{"type": "FeatureCollection", "features": [{"id": "10.1002/2015gb005239", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:14:01Z", "type": "Journal Article", "created": "2015-12-19", "title": "Toward More Realistic Projections Of Soil Carbon Dynamics By Earth System Models", "description": "Abstract

Soil carbon (C) is a critical component of Earth system models (ESMs), and its diverse representations are a major source of the large spread across models in the terrestrial C sink from the third to fifth assessment reports of the Intergovernmental Panel on Climate Change (IPCC). Improving soil C projections is of a high priority for Earth system modeling in the future IPCC and other assessments. To achieve this goal, we suggest that (1) model structures should reflect real\uffe2\uff80\uff90world processes, (2) parameters should be calibrated to match model outputs with observations, and (3) external forcing variables should accurately prescribe the environmental conditions that soils experience. First, most soil C cycle models simulate C input from litter production and C release through decomposition. The latter process has traditionally been represented by first\uffe2\uff80\uff90order decay functions, regulated primarily by temperature, moisture, litter quality, and soil texture. While this formulation well captures macroscopic soil organic C (SOC) dynamics, better understanding is needed of their underlying mechanisms as related to microbial processes, depth\uffe2\uff80\uff90dependent environmental controls, and other processes that strongly affect soil C dynamics. Second, incomplete use of observations in model parameterization is a major cause of bias in soil C projections from ESMs. Optimal parameter calibration with both pool\uffe2\uff80\uff90 and flux\uffe2\uff80\uff90based data sets through data assimilation is among the highest priorities for near\uffe2\uff80\uff90term research to reduce biases among ESMs. Third, external variables are represented inconsistently among ESMs, leading to differences in modeled soil C dynamics. We recommend the implementation of traceability analyses to identify how external variables and model parameterizations influence SOC dynamics in different ESMs. Overall, projections of the terrestrial C sink can be substantially improved when reliable data sets are available to select the most representative model structure, constrain parameters, and prescribe forcing fields.

", "keywords": ["550", "LAND MODELS", "Oceanography", "HETEROTROPHIC RESPIRATION", "01 natural sciences", "Atmospheric Sciences", "LITTER DECOMPOSITION", "ORGANIC-CARBON", "Geoinformatics", "GLOBAL CLIMATE-CHANGE", "DATA-ASSIMILATION", "Meteorology & Atmospheric Sciences", "TEMPERATURE SENSITIVITY", "CMIP5", "MICROBIAL MODELS", "0105 earth and related environmental sciences", "2. Zero hunger", "[SDU.OCEAN]Sciences of the Universe [physics]/Ocean", "Atmosphere", "[SDU.OCEAN] Sciences of the Universe [physics]/Ocean", " Atmosphere", "500", "Earth system models", "04 agricultural and veterinary sciences", "15. Life on land", "[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces", " environment", "6. Clean water", "TERRESTRIAL ECOSYSTEMS", "Climate Action", "Geochemistry", "Climate change impacts and adaptation", "realistic projections", "13. Climate action", "recommendations", "Earth Sciences", "0401 agriculture", " forestry", " and fisheries", "soil carbon dynamics", "[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces", "environment", "Climate Change Impacts and Adaptation", "Environmental Sciences", "PARAMETER-ESTIMATION"]}, "links": [{"href": "https://escholarship.org/content/qt1pw7g2r2/qt1pw7g2r2.pdf"}, {"href": "https://doi.org/10.1002/2015gb005239"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Global%20Biogeochemical%20Cycles", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1002/2015gb005239", "name": "item", "description": "10.1002/2015gb005239", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1002/2015gb005239"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-01-01T00:00:00Z"}}, {"id": "10.1016/j.earscirev.2022.104055", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:15:21Z", "type": "Journal Article", "created": "2022-05-12", "title": "The uncertain role of rising atmospheric CO2 on global plant transpiration", "description": "As CO2 concentration in the atmosphere rises, there is a need for improved physical understanding of its impact on global plant transpiration. This knowledge gap poses a major hurdle in robustly projecting changes in the global hydrologic cycle. For this reason, here we review the different processes by which atmospheric CO2 concentration affects plant transpiration, the several uncertainties related to the complex physiological and radiative processes involved, and the knowledge gaps which need to be filled in order to improve predictions of plant transpiration. Although there is a high degree of certainty that rising CO2 will impact plant transpiration, the exact nature of this impact remains unclear due to complex interactions between CO2 and climate, and key aspects of plant morphology and physiology. The interplay between these factors has substantial consequences not only for future climate and global vegetation, but also for water availability needed for sustaining the productivity of terrestrial ecosystems. Future changes in global plant transpiration in response to enhanced CO2 are expected to be driven by water availability, atmospheric evaporative demand, plant physiological processes, emergent plant disturbances related to increasing temperatures, and the modification of plant physiology and coverage. Considering the universal sensitivity of natural and agricultural systems to terrestrial water availability we argue that reliable future projections of transpiration is an issue of the highest priority, which can only be achieved by integrating monitoring and modeling efforts to improve the representation of CO2 effects on plant transpiration in the next generation of earth system models. \u00a9 2022 The Authors", "keywords": ["0301 basic medicine", "2. Zero hunger", "VAPOR-PRESSURE DEFICIT", "COMMUNITY LAND MODEL", "DECIDUOUS FOREST TREES", "TROPICAL RAIN-FOREST", "EARTH SYSTEM MODELS", "STOMATAL CONDUCTANCE", "Earth system models", "15. Life on land", "01 natural sciences", "6. Clean water", "Transpiration", "03 medical and health sciences", "DYNAMIC VEGETATION MODELS", "13. Climate action", "Earth and Environmental Sciences", "MOJAVE DESERT SHRUBS", "Climate change", "CO2", "ELEVATED CO2", "Atmospheric water demand", "WATER-USE EFFICIENCY", "Projections", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.earscirev.2022.104055"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Earth-Science%20Reviews", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.earscirev.2022.104055", "name": "item", "description": "10.1016/j.earscirev.2022.104055", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.earscirev.2022.104055"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-07-01T00:00:00Z"}}, {"id": "10.1016/j.physrep.2020.09.005", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:15:55Z", "type": "Journal Article", "created": "2020-10-03", "title": "Statistical physics approaches to the complex Earth system", "description": "Global climate change, extreme climate events, earthquakes and their accompanying natural disasters pose significant risks to humanity. Yet due to the nonlinear feedbacks, strategic interactions and complex structure of the Earth system, the understanding and in particular the predicting of such disruptive events represent formidable challenges for both scientific and policy communities. During the past years, the emergence and evolution of Earth system science has attracted much attention and produced new concepts and frameworks. Especially, novel statistical physics and complex networks-based techniques have been developed and implemented to substantially advance our knowledge for a better understanding of the Earth system, including climate extreme events, earthquakes and Earth geometric relief features, leading to substantially improved predictive performances. We present here a comprehensive review on the recent scientific progress in the development and application of how combined statistical physics and complex systems science approaches such as, critical phenomena, network theory, percolation, tipping points analysis, as well as entropy can be applied to complex Earth systems (climate, earthquakes, etc.). Notably, these integrating tools and approaches provide new insights and perspectives for understanding the dynamics of the Earth systems. The overall aim of this review is to offer readers the knowledge on how statistical physics approaches can be useful in the field of Earth system science.", "keywords": ["0301 basic medicine", "Physics - Physics and Society", "Earthquake", "550", "Climate Change", "Complex Network", "FOS: Physical sciences", "Physics and Society (physics.soc-ph)", "Complex Earth Systems", "Article", "Physics - Geophysics", "03 medical and health sciences", "S\u00edndrome respiratorio agudo grave", "11. Sustainability", "Condensed Matter - Statistical Mechanics", "0303 health sciences", "Statistical Mechanics (cond-mat.stat-mech)", "SARS-CoV-2", "Statistical Physics", "COVID-19", "500", "Geophysics (physics.geo-ph)", "Coronavirus", "13. Climate action", "Physics - Data Analysis", " Statistics and Probability", "Data Analysis", " Statistics and Probability (physics.data-an)"]}, "links": [{"href": "https://doi.org/10.1016/j.physrep.2020.09.005"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Physics%20Reports", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.physrep.2020.09.005", "name": "item", "description": "10.1016/j.physrep.2020.09.005", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.physrep.2020.09.005"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-02-01T00:00:00Z"}}, {"id": "10.1016/j.scitotenv.2024.171158", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:16:03Z", "type": "Journal Article", "created": "2024-02-20", "title": "Topsoil porosity prediction across habitats at large scales using environmental variables", "description": "Soil porosity and its reciprocal bulk density are important environmental state variables that enable modelers to represent hydraulic function and carbon storage. Biotic effects and their 'dynamic' influence on such state variables remain largely unknown for larger scales and may result in important, yet poorly quantified environmental feedbacks. Existing representation of hydraulic function is often invariant to environmental change and may be poor in some systems, particularly non-arable soils. Here we assess predictors of total porosity across two comprehensive national topsoil (0-15\u00a0cm) data sets, covering the full range of soil organic matter (SOM) and habitats (n\u00a0=\u00a01385 & n\u00a0=\u00a02570), using generalized additive mixed models and machine learning. Novel aspects of this work include the testing of metrics on aggregate size and livestock density alongside a range of different particle size distribution metrics. We demonstrate that porosity trends in Great Britain are dominated by biotic metrics, soil carbon and land use. Incorporating these variables into porosity prediction improves performance, paving the way for new dynamic calculation of porosity using surrogate measures with remote sensing, which may help improve prediction in data sparse regions of the world. Moreover, dynamic calculation of porosity could support representation of feedbacks in environmental and Earth System Models. Representing the hydrological feedbacks from changes in structural porosity also requires data and models at appropriate spatial scales to capture conditions leading to near-saturated soil conditions. Classification. Environmental Sciences.", "keywords": ["land use change", "soil compaction", "climate change", "earth system model", "13. Climate action", "soil porosity", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "soil carbon", "15. Life on land", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.scitotenv.2024.171158"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Science%20of%20The%20Total%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.scitotenv.2024.171158", "name": "item", "description": "10.1016/j.scitotenv.2024.171158", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.scitotenv.2024.171158"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-04-01T00:00:00Z"}}, {"id": "10.1029/2018jg004795", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:16:41Z", "type": "Journal Article", "created": "2019-04-09", "title": "Comparison With Global Soil Radiocarbon Observations Indicates Needed Carbon Cycle Improvements in the E3SM Land Model", "description": "Abstract

We evaluated global soil organic carbon (SOC) stocks and turnover time predictions from a global land model (ELMv1\uffe2\uff80\uff90ECA) integrated in an Earth System Model (E3SM) by comparing them with observed soil bulk and \uffce\uff9414C values around the world. We analyzed observed and simulated SOC stocks and \uffce\uff9414C values using machine learning methods at the Earth System Model grid cell scale (~200\uffc2\uffa0km). In grid cells with sufficient observations, the model provided reasonable estimates of soil carbon stocks across soil depth and \uffce\uff9414C values near the surface but underestimated \uffce\uff9414C at depth. Among many explanatory variables, soil albedo index, soil order, plant function type, air temperature, and SOC content were major factors affecting predicted SOC \uffce\uff9414C values. The influences of soil albedo index, soil order, and air temperature were primarily important in the shallow subsurface (\uffe2\uff89\uffa430\uffc2\uffa0cm). We also performed sensitivity studies using different vertical root distributions and decomposition turnover times and compared to observed SOC stock and \uffce\uff9414C profiles. The analyses support the role of vegetation in affecting soil carbon turnover, particularly in deep soil, possibly through supplying fresh carbon and degrading physical\uffe2\uff80\uff90chemical protection of SOC via root activities. Allowing for grid cell\uffe2\uff80\uff90specific rooting and decomposition rates substantially reduced discrepancies between observed and predicted \uffce\uff9414C values and SOC content. Our results highlight the need for more explicit representation of roots, microbes, and soil physical protection in land models.Radiocarbon (14C) is a powerful tracer of the global carbon cycle that is commonly used to assess carbon cycling rates in various Earth system reservoirs and as a benchmark to assess model performance. Therefore, it has been recommended that Earth System Models (ESMs) participating in the Coupled Model Intercomparison Project Phase 6 report predicted radiocarbon values for relevant carbon pools. However, a detailed representation of radiocarbon dynamics may be an impractical burden on model developers. Here, we present an alternative approach to compute radiocarbon values from the numerical output of an ESM that does not explicitly represent these dynamics. The approach requires computed 12C stocks and fluxes among all carbon pools for a particular simulation of the model. From this output, a time\uffe2\uff80\uff90dependent linear compartmental system is computed with its respective state\uffe2\uff80\uff90transition matrix. Using transient atmospheric 14C values as inputs, the state\uffe2\uff80\uff90transition matrix is then applied to compute radiocarbon values for each pool, the average value for the entire system, and component fluxes. We demonstrate the approach with ELMv1\uffe2\uff80\uff90ECA, the land component of an ESM model that explicitly represents 12C, and 14C in 7 soil pools and 10 vertical layers. Results from our proposed method are highly accurate (relative error <0.01%) compared with the ELMv1\uffe2\uff80\uff90ECA 12C and 14C predictions, demonstrating the potential to use this approach in CMIP6 and other model simulations that do not explicitly represent 14C.Mineral dust produced by wind erosion of arid and semiarid surfaces is a major component of atmospheric aerosol that affects climate, weather, ecosystems, and socioeconomic sectors such as human health, transportation, solar energy, and air quality. Understanding these effects and ultimately improving the resilience of affected countries requires a reliable, dense, and diverse set of dust observations, fundamental for the development and the provision of skillful dust-forecast-tailored products. The last decade has seen a notable improvement of dust observational capabilities in terms of considered parameters, geographical coverage, and delivery times, as well as of tailored products of interest to both the scientific community and the various end-users. Given this progress, here we review the current state of observational capabilities, including in situ, ground-based, and satellite remote sensing observations in northern Africa, the Middle East, and Europe for the provision of dust information considering the needs of various users. We also critically discuss observational gaps and related unresolved questions while providing suggestions for overcoming the current limitations. Our review aims to be a milestone for discussing dust observational gaps at a global level to address the needs of users, from research communities to nonscientific stakeholders.

Abstract. Quantifying the dust optical depth (DOD) and its uncertainty across spatiotemporal scales is key to understanding and constraining the dust cycle and its interactions with the Earth System. This study quantifies the DOD along with its monthly and year-to-year variability between 2003 and 2017 at global and regional levels based on the MIDAS (ModIs Dust AeroSol) dataset, which combines Moderate Resolution Imaging Spectroradiometer (MODIS)-Aqua retrievals and Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), reanalysis products. We also describe the annual and seasonal geographical distributions of DOD across the main dust source regions and transport pathways. MIDAS provides columnar mid-visible (550\u2009nm) DOD at fine spatial resolution (0.1\u2218\u00d70.1\u2218), expanding the current observational capabilities for monitoring the highly variable spatiotemporal features of the dust burden. We obtain a global DOD of 0.032\u00b10.003 \u2013 approximately a quarter (23.4\u2009%\u00b12.4\u2009%) of the global aerosol optical depth (AOD) \u2013 with about 1\u00a0order of magnitude more DOD in the Northern Hemisphere (0.056\u00b10.004; 31.8\u2009%\u00b12.7\u2009%) than in the Southern Hemisphere (0.008\u00b10.001; 8.2\u2009%\u00b11.1\u2009%) and about 3.5 times more DOD over land (0.070\u00b10.005) than over ocean (0.019\u00b10.002). The Northern Hemisphere monthly DOD is highly correlated with the corresponding monthly AOD (R2=0.94) and contributes 20\u2009% to 48\u2009% of it, both indicating a dominant dust contribution. In contrast, the contribution of dust to the monthly AOD does not exceed 17\u2009% in the Southern Hemisphere, although the uncertainty in this region is larger. Among the major dust sources of the planet, the maximum DODs (\u223c1.2) are recorded in the Bod\u00e9l\u00e9 Depression of the northern Lake Chad Basin, whereas moderate-to-high intensities are encountered in the Western Sahara (boreal summer), along the eastern parts of the Middle East (boreal summer) and in the Taklamakan Desert (spring). Over oceans, major long-range dust transport is observed primarily along the tropical Atlantic (intensified during boreal summer) and secondarily in the North Pacific (intensified during boreal spring). Our calculated global and regional averages and associated uncertainties are consistent with some but not all recent observation-based studies. Our work provides a simple yet flexible method to estimate consistent uncertainties across spatiotemporal scales, which will enhance the use of the MIDAS dataset in a variety of future studies.

", "keywords": ["Mineral dusts", ":Enginyeria agroaliment\u00e0ria::Ci\u00e8ncies de la terra i de la vida::Climatologia i meteorologia [\u00c0rees tem\u00e0tiques de la UPC]", "Physics", "QC1-999", "MIDAS global dataset", "16. Peace & justice", "01 natural sciences", "Atmospheric Sciences", "Climate Action", "Chemistry", "\u00c0rees tem\u00e0tiques de la UPC::Enginyeria agroaliment\u00e0ria::Ci\u00e8ncies de la terra i de la vida::Climatologia i meteorologia", "13. Climate action", "Mineral dust particles", "Simulaci\u00f3 per ordinador", "Pols", "Meteorology & Atmospheric Sciences", "Datasets", "Dust optical depth (DOD)", "Earth System", "QD1-999", "Astronomical and Space Sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://acp.copernicus.org/articles/22/3553/2022/acp-22-3553-2022.pdf"}, {"href": "https://escholarship.org/content/qt9v38c6qs/qt9v38c6qs.pdf"}, {"href": "https://doi.org/10.5194/acp-22-3553-2022"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Atmospheric%20Chemistry%20and%20Physics", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/acp-22-3553-2022", "name": "item", "description": "10.5194/acp-22-3553-2022", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/acp-22-3553-2022"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-07-19T00:00:00Z"}}, {"id": "10.1594/pangaea.814272", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:18:17Z", "type": "Dataset", "title": "Underway physical oceanography and carbon dioxide measurements during G. O. Sars cruise 58GS20110516", "description": "Cruise QC flag: C (see further details). The Fair Data Use Statement for SOCAT can be found at hdl:10013/epic.48576.d001", "keywords": ["extracted from the World Ocean Atlas 2005", "Salinity", "Salinity", " interpolated", "Fugacity of carbon dioxide (water) at equilibrator temperature (wet air)", "interpolated", "Depth", " bathymetric", " interpolated/gridded", "atmospheric", "Quality flag", "Temperature", " water", "Changes in the carbon uptake and emissions by oceans in a changing climate (CARBOCHANGE)", "G O Sars 2003", "extracted from the NCEP NCAR 40 Year Reanalysis Project", "Distance", "Temperature", "Surface Ocean - Lower Atmosphere Study (SOLAS-Norway)", "extracted from the NCEP/NCAR 40-Year Reanalysis Project", "Surface Ocean CO2 Atlas Project SOCAT", "Algorithm", "extracted from the 2 Minute Gridded Global Relief Data ETOPO2", "Earth System Research", "G. O. Sars (2003)", "Surface Ocean Lower Atmosphere Study SOLAS Norway", "2013", "xCO2 (air)", " interpolated", "bathymetric", "water", "interpolated gridded", "DATE TIME", "Pressure", "14. Life underwater", "Fugacity of carbon dioxide water at equilibrator temperature wet air", "xCO2 water at equilibrator temperature dry air", "58GS20110516", "extracted from the 2-Minute Gridded Global Relief Data (ETOPO2)", "LONGITUDE", "xCO2 air", "extracted from GLOBALVIEW CO2", "DEPTH", " water", "Underway cruise track measurements", "Depth", "Temperature at equilibration", "Surface Ocean CO2 Atlas Project (SOCAT)", "Pressure at equilibration", "Fugacity of carbon dioxide (water) at sea surface temperature (wet air)", "extracted from GLOBALVIEW-CO2", "Changes in the carbon uptake and emissions by oceans in a changing climate CARBOCHANGE", "DATE/TIME", "Recomputed after SOCAT (Pfeil et al.", " 2013)", "13. Climate action", "DEPTH", "LATITUDE", "Recomputed after SOCAT Pfeil et al", "Fugacity of carbon dioxide water at sea surface temperature wet air", "xCO2 (water) at equilibrator temperature (dry air)", "Pressure", " atmospheric", " interpolated"], "contacts": [{"organization": "Johannessen, Truls, Lauvset, Siv K,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1594/pangaea.814272"}, {"rel": "self", "type": "application/geo+json", "title": "10.1594/pangaea.814272", "name": "item", "description": "10.1594/pangaea.814272", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1594/pangaea.814272"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2014-01-01T00:00:00Z"}}, {"id": "10.1594/PANGAEA.880120", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:18:16Z", "type": "Dataset", "title": "Measurements in soil and air at Bayelva Station", "description": "Open AccessSupplement to: Boike, Julia; Juszak, Inge; Lange, Stephan; Chadburn, Sarah; Burke, Eleanor J; Overduin, Pier Paul; Roth, Kurt; Ippisch, Olaf; Bornemann, Niko; Stern, Lielle; Gouttevin, Isabelle; Hauber, Ernst; Westermann, Sebastian (2018): A 20-year record (1998-2017) of permafrost, active layer and meteorological conditions at a high Arctic permafrost research site (Bayelva, Spitsbergen). Earth System Science Data, 10(1), 355-390", "keywords": ["Bayelva permafrost long term observations LTO_Permafrost_Bayelva", "13. Climate action", "Earth System Research", "Bayelva permafrost long-term observations (LTO_Permafrost_Bayelva)", "15. Life on land"]}, "links": [{"href": "https://doi.org/10.1594/PANGAEA.880120"}, {"rel": "self", "type": "application/geo+json", "title": "10.1594/PANGAEA.880120", "name": "item", "description": "10.1594/PANGAEA.880120", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1594/PANGAEA.880120"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-01-01T00:00:00Z"}}, {"id": "10.1594/pangaea.854694", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-09-20T16:18:17Z", "description": "Open AccessIn the data file you find data on the standard deviation (SD), mean and stability (stab) of soil microbial basal respiration [\u00b5LO2/ h/g dry soil] and microbial biomass carbon [\u00b5gC/g dry soil]. Data were derived by taking soil samples and measuring basal and substrate-induced microbial respiration with an oxygen consumption apparatus. Oxygen consumption of soil microorganisms in fresh soil equivalent to 3.5 g dry weight was measured at 22\u00b0C over a period of 24 h. Microbial basal respiration [BR; \u00b5lO2/g dry soil/h] was calculated as mean of the oxygen consumption rates of hours 14 to 24 after the start of measurements. Substrate- induced respiration was determined by adding D-glucose to saturate catabolic enzymes of microorganisms according to preliminary studies (4 mg g dry soil solved in 400 \u00b5L deionized water). Maximum initial respiratory response (MIRR; [\u00b5lO2/g dry soil/h]) was calculated as mean of the lowest three oxygen consumption values within the first 10 h after glucose addition. Microbial biomass carbon [Cmic; \u00b5gC/g dry soil] was calculated as 38 \u00d7 MIRR according to prelimiray studies, see further details. Samples for calculating the spatial stability of soil microbial properties were taken in 2010. Samples for calculating the temporal stability were taken from 2003 to 2014.", "keywords": ["The Jena Experiment JenExp", "Earth System Research", "The Jena Experiment (JenExp)"], "contacts": [{"organization": "Strecker, Tanja, Gonzalez, Odette, Scheu, Stefan, Eisenhauer, Nico,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1594/pangaea.854694"}, {"rel": "self", "type": "application/geo+json", "title": "10.1594/pangaea.854694", "name": "item", "description": "10.1594/pangaea.854694", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1594/pangaea.854694"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2015-01-01T00:00:00Z"}}, {"id": "10.1594/pangaea.194648", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:18:16Z", "type": "Dataset", "title": "Physical oceanography at station JCR2_CTD24", "description": "Plymouth Marine Laboratory. Authorship was originally 'BODC' and was changed by request of the BODC.", "keywords": ["Salinity", "potential", "Density", " sigma-theta (0)", "water", "James Clark Ross", "Fluorometer", "Density", "Irradiance", " downward PAR", "CTD/Rosette", "Fluorescence", "hemispherical photodiode", "Temperature", " water", "Irradiance", "Pressure", "Calculated", "chlorophyll", "14. 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"https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1594/pangaea.194648"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2004-01-01T00:00:00Z"}}, {"id": "10.1594/pangaea.261535", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:18:16Z", "type": "Dataset", "title": "Physical properties of sediment core GIK23291-2", "keywords": ["wet bulk", "M7/3", "Gravity corer (Kiel type)", "Density", "DEPTH", " sediment/rock", "Quaternary Environment of the Eurasian North QUEEN", "Water content", " dry mass", "dry mass", "M7 3", "Density", " dry bulk", "Calculated", "Pore number", "Meteor 1986", "Water content", "Meteor (1986)", "dry bulk", "Calculated from mass volume", "Global Environmental Change: The Northern North Atlantic (SFB313)", "sediment rock", "Gravity corer Kiel 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{"updated": "2026-09-20T16:18:16Z", "type": "Dataset", "title": "Calcium carbonate content of sediment core SO79-167KG", "keywords": ["sediment rock", "Sonne", "1994", "Box corer (Reineck)", "DEPTH", "Earth System Research", "Box corer Reineck", "Element analysis (Klosa", " 1994)", "DEPTH", " sediment/rock", "Calcium carbonate", "Element analysis Klosa", "SO79"], "contacts": [{"organization": "Weber, Michael E, Wiedicke-Hombach, Michael, Riech, Volkher, Erlenkeuser, Helmut,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1594/pangaea.351631"}, {"rel": "self", "type": "application/geo+json", "title": "10.1594/pangaea.351631", "name": "item", "description": "10.1594/pangaea.351631", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1594/pangaea.351631"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "1995-01-01T00:00:00Z"}}, {"id": "10.1594/pangaea.428754", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:18:16Z", "type": "Dataset", "title": "Daily sea level from coastal tide gauge station Ketchikan in 1974 (Research quality database)", "keywords": ["DATE/TIME", "SeaLevel", "World Ocean Circulation Experiment WOCE", "DATE TIME", "Earth System Research", "Tide gauge station", "Sea level", "World Ocean Circulation Experiment (WOCE)"], "contacts": [{"organization": "WOCE Sea Level, WSL", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1594/pangaea.428754"}, {"rel": "self", "type": "application/geo+json", "title": "10.1594/pangaea.428754", "name": "item", "description": "10.1594/pangaea.428754", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1594/pangaea.428754"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2006-01-01T00:00:00Z"}}, {"id": "10.1594/pangaea.583345", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:18:17Z", "type": "Dataset", "title": "Tree-ring width of Quercus species from historical object sample IB21533-47", "description": "Species QUSP; No of rings 114; Begin 1256; End 1369", "keywords": ["Historical and Postglacial Tree Ring Archive of Hohenheim (HISTRA)", "AGE", "Age", "Historical object", "Historical and Postglacial Tree Ring Archive of Hohenheim HISTRA", "Dendrochronological crossdating", "TreeRings_SouthGermany", "Earth System Research", "15. 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Deep-Sea Res 10: 221-231. Chlorophyll a and Phaeopigments were measured with a Turner 700 fluorometre following Shuman and Lorenzen (1975): Quantitative degradation of chlorophyll by a marine herbivore, Limnology and Oceanography, 20.", "keywords": ["Replicates", "PE2xx", "bottom max", "Chlorophyll a", "Depth", "Depth", " top/min", "DEPTH", " sediment/rock", "Hotspot Ecosystem Research on the Margins of European Seas HERMES", "Chlorophyll pigment equivalents", "sediment rock", "Chloroplastic pigment equivalents", "Phaeopigments", " standard deviation", "Chloroplastic pigment equivalents", " standard deviation", "European Margin Strata Formation (EuroSTRATAFORM)", "DEPTH", "top min", "Earth System Research", "Depth", " bottom/max", "14. Life underwater", "standard deviation", "Phaeopigments", "Chlorophyll a", " standard deviation", "European Margin Strata Formation EuroSTRATAFORM", "Hotspot Ecosystem Research on the Margins of European Seas (HERMES)", "MultiCorer"], "contacts": [{"organization": "Garcia, Rosa, Thomsen, Laurenz,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1594/pangaea.615227"}, {"rel": "self", "type": "application/geo+json", "title": "10.1594/pangaea.615227", "name": "item", "description": "10.1594/pangaea.615227", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1594/pangaea.615227"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2007-01-01T00:00:00Z"}}, {"id": "10.1594/pangaea.913721", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:18:17Z", "type": "Dataset", "title": "Biogeochemistry of suspended particulate matter and sediment from the nearshore zone of Herschel Island, Canada", "description": "Collapse of permafrost coasts delivers large quantities of particulate organic carbon (POC) to arctic coastal areas. The objective of this study is to assess the pathways and fate of POC derived from thawing and eroding permafrost coasts in the nearshore zone, to better understand its impact on the carbon cycle and climate. We collected suspended particulate matter and sediment samples at the coastline and in the nearshore zone of Herschel Island - Qikiqtaruk (N 69.60\u00b0; W 139.00\u00b0) during a two\u2010week period in July\u2010August 2017. Locations were labelled A - H clockwise around the island, starting at the NE corner (Collinson Head). Samples were taken in transects perpendicular to the coast, at point locations offshore ('Monitoring point 1 - 3'), and from 'thaw streams', creeks carrying material from retrogressive thaw slumps and other abrupt thaw features, at various locations around the island. A total of 49 locations were visited; 12 at thaw streams, and 37 in the nearshore zone ranging from right at the shoreline to up to 20 m water depth (about 2 km offshore). We performed biogeochemical analyses (CN, \u03b413C, \u039414C) and sedimentological analyses (grain size, mineral surface area) in order to trace the pathway of permafrost material from its source to the nearshore water column and sediments.", "keywords": ["Arctic", "13. Climate action", "11. Sustainability", "Earth System Research", "Nearshore zone", "Permafrost", "14. Life underwater", "15. Life on land", "Coastal erosion", "Organic carbon", "coastal erosion"]}, "links": [{"href": "https://doi.org/10.1594/pangaea.913721"}, {"rel": "self", "type": "application/geo+json", "title": "10.1594/pangaea.913721", "name": "item", "description": "10.1594/pangaea.913721", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1594/pangaea.913721"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-01-01T00:00:00Z"}}, {"id": "10.1594/pangaea.939352", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-09-20T16:18:17Z", "type": "Dataset", "title": "Global fraction of lightning fires and burned area from lightning", "description": "This dataset contains the global fraction of lightning fires and burned area from lightning, and associated uncertainties, at 0.5 degree resolution. The dataset is representative for contemporary fire regimes (between 2001 and 2020). The dataset is based on a statistical model with three geospatial predictor variables: the seasonal correlation between lightning and burned area, the seasonal correlation between fire weather and burned area, and the fraction of low impact land. These variables are derivatives from remote sensing products. The statistical model was calibrated and validated with fire cause reference data from seven different parts of the world: USA including Alaska, Canada, Portugal, southern France, Yakutia (Russia), Victoria (Australia) and Tasmania (Australia). The statistical model explained 53 % of the variability in the reference data for the fraction of lightning fires, and 39 % for the burned area from lightning. All other relevant datasets from the study, processed to 0.5 degree resolution, are also provided. These include burned land, seasonal correlation between lightning and burned area, seasonal correlation between fire weather and burned area, low impact land, fire cause reference data, intact forests, fire-related forest loss, carbon combustion and future lightning projections.", "keywords": ["13. Climate action", "Earth System Research", "15. Life on land", "global", "lightning", "burned area", "fire"], "contacts": [{"organization": "Janssen, Thomas, Jones, Matthew W, Finney, Declan, van der Werf, Guido R, van Wees, Dave, Xu, Wenxuan, Veraverbeke, Sander,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1594/pangaea.939352"}, {"rel": "self", "type": "application/geo+json", "title": "10.1594/pangaea.939352", "name": "item", "description": "10.1594/pangaea.939352", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1594/pangaea.939352"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-01-01T00:00:00Z"}}, {"id": "10.1594/pangaea.960025", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:18:17Z", "type": "Dataset", "title": "Analysis of the high density coarse fraction (HDC) from the nearshore zone of Herschel Island (Yukon, Canada)", "keywords": ["14C AMS", "MICADAS accelerator mass spectrometer AMS", "Elemental analyzer (EA)", " Thermo Scientific", " FlashEA 1112", "Fraction modern carbon", "Permafrost", "Quantachrome", "Age", " dated", "Surface area analyzer", " Quantachrome", " Nova 4200e; 6-point Brunauer\u2013Emmett\u2013Teller (BET) method according to Brunauer et al. (1938)", "Arctic", "Elemental analyzer EA", "Isotope ratio mass spectrometry-elemental analyzer (IRMS-EA)", " Thermo Finnigan", " Delta XP; Elemental analyzer (EA)", " Thermo Scientific", " FlashEA 1112", "Thermo Scientific", "Calculated", "Carbon Nitrogen ratio", "Carbon", " organic", " loading", "total", "Laboratory code label", "Minerals", "Multiple investigations", "Laboratory code/label", "Ionplus according to McIntyre et al 2017 and Haghipour et al 2018", "Minerals", " surface area", "error", "loading", "Nitrogen", " total", "Earth System Research", "\u03b413C", "FlashEA 1112", "Isotope ratio mass spectrometry elemental analyzer IRMS EA", "Nitrogen", "organic", "\u039414C", "MICADAS accelerator mass spectrometer (AMS)", " Ionplus; according to McIntyre et al. (2017) and Haghipour et al. (2018)", "Surface area analyzer", "dated", "Age", "Delta XP Elemental analyzer EA", "Organic carbon", "Comment", "surface area", "Carbon", "Carbon/Nitrogen ratio", "relative", "Thermo Finnigan", "sediment", "Sample ID", "Age", " 14C AMS", "Biomarkers", "Nova 4200e 6 point Brunauer Emmett Teller BET method according to Brunauer et al 1938", "Carbon", " organic", " total", "Fraction modern carbon", " error", " relative"]}, "links": [{"href": "https://doi.org/10.1594/pangaea.960025"}, {"rel": "self", "type": "application/geo+json", "title": "10.1594/pangaea.960025", "name": "item", "description": "10.1594/pangaea.960025", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1594/pangaea.960025"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-01-01T00:00:00Z"}}, {"id": "10.1594/pangaea.960026", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:18:17Z", "type": "Dataset", "title": "Sedimentological and biogeochemical composition of fractionated permafrost- and sediment organic carbon of the nearshore zone of Herschel Island (Yukon, Canada)", "description": "This study aims to give insight into the processes affecting permafrost organic carbon (OC) during transport from its source to its sink, through a study on three sediment fractions along a land-to-ocean transect. Material was followed from thawing permafrost, through a dynamic 'disturbed zone' and the nearshore zone, to an enclosed basin offshore Herschel Island - Qikiqtaruk, to assess sorting and degradation processes on specific fractions of sediment OC. Sediment, soil and permafrost samples were taken along a transect from the source (undisturbed active layer and permafrost), via two transitional zones (a terrestrial disturbed zone, i.e. the 'scar zone' of the RTS, and the marine nearshore zone up to a water depth of 5 m), to sink (basin sediment, water depth >20 m) at the coast of Herschel Island \u2013 Qikiqtaruk and the (semi-enclosed) Herschel Basin in Yukon, Canada, just west of the Mackenzie River delta. Samples were taken in May 2016 and July 2017. Sample material was fractionated with an aqueous (MilliQ) solution of sodium polytungstate (SPT; Na6[H2W12O40]), with a density of 1.8 g cm\u00b3, followed by wet-sieving over a 63 \u00b5m mesh, thus separating loose OC from mineral-associated OC. Each fraction was analysed for element content (TOC, TN), carbon isotopes (\u03b4\u00b9\u00b3C, \u0394\u00b9\u2074C), molecular biomarkers (n-alkanes, n-alkanoic acids, lignin phenols, cutin acids), and mineral surface area. The relative abundance of specific biomarkers can also be used as indicator for degradation of organic carbon. Furthermore, the OC 'loading' (concentration of OC normalised to mineral surface area; in mgOC/m\u00b2) and terrestrial biomarker loading (\u00b5gOC/m\u00b2) can be used to assess loss of (permafrost) OC from mineral particles. The combination of these methods allows us to disentangle sorting processes from degradation of OC along the land-to-ocean continuum, and provides a detailed insight into the fate of thawed and eroded permafrost OC.", "keywords": ["Arctic", "sediment", "13. Climate action", "Multiple investigations", "Earth System Research", "Permafrost", "15. Life on land", "Biomarkers", "Organic carbon"]}, "links": [{"href": "https://doi.org/10.1594/pangaea.960026"}, {"rel": "self", "type": "application/geo+json", "title": "10.1594/pangaea.960026", "name": "item", "description": "10.1594/pangaea.960026", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1594/pangaea.960026"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-01-01T00:00:00Z"}}, {"id": "10.1594/pangaea.972409", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:18:17Z", "type": "Dataset", "title": "Organic carbon content, stable carbon isotope ratios, and lignin phenol fingerprint of terrestrial material deposited at the paleo-delta of the Lena River at the transition to the Preboreal", "description": "The dataset was used to reconstruct the release of permafrost organic carbon from the watershed of the Lena River (Russia) between 11.1 and 11.7 calibrated thousand years Before Present (cal. kyr BP, Present = 1950 AD) and to model potential methane emissions from this carbon source. Data were obtained analyzing plant debris isolated from the low density fraction (<1.8 g/cm3) of muddy sediments from the Piston Core 23 (PC23). The sediment core was retrieved in July 2014 in the mid/outer-shelf of the Laptev Sea shelf (76\u00b0 10' 15.6''N; 129\u00b0 20' 13.2''E, water depth of 56 m) during Leg 1 of the SWERUS-C3 expedition (Swedish-Russian-U.S. Arctic Ocean \u2013 Investigation of Climate-Cryosphere-Carbon interactions). Measurement of total organic carbon (TOC) and stable (d\u00b9\u00b3C) carbon isotopes were performed on 0.3 to 0.7 mg of samples on February 2022 using a Thermo DeltaQ isotope-ratio mass spectrometer (IRMS) coupled to a Thermo Flash 2000 Elemental Analyzer via a ConFlo IV interface at the at the Institute of Polar Sciences from the National Research Council of Italy (Bologna Section, Italy). The methodology for sample preparation followed Nieuwenhuize et al. (1994). Data on biomarkers (lignin phenols) were obtained extracting 2 to 3 mg of samples using a Microwave Accelerated Reaction System (MARS) 5 from CEM and following the methodology from Go\u00f1i & Montgomery (2000). The extracts were analysed using a Agilent 7890A gas chromatograph (GC) coupled to an Agilent 5975C mass spectrometer to identify and quantify the compounds of interest. Biomarkers extraction and analyses were carried out on March 2022 in the organic chemistry laboratories of the Ente Nazionale Idrocarburi (ENI)-National Research Council (CNR) of Italy Joint Research Center 'Aldo Pontremoli' (Lecce, Italy). Stable isotope ratios and biomarkers were used to gain insights on the main vegetation source of the plant debris and (biomarkers only) to investigate the degradation state of the terrestrial material.", "keywords": ["5 dihydroxybenzoic acid per unit mass organic carbon", "p Coumaric acid per unit mass organic carbon", "SWERUS C3", "p-Hydroxybenzaldehyde per unit mass organic carbon", "Permafrost", "p Hydroxybenzaldehyde per unit mass organic carbon", "Latitude of event", "Arctic", "Gas chromatography (GC", " Agilent 7890A) equipped with a mass selective detector (MSD", " Agilent 5975C) and a flame ionization detector (FID", " Agilent 7683B)", "p-Hydroxybenzoic acid per unit mass organic carbon", "p-Hydroxyacetophenone/p-hydroxyl phenols ratio", "bottom maximum", "top min", "total", "Sample code/label", "p-Coumaric acid per unit mass organic carbon", "Vanillic acid vanillin ratio", "Deglaciation", "p-Hydroxyl phenols/vanillyl phenols ratio", "Depth", " sediment/rock", " bottom/maximum", "Syringic acid per unit mass organic carbon", "p-Hydroxyl phenols per unit mass organic carbon", "Sample code label", "p Hydroxyl phenols per unit mass organic carbon", "Depth", " top/min", "Acetovanillone per unit mass organic carbon", "Vanillic acid per unit mass organic carbon", "p Hydroxybenzoic acid per unit mass organic carbon", "p Hydroxyacetophenone per unit mass organic carbon", "Vanillic acid/vanillin ratio", "sediment rock", "p Hydroxyl phenols vanillyl phenols ratio", "Syringyl phenols vanillyl phenols ratio", "Earth System Research", "\u03b413C", "Ferulic acid per unit mass organic carbon", "Syringaldehyde per unit mass organic carbon", "Vanillin per unit mass organic carbon", "Methane", "Piston corer", "Isotope ratio mass spectrometer", " Thermo", " DeltaQ; coupled to an Elemental Analyzer; Thermo Flash 2000 via a ConFlo IV", "Longitude of event", "Syringyl phenols per unit mass organic carbon", "organic", "Syringic acid/syringaldehyde ratio", "Cinnamyl phenols/vanillyl phenols ratio", "DEPTH", " sediment/rock", "5 dihydroxybenzoic acid vanillyl phenols ratio", "Oden", "Cinnamyl phenols vanillyl phenols ratio", "Agilent 7683B", "p-Hydroxyacetophenone per unit mass organic carbon", "Date/Time of event", "Acetosyringone per unit mass organic carbon", "3", "5-dihydroxybenzoic acid per unit mass organic carbon", "Depth", "Event label", "Date Time of event", "p Hydroxyacetophenone p hydroxyl phenols ratio", "Vanillyl phenols per unit mass organic carbon", "Elevation of event", "Syringyl phenols/vanillyl phenols ratio", "Agilent 5975C and a flame ionization detector FID", "Carbon", "Cinnamyl phenols per unit mass organic carbon", "Agilent 7890A equipped with a mass selective detector MSD", "DEPTH", "Syringic acid syringaldehyde ratio", "3", "5-dihydroxybenzoic acid/vanillyl phenols ratio", "Gas chromatography GC", "Thermo", "SWERUS-C3", "Isotope ratio mass spectrometer", "DeltaQ coupled to an Elemental Analyzer Thermo Flash 2000 via a ConFlo IV", "Carbon", " organic", " total"], "contacts": [{"organization": "Sabino, Mathia, Gustafsson, \u00d6rjan, Wild, Birgit, Semiletov, Igor P, Dudarev, Oleg V, Ingrosso, Gianmarco, Tesi, Tommaso,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1594/pangaea.972409"}, {"rel": "self", "type": "application/geo+json", "title": "10.1594/pangaea.972409", "name": "item", "description": "10.1594/pangaea.972409", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1594/pangaea.972409"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-01-01T00:00:00Z"}}, {"id": "10.1594/pangaea.972412", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:18:17Z", "type": "Dataset", "title": "Radiocarbon content and age of terrestrial material deposited at the paleo-delta of the Lena River at the transition to the Preboreal", "description": "The dataset was used to reconstruct the release of permafrost organic carbon from the watershed of the Lena River (Russia) between 11.1 and 11.7 calibrated thousand years Before Present (cal. kyr BP, Present = 1950 AD) and to model potential methane emissions from this carbon source. Data were obtained analyzing plant debris isolated from the low density fraction (<1.8 g/cm3) of muddy sediments from the Piston Core 23 (PC23). The sediment core was retrieved in July 2014 in the mid/outer-shelf of the Laptev Sea shelf (76\u00b0 10' 15.6''N; 129\u00b0 20' 13.2''E, water depth of 56 m) during Leg 1 of the SWERUS-C3 expedition (Swedish-Russian-U.S. Arctic Ocean \u2013 Investigation of Climate-Cryosphere-Carbon interactions). Radiocarbon (\u00b9\u2074C) content measurements were performed on 4 to 7 mg of sample on May 2022 using the Continuous Flow Accelerator Mass Spectrometry (CFAMS) system at the National Ocean Sciences Accelerator Mass Spectrometry (NOSAMS) facility (Woods Hole Oceanographic Institution, Woods Hole, MA, USA). The \u00b9\u2074C content was used to calculate \u00b9\u2074C isotope ratios (D\u00b9\u2074C) and to reconstruct non-calibrated and calibrated \u00b9\u2074C ages of plant debris isolated from the sediment fraction with a density lower than 1.8 g/cm3. Additionally, D\u00b9\u2074C values were used to calculate the \u00b9\u2074C content of plant debris at time of sediment deposition (D\u00b9\u2074Ci) and the latter to obtain pre-depositional \u00b9\u2074C ages. The dataset allowed to reconstruct the age of the terrestrial plant material when deposited at the coring site and identify its provenance from within the permafrost OC pool (sub-surface soil within 1 m depth vs deep soil) after remobilization. The average pre-depositional \u00b9\u2074C age of plant debris was ultimately used to model methane emissions from relatively young permafrost organic carbon during the late deglaciation (ca. 10 to 15 cal. kyr BP).", "keywords": ["Piston corer", "SWERUS C3", "Longitude of event", "Age", " 14C", "\u039414C", "Fraction modern carbon", "Calendar age", "Permafrost", "DEPTH", " sediment/rock", "Latitude of event", "Oden", "Age", "Arctic", "AGE", "pre depositional", "bottom maximum", "top min", "Date/Time of event", "Calculated", "\u039414C", " initial", " error", "Fraction modern carbon", " error", "Sample code/label", "Deglaciation", "Depth", " sediment/rock", " bottom/maximum", "\u039414C", " error", "Age", " pre-depositional", " error", "Depth", "Event label", "Date Time of event", "Continuous Flow Accelerator Mass Spectrometry", "initial", "Sample code label", "Depth", " top/min", "Calendar age", " standard error", "Age", " error", "error", "Elevation of event", "sediment rock", "\u039414C", " initial", "14C", "standard error", "DEPTH", "Age", " pre-depositional", "Earth System Research", "SWERUS-C3", "Methane"], "contacts": [{"organization": "Sabino, Mathia, Gustafsson, \u00d6rjan, Wild, Birgit, Semiletov, Igor P, Dudarev, Oleg V, Ingrosso, Gianmarco, Tesi, Tommaso,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1594/pangaea.972412"}, {"rel": "self", "type": "application/geo+json", "title": "10.1594/pangaea.972412", "name": "item", "description": "10.1594/pangaea.972412", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1594/pangaea.972412"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-01-01T00:00:00Z"}}, {"id": "10.31223/x5qd36", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:18:53Z", "type": "Journal Article", "created": "2022-08-31", "title": "A review of coarse mineral dust in the Earth system", "description": "

Mineral dust particles suspended in the atmosphere span more than three orders of magnitude in diameter, from less than 0.1 \u00b5m to more than 100 \u00b5m. This wide size range makes dust a unique aerosol species with the ability to interact with many aspects of the Earth system, including radiation, clouds, hydrology, atmospheric chemistry, and biogeochemistry. This review focuses on coarse and super-coarse dust aerosols, which we respectively define as dust particles with a diameter between 2.5 - 10 \u00b5m and 10 - 62.5 \u00b5m. We review several lines of observational evidence indicating that coarse and super-coarse dust particles are transported farther than previously expected and that the abundance of these particles is substantially underestimated in current global models. We synthesize previous studies that used observations, theories, and model simulations to highlight the impacts of coarse and super-coarse dust aerosols on the Earth system, including their effects on dust-radiation interactions, dust-cloud interactions, and atmospheric chemistry, and biogeochemistry. In addition, we examine several limitations in the representation of coarse and super-coarse dust aerosols in current model simulations and in remote-sensing retrievals. Because these limitations substantially contribute to the uncertainties in simulating the abundance and impacts of coarse and super-coarse dust aerosols, we offer some recommendations to facilitate future studies. Overall, we conclude that an accurate representation of coarse and super-coarse properties is critical in understanding the overall impacts of dust aerosols on the Earth system.

", "keywords": ["[SDU.OCEAN]Sciences of the Universe [physics]/Ocean", "info:eu-repo/classification/ddc/550", "550", "ddc:550", "Atmosphere", "[SDU.OCEAN] Sciences of the Universe [physics]/Ocean", " Atmosphere", "Climate", "Size distribution", "Mineral dust", "01 natural sciences", "[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces", " environment", "Atmospheric Sciences", "Coarse dust", "Climate Action", "Environmental sciences", "Earth sciences", "13. Climate action", "Earth Sciences", "[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces", "environment", "Earth system", "Environmental Sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://escholarship.org/content/qt9cp497d5/qt9cp497d5.pdf"}, {"href": "https://doi.org/10.31223/x5qd36"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Aeolian%20Research", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.31223/x5qd36", "name": "item", "description": "10.31223/x5qd36", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.31223/x5qd36"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-09-02T00:00:00Z"}}, {"id": "10.3389/fpls.2021.626709", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:18:58Z", "type": "Journal Article", "created": "2021-02-01", "title": "Potential Effects of Microplastic on Arbuscular Mycorrhizal Fungi", "description": "

Microplastics (MPs) are ubiquitously found in terrestrial ecosystems and are increasingly recognized as a factor of global change (GCF). Current research shows that MP can alter plant growth, soil inherent properties, and the composition and activity of microbial communities. However, knowledge about how microplastic affects arbuscular mycorrhizal fungi (AMF) is scarce. For plants it has been shown that microplastic can both increase and decrease the aboveground biomass and reduce the root diameter, which could indirectly cause a change in AMF abundance and activity. One of the main direct effects of microplastic is the reduction of the soil bulk density, which translates to an altered soil pore structure and water transport. Moreover, especially fibers can have considerable impacts on soil structure, namely the size distribution and stability of soil aggregates. Therefore, microplastic alters a number of soil parameters that determine habitat space and conditions for AMF. We expect that this will influence functions mediated by AMF, such as soil aggregation, water and nutrient transport. We discuss how the impacts of microplastic on AMF could alter how plants deal with other GCFs in the context of sustainable food production. The co-occurrence of several GCFs, e.g., elevated temperature, drought, pesticides, and microplastic could modify the impact of microplastic on AMF. Furthermore, the ubiquitous presence of microplastic also relates to earth system processes, e.g., net primary production (NPP), carbon and nitrogen cycling, which involve AMF as key soil organisms. For future research, we outline which experiments should be prioritized.

", "keywords": ["0301 basic medicine", "2. Zero hunger", "570", "0303 health sciences", "Plant culture", "arbuscular mycorrhizal fungi", "Plant Science", "500 Naturwissenschaften und Mathematik::570 Biowissenschaften; Biologie::570 Biowissenschaften; Biologie", "15. Life on land", "6. Clean water", "SB1-1110", "03 medical and health sciences", "13. Climate action", "earth system processes", "pollution", "microplastic", "global change"]}, "links": [{"href": "https://doi.org/10.3389/fpls.2021.626709"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Frontiers%20in%20Plant%20Science", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3389/fpls.2021.626709", "name": "item", "description": "10.3389/fpls.2021.626709", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3389/fpls.2021.626709"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-02-01T00:00:00Z"}}, {"id": "10.3535/2p4-8vy-qaf", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-09-20T16:19:16Z", "type": "Dataset", "title": "rocks", "description": "Digital Specimen for the physical specimen hosted at Tallinn University of Technology.", "keywords": ["Geology", "FOS: Earth and related environmental sciences", "Earth System"], "contacts": [{"organization": "Tallinn University of Technology", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.3535/2p4-8vy-qaf"}, {"rel": "self", "type": "application/geo+json", "title": "10.3535/2p4-8vy-qaf", "name": "item", "description": "10.3535/2p4-8vy-qaf", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3535/2p4-8vy-qaf"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-03-31T00:00:00Z"}}, {"id": "10.3535/5td-xfj-g5x", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-09-20T16:19:16Z", "type": "Dataset", "title": "igneous rocks", "description": "Digital Specimen for the physical specimen hosted at Tallinn University of Technology.", "keywords": ["Geology", "FOS: Earth and related environmental sciences", "Earth System"], "contacts": [{"organization": "Tallinn University of Technology", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.3535/5td-xfj-g5x"}, {"rel": "self", "type": "application/geo+json", "title": "10.3535/5td-xfj-g5x", "name": "item", "description": "10.3535/5td-xfj-g5x", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3535/5td-xfj-g5x"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-03-31T00:00:00Z"}}, {"id": "10.5194/gmd-2020-413", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:19:43Z", "type": "Journal Article", "created": "2021-09-13", "title": "EC-Earth3-AerChem, a global climate model with interactive aerosols and atmospheric chemistry participating in CMIP6", "description": "

Abstract. This paper documents the global climate model EC-Earth3-AerChem, one of the members of the EC-Earth3 family of models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6). EC-Earth3-AerChem has interactive aerosols and atmospheric chemistry and contributes to the Aerosols and Chemistry Model Intercomparison Project (AerChemMIP). In this paper, we give an overview of the model, describe in detail how it differs from the other EC-Earth3 configurations, and outline the new features compared with the previously documented version of the model (EC-Earth 2.4). We explain how the model was tuned and spun up under preindustrial conditions and characterize the model's general performance on the basis of a selection of coupled simulations conducted for CMIP6. The net energy imbalance at the top of the atmosphere in the preindustrial control simulation is on average \uffe2\uff88\uff920.09\uffe2\uff80\uff89W\uffe2\uff80\uff89m\uffe2\uff88\uff922 with a standard deviation due to interannual variability of 0.25\uffe2\uff80\uff89W\uffe2\uff80\uff89m\uffe2\uff88\uff922, showing no significant drift. The global surface air temperature in the simulation is on average 14.08\uffe2\uff80\uff89\uffe2\uff88\uff98C with an interannual standard deviation of 0.17\uffe2\uff80\uff89\uffe2\uff88\uff98C, exhibiting a small drift of 0.015\uffe2\uff80\uff89\uffc2\uffb1\uffe2\uff80\uff890.005\uffe2\uff80\uff89\uffe2\uff88\uff98C per century. The model's effective equilibrium climate sensitivity is estimated at 3.9\uffe2\uff80\uff89\uffe2\uff88\uff98C, and its transient climate response is estimated at 2.1\uffe2\uff80\uff89\uffe2\uff88\uff98C. The CMIP6 historical simulation displays spurious interdecadal variability in Northern Hemisphere temperatures, resulting in a large spread across ensemble members and a tendency to underestimate observed annual surface temperature anomalies from the early 20th century onwards. The observed warming of the Southern Hemisphere is well reproduced by the model. Compared with the ECMWF (European Centre for Medium-Range Weather Forecasts) Reanalysis version 5 (ERA5), the surface air temperature climatology for 1995\uffe2\uff80\uff932014 has an average bias of \uffe2\uff88\uff920.86\uffe2\uff80\uff89\uffc2\uffb1\uffe2\uff80\uff890.05\uffe2\uff80\uff89\uffe2\uff88\uff98C with a standard deviation across ensemble members of 0.35\uffe2\uff80\uff89\uffe2\uff88\uff98C in the Northern Hemisphere and 1.29\uffe2\uff80\uff89\uffc2\uffb1\uffe2\uff80\uff890.02\uffe2\uff80\uff89\uffe2\uff88\uff98C with a corresponding standard deviation of 0.05\uffe2\uff80\uff89\uffe2\uff88\uff98C in the Southern Hemisphere. The Southern Hemisphere warm bias is largely caused by errors in shortwave cloud radiative effects over the Southern Ocean, a deficiency of many climate models. Changes in the emissions of near-term climate forcers (NTCFs) have significant effects on the global climate from the second half of the 20th century onwards. For the SSP3-7.0 Shared Socioeconomic Pathway, the model gives a global warming at the end of the 21st century (2091\uffe2\uff80\uff932100) of 4.9\uffe2\uff80\uff89\uffe2\uff88\uff98C above the preindustrial mean. A 0.5\uffe2\uff80\uff89\uffe2\uff88\uff98C stronger warming is obtained for the AerChemMIP scenario with reduced emissions of NTCFs. With concurrent reductions of future methane concentrations, the warming is projected to be reduced by 0.5\uffe2\uff80\uff89\uffe2\uff88\uff98C.

", "keywords": ["Atmospheric chemistry", ":Desenvolupament hum\u00e0 i sostenible::Degradaci\u00f3 ambiental [\u00c0rees tem\u00e0tiques de la UPC]", "EARTH SYSTEM MODELS", "MINERAL-COMPOSITION", "MODIFIED BAND APPROACH", "7. Clean energy", ":Enginyeria qu\u00edmica::Qu\u00edmica del medi ambient::Qu\u00edmica atmosf\u00e8rica [\u00c0rees tem\u00e0tiques de la UPC]", "SULFURIC-ACID", "\u00c0rees tem\u00e0tiques de la UPC::Enginyeria qu\u00edmica::Qu\u00edmica del medi ambient::Qu\u00edmica atmosf\u00e8rica", "EC-EARTH", "ORGANIC AEROSOL", "\u00c0rees tem\u00e0tiques de la UPC::Desenvolupament hum\u00e0 i sostenible::Degradaci\u00f3 ambiental", "Aerosols", "QE1-996.5", "Escalfament global", "Global warming", "Geology", "Climatic changes", "16. Peace & justice", "Climate Science", "COMPUTATIONAL PERFORMANCE", "DUST AEROSOLS", "Qu\u00edmica atmosf\u00e8rica", "13. Climate action", "GREENHOUSE-GAS CONCENTRATIONS", "BIOMASS BURNING EMISSIONS", "Geosciences", "Klimatvetenskap", "Canvis clim\u00e0tics"]}, "links": [{"href": "https://iris.polito.it/bitstream/11583/2959536/1/vannoije2021_gmd.pdf"}, {"href": "https://gmd.copernicus.org/articles/14/5637/2021/gmd-14-5637-2021.pdf"}, {"href": "https://doi.org/10.5194/gmd-2020-413"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoscientific%20Model%20Development", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/gmd-2020-413", "name": "item", "description": "10.5194/gmd-2020-413", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/gmd-2020-413"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-12-21T00:00:00Z"}}, {"id": "10.48620/90780", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:19:25Z", "type": "Journal Article", "created": "2024-10-23", "title": "Warming of Northern Peatlands Increases the Global Temperature Overshoot Challenge", "description": "Meeting the Paris Agreement's temperature goals requires limiting future carbon emissions, yet current policies make temporarily overshooting the 1.5\u00b0C target likely. The potential climate feedback from destabilizing peatlands, storing large amounts of carbon, remains poorly quantified. Using the reduced-complexity Earth System Model OSCAR with an integrated peat carbon module, we found that across various overshoot pathways that temporarily exceed 1.5\u00b0C-2.5\u00b0C, northern peatlands exhibit net positive feedback, amplifying the overshoot challenge. Warming increases peatlands' net carbon uptake, but this is largely offset by higher methane emissions. We estimated that for each 1\u00b0C increase in peak warming, the positive feedback from peatlands decreases the remaining carbon budget by 37 GtCO2 (22-48 GtCO2). If the 1.5\u00b0C temperature target is exceeded, peatlands would increase carbon removal requirement by about 40 GtCO2 (16-60 GtCO2) (8.6%). Our findings highlight the importance of properly accounting for northern peatlands for estimating climate feedbacks, especially under overshoot scenarios.", "keywords": ["[SDU.STU.CL] Sciences of the Universe [physics]/Earth Sciences/Climatology", "climate change", "northern peatlands", "carbon", "greenhouse gases", "land surface model", "reduced-complexity earth system model", "FairCarboN", "temperature feedback", "[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces", " environment", "Article", "overshoot"]}, "links": [{"href": "https://oceanrep.geomar.de/id/eprint/62739/1/1-s2.0-S2590332225001794-main.pdf"}, {"href": "https://pure.iiasa.ac.at/id/eprint/20730/1/1-s2.0-S2590332225001794-main.pdf"}, {"href": "https://doi.org/10.48620/90780"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/One%20Earth", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.48620/90780", "name": "item", "description": "10.48620/90780", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.48620/90780"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-23T00:00:00Z"}}, {"id": "10.5194/acp-2021-4", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:19:34Z", "type": "Journal Article", "created": "2021-01-18", "title": "Contribution of the world's main dust source regions to the global cycle of desert dust", "description": "

Abstract. Even though desert dust is the most abundant aerosol by mass in Earth's atmosphere, the relative contributions of the world\u2019s major dust source regions to the global dust cycle remain poorly constrained. This problem hinders accounting for the potentially large impact of regional differences in dust properties on clouds, the Earth's energy balance, and terrestrial and marine biogeochemical cycles. Here, we constrain the contribution of each of the world\u2019s main dust source regions to the global dust cycle. We use an analytical framework that integrates an ensemble of global model simulations with observationally informed constraints on the dust size distribution, extinction efficiency, and regional dust aerosol optical depth. We obtain a data set that constrains the relative contribution of each of nine major source regions to size-resolved dust emission, atmospheric loading, optical depth, concentration, and deposition flux. We find that the 22\u201329\u2009Tg (one standard error range) global loading of dust with geometric diameter up to 20\u2009\u03bcm is partitioned as follows: North African source regions contribute ~50\u2009% (11\u201315\u2009Tg), Asian source regions contribute ~40\u2009% (8\u201313\u2009Tg), and North American and Southern Hemisphere regions contribute ~10\u2009% (1.8\u20133.2\u2009Tg). Current models might on average be overestimating the contribution of North African sources to atmospheric dust loading at ~65\u2009%, while underestimating the contribution of Asian dust at ~30\u2009%. However, both our results and current models could be affected by unquantified biases, such as due to errors in separating dust aerosol optical depth from that produced by other aerosol species in remote sensing retrievals in poorly observed desert regions. Our results further show that each source region's dust loading peaks in local spring and summer, which is partially driven by increased dust lifetime in those seasons. We also quantify the dust deposition flux to the Amazon rainforest to be ~10\u2009Tg/year, which is a factor of 2\u20133 less than inferred from satellite data by previous work that likely overestimated dust deposition by underestimating the dust mass extinction efficiency. The data obtained in this paper can be used to obtain improved constraints on dust impacts on clouds, climate, biogeochemical cycles, and other parts of the Earth system.

", "keywords": ["Atmospheric sciences", "550", "QC1-999", "Global dust cycle", "\u00c0rees tem\u00e0tiques de la UPC::Enginyeria agroaliment\u00e0ria::Ci\u00e8ncies de la terra i de la vida", "01 natural sciences", "Atmospheric Sciences", "Atmospheric models", "Earth's atmosphere", "Simulaci\u00f3 per ordinador", "Meteorology & Atmospheric Sciences", "Dust; Aerosols; Climate Models; Earth System Models;", "14. Life underwater", "[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces", " environment", "Life Below Water", "QD1-999", "0105 earth and related environmental sciences", "[SDU.OCEAN]Sciences of the Universe [physics]/Ocean", " Atmosphere", "[SDU.OCEAN]Sciences of the Universe [physics]/Ocean", "info:eu-repo/classification/ddc/550", "Atmosphere", "Climate change science", "ddc:550", "[SDU.OCEAN] Sciences of the Universe [physics]/Ocean", " Atmosphere", "Physics", "Aerosol model simulations", "15. Life on land", "Atmosfera -- Aspectes ambientals", "[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces", " environment", "Climate Action", "Earth sciences", "Chemistry", "13. Climate action", ":Enginyeria agroaliment\u00e0ria::Ci\u00e8ncies de la terra i de la vida [\u00c0rees tem\u00e0tiques de la UPC]", "Air quality", "Earth Sciences", "Aerosols--Measurement", "Desert dust", "[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces", "environment", "Astronomical and Space Sciences"]}, "links": [{"href": "https://boa.unimib.it/bitstream/10281/321610/1/Kok_2021_ACP_Dust-global.pdf"}, {"href": "https://acp.copernicus.org/articles/21/8169/2021/acp-21-8169-2021.pdf"}, {"href": "https://acp.copernicus.org/articles/21/8169/2021/acp-21-8169-2021-supplement.pdf"}, {"href": "https://escholarship.org/content/qt31s4c3tr/qt31s4c3tr.pdf"}, {"href": "https://escholarship.org/content/qt4f95b02f/qt4f95b02f.pdf"}, {"href": "https://doi.org/10.5194/acp-2021-4"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Goldschmidt2021%20abstracts", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/acp-2021-4", "name": "item", "description": "10.5194/acp-2021-4", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/acp-2021-4"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-01-01T00:00:00Z"}}, {"id": "10.5194/essd-10-405-2018", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:19:41Z", "type": "Journal Article", "created": "2018-03-12", "title": "Global Carbon Budget 2017", "description": "

Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere \u2013 the global carbon budget \u2013 is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on land-cover change data and bookkeeping models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as \u00b11\u03c3. For the last decade available (2007\u20132016), EFF was 9.4\u202f\u00b1\u202f0.5\u202fGtC\u202fyr\u22121, ELUC 1.3\u202f\u00b1\u202f0.7\u202fGtC\u202fyr\u22121, GATM 4.7\u202f\u00b1\u202f0.1\u202fGtC\u202fyr\u22121, SOCEAN 2.4\u202f\u00b1\u202f0.5\u202fGtC\u202fyr\u22121, and SLAND 3.0\u202f\u00b1\u202f0.8\u202fGtC\u202fyr\u22121, with a budget imbalance BIM of 0.6\u202fGtC\u202fyr\u22121 indicating overestimated emissions and/or underestimated sinks. For year 2016 alone, the growth in EFF was approximately zero and emissions remained at 9.9\u202f\u00b1\u202f0.5\u202fGtC\u202fyr\u22121. Also for 2016, ELUC was 1.3\u202f\u00b1\u202f0.7\u202fGtC\u202fyr\u22121, GATM was 6.1\u202f\u00b1\u202f0.2\u202fGtC\u202fyr\u22121, SOCEAN was 2.6\u202f\u00b1\u202f0.5\u202fGtC\u202fyr\u22121, and SLAND was 2.7\u202f\u00b1\u202f1.0\u202fGtC\u202fyr\u22121, with a small BIM of \u22120.3\u202fGtC. GATM continued to be higher in 2016 compared to the past decade (2007\u20132016), reflecting in part the high fossil emissions and the small SLAND consistent with El Ni\u00f1o conditions. The global atmospheric CO2 concentration reached 402.8\u202f\u00b1\u202f0.1\u202fppm averaged over 2016. For 2017, preliminary data for the first 6\u20139\u00a0months indicate a renewed growth in EFF of +2.0\u202f% (range of 0.8 to 3.0\u202f%) based on national emissions projections for China, USA, and India, and projections of gross domestic product (GDP) corrected for recent changes in the carbon intensity of the economy for the rest of the world. This living data update documents changes in the methods and data sets used in this new global carbon budget compared with previous publications of this data set (Le Qu\u00e9r\u00e9 et al., 2016, 2015b, a, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2017 (GCP, 2017).

", "keywords": ["ENVIRONMENT SIMULATOR JULES", "550", "530 Physics", "[PHYS.PHYS.PHYS-GEO-PH] Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph]", "MIXED-LAYER SCHEME", "INTERNATIONAL-TRADE", "7. Clean energy", "01 natural sciences", "333", "12. Responsible consumption", "FOSSIL-FUEL COMBUSTION", "ANTHROPOGENIC CO2 UPTAKE", "11. Sustainability", "SDG 13 - Climate Action", "Life Science", "GE1-350", "SDG 14 - Life Below Water", "ATMOSPHERIC CO2", "DIOXIDE EMISSIONS", "SDG 15 - Life on Land", "0105 earth and related environmental sciences", "LAND-COVER CHANGE", "QE1-996.5", "info:eu-repo/classification/ddc/550", "EARTH SYSTEM MODEL", "ddc:550", "VEGETATION MODEL", "Geology", "15. Life on land", "Environmental sciences", "Earth sciences", "13. Climate action", "8. Economic growth", "General Earth and Planetary Sciences"]}, "links": [{"href": "https://ueaeprints.uea.ac.uk/id/eprint/66578/1/Published_manuscript.pdf"}, {"href": "http://oceanrep.geomar.de/42391/1/essd-10-405-2018.pdf"}, {"href": "https://boris.unibe.ch/116576/1/lequere18essd.pdf"}, {"href": "https://pure.iiasa.ac.at/id/eprint/15161/1/essd-10-405-2018.pdf"}, {"href": "http://pure.iiasa.ac.at/id/eprint/15161/1/essd-10-405-2018.pdf"}, {"href": "https://essd.copernicus.org/articles/10/405/2018/essd-10-405-2018.pdf"}, {"href": "https://doi.org/10.5194/essd-10-405-2018"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Earth%20System%20Science%20Data", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/essd-10-405-2018", "name": "item", "description": "10.5194/essd-10-405-2018", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/essd-10-405-2018"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-03-12T00:00:00Z"}}, {"id": "10.5061/dryad.s87008d", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:19:32Z", "type": "Dataset", "title": "Data from: Cross-biome patterns in soil microbial respiration predictable from evolutionary theory on thermal adaptation", "description": "unspecifiedClimate warming may stimulate microbial metabolism of soil carbon, causing a carbon cycle-climate feedback whereby carbon is redistributed from soil to atmospheric CO2. The magnitude of this feedback is uncertain, in part because warming-induced shifts in microbial physiology and/or community composition could retard or accelerate soil carbon losses. Here, we measure microbial respiration rates for soils collected from 22 sites in each of three years, at locations spanning boreal to tropical climates. Respiration was measured in the laboratory with standard temperatures, moisture and excess carbon substrate, to allow physiological and community effects to be detected independent from the influence of these abiotic controls. Patterns in respiration for soils collected across the climate gradient are consistent with evolutionary theory on physiological responses that compensate for positive effects of temperature on metabolism. Respiration rates per unit microbial biomass were as much as 2.6-times higher for soils sampled from sites with a mean annual temperature (MAT) of -2.0 versus 21.7\u00baC. Subsequent 100-day incubations suggested differences in the plasticity of the thermal response among microbial communities, with communities sampled from sites with higher MAT having a more plastic response. Our findings are consistent with adaptive metabolic responses to contrasting thermal regimes that are also observed in plants and animals. These results may help build confidence in soil carbon-climate feedback projections by improving understanding of microbial processes represented in biogeochemical models.", "keywords": ["2. Zero hunger", "soil organic carbon", "Thermal acclimation", "Microbial physiology", "13. Climate action", "soil biogeochemical models", "Earth system models", "Soil respiration", "15. Life on land", "Soil carbon", "soil microbial biomass"], "contacts": [{"organization": "Bradford, Mark A., McCulley, Rebecca L., Crowther, Thomas W., Oldfield, Emily E., Wood, Stephen A., Fierer, Noah,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.s87008d"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.s87008d", "name": "item", "description": "10.5061/dryad.s87008d", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.s87008d"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-01-18T00:00:00Z"}}, {"id": "10.5194/bg-16-4851-2019", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:19:36Z", "type": "Journal Article", "created": "2019-12-20", "title": "\"Global biosphere\u2013climate interaction: a causal appraisal of observations and models over multiple temporal scales\"", "description": "

Abstract. Improving the skill of Earth system models (ESMs) in representing climate\uffe2\uff80\uff93vegetation interactions is crucial to enhance our predictions of future climate and ecosystem functioning. Therefore, ESMs need to correctly simulate the impact of climate on vegetation, but likewise feedbacks of vegetation on climate must be adequately represented. However, model predictions at large spatial scales remain subjected to large uncertainties, mostly due to the lack of observational patterns to benchmark them. Here, the bidirectional nature of climate\uffe2\uff80\uff93vegetation interactions is explored across multiple temporal scales by adopting a spectral Granger causality framework that allows identification of potentially co-dependent variables. Results based on global and multi-decadal records of remotely sensed leaf area index (LAI) and observed atmospheric data show that the climate control on vegetation variability increases with longer temporal scales, being higher at inter-annual than multi-month scales. Globally, precipitation is the most dominant driver of vegetation at monthly scales, particularly in (semi-)arid regions. The seasonal LAI variability in energy-driven latitudes is mainly controlled by radiation, while air temperature controls vegetation growth and decay in high northern latitudes at inter-annual scales. These observational results are used as a benchmark to evaluate four ESM simulations from the Coupled Model Intercomparison Project Phase\uffc2\uffa05 (CMIP5). Findings indicate a tendency of ESMs to over-represent the climate control on LAI dynamics and a particular overestimation of the dominance of precipitation in arid and semi-arid regions at inter-annual scales. Analogously, CMIP5 models overestimate the control of air temperature on seasonal vegetation variability, especially in forested regions. Overall, climate impacts on LAI are found to be stronger than the feedbacks of LAI on climate in both observations and models; in other words, local climate variability leaves a larger imprint on temporal LAI dynamics than vice versa. Note however that while vegetation reacts directly to its local climate conditions, the spatially collocated character of the analysis does not allow for the identification of remote feedbacks, which might result in an underestimation of the biophysical effects of vegetation on climate. Nonetheless, the widespread effect of LAI variability on radiation, as observed over the northern latitudes due to albedo changes, is overestimated by the CMIP5 models. Overall, our experiments emphasise the potential of benchmarking the representation of particular interactions in online ESMs using causal statistics in combination with observational data, as opposed to the more conventional evaluation of the magnitude and dynamics of individual variables.

", "keywords": ["0301 basic medicine", "Evolution", "LAND-SURFACE MODELS", "01 natural sciences", "RECENT TRENDS", "03 medical and health sciences", "Behavior and Systematics", "Life", "QH501-531", "NET PRIMARY PRODUCTION", "QH540-549.5", "Earth-Surface Processes", "0105 earth and related environmental sciences", "QE1-996.5", "EARTH SYSTEM MODEL", "Ecology", "LEAF-AREA INDEX", "Biology and Life Sciences", "Geology", "15. Life on land", "DATA SETS", "13. Climate action", "Earth and Environmental Sciences", "FEEDBACKS", "CO2", "VEGETATION", "SENSITIVITY"]}, "links": [{"href": "https://bg.copernicus.org/articles/16/4851/2019/bg-16-4851-2019.pdf"}, {"href": "https://doi.org/10.5194/bg-16-4851-2019"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Biogeosciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/bg-16-4851-2019", "name": "item", "description": "10.5194/bg-16-4851-2019", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/bg-16-4851-2019"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-12-20T00:00:00Z"}}, {"id": "10.5194/acp-21-8127-2021", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:19:35Z", "type": "Journal Article", "created": "2021-05-27", "title": "Improved representation of the global dust cycle using observational constraints on dust properties and abundance", "description": "

Abstract. Even though desert dust is the most abundant aerosol by mass in Earth's atmosphere, atmospheric models struggle to accurately represent its spatial and temporal distribution. These model errors are partially caused by fundamental difficulties in simulating dust emission in coarse-resolution models and in accurately representing dust microphysical properties. Here we mitigate these problems by developing a new methodology that yields an improved representation of the global dust cycle. We present an analytical framework that uses inverse modeling to integrate an ensemble of global model simulations with observational constraints on the dust size distribution, extinction efficiency, and regional dust aerosol optical depth. We then compare the inverse model results against independent measurements of dust surface concentration and deposition flux and find that errors are reduced by approximately a factor of 2\u00a0relative to current model simulations of the Northern Hemisphere dust cycle. The inverse model results show smaller improvements in the less dusty Southern Hemisphere, most likely because both the model simulations and the observational constraints used in the inverse model are less accurate. On a global basis, we find that the emission flux of dust with a geometric diameter up to 20\u2009\u00b5m (PM20) is approximately 5000\u2009Tg\u2009yr\u22121, which is greater than most models account for. This larger PM20 dust flux is needed to match observational constraints showing a large atmospheric loading of coarse dust. We obtain gridded datasets of dust emission, vertically integrated loading, dust aerosol optical depth, (surface) concentration, and wet and dry deposition fluxes that are resolved by season and particle size. As our results indicate that this dataset is more accurate than current model simulations and the MERRA-2 dust reanalysis product, it can be used to improve quantifications of dust impacts on the Earth system.

", "keywords": ["Atmospheric sciences", "550", "QC1-999", "\u00c0rees tem\u00e0tiques de la UPC::Enginyeria agroaliment\u00e0ria::Ci\u00e8ncies de la terra i de la vida", "Dust emissions", "01 natural sciences", "Earth system -- environmental sciences", "Atmospheric Sciences", "Dust; Aerosol; Climate Models; Earth System Models;", "Atmospheric models", "Simulaci\u00f3 per ordinador", "Meteorology & Atmospheric Sciences", "Atmospheric model simulations", "QD1-999", "Earth system", "0105 earth and related environmental sciences", "[SDU.OCEAN]Sciences of the Universe [physics]/Ocean", "info:eu-repo/classification/ddc/550", "Atmosphere", "Climate change science", "ddc:550", "[SDU.OCEAN] Sciences of the Universe [physics]/Ocean", " Atmosphere", "Physics", "Dust", "Computer simulation", "15. Life on land", "Atmosfera -- Aspectes ambientals", "520", "[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces", " environment", "Climate Action", "Earth sciences", "Chemistry", "Model simulation", "13. Climate action", ":Enginyeria agroaliment\u00e0ria::Ci\u00e8ncies de la terra i de la vida [\u00c0rees tem\u00e0tiques de la UPC]", "Earth Sciences", "\u00c0rees tem\u00e0tiques de la UPC::Desenvolupament hum\u00e0 i sostenible::Degradaci\u00f3 ambiental::Contaminaci\u00f3 atmosf\u00e8rica", "Aerosols--Measurement", "Desert dust", "[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces", "environment", "Astronomical and Space Sciences", ":Desenvolupament hum\u00e0 i sostenible::Degradaci\u00f3 ambiental::Contaminaci\u00f3 atmosf\u00e8rica [\u00c0rees tem\u00e0tiques de la UPC]"]}, "links": [{"href": "https://boa.unimib.it/bitstream/10281/321612/2/10281-321612_VoR.pdf"}, {"href": "https://acp.copernicus.org/articles/21/8127/2021/acp-21-8127-2021.pdf"}, {"href": "https://acp.copernicus.org/articles/21/8127/2021/acp-21-8127-2021-supplement.pdf"}, {"href": "https://escholarship.org/content/qt5g7457v8/qt5g7457v8.pdf"}, {"href": "https://doi.org/10.5194/acp-21-8127-2021"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Atmospheric%20Chemistry%20and%20Physics", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/acp-21-8127-2021", "name": "item", "description": "10.5194/acp-21-8127-2021", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/acp-21-8127-2021"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-11-23T00:00:00Z"}}, {"id": "10.5194/gmd-14-5637-2021", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:19:43Z", "type": "Journal Article", "created": "2021-09-13", "title": "EC-Earth3-AerChem: a global climate model with interactive aerosols and atmospheric chemistry participating in CMIP6", "description": "

Abstract. This paper documents the global climate model EC-Earth3-AerChem, one of the members of the EC-Earth3 family of models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6). EC-Earth3-AerChem has interactive aerosols and atmospheric chemistry and contributes to the Aerosols and Chemistry Model Intercomparison Project (AerChemMIP). In this paper, we give an overview of the model, describe in detail how it differs from the other EC-Earth3 configurations, and outline the new features compared with the previously documented version of the model (EC-Earth 2.4). We explain how the model was tuned and spun up under preindustrial conditions and characterize the model's general performance on the basis of a selection of coupled simulations conducted for CMIP6. The net energy imbalance at the top of the atmosphere in the preindustrial control simulation is on average \u22120.09\u2009W\u2009m\u22122 with a standard deviation due to interannual variability of 0.25\u2009W\u2009m\u22122, showing no significant drift. The global surface air temperature in the simulation is on average 14.08\u2009\u2218C with an interannual standard deviation of 0.17\u2009\u2218C, exhibiting a small drift of 0.015\u2009\u00b1\u20090.005\u2009\u2218C per century. The model's effective equilibrium climate sensitivity is estimated at 3.9\u2009\u2218C, and its transient climate response is estimated at 2.1\u2009\u2218C. The CMIP6 historical simulation displays spurious interdecadal variability in Northern Hemisphere temperatures, resulting in a large spread across ensemble members and a tendency to underestimate observed annual surface temperature anomalies from the early 20th century onwards. The observed warming of the Southern Hemisphere is well reproduced by the model. Compared with the ECMWF (European Centre for Medium-Range Weather Forecasts) Reanalysis version 5 (ERA5), the surface air temperature climatology for 1995\u20132014 has an average bias of \u22120.86\u2009\u00b1\u20090.05\u2009\u2218C with a standard deviation across ensemble members of 0.35\u2009\u2218C in the Northern Hemisphere and 1.29\u2009\u00b1\u20090.02\u2009\u2218C with a corresponding standard deviation of 0.05\u2009\u2218C in the Southern Hemisphere. The Southern Hemisphere warm bias is largely caused by errors in shortwave cloud radiative effects over the Southern Ocean, a deficiency of many climate models. Changes in the emissions of near-term climate forcers (NTCFs) have significant effects on the global climate from the second half of the 20th century onwards. For the SSP3-7.0 Shared Socioeconomic Pathway, the model gives a global warming at the end of the 21st century (2091\u20132100) of 4.9\u2009\u2218C above the preindustrial mean. A 0.5\u2009\u2218C stronger warming is obtained for the AerChemMIP scenario with reduced emissions of NTCFs. With concurrent reductions of future methane concentrations, the warming is projected to be reduced by 0.5\u2009\u2218C.

", "keywords": ["Atmospheric chemistry", ":Desenvolupament hum\u00e0 i sostenible::Degradaci\u00f3 ambiental [\u00c0rees tem\u00e0tiques de la UPC]", "EARTH SYSTEM MODELS", "MINERAL-COMPOSITION", "MODIFIED BAND APPROACH", "7. Clean energy", ":Enginyeria qu\u00edmica::Qu\u00edmica del medi ambient::Qu\u00edmica atmosf\u00e8rica [\u00c0rees tem\u00e0tiques de la UPC]", "SULFURIC-ACID", "\u00c0rees tem\u00e0tiques de la UPC::Enginyeria qu\u00edmica::Qu\u00edmica del medi ambient::Qu\u00edmica atmosf\u00e8rica", "EC-EARTH", "ORGANIC AEROSOL", "\u00c0rees tem\u00e0tiques de la UPC::Desenvolupament hum\u00e0 i sostenible::Degradaci\u00f3 ambiental", "Aerosols", "QE1-996.5", "Escalfament global", "Global warming", "Geology", "Climatic changes", "16. Peace & justice", "Climate Science", "COMPUTATIONAL PERFORMANCE", "DUST AEROSOLS", "Qu\u00edmica atmosf\u00e8rica", "13. Climate action", "GREENHOUSE-GAS CONCENTRATIONS", "BIOMASS BURNING EMISSIONS", "Geosciences", "Klimatvetenskap", "Canvis clim\u00e0tics"]}, "links": [{"href": "https://iris.polito.it/bitstream/11583/2959536/1/vannoije2021_gmd.pdf"}, {"href": "https://gmd.copernicus.org/articles/14/5637/2021/gmd-14-5637-2021.pdf"}, {"href": "https://doi.org/10.5194/gmd-14-5637-2021"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoscientific%20Model%20Development", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/gmd-14-5637-2021", "name": "item", "description": "10.5194/gmd-14-5637-2021", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/gmd-14-5637-2021"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-12-21T00:00:00Z"}}, {"id": "10.5281/zenodo.14563816", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:20:18Z", "type": "Dataset", "title": "Transformation Rate Maps of Dissolved Organic Carbon in the Contiguous U.S.", "description": "unspecifiedWe develop two new maps of the dissolved organic carbon (DOC) transformation rate ( (P_r )) over the contiguous United States. Those maps are derived by combining the USGS riverine DOC observations, soil organic carbon (SOC) data from two sources\u2014HWSD v1.2 and SoilGrids 2.0, and the watershed characteristics from two existing datasets medium-resolution NHDplus and ScienceBase, and state-of-the-art machine learning techniques.", "keywords": ["13. Climate action", "Machine learning", "Earth system modeling", "15. Life on land", "Riverine biogeochemical", "Dissolved organic carbon"], "contacts": [{"organization": "Li, Lingbo, Li, Hong-Yi, Abeshu, Guta,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.14563816"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.14563816", "name": "item", "description": "10.5281/zenodo.14563816", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.14563816"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-12-27T00:00:00Z"}}, {"id": "21.11116/0000-0005-8A29-2", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:22:20Z", "type": "Journal Article", "created": "2019-04-09", "title": "Comparison With Global Soil Radiocarbon Observations Indicates Needed Carbon Cycle Improvements in the E3SM Land Model", "description": "Abstract

We evaluated global soil organic carbon (SOC) stocks and turnover time predictions from a global land model (ELMv1\uffe2\uff80\uff90ECA) integrated in an Earth System Model (E3SM) by comparing them with observed soil bulk and \uffce\uff9414C values around the world. We analyzed observed and simulated SOC stocks and \uffce\uff9414C values using machine learning methods at the Earth System Model grid cell scale (~200\uffc2\uffa0km). In grid cells with sufficient observations, the model provided reasonable estimates of soil carbon stocks across soil depth and \uffce\uff9414C values near the surface but underestimated \uffce\uff9414C at depth. Among many explanatory variables, soil albedo index, soil order, plant function type, air temperature, and SOC content were major factors affecting predicted SOC \uffce\uff9414C values. The influences of soil albedo index, soil order, and air temperature were primarily important in the shallow subsurface (\uffe2\uff89\uffa430\uffc2\uffa0cm). We also performed sensitivity studies using different vertical root distributions and decomposition turnover times and compared to observed SOC stock and \uffce\uff9414C profiles. The analyses support the role of vegetation in affecting soil carbon turnover, particularly in deep soil, possibly through supplying fresh carbon and degrading physical\uffe2\uff80\uff90chemical protection of SOC via root activities. Allowing for grid cell\uffe2\uff80\uff90specific rooting and decomposition rates substantially reduced discrepancies between observed and predicted \uffce\uff9414C values and SOC content. Our results highlight the need for more explicit representation of roots, microbes, and soil physical protection in land models. - The SMAP L4C Nature Run uses soil moisture and soil temperature estimates from the L4SM Nature Run, which is a model-only version of the operational L4SM product that does not assimilate SMAP brightness temperature data. This repository contains the full README for the data. The data can be downloaded from: http://files.ntsg.umt.edu/data/SMAP_L4C_NatureRun/NRv7.2/", "keywords": ["carbon flux", "soil organic carbon", "primary productivity", "13. Climate action", "net ecosystem exchange", "15. Life on land", "earth system", "respiration"], "contacts": [{"organization": "Endsley, K. Arthur, Jones, Lucas, Kimball, John,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4247969"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4247969", "name": "item", "description": "10.5281/zenodo.4247969", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4247969"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-11-05T00:00:00Z"}}, {"id": "11583/2959536", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:21:57Z", "type": "Journal Article", "created": "2021-09-13", "title": "EC-Earth3-AerChem: a global climate model with interactive aerosols and atmospheric chemistry participating in CMIP6", "description": "

Abstract. This paper documents the global climate model EC-Earth3-AerChem, one of the members of the EC-Earth3 family of models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6). EC-Earth3-AerChem has interactive aerosols and atmospheric chemistry and contributes to the Aerosols and Chemistry Model Intercomparison Project (AerChemMIP). In this paper, we give an overview of the model, describe in detail how it differs from the other EC-Earth3 configurations, and outline the new features compared with the previously documented version of the model (EC-Earth 2.4). We explain how the model was tuned and spun up under preindustrial conditions and characterize the model's general performance on the basis of a selection of coupled simulations conducted for CMIP6. The net energy imbalance at the top of the atmosphere in the preindustrial control simulation is on average \u22120.09\u2009W\u2009m\u22122 with a standard deviation due to interannual variability of 0.25\u2009W\u2009m\u22122, showing no significant drift. The global surface air temperature in the simulation is on average 14.08\u2009\u2218C with an interannual standard deviation of 0.17\u2009\u2218C, exhibiting a small drift of 0.015\u2009\u00b1\u20090.005\u2009\u2218C per century. The model's effective equilibrium climate sensitivity is estimated at 3.9\u2009\u2218C, and its transient climate response is estimated at 2.1\u2009\u2218C. The CMIP6 historical simulation displays spurious interdecadal variability in Northern Hemisphere temperatures, resulting in a large spread across ensemble members and a tendency to underestimate observed annual surface temperature anomalies from the early 20th century onwards. The observed warming of the Southern Hemisphere is well reproduced by the model. Compared with the ECMWF (European Centre for Medium-Range Weather Forecasts) Reanalysis version 5 (ERA5), the surface air temperature climatology for 1995\u20132014 has an average bias of \u22120.86\u2009\u00b1\u20090.05\u2009\u2218C with a standard deviation across ensemble members of 0.35\u2009\u2218C in the Northern Hemisphere and 1.29\u2009\u00b1\u20090.02\u2009\u2218C with a corresponding standard deviation of 0.05\u2009\u2218C in the Southern Hemisphere. The Southern Hemisphere warm bias is largely caused by errors in shortwave cloud radiative effects over the Southern Ocean, a deficiency of many climate models. Changes in the emissions of near-term climate forcers (NTCFs) have significant effects on the global climate from the second half of the 20th century onwards. For the SSP3-7.0 Shared Socioeconomic Pathway, the model gives a global warming at the end of the 21st century (2091\u20132100) of 4.9\u2009\u2218C above the preindustrial mean. A 0.5\u2009\u2218C stronger warming is obtained for the AerChemMIP scenario with reduced emissions of NTCFs. With concurrent reductions of future methane concentrations, the warming is projected to be reduced by 0.5\u2009\u2218C.

", "keywords": ["Atmospheric chemistry", ":Desenvolupament hum\u00e0 i sostenible::Degradaci\u00f3 ambiental [\u00c0rees tem\u00e0tiques de la UPC]", "EARTH SYSTEM MODELS", "MINERAL-COMPOSITION", "MODIFIED BAND APPROACH", "7. Clean energy", ":Enginyeria qu\u00edmica::Qu\u00edmica del medi ambient::Qu\u00edmica atmosf\u00e8rica [\u00c0rees tem\u00e0tiques de la UPC]", "SULFURIC-ACID", "\u00c0rees tem\u00e0tiques de la UPC::Enginyeria qu\u00edmica::Qu\u00edmica del medi ambient::Qu\u00edmica atmosf\u00e8rica", "EC-EARTH", "ORGANIC AEROSOL", "\u00c0rees tem\u00e0tiques de la UPC::Desenvolupament hum\u00e0 i sostenible::Degradaci\u00f3 ambiental", "Aerosols", "QE1-996.5", "Escalfament global", "Global warming", "Geology", "Climatic changes", "16. Peace & justice", "Climate Science", "COMPUTATIONAL PERFORMANCE", "DUST AEROSOLS", "Qu\u00edmica atmosf\u00e8rica", "13. Climate action", "GREENHOUSE-GAS CONCENTRATIONS", "BIOMASS BURNING EMISSIONS", "Geosciences", "Klimatvetenskap", "Canvis clim\u00e0tics"]}, "links": [{"href": "https://iris.polito.it/bitstream/11583/2959536/1/vannoije2021_gmd.pdf"}, {"href": "https://gmd.copernicus.org/articles/14/5637/2021/gmd-14-5637-2021.pdf"}, {"href": "https://doi.org/11583/2959536"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoscientific%20Model%20Development", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "11583/2959536", "name": "item", "description": "11583/2959536", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/11583/2959536"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-12-21T00:00:00Z"}}, {"id": "10.7941/D1432P", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:21:35Z", "type": "Dataset", "title": "Continental United States may lose 1.8 petagrams of soil organic carbon under climate change by 2100", "description": "unspecifiedAims: High-resolution information on soils\u2019 vulnerability to climate-induced soil organic carbon (SOC) loss can enable environmental scientists, land managers, and policy makers to develop targeted mitigation strategies. This study aims to estimate baseline and decadal changes in continental US surface SOC stocks under future emission scenarios. \u00a0 Location: Continental United States \u00a0 Time Period: 2014-2100 \u00a0 Results: Baseline SOC projections from ML approaches captured more than 50% of variability in SOC observations, whereas ESMs represented only 6-16% of observed SOC variability. ML estimates showed a mean total loss of 1.8 Pg C from US surface soils under the high-emission scenario by 2100, whereas ESMs showed no significant change in SOC stocks with wide variation among ESMs. Both ML and ESM predictions agree on the direction of SOC change (net emissions or sequestration) across 46%\u201351% of continental US land area. These differences are attributable to the high-resolution site-specific data used in ML model compared to the relatively coarse grid represented in CMIP6 ESMs. \u00a0 Main conclusions: Our high-resolution estimates of baseline SOC stocks, identification of key environmental controllers, and projection of SOC changes from US land cover types under future climate scenarios suggest the need for high-resolution simulations of SOC in ESMs to represent the heterogeneity of SOC. We found that the SOC change is sensitive to key soil related factors (e.g. soil drainage and soil order) that have not been historically considered as input parameters in ESMs, because currently more than 95% variability in the SOC of CMIP6 ESMs are controlled by net primary productivity, temperature, and precipitation. Using additional environmental factors to estimate the baseline SOC stocks and predict the future trajectory of SOC change can provide more accurate results.", "keywords": ["soil organic carbon", "earth system model", "13. Climate action", "environmental factors", "future projection", "FOS: Earth and related environmental sciences", "15. Life on land", "climate"], "contacts": [{"organization": "Gautam, Sagar", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.7941/D1432P"}, {"rel": "self", "type": "application/geo+json", "title": "10.7941/D1432P", "name": "item", "description": "10.7941/D1432P", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7941/D1432P"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-03-31T00:00:00Z"}}, {"id": "10281/321612", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:21:45Z", "type": "Journal Article", "created": "2021-05-27", "title": "Improved representation of the global dust cycle using observational constraints on dust properties and abundance", "description": "

Abstract. Even though desert dust is the most abundant aerosol by mass in Earth's atmosphere, atmospheric models struggle to accurately represent its spatial and temporal distribution. These model errors are partially caused by fundamental difficulties in simulating dust emission in coarse-resolution models and in accurately representing dust microphysical properties. Here we mitigate these problems by developing a new methodology that yields an improved representation of the global dust cycle. We present an analytical framework that uses inverse modeling to integrate an ensemble of global model simulations with observational constraints on the dust size distribution, extinction efficiency, and regional dust aerosol optical depth. We then compare the inverse model results against independent measurements of dust surface concentration and deposition flux and find that errors are reduced by approximately a factor of 2\u00a0relative to current model simulations of the Northern Hemisphere dust cycle. The inverse model results show smaller improvements in the less dusty Southern Hemisphere, most likely because both the model simulations and the observational constraints used in the inverse model are less accurate. On a global basis, we find that the emission flux of dust with a geometric diameter up to 20\u2009\u00b5m (PM20) is approximately 5000\u2009Tg\u2009yr\u22121, which is greater than most models account for. This larger PM20 dust flux is needed to match observational constraints showing a large atmospheric loading of coarse dust. We obtain gridded datasets of dust emission, vertically integrated loading, dust aerosol optical depth, (surface) concentration, and wet and dry deposition fluxes that are resolved by season and particle size. As our results indicate that this dataset is more accurate than current model simulations and the MERRA-2 dust reanalysis product, it can be used to improve quantifications of dust impacts on the Earth system.

", "keywords": ["Atmospheric sciences", "550", "QC1-999", "\u00c0rees tem\u00e0tiques de la UPC::Enginyeria agroaliment\u00e0ria::Ci\u00e8ncies de la terra i de la vida", "Dust emissions", "01 natural sciences", "Earth system -- environmental sciences", "Atmospheric Sciences", "Dust; Aerosol; Climate Models; Earth System Models;", "Atmospheric models", "Simulaci\u00f3 per ordinador", "Meteorology & Atmospheric Sciences", "Atmospheric model simulations", "QD1-999", "Earth system", "0105 earth and related environmental sciences", "[SDU.OCEAN]Sciences of the Universe [physics]/Ocean", "info:eu-repo/classification/ddc/550", "Atmosphere", "Climate change science", "ddc:550", "[SDU.OCEAN] Sciences of the Universe [physics]/Ocean", " Atmosphere", "Physics", "Dust", "Computer simulation", "15. Life on land", "Atmosfera -- Aspectes ambientals", "520", "[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces", " environment", "Climate Action", "Earth sciences", "Chemistry", "Model simulation", "13. Climate action", ":Enginyeria agroaliment\u00e0ria::Ci\u00e8ncies de la terra i de la vida [\u00c0rees tem\u00e0tiques de la UPC]", "Earth Sciences", "\u00c0rees tem\u00e0tiques de la UPC::Desenvolupament hum\u00e0 i sostenible::Degradaci\u00f3 ambiental::Contaminaci\u00f3 atmosf\u00e8rica", "Aerosols--Measurement", "Desert dust", "[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces", "environment", "Astronomical and Space Sciences", ":Desenvolupament hum\u00e0 i sostenible::Degradaci\u00f3 ambiental::Contaminaci\u00f3 atmosf\u00e8rica [\u00c0rees tem\u00e0tiques de la UPC]"]}, "links": [{"href": "https://boa.unimib.it/bitstream/10281/321612/2/10281-321612_VoR.pdf"}, {"href": "https://acp.copernicus.org/articles/21/8127/2021/acp-21-8127-2021.pdf"}, {"href": "https://acp.copernicus.org/articles/21/8127/2021/acp-21-8127-2021-supplement.pdf"}, {"href": "https://escholarship.org/content/qt5g7457v8/qt5g7457v8.pdf"}, {"href": "https://doi.org/10281/321612"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Atmospheric%20Chemistry%20and%20Physics", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10281/321612", "name": "item", "description": "10281/321612", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10281/321612"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-11-23T00:00:00Z"}}, {"id": "10281/321610", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:21:45Z", "type": "Journal Article", "created": "2021-01-18", "title": "Contribution of the world's main dust source regions to the global cycle of desert dust", "description": "

Abstract. Even though desert dust is the most abundant aerosol by mass in Earth's atmosphere, the relative contributions of the world\u2019s major dust source regions to the global dust cycle remain poorly constrained. This problem hinders accounting for the potentially large impact of regional differences in dust properties on clouds, the Earth's energy balance, and terrestrial and marine biogeochemical cycles. Here, we constrain the contribution of each of the world\u2019s main dust source regions to the global dust cycle. We use an analytical framework that integrates an ensemble of global model simulations with observationally informed constraints on the dust size distribution, extinction efficiency, and regional dust aerosol optical depth. We obtain a data set that constrains the relative contribution of each of nine major source regions to size-resolved dust emission, atmospheric loading, optical depth, concentration, and deposition flux. We find that the 22\u201329\u2009Tg (one standard error range) global loading of dust with geometric diameter up to 20\u2009\u03bcm is partitioned as follows: North African source regions contribute ~50\u2009% (11\u201315\u2009Tg), Asian source regions contribute ~40\u2009% (8\u201313\u2009Tg), and North American and Southern Hemisphere regions contribute ~10\u2009% (1.8\u20133.2\u2009Tg). Current models might on average be overestimating the contribution of North African sources to atmospheric dust loading at ~65\u2009%, while underestimating the contribution of Asian dust at ~30\u2009%. However, both our results and current models could be affected by unquantified biases, such as due to errors in separating dust aerosol optical depth from that produced by other aerosol species in remote sensing retrievals in poorly observed desert regions. Our results further show that each source region's dust loading peaks in local spring and summer, which is partially driven by increased dust lifetime in those seasons. We also quantify the dust deposition flux to the Amazon rainforest to be ~10\u2009Tg/year, which is a factor of 2\u20133 less than inferred from satellite data by previous work that likely overestimated dust deposition by underestimating the dust mass extinction efficiency. The data obtained in this paper can be used to obtain improved constraints on dust impacts on clouds, climate, biogeochemical cycles, and other parts of the Earth system.

", "keywords": ["550", "3702 Climate change science (for-2020)", "QC1-999", "Global dust cycle", "0201 Astronomical and Space Sciences (for)", "0401 Atmospheric Sciences (for)", "\u00c0rees tem\u00e0tiques de la UPC::Enginyeria agroaliment\u00e0ria::Ci\u00e8ncies de la terra i de la vida", "3701 Atmospheric Sciences (for-2020)", "01 natural sciences", "Meteorology & Atmospheric Sciences (science-metrix)", "Atmospheric Sciences", "Atmospheric models", "Earth's atmosphere", "Simulaci\u00f3 per ordinador", "14 Life Below Water (sdg)", "Meteorology & Atmospheric Sciences", "Dust; Aerosols; Climate Models; Earth System Models;", "14. Life underwater", "Life Below Water", "QD1-999", "0105 earth and related environmental sciences", "[SDU.OCEAN]Sciences of the Universe [physics]/Ocean", "info:eu-repo/classification/ddc/550", "3701 Atmospheric sciences (for-2020)", "Climate change science", "Atmosphere", "ddc:550", "[SDU.OCEAN] Sciences of the Universe [physics]/Ocean", " Atmosphere", "Physics", "Aerosol model simulations", "15. Life on land", "Atmosfera -- Aspectes ambientals", "[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces", " environment", "Climate Action", "Earth sciences", "Chemistry", "37 Earth Sciences (for-2020)", "13. Climate action", ":Enginyeria agroaliment\u00e0ria::Ci\u00e8ncies de la terra i de la vida [\u00c0rees tem\u00e0tiques de la UPC]", "Air quality", "Earth Sciences", "13 Climate Action (sdg)", "Aerosols--Measurement", "Desert dust", "[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces", "environment", "Astronomical and Space Sciences"]}, "links": [{"href": "https://boa.unimib.it/bitstream/10281/321610/1/Kok_2021_ACP_Dust-global.pdf"}, {"href": "https://acp.copernicus.org/articles/21/8169/2021/acp-21-8169-2021.pdf"}, {"href": "https://acp.copernicus.org/articles/21/8169/2021/acp-21-8169-2021-supplement.pdf"}, {"href": "https://escholarship.org/content/qt31s4c3tr/qt31s4c3tr.pdf"}, {"href": "https://escholarship.org/content/qt4f95b02f/qt4f95b02f.pdf"}, {"href": "https://doi.org/10281/321610"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Goldschmidt2021%20abstracts", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10281/321610", "name": "item", "description": "10281/321610", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10281/321610"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-01-01T00:00:00Z"}}, {"id": "11386/4857971", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:21:55Z", "type": "Journal Article", "created": "2023-08-23", "title": "Observing Mineral Dust in Northern Africa, the Middle East, and Europe: Current Capabilities and Challenges ahead for the Development of Dust Services", "description": "Abstract

Mineral dust produced by wind erosion of arid and semiarid surfaces is a major component of atmospheric aerosol that affects climate, weather, ecosystems, and socioeconomic sectors such as human health, transportation, solar energy, and air quality. Understanding these effects and ultimately improving the resilience of affected countries requires a reliable, dense, and diverse set of dust observations, fundamental for the development and the provision of skillful dust-forecast-tailored products. The last decade has seen a notable improvement of dust observational capabilities in terms of considered parameters, geographical coverage, and delivery times, as well as of tailored products of interest to both the scientific community and the various end-users. Given this progress, here we review the current state of observational capabilities, including in situ, ground-based, and satellite remote sensing observations in northern Africa, the Middle East, and Europe for the provision of dust information considering the needs of various users. We also critically discuss observational gaps and related unresolved questions while providing suggestions for overcoming the current limitations. Our review aims to be a milestone for discussing dust observational gaps at a global level to address the needs of users, from research communities to nonscientific stakeholders.

Mineral dust particles suspended in the atmosphere span more than three orders of magnitude in diameter, from less than 0.1 \u00b5m to more than 100 \u00b5m. This wide size range makes dust a unique aerosol species with the ability to interact with many aspects of the Earth system, including radiation, clouds, hydrology, atmospheric chemistry, and biogeochemistry. This review focuses on coarse and super-coarse dust aerosols, which we respectively define as dust particles with a diameter between 2.5 - 10 \u00b5m and 10 - 62.5 \u00b5m. We review several lines of observational evidence indicating that coarse and super-coarse dust particles are transported farther than previously expected and that the abundance of these particles is substantially underestimated in current global models. We synthesize previous studies that used observations, theories, and model simulations to highlight the impacts of coarse and super-coarse dust aerosols on the Earth system, including their effects on dust-radiation interactions, dust-cloud interactions, and atmospheric chemistry, and biogeochemistry. In addition, we examine several limitations in the representation of coarse and super-coarse dust aerosols in current model simulations and in remote-sensing retrievals. Because these limitations substantially contribute to the uncertainties in simulating the abundance and impacts of coarse and super-coarse dust aerosols, we offer some recommendations to facilitate future studies. Overall, we conclude that an accurate representation of coarse and super-coarse properties is critical in understanding the overall impacts of dust aerosols on the Earth system.

", "keywords": ["550", "Climate", "3701 Atmospheric Sciences (for-2020)", "Mineral dust", "01 natural sciences", "Atmospheric Sciences", "04 Earth Sciences (for)", "Earth system", "0105 earth and related environmental sciences", "[SDU.OCEAN]Sciences of the Universe [physics]/Ocean", "37 Earth sciences (for-2020)", "info:eu-repo/classification/ddc/550", "ddc:550", "Atmosphere", "[SDU.OCEAN] Sciences of the Universe [physics]/Ocean", " Atmosphere", "Size distribution", "[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces", " environment", "Coarse dust", "Climate Action", "Earth sciences", "37 Earth Sciences (for-2020)", "41 Environmental sciences (for-2020)", "13. Climate action", "Earth Sciences", "13 Climate Action (sdg)", "[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces", "environment", "Environmental Sciences", "05 Environmental Sciences (for)"]}, "links": [{"href": "https://escholarship.org/content/qt9cp497d5/qt9cp497d5.pdf"}, {"href": "https://doi.org/11250/3119077"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Aeolian%20Research", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "11250/3119077", "name": "item", "description": "11250/3119077", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/11250/3119077"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-09-02T00:00:00Z"}}, {"id": "1912/10214", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:22:07Z", "type": "Journal Article", "created": "2018-03-12", "title": "Global Carbon Budget 2017", "description": "

Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere \u2013 the global carbon budget \u2013 is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on land-cover change data and bookkeeping models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as \u00b11\u03c3. For the last decade available (2007\u20132016), EFF was 9.4\u202f\u00b1\u202f0.5\u202fGtC\u202fyr\u22121, ELUC 1.3\u202f\u00b1\u202f0.7\u202fGtC\u202fyr\u22121, GATM 4.7\u202f\u00b1\u202f0.1\u202fGtC\u202fyr\u22121, SOCEAN 2.4\u202f\u00b1\u202f0.5\u202fGtC\u202fyr\u22121, and SLAND 3.0\u202f\u00b1\u202f0.8\u202fGtC\u202fyr\u22121, with a budget imbalance BIM of 0.6\u202fGtC\u202fyr\u22121 indicating overestimated emissions and/or underestimated sinks. For year 2016 alone, the growth in EFF was approximately zero and emissions remained at 9.9\u202f\u00b1\u202f0.5\u202fGtC\u202fyr\u22121. Also for 2016, ELUC was 1.3\u202f\u00b1\u202f0.7\u202fGtC\u202fyr\u22121, GATM was 6.1\u202f\u00b1\u202f0.2\u202fGtC\u202fyr\u22121, SOCEAN was 2.6\u202f\u00b1\u202f0.5\u202fGtC\u202fyr\u22121, and SLAND was 2.7\u202f\u00b1\u202f1.0\u202fGtC\u202fyr\u22121, with a small BIM of \u22120.3\u202fGtC. GATM continued to be higher in 2016 compared to the past decade (2007\u20132016), reflecting in part the high fossil emissions and the small SLAND consistent with El Ni\u00f1o conditions. The global atmospheric CO2 concentration reached 402.8\u202f\u00b1\u202f0.1\u202fppm averaged over 2016. For 2017, preliminary data for the first 6\u20139\u00a0months indicate a renewed growth in EFF of +2.0\u202f% (range of 0.8 to 3.0\u202f%) based on national emissions projections for China, USA, and India, and projections of gross domestic product (GDP) corrected for recent changes in the carbon intensity of the economy for the rest of the world. This living data update documents changes in the methods and data sets used in this new global carbon budget compared with previous publications of this data set (Le Qu\u00e9r\u00e9 et al., 2016, 2015b, a, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2017 (GCP, 2017).

", "keywords": ["ENVIRONMENT SIMULATOR JULES", "550", "530 Physics", "[PHYS.PHYS.PHYS-GEO-PH] Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph]", "MIXED-LAYER SCHEME", "INTERNATIONAL-TRADE", "7. Clean energy", "01 natural sciences", "333", "12. Responsible consumption", "FOSSIL-FUEL COMBUSTION", "ANTHROPOGENIC CO2 UPTAKE", "11. Sustainability", "SDG 13 - Climate Action", "Life Science", "GE1-350", "SDG 14 - Life Below Water", "ATMOSPHERIC CO2", "DIOXIDE EMISSIONS", "SDG 15 - Life on Land", "0105 earth and related environmental sciences", "LAND-COVER CHANGE", "QE1-996.5", "info:eu-repo/classification/ddc/550", "EARTH SYSTEM MODEL", "ddc:550", "VEGETATION MODEL", "Geology", "15. Life on land", "Environmental sciences", "Earth sciences", "13. Climate action", "8. Economic growth", "General Earth and Planetary Sciences"]}, "links": [{"href": "https://ueaeprints.uea.ac.uk/id/eprint/66578/1/Published_manuscript.pdf"}, {"href": "http://oceanrep.geomar.de/42391/1/essd-10-405-2018.pdf"}, {"href": "https://boris.unibe.ch/116576/1/lequere18essd.pdf"}, {"href": "http://pure.iiasa.ac.at/id/eprint/15161/1/essd-10-405-2018.pdf"}, {"href": "https://pure.iiasa.ac.at/id/eprint/15161/1/essd-10-405-2018.pdf"}, {"href": "https://essd.copernicus.org/articles/10/405/2018/essd-10-405-2018.pdf"}, {"href": "https://doi.org/1912/10214"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Earth%20System%20Science%20Data", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "1912/10214", "name": "item", "description": "1912/10214", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1912/10214"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-03-12T00:00:00Z"}}, {"id": "21.11116/0000-0005-C54E-6", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:22:20Z", "type": "Report", "created": "2020-03-09", "title": "Mathematical Reconstruction of Land Carbon Models From Their Numerical Output: Computing Soil Radiocarbon From 12C Dynamics", "description": "

&lt;p&gt;Radiocarbon (&lt;sup&gt;14&lt;/sup&gt;C) is a powerful tracer of the global carbon cycle that is commonly used to assess carbon cycling rates in various Earth system reservoirs and as a benchmark to assess model performance. Therefore, it has been recommended that Earth System Models (ESMs) participating in the Coupled Model Intercomparison Project Phase 6 report predicted radiocarbon values for relevant carbon pools. However, a detailed representation of radiocarbon dynamics may be an impractical burden on model developers. Here, we present an alternative approach to compute radiocarbon values from the numerical output of an ESM that does not explicitly represent these dynamics. The approach requires computed &lt;sup&gt;12&lt;/sup&gt;C stocks and fluxes among all carbon pools for a particular simulation of the model. From this output, a time&amp;#8208;dependent linear compartmental system is computed with its respective state&amp;#8208;transition matrix. Using transient atmospheric &lt;sup&gt;14&lt;/sup&gt;C values as inputs, the state&amp;#8208;transition matrix is then applied to compute radiocarbon values for each pool, the average value for the entire system, and component fluxes. We demonstrate the approach with ELMv1&amp;#8208;ECA, the land component of an ESM model that explicitly represents &lt;sup&gt;12&lt;/sup&gt;C, and &lt;sup&gt;14&lt;/sup&gt;C in 7 soil pools and 10 vertical layers. Results from our proposed method are highly accurate (relative error &lt;0.01%) compared with the ELMv1&amp;#8208;ECA &lt;sup&gt;12&lt;/sup&gt;C and &lt;sup&gt;14&lt;/sup&gt;C predictions, demonstrating the potential to use this approach in CMIP6 and other model simulations that do not explicitly represent &lt;sup&gt;14&lt;/sup&gt;C.&lt;/p&gt;

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