Li
Abstract. Since 2008, the Yellow Sea has experienced a world's largest-scale marine disasters, known as the green tide, marked by the rapid proliferation and accumulation of large floating algae. Leveraging advanced AI models, namely AlgaeNet and GANet, this study comprehensively extracted and analyzed green tide occurrences using optical Moderate Resolution Imaging Spectroradiometer (MODIS) images
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Deep Convective Microphysics Experiment (DCMEX) coordinated aircraft and ground observations: microphysics, aerosol, and dynamics during cumulonimbus development Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-05-03 Declan L. Finney, Alan M. Blyth, Martin Gallagher, Huihui Wu, Graeme J. Nott, Michael I. Biggerstaff, Richard G. Sonnenfeld, Martin Daily, Dan Walker, David Dufton, Keith Bower, Steven Böing, Thomas Choularton, Jonathan Crosier, James Groves, Paul R. Field, Hugh Coe, Benjamin J. Murray, Gary Lloyd, Nicholas A. Marsden, Michael Flynn, Kezhen Hu, Navaneeth M. Thamban, Paul I. Williams, Paul J. Connolly
Abstract. Cloud feedbacks associated with deep convective anvils remain highly uncertain. In part, this uncertainty arises from a lack of understanding of how microphysical processes influence the cloud radiative effect. In particular, climate models have a poor representation of microphysics processes, thereby encouraging the collection and study of observation data to enable better representation
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Data mining-based machine learning methods for improving hydrological data a case study of salinity field in the Western Arctic Ocean Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-05-03 Shuhao Tao, Ling Du, Jiahao Li
Abstract. In the Western Arctic Ocean lies the largest freshwater reservoir in the Arctic Ocean, the Beaufort Gyre. Long-term changes in freshwater reservoirs are critical for understanding the Arctic Ocean, and data from various sources, particularly measured or reanalyzed data, must be used to the greatest extent possible. Over the past two decades, a large number of intensive field observations
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Updated climatological mean ΔfCO2 and net sea–air CO2 flux over the global open ocean regions Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-05-02 Amanda R. Fay, David R. Munro, Galen A. McKinley, Denis Pierrot, Stewart C. Sutherland, Colm Sweeney, Rik Wanninkhof
Abstract. The late Taro Takahashi (Lamont-Doherty Earth Observatory (LDEO), Columbia University) and colleagues provided the first near-global monthly air–sea CO2 flux climatology in Takahashi et al. (1997), based on available surface water partial pressure of CO2 measurements. This product has been a benchmark for uptake of CO2 in the ocean. Several versions have been provided since, with improvements
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In situ airborne measurements of atmospheric parameters and airborne sea surface properties related to offshore wind parks in the German Bight during the project X-Wakes Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-05-02 Astrid Lampert, Rudolf Hankers, Thomas Feuerle, Thomas Rausch, Matthias Cremer, Maik Angermann, Mark Bitter, Jonas Füllgraf, Helmut Schulz, Ulf Bestmann, Konrad B. Bärfuss
Abstract. Between 14 March 2020 and 11 September 2021, meteorological measurement flights were conducted above the German Bight in the framework of the project X-Wakes. The scope of the measurements was to study the transition of the wind field and atmospheric stability from the coast to the sea, to study the interaction of wind park wakes, and to study the large-scale modification of the marine atmospheric
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Crop-specific Management History of Phosphorus Fertilizer Input (CMH-P) in the Croplands of United States: Reconciliation of Top-down and Bottom-up data Sources Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-05-02 Peiyu Cao, Bo Yi, Franco Bilotto, Carlos Gonzalez Fischer, Mario Herrero, Chaoqun Lu
Abstract. Understanding and assessing the spatiotemporal patterns in crop-specific phosphorus (P) fertilizer management is crucial for promoting crop yield and mitigating environmental problems. The existing P fertilizer dataset, derived from sales data, depicts an average application rate on total cropland at the county level but overlooks cross-crop variations. Conversely, the survey-based dataset
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Earth Virtualization Engines (EVE) Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-04-30 Bjorn Stevens, Stefan Adami, Tariq Ali, Hartwig Anzt, Zafer Aslan, Sabine Attinger, Jaana Bäck, Johanna Baehr, Peter Bauer, Natacha Bernier, Bob Bishop, Hendryk Bockelmann, Sandrine Bony, Guy Brasseur, David N. Bresch, Sean Breyer, Gilbert Brunet, Pier Luigi Buttigieg, Junji Cao, Christelle Castet, Yafang Cheng, Ayantika Dey Choudhury, Deborah Coen, Susanne Crewell, Atish Dabholkar, Qing Dai, Francisco
Abstract not available
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Simbi: historical hydro-meteorological time series and signatures for 24 catchments in Haiti Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-04-30 Ralph Bathelemy, Pierre Brigode, Vazken Andréassian, Charles Perrin, Vincent Moron, Cédric Gaucherel, Emmanuel Tric, Dominique Boisson
Abstract. Haiti, a Caribbean country, is highly vulnerable to hydroclimatic hazards due to heavy rainfall, which is partly linked to tropical cyclones. Additionally, its steep slopes generate flash floods, particularly in small catchments. Moreover, the hydrology of this region remains poorly understood and understudied. Unfortunately, there is no accessible database for the scientific community to
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Lagrangian surface drifter observations in the North Sea: an overview of high-resolution tidal dynamics and surface currents Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-04-30 Lisa Deyle, Thomas H. Badewien, Oliver Wurl, Jens Meyerjürgens
Abstract. A dataset of 85 Lagrangian surface drifter trajectories covering the central North Sea area and the Skagerrak from 2017–2021 of 17 deployments is presented. The data have been quality-controlled, uniformly structured, and assimilated in a standard NetCDF format (https://doi.org/10.1594/PANGAEA.963166, Meyerjürgens et al., 2023a). Using appropriate methods presented in detail here, surface
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The annual update GLODAPv2.2023: the global interior ocean biogeochemical data product Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-04-30 Siv K. Lauvset, Nico Lange, Toste Tanhua, Henry C. Bittig, Are Olsen, Alex Kozyr, Marta Álvarez, Kumiko Azetsu-Scott, Peter J. Brown, Brendan R. Carter, Leticia Cotrim da Cunha, Mario Hoppema, Matthew P. Humphreys, Masao Ishii, Emil Jeansson, Akihiko Murata, Jens Daniel Müller, Fiz F. Pérez, Carsten Schirnick, Reiner Steinfeldt, Toru Suzuki, Adam Ulfsbo, Anton Velo, Ryan J. Woosley, Robert M. Key
Abstract. The Global Ocean Data Analysis Project (GLODAP) is a synthesis effort providing regular compilations of surface to bottom ocean biogeochemical bottle data, with an emphasis on seawater inorganic carbon chemistry and related variables determined through chemical analysis of seawater samples. GLODAPv2.2023 is an update of the previous version, GLODAPv2.2022 (Lauvset et al., 2022). The major
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Global 1 km land surface parameters for kilometer-scale Earth system modeling Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-04-29 Lingcheng Li, Gautam Bisht, Dalei Hao, L. Ruby Leung
Abstract. Earth system models (ESMs) are progressively advancing towards the kilometer scale (“k-scale”). However, the surface parameters for land surface models (LSMs) within ESMs running at the k-scale are typically derived from coarse-resolution and outdated datasets. This study aims to develop a new set of global land surface parameters with a resolution of 1 km for multiple years from 2001 to
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The first hillslope thermokarst inventory for the permafrost region of the Qilian Mountains Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-04-29 Xiaoqing Peng, Guangshang Yang, Oliver W. Frauenfeld, Xuanjia Li, Weiwei Tian, Guanqun Chen, Yuan Huang, Gang Wei, Jing Luo, Cuicui Mu, Fujun Niu
Abstract. Climate warming and anthropogenic disturbances result in permafrost degradation in cold regions, including in the Qilian Mountains. These changes lead to extensive hillslope thermokarst (HT) formation, such as retrogressive thaw slumps, active-layer detachment slides, and thermal erosion gullies. These in turn cause, e.g., degradation of local vegetation, economic losses, infrastructure damages
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SISALv3: a global speleothem stable isotope and trace element database Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-04-26 Nikita Kaushal, Franziska A. Lechleitner, Micah Wilhelm, Khalil Azennoud, Janica C. Bühler, Kerstin Braun, Yassine Ait Brahim, Andy Baker, Yuval Burstyn, Laia Comas-Bru, Jens Fohlmeister, Yonaton Goldsmith, Sandy P. Harrison, István G. Hatvani, Kira Rehfeld, Magdalena Ritzau, Vanessa Skiba, Heather M. Stoll, József G. Szűcs, Péter Tanos, Pauline C. Treble, Vitor Azevedo, Jonathan L. Baker, Andrea Borsato
Abstract. Palaeoclimate information on multiple climate variables at different spatiotemporal scales is becoming increasingly important to understand environmental and societal responses to climate change. A lack of high-quality reconstructions of past hydroclimate has recently been identified as a critical research gap. Speleothems, with their precise chronologies, widespread distribution, and ability
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The 2023 National Offshore Wind data set (NOW-23) Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-04-26 Nicola Bodini, Mike Optis, Stephanie Redfern, David Rosencrans, Alex Rybchuk, Julie K. Lundquist, Vincent Pronk, Simon Castagneri, Avi Purkayastha, Caroline Draxl, Raghavendra Krishnamurthy, Ethan Young, Billy Roberts, Evan Rosenlieb, Walter Musial
Abstract. This article introduces the 2023 National Offshore Wind data set (NOW-23), which offers the latest wind resource information for offshore regions in the United States. NOW-23 supersedes, for its offshore component, the Wind Integration National Dataset (WIND) Toolkit, which was published a decade ago and is currently a primary resource for wind resource assessments and grid integration studies
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Modeling fuel-, vehicle type-, and age-specific CO2 emissions from global on-road vehicles, 1970–2020 Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-04-25 Liu Yan, Qiang Zhang, Kebin He, Bo Zheng
Abstract. Vehicles are among the most important contributors to global anthropogenic CO2 emissions. However, the lack of fuel-, vehicle type-, and age-specific information about global on-road CO2 emissions in existing datasets, which are available only at the sector level, makes these datasets insufficient to support the establishment of emission mitigation strategies. Thus, a fleet turnover model
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Ecosystem characteristics of land covers with various anthropogenic impacts in a tropical forest region of Southeast Asia Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-04-23 Chansopheaktra Sovann, Torbern Tagesson, Patrik Vestin, Sakada Sakhoeun, Soben Kim, Sothea Kok, Stefan Olin
Abstract. Given the severe anthropogenic pressure on tropical forests and the high demand for field observations of ecosystem characteristics, it is crucial to collect such data both in pristine tropical forests and in the converted deforested land cover classes. To gain insight into the ecosystem characteristics of pristine tropical forests, regrowth forests, and cashew plantations, we established
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SARAH-3 – satellite-based climate data records of surface solar radiation Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-04-18 Uwe Pfeifroth, Jaqueline Drücke, Steffen Kothe, Jörg Trentmann, Marc Schröder, Rainer Hollmann
Abstract. The amount of energy reaching the Earth’s surface from the sun is a quantity of high importance for the climate system and for renewable energy applications. SARAH-3 is a new edition of a satellite-based climate data record of surface solar radiation parameters. It is generated and distributed by the European Organisation of Meteorological Satellites (EUMETSAT) Satellite Application Facility
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Synthesis Product for Ocean Time Series (SPOTS) – a ship-based biogeochemical pilot Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-04-16 Nico Lange, Björn Fiedler, Marta Álvarez, Alice Benoit-Cattin, Heather Benway, Pier Luigi Buttigieg, Laurent Coppola, Kim Currie, Susana Flecha, Dana S. Gerlach, Makio Honda, I. Emma Huertas, Siv K. Lauvset, Frank Muller-Karger, Arne Körtzinger, Kevin M. O'Brien, Sólveig R. Ólafsdóttir, Fernando C. Pacheco, Digna Rueda-Roa, Ingunn Skjelvan, Masahide Wakita, Angelicque White, Toste Tanhua
Abstract. The presented pilot for the Synthesis Product for Ocean Time Series (SPOTS) includes data from 12 fixed ship-based time-series programs. The related stations represent unique open-ocean and coastal marine environments within the Atlantic Ocean, Pacific Ocean, Mediterranean Sea, Nordic Seas, and Caribbean Sea. The focus of the pilot has been placed on biogeochemical essential ocean variables:
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Spatial and temporal stable water isotope data from the upper snowpack at the EastGRIP camp site, NE Greenland, sampled in summer 2018 Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-04-16 Alexandra M. Zuhr, Sonja Wahl, Hans Christian Steen-Larsen, Maria Hörhold, Hanno Meyer, Vasileios Gkinis, Thomas Laepple
Abstract. Stable water isotopes stored in snow, firn and ice are used to reconstruct climatic parameters. The imprint of these parameters at the snow surface and their preservation in the upper snowpack are determined by a number of processes influencing the recording of the environmental signal. Here, we present a dataset of approximately 3800 snow samples analysed for their stable water isotope composition
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High-resolution physicochemical dataset of atmospheric aerosols over the Tibetan Plateau and its surroundings Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-04-16 Jianzhong Xu, Xinghua Zhang, Wenhui Zhao, Lixiang Zhai, Miao Zhong, Jinsen Shi, Junying Sun, Yanmei Liu, Conghui Xie, Yulong Tan, Kemei Li, Xinlei Ge, Qi Zhang, Shichang Kang
Abstract. Atmospheric aerosol in the Tibetan Plateau (TP) and its surroundings has attracted significant scientific interest in recent decades due to its notable impacts on regional climatic and cryospheric changes, ecological and environmental security, and the hydrological cycle. However, our understanding of the atmospheric aerosol in this remote region is highly limited by the scarcity of available
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High temporal resolution records of the velocity of Hansbreen, a tidewater glacier in Svalbard Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-04-15 Małgorzata Błaszczyk, Bartłomiej Luks, Michał Pętlicki, Dariusz Puczko, Dariusz Ignatiuk, Michał Laska, Jacek Jania, Piotr Głowacki
Abstract. Monitoring changes in glacial dynamics is essential for understanding the environmental response to accelerated climate warming in the Arctic. However, geodetic surveys in polar regions continue to present considerable challenges because of the harsh environmental conditions and the polar night. This study records a 14-year-long time series (2006–2019) of global navigation satellite system
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Mapping sugarcane globally at 10 m resolution using GEDI and Sentinel-2 Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-04-15 Stefania Di Tommaso, Sherrie Wang, Rob Strey, David B. Lobell
Abstract. Sugarcane is an important source of food, biofuel, and farmer income in many countries. At the same time, sugarcane is implicated in many social and environmental challenges, including water scarcity and nutrient pollution. Currently, few of the top sugar-producing countries generate reliable maps of where sugarcane is cultivated. To fill this gap, we introduce a dataset of detailed sugarcane
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CAMELE: Collocation-Analyzed Multi-source Ensembled Land Evapotranspiration Data Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-04-12 Changming Li, Ziwei Liu, Wencong Yang, Zhuoyi Tu, Juntai Han, Sien Li, Hanbo Yang
Abstract. Land evapotranspiration (ET) plays a crucial role in Earth's water–carbon cycle, and accurately estimating global land ET is vital for advancing our understanding of land–atmosphere interactions. Despite the development of numerous ET products in recent decades, widely used products still possess inherent uncertainties arising from using different forcing inputs and imperfect model parameterizations
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Spatial mapping of key plant functional traits in terrestrial ecosystems across China Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-04-11 Nannan An, Nan Lu, Weiliang Chen, Yongzhe Chen, Hao Shi, Fuzhong Wu, Bojie Fu
Abstract. Trait-based approaches are of increasing concern in predicting vegetation changes and linking ecosystem structures to functions at large scales. However, a critical challenge for such approaches is acquiring spatially continuous plant functional trait maps. Here, six key plant functional traits were selected as they can reflect plant resource acquisition strategies and ecosystem functions
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A flux tower site attribute dataset intended for land surface modeling Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-04-10 Jiahao Shi, Hua Yuan, Wanyi Lin, Wenzong Dong, Hongbin Liang, Zhuo Liu, Jianxin Zeng, Haolin Zhang, Nan Wei, Zhongwang Wei, Shupeng Zhang, Shaofeng Liu, Xingjie Lu, Yongjiu Dai
Abstract. Land surface models (LSMs) should have reliable forcing, validation, and surface attribute data as the foundation for effective model development and improvement. Eddy covariance flux tower data are considered the benchmarking data for LSMs. However, currently available flux tower datasets often require multiple aspects of processing to ensure data quality before application to LSMs. More
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ISASO2 : Recent trends and regional patterns of Ocean Dissolved Oxygen change Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-04-10 Nicolas Kolodziejczyk, Esther Portela, Virginie Thierry, Annaig Prigent
Abstract. Recent estimates of the global inventory of dissolved oxygen (DO) have suggested a decrease of 2 % since the 1960s. However, due to the sparse historical oxygen data coverage, the DO inventory exhibits large regional uncertainties at interannual timescale. Using ISASO2, a new DO Argo-based optimally interpolated climatology https://doi.org/10.17882/52367 (Kolodziejczyk et al.,2021), we have
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Enhancing Long-Term Vegetation Monitoring in Australia: A New Approach for Harmonising and Gap-Filling AVHRR and MODIS NDVI Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-04-09 Chad A. Burton, Sami W. Rifai, Luigi J. Renzullo, Albert I. J. M. Van Dijk
Abstract. Long-term, reliable datasets of satellite-based vegetation condition are essential for understanding terrestrial ecosystem responses to global environmental change, particularly in Australia which is characterised by diverse ecosystems and strong interannual climate variability. We comprehensively evaluate several existing global AVHRR NDVI products for their suitability for long-term vegetation
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Introduction to the NJIAS Himawari-8/9 Cloud Feature Dataset for climate and typhoon research Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-04-08 Xiaoyong Zhuge, Xiaolei Zou, Lu Yu, Xin Li, Mingjian Zeng, Yilun Chen, Bing Zhang, Bin Yao, Fei Tang, Fengjiao Chen, Wanlin Kan
Abstract. The use of remote sensing methods to accurately measure cloud properties and their spatiotemporal changes has been widely welcomed in many fields of atmospheric research. The Nanjing Joint Institute for Atmospheric Sciences (NJIAS) Himawari-8/9 Cloud Feature Dataset (HCFD) provides a comprehensive description of cloud features over the East Asia and west North Pacific regions for the 7-year
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A 28 time-points cropland area change dataset in Northeast China from 1000 to 2020 Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-04-08 Ran Jia, Xiuqi Fang, Yundi Yang, Masayuki Yokozawa, Yu Ye
Abstract. Based on historical documents, population data, published results, remote sensing data products, statistical data and survey data, this study reconstructed the cropland area and the spatial pattern changes at 28 time points from 1000 to 2020 in Northeast China. 1000 to 1600 corresponds to historical provincial-level administrative districts, while 1700 to 2020 corresponds to modern county-level
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CHclim25 – a spatially and temporally very high-resolution climatic dataset for Switzerland Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-04-08 Olivier Broennimann, Antoine Guisan
Abstract. CHclim25 is a climatic dataset with a 25 m resolution for Switzerland that includes daily, monthly and yearly layers for temperature, precipitation, relative sunshine duration, growing degree-days, potential evapotranspiration, bioclimatic variables and aridity. The dataset is downscaled from a daily 1 km resolution dataset from the Swiss federal agency for meteorology using local regressions
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Enriching the GEOFON seismic catalog with automatic energy magnitude estimations Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-04-05 Dino Bindi, Riccardo Zaccarelli, Angelo Strollo, Domenico Di Giacomo, Andres Heinloo, Peter Evans, Fabrice Cotton, Frederik Tilmann
Abstract. We present a seismic catalog (Bindi et al., 2024, https://doi.org/10.5880/GFZ.2.6.2023.010) including energy magnitude Me estimated from P waves recorded at teleseismic distances in the range 20°≤Δ≤98° and for depths shorter than 80 km. The catalog is built starting from the event catalog disseminated by GEOFON (GEOFOrschungsNetz), considering 6349 earthquakes with moment magnitude Mw≥5 occurring
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ChinaRiceCalendar – seasonal crop calendars for early-, middle-, and late-season rice in China Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-04-04 Hui Li, Xiaobo Wang, Shaoqiang Wang, Jinyuan Liu, Yuanyuan Liu, Zhenhai Liu, Shiliang Chen, Qinyi Wang, Tongtong Zhu, Lunche Wang, Lizhe Wang
Abstract. Long time series and large-scale rice calendar datasets provide valuable information for agricultural planning and field management in rice-based cropping systems. However, current regional-level rice calendar datasets do not accurately distinguish between rice seasons in China, causing uncertainty in crop model simulation and climate change impact analysis. Based on satellite remote sensing
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French coastal network for carbonate system monitoring: the CocoriCO2 dataset Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-04-04 Sébastien Petton, Fabrice Pernet, Valérian Le Roy, Matthias Huber, Sophie Martin, Éric Macé, Yann Bozec, Stéphane Loisel, Peggy Rimmelin-Maury, Émilie Grossteffan, Michel Repecaud, Loïc Quemener, Michael Retho, Soazig Manac'h, Mathias Papin, Philippe Pineau, Thomas Lacoue-Labarthe, Jonathan Deborde, Louis Costes, Pierre Polsenaere, Loïc Rigouin, Jérémy Benhamou, Laure Gouriou, Joséphine Lequeux, Nathalie
Abstract. Since the beginning of the industrial revolution, atmospheric carbon dioxide (CO2) concentrations have risen steadily and have induced a decrease of the averaged surface ocean pH by 0.1 units, corresponding to an increase in ocean acidity of about 30 %. In addition to ocean warming, ocean acidification poses a tremendous challenge to some marine organisms, especially calcifiers. The need
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The physical and biogeochemical parameters along the coastal waters of Saudi Arabia during field surveys in summer, 2021 Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-04-04 Yasser O. Abualnaja, Alexandra Pavlidou, James H. Churchill, Ioannis Hatzianestis, Dimitris Velaoras, Harilaos Kontoyiannis, Vassilis P. Papadopoulos, Aristomenis P. Karageorgis, Georgia Assimakopoulou, Helen Kaberi, Theodoros Kannelopoulos, Constantine Parinos, Christina Zeri, Dionysios Ballas, Elli Pitta, Vassiliki Paraskevopoulou, Afroditi Androni, Styliani Chourdaki, Vassileia Fioraki, Stylianos
Abstract. During the last decades, the coastal areas of the Kingdom of Saudi Arabia, on the Red Sea and the Arabian Gulf, have been subjected to intense economic and industrial growth. As a result, it may be expected that the overall environmental status of Saudi Arabian coastal marine waters has been affected by human activities. As a consequence, adequate management of the Saudi Arabian coastal zone
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A hydrogeomorphic dataset for characterizing catchment hydrological behavior across the Tibetan Plateau Earth Syst. Sci. Data (IF 11.4) Pub Date : 2024-04-03 Yuhan Guo, Hongxing Zheng, Yuting Yang, Yanfang Sang, Congcong Wen
Abstract. Hydrologic and geomorphic processes are intricately linked within the Earth system, jointly characterizing terrestrial hydrological behaviors and biogeochemical cycles across diverse temporal and spatial scales. The Tibetan Plateau provides an ideal setting for investigating the interactions between hydrological and geomorphic processes in a largely pristine natural environment. Nonetheless