{"type": "FeatureCollection", "features": [{"id": "10.1016/j.earscirev.2022.104055", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:15:58Z", "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": "10.1002/2015gb005239", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:14:07Z", "type": "Journal Article", "created": "2015-12-19", "title": "Toward More Realistic Projections Of Soil Carbon Dynamics By Earth System Models", "description": "Abstract<p>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.</p>", "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.scitotenv.2024.171158", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:16:54Z", "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": "2026-05-29T16:17:41Z", "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<p>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.</p", "keywords": ["2. Zero hunger", "advanced land modeling", "Earth System Models", "3706 Geophysics (for-2020)", "15. Life on land", "01 natural sciences", "Climate Action", "soil organic carbon", "Geophysics", "37 Earth Sciences (for-2020)", "machine learning", "statistical analysis", "13. Climate action", "0404 Geophysics (for)", "Earth Sciences", "radiocarbon", "13 Climate Action (sdg)", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2018JG004795"}, {"href": "https://escholarship.org/content/qt4h72t9fq/qt4h72t9fq.pdf"}, {"href": "https://doi.org/10.1029/2018jg004795"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Geophysical%20Research%3A%20Biogeosciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1029/2018jg004795", "name": "item", "description": "10.1029/2018jg004795", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1029/2018jg004795"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-05-01T00:00:00Z"}}, {"id": "10.1029/2019ms001776", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:17:41Z", "type": "Journal Article", "created": "2019-12-20", "title": "Mathematical Reconstruction of Land Carbon Models From Their Numerical Output: Computing Soil Radiocarbon From C Dynamics", "description": "Abstract<p>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 &lt;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.</p", "keywords": ["3701 Atmospheric sciences (for-2020)", "Life on Land", "3704 Geoinformatics (for-2020)", "Bioengineering", "Earth system models", "dynamical systems", "0401 Atmospheric Sciences (for)", "3701 Atmospheric Sciences (for-2020)", "compartmental systems", "01 natural sciences", "Atmospheric Sciences", "37 Earth Sciences (for-2020)", "13. Climate action", "Geoinformatics", "Earth Sciences", "radiocarbon", "15 Life on Land (sdg)", "model diagnostics", "carbon cycle models", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2019MS001776"}, {"href": "https://doi.org/10.1029/2019ms001776"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Advances%20in%20Modeling%20Earth%20Systems", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1029/2019ms001776", "name": "item", "description": "10.1029/2019ms001776", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1029/2019ms001776"}, {"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": "10.5194/bg-16-4851-2019", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:21:53Z", "type": "Journal Article", "created": "2019-12-20", "title": "\"Global biosphere\u2013climate interaction: a causal appraisal of observations and models over multiple temporal scales\"", "description": "<p>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.                     </p>", "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/gmd-2020-413", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-05-29T16:22:03Z", "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": "<p>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.                     </p>", "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": "2026-05-29T16:21:36Z", "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": "10.5061/dryad.s87008d", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:21:47Z", "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/acp-2021-4", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:21:50Z", "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": "<?xml version='1.0' encoding='UTF-8'?><article><p>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.                         </p></article>", "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/acp-21-8127-2021", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:21:51Z", "type": "Journal Article", "created": "2021-05-27", "title": "Improved representation of the global dust cycle using observational constraints on dust properties and abundance", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>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.                     </p></article>", "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/essd-10-405-2018", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:22:00Z", "type": "Journal Article", "created": "2018-03-12", "title": "Global Carbon Budget 2017", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>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).                     </p></article>", "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": "10.5194/gmd-14-5637-2021", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:22:02Z", "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": "<?xml version='1.0' encoding='UTF-8'?><article><p>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.                     </p></article>", "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": "2026-05-29T16:22:51Z", "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": "11583/2959536", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:25:16Z", "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": "<?xml version='1.0' encoding='UTF-8'?><article><p>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.</p></article>", "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": "2026-05-29T16:24:40Z", "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": "10281/321610", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:24:56Z", "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": "<?xml version='1.0' encoding='UTF-8'?><article><p>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.</p></article>", "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": "10281/321612", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:24:56Z", "type": "Journal Article", "created": "2021-05-27", "title": "Improved representation of the global dust cycle using observational constraints on dust properties and abundance", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>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.</p></article>", "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": "1912/10214", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:25:33Z", "type": "Journal Article", "created": "2018-03-12", "title": "Global Carbon Budget 2017", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>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).</p></article>", "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": "21.11116/0000-0005-8A29-2", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:25:52Z", "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<p>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.</p", "keywords": ["2. Zero hunger", "advanced land modeling", "Earth System Models", "3706 Geophysics (for-2020)", "15. Life on land", "01 natural sciences", "Climate Action", "soil organic carbon", "Geophysics", "37 Earth Sciences (for-2020)", "machine learning", "statistical analysis", "13. Climate action", "0404 Geophysics (for)", "Earth Sciences", "radiocarbon", "13 Climate Action (sdg)", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2018JG004795"}, {"href": "https://escholarship.org/content/qt4h72t9fq/qt4h72t9fq.pdf"}, {"href": "https://doi.org/21.11116/0000-0005-8A29-2"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Geophysical%20Research%3A%20Biogeosciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "21.11116/0000-0005-8A29-2", "name": "item", "description": "21.11116/0000-0005-8A29-2", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/21.11116/0000-0005-8A29-2"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-05-01T00:00:00Z"}}, {"id": "21.11116/0000-0005-C54E-6", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-05-29T16:25:52Z", "type": "Report", "created": "2020-03-09", "title": "Mathematical Reconstruction of Land Carbon Models From Their Numerical Output: Computing Soil Radiocarbon From 12C Dynamics", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>         &amp;lt;p&amp;gt;Radiocarbon (&amp;lt;sup&amp;gt;14&amp;lt;/sup&amp;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 &amp;lt;sup&amp;gt;12&amp;lt;/sup&amp;gt;C stocks and fluxes among all carbon pools for a particular simulation of the model. From this output, a time&amp;amp;#8208;dependent linear compartmental system is computed with its respective state&amp;amp;#8208;transition matrix. Using transient atmospheric &amp;lt;sup&amp;gt;14&amp;lt;/sup&amp;gt;C values as inputs, the state&amp;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;amp;#8208;ECA, the land component of an ESM model that explicitly represents &amp;lt;sup&amp;gt;12&amp;lt;/sup&amp;gt;C, and &amp;lt;sup&amp;gt;14&amp;lt;/sup&amp;gt;C in 7 soil pools and 10 vertical layers. Results from our proposed method are highly accurate (relative error &amp;lt;0.01%) compared with the ELMv1&amp;amp;#8208;ECA &amp;lt;sup&amp;gt;12&amp;lt;/sup&amp;gt;C and &amp;lt;sup&amp;gt;14&amp;lt;/sup&amp;gt;C predictions, demonstrating the potential to use this approach in CMIP6 and other model simulations that do not explicitly represent &amp;lt;sup&amp;gt;14&amp;lt;/sup&amp;gt;C.&amp;lt;/p&amp;gt;         </p></article>", "keywords": ["Physical geography", "Earth system models", "GC1-1581", "dynamical systems", "15. Life on land", "Oceanography", "compartmental systems", "01 natural sciences", "GB3-5030", "13. Climate action", "radiocarbon", "model diagnostics", "carbon cycle models", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/21.11116/0000-0005-C54E-6"}, {"rel": "self", "type": "application/geo+json", "title": "21.11116/0000-0005-C54E-6", "name": "item", "description": "21.11116/0000-0005-C54E-6", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/21.11116/0000-0005-C54E-6"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-03-23T00:00:00Z"}}, {"id": "2938082089", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:26:14Z", "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<p>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.</p", "keywords": ["2. Zero hunger", "advanced land modeling", "Earth System Models", "15. Life on land", "01 natural sciences", "Climate Action", "soil organic carbon", "Geophysics", "machine learning", "statistical analysis", "13. Climate action", "Earth Sciences", "radiocarbon", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2018JG004795"}, {"href": "https://escholarship.org/content/qt4h72t9fq/qt4h72t9fq.pdf"}, {"href": "https://doi.org/2938082089"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Geophysical%20Research%3A%20Biogeosciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2938082089", "name": "item", "description": "2938082089", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2938082089"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-05-01T00:00:00Z"}}, {"id": "2994789089", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:26:17Z", "type": "Journal Article", "created": "2019-12-20", "title": "Mathematical Reconstruction of Land Carbon Models From Their Numerical Output: Computing Soil Radiocarbon From C Dynamics", "description": "Abstract<p>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 &lt;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.</p", "keywords": ["Atmospheric sciences", "Life on Land", "Bioengineering", "Earth system models", "dynamical systems", "compartmental systems", "01 natural sciences", "Atmospheric Sciences", "13. Climate action", "Geoinformatics", "Earth Sciences", "radiocarbon", "model diagnostics", "carbon cycle models", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2019MS001776"}, {"href": "https://doi.org/2994789089"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Advances%20in%20Modeling%20Earth%20Systems", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2994789089", "name": "item", "description": "2994789089", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2994789089"}, {"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": "38387558", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:26:50Z", "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/38387558"}, {"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": "38387558", "name": "item", "description": "38387558", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/38387558"}, {"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"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=earth+system+model&f=json", "hreflang": "en-US"}, {"rel": "alternate", "type": "text/html", "title": "This document as HTML", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=earth+system+model&f=html", "hreflang": "en-US"}, {"rel": "collection", "type": "application/json", "title": "Collection URL", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main", "hreflang": "en-US"}, {"type": "application/geo+json", "rel": "first", "title": "items (first)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=earth+system+model&", "hreflang": "en-US"}, {"rel": "last", "type": "application/geo+json", "title": "items (last)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=earth+system+model&offset=24", "hreflang": "en-US"}], "numberMatched": 24, "numberReturned": 24, "distributedFeatures": [], "timeStamp": "2026-05-30T09:05:20.886843Z"}