{"type": "FeatureCollection", "features": [{"id": "10.5194/essd-13-367-2021", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:20:16Z", "type": "Journal Article", "created": "2021-02-13", "title": "Copernicus Atmosphere Monitoring Service TEMPOral profiles (CAMS-TEMPO): global and European emission temporal profile maps for atmospheric chemistry modelling", "description": "

Abstract. We present the Copernicus Atmosphere Monitoring Service TEMPOral profiles (CAMS-TEMPO), a dataset of global and European emission temporal profiles that provides gridded monthly, daily, weekly and hourly weight factors for atmospheric chemistry modelling. CAMS-TEMPO includes temporal profiles for the priority air pollutants (NOx; SOx; NMVOC, non-methane volatile organic compound; NH3; CO; PM10; and PM2.5) and the greenhouse gases (CO2 and CH4) for each of the following anthropogenic source categories: energy industry (power plants), residential combustion, manufacturing industry, transport (road traffic and air traffic in airports) and agricultural activities (fertilizer use and livestock). The profiles are computed on a global 0.1\u2009\u00d7\u20090.1\u2218 and regional European 0.1\u2009\u00d7\u20090.05\u2218 grid following the domain and sector classification descriptions of the global and regional emission inventories developed under the CAMS programme. The profiles account for the variability of the main emission drivers of each sector. Statistical information linked to emission variability (e.g. electricity production and traffic counts) at national and local levels were collected and combined with existing meteorology-dependent parametrizations to account for the influences of sociodemographic factors and climatological conditions. Depending on the sector and the temporal resolution (i.e. monthly, weekly, daily and hourly) the resulting profiles are pollutant-dependent, year-dependent (i.e. time series from 2010 to 2017) and/or spatially dependent (i.e. the temporal weights vary per country or region). We provide a complete description of the data and methods used to build the CAMS-TEMPO profiles, and whenever possible, we evaluate the representativeness of the proxies used to compute the temporal weights against existing observational data. We find important discrepancies when comparing the obtained temporal weights with other currently used datasets. The CAMS-TEMPO data product including the global (CAMS-GLOB-TEMPOv2.1, https://doi.org/10.24380/ks45-9147, Guevara et al., 2020a) and regional European (CAMS-REG-TEMPOv2.1, https://doi.org/10.24380/1cx4-zy68, Guevara et al., 2020b) temporal profiles are distributed from the Emissions of atmospheric Compounds and Compilation of Ancillary Data (ECCAD) system (https://eccad.aeris-data.fr/, last access: February 2021).

", "keywords": ["China", "Atmospheric chemistry", "550", "Anthropogenic emissions", "Ammonia emissions", "Urbanisation", "Environment", "7. Clean energy", "[SDU] Sciences of the Universe [physics]", "11. Sustainability", "Air-pollution", "GE1-350", "Gridded emissions", "Fuel use", "QE1-996.5", "[SDU.OCEAN] Sciences of the Universe [physics]/Ocean", " Atmosphere", "Inventory", "Geology", "Environmental sciences", "Data product", "Qu\u00edmica atmosf\u00e8rica", "13. Climate action", "Air quality", "Transport model", "Data sets", "Bottom-up", "\u00c0rees tem\u00e0tiques de la UPC::Desenvolupament hum\u00e0 i sostenible::Degradaci\u00f3 ambiental::Contaminaci\u00f3 atmosf\u00e8rica", ":Desenvolupament hum\u00e0 i sostenible::Degradaci\u00f3 ambiental::Contaminaci\u00f3 atmosf\u00e8rica [\u00c0rees tem\u00e0tiques de la UPC]", "Air pollutants"]}, "links": [{"href": "https://essd.copernicus.org/articles/13/367/2021/essd-13-367-2021.pdf"}, {"href": "https://doi.org/10.5194/essd-13-367-2021"}, {"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-13-367-2021", "name": "item", "description": "10.5194/essd-13-367-2021", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/essd-13-367-2021"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-02-12T00:00:00Z"}}, {"id": "10.5194/essd-13-3707-2021", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:20:16Z", "type": "Journal Article", "created": "2021-01-07", "title": "C-band radar data and in situ measurements for the monitoring of wheat crops in a semi-arid area (center of Morocco)", "description": "

Abstract. A better understanding of the hydrological functioning of irrigated crops using remote sensing observations is of prime importance in the semi-arid areas where the water resources are limited. Radar observations, available at high resolution and revisit time since the launch of Sentinel-1 in 2014, have shown great potential for the monitoring of the water content of the upper soil and of the canopy. In this paper, a complete set of data for radar signal analysis is shared to the scientific community for the first time to our knowledge. The data set is composed of Sentinel-1 products and in situ measurements of soil and vegetation variables collected during three agricultural seasons over drip-irrigated winter wheat in the Haouz plain in Morocco. The in situ data gathers soil measurements (time series of half-hourly surface soil moisture, surface roughness and agricultural practices) and vegetation measurements collected every week/two weeks including above-ground fresh and dry biomasses, vegetation water content based on destructive measurements, cover fraction, leaf area index and plant height. Radar data are the backscattering coefficient and the interferometric coherence derived from Sentinel-1 GRDH (Ground Range Detected High resolution) and SLC (Single Look Complex) products, respectively. The normalized difference vegetation index derived from Sentinel-2 data based on Level-2A (surface reflectance and cloud mask) atmospheric effects-corrected products is also provided. This database, which is the first of its kind made available in open access, is described here comprehensively in order to help the scientific community to evaluate and to develop new or existing remote sensing algorithms for monitoring wheat canopy under semi-arid conditions. The data set is particularly relevant for the development of radar applications including surface soil moisture and vegetation parameters retrieval using either physically based or empirical approaches such as machine and deep learning algorithms. The database is archived in the DataSuds repository and is freely-accessible via the DOI: https://doi.org/10.23708/8D6WQC (Ouaadi et al., 2020a).

", "keywords": ["550", "Arid", "Soil Moisture", "0211 other engineering and technologies", "FOS: Mechanical engineering", "02 engineering and technology", "Digital Soil Mapping Techniques", "Normalized Difference Vegetation Index", "630", "Agricultural and Biological Sciences", "Engineering", "Pathology", "GE1-350", "2. Zero hunger", "QE1-996.5", "Vegetation Monitoring", "Water content", "Ecology", "Geography", "Statistics", "Life Sciences", "Hydrology (agriculture)", "Geology", "Remote Sensing in Vegetation Monitoring and Phenology", "04 agricultural and veterinary sciences", "Remote sensing", "Soil Erosion and Agricultural Sustainability", "6. Clean water", "Satellite Observations", "Archaeology", "Physical Sciences", "Leaf area index", "Telecommunications", "Medicine", "Vegetation (pathology)", "Environmental Engineering", "Data set", "[SDU.STU]Sciences of the Universe [physics]/Earth Sciences", "Aerospace Engineering", "Soil Science", "Environmental science", "Digital Soil Mapping", "[SDU] Sciences of the Universe [physics]", "Global Soil Information", "FOS: Mathematics", "Biology", "Radar", "Synthetic Aperture Radar Interferometry", "Canopy", "FOS: Environmental engineering", "Soil Properties", "Paleontology", "FOS: Earth and related environmental sciences", "15. Life on land", "Remote Sensing of Soil Moisture", "Surface Deformation Monitoring", "Computer science", "Agronomy", "Environmental sciences", "Geotechnical engineering", "[SDU]Sciences of the Universe [physics]", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "[SDU.STU] Sciences of the Universe [physics]/Earth Sciences", "0401 agriculture", " forestry", " and fisheries", "Mathematics"]}, "links": [{"href": "https://essd.copernicus.org/articles/13/3707/2021/essd-13-3707-2021.pdf"}, {"href": "https://doi.org/10.5194/essd-13-3707-2021"}, {"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-13-3707-2021", "name": "item", "description": "10.5194/essd-13-3707-2021", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/essd-13-3707-2021"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-01-07T00:00:00Z"}}, {"id": "10.5194/essd-13-4349-2021", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:20:16Z", "type": "Journal Article", "created": "2021-09-07", "title": "ERA5-Land: a state-of-the-art global reanalysis dataset for land applications", "description": "

Abstract. Framed within the Copernicus Climate Change Service (C3S) of the European Commission, the European Centre for Medium-Range Weather Forecasts (ECMWF) is producing an enhanced global dataset for the land component of the fifth generation of European ReAnalysis (ERA5), hereafter referred to as ERA5-Land. Once completed, the period covered will span from 1950 to the present, with continuous updates to support land monitoring applications. ERA5-Land describes the evolution of the water and energy cycles over land in a consistent manner over the production period, which, among others, could be used to analyse trends and anomalies. This is achieved through global high-resolution numerical integrations of the ECMWF land surface model driven by the downscaled meteorological forcing from the ERA5 climate reanalysis, including an elevation correction for the thermodynamic near-surface state. ERA5-Land shares with ERA5 most of the parameterizations that guarantees the use of the state-of-the-art land surface modelling applied to numerical weather prediction (NWP) models. A main advantage of ERA5-Land compared to ERA5 and the older ERA-Interim is the horizontal resolution, which is enhanced globally to 9\uffe2\uff80\uff89km compared to 31\uffe2\uff80\uff89km (ERA5) or 80\uffe2\uff80\uff89km (ERA-Interim), whereas the temporal resolution is hourly as in ERA5. Evaluation against independent in situ observations and global model or satellite-based reference datasets shows the added value of ERA5-Land in the description of the hydrological cycle, in particular with enhanced soil moisture and lake description, and an overall better agreement of river discharge estimations with available observations. However, ERA5-Land snow depth fields present a mixed performance when compared to those of ERA5, depending on geographical location and altitude. The description of the energy cycle shows comparable results with ERA5. Nevertheless, ERA5-Land reduces the global averaged root mean square error of the skin temperature, taking as reference MODIS data, mainly due to the contribution of coastal points where spatial resolution is important. Since January\uffc2\uffa02020, the ERA5-Land period available has extended from January\uffc2\uffa01981 to the near present, with a 2- to 3-month delay with respect to real time. The segment prior to 1981 is in production, aiming for a release of the whole dataset in summer/autumn\uffc2\uffa02021. The high spatial and temporal resolution of ERA5-Land, its extended period, and the consistency of the fields produced makes it a valuable dataset to support hydrological studies, to initialize NWP and climate models, and to support diverse applications dealing with water resource, land, and environmental management. The full ERA5-Land hourly (Mu\uffc3\uffb1oz-Sabater,\uffc2\uffa02019a) and monthly (Mu\uffc3\uffb1oz-Sabater,\uffc2\uffa02019b) averaged datasets presented in this paper are available through the C3S Climate Data Store at https://doi.org/10.24381/cds.e2161bac and https://doi.org/10.24381/cds.68d2bb30, respectively.

", "keywords": ["QE1-996.5", "550", "IN-SITU", "LEAF-AREA", "[SDU.STU]Sciences of the Universe [physics]/Earth Sciences", "Geology", "OPERATIONAL IMPLEMENTATION", "15. Life on land", "551", "SOIL-MOISTURE", "SURFACE-TEMPERATURE", "01 natural sciences", "LAKE PARAMETERIZATION", "[SDU] Sciences of the Universe [physics]", "Environmental sciences", "[SDU]Sciences of the Universe [physics]", "13. Climate action", "Earth and Environmental Sciences", "[SDU.STU] Sciences of the Universe [physics]/Earth Sciences", "SNOW MODELS", "GE1-350", "WEST-AFRICA", "SATELLITE", "NUMERICAL WEATHER PREDICTION", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://centaur.reading.ac.uk/106796/1/essd-13-4349-2021.pdf"}, {"href": "https://essd.copernicus.org/articles/13/4349/2021/essd-13-4349-2021.pdf"}, {"href": "https://doi.org/10.5194/essd-13-4349-2021"}, {"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-13-4349-2021", "name": "item", "description": "10.5194/essd-13-4349-2021", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/essd-13-4349-2021"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-03-15T00:00:00Z"}}, {"id": "10.5194/essd-2021-358", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:20:17Z", "type": "Journal Article", "created": "2021-10-28", "title": "The MONARCH high-resolution reanalysis of desert dust aerosol over Northern Africa, the Middle East and Europe (2007\u20132016)", "description": "

Abstract. One of the challenges in studying desert dust aerosol along with its numerous interactions and impacts is the paucity of direct in-situ measurements, particularly in the areas most affected by dust storms. Satellites typically provide columnintegrated aerosol measurements, but observationally-constrained continuous 3D dust fields are needed to assess dust variability, climate effects and impacts upon a variety of socio-economic sectors. Here, we present a high resolution regional reanalysis data set of desert dust aerosols that covers Northern Africa, the Middle East and Europe along with the Mediterranean sea and parts of Central Asia, and the Atlantic and Indian Oceans between 2007 and 2016. The horizontal resolution is 0.1\u00b0 latitude\u2009\u00d7\u20090.1\u00b0 longitude, and the temporal resolution is 3 hours. The reanalysis was produced using Local Ensemble Transform Kalman Filter (LETKF) data assimilation in the Multiscale Online Non-hydrostatic AtmospheRe CHemistry model (MONARCH) developed at the Barcelona Supercomputing Center (BSC). The assimilated data are coarse-mode dust optical depth retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue Level 2 products. The reanalysis data set consists of upper air (dust mass concentrations and extinction coefficient), surface (dust deposition and solar irradiance fields, among them) and total column (e.g., dust optical depth and load) variables. Some dust variables, such as concentrations and wet and dry deposition, are expressed for a binned size distribution that ranges from 0.2 to 20\u2009\u03bcm in particle diameter. Both analysis and first-guess (analysis-initialized simulation) fields are available for the variables that are diagnosed from the state vector. A set of ensemble statistics is archived for each output variable, namely the ensemble mean, standard deviation, maximum and median. The spatial and temporal distribution of the dust fields follows well-known dust cycle features controlled by seasonal changes in meteorology and vegetation cover. The analysis is statistically closer to the assimilated retrievals than the first-guess, which proves the consistency of the data assimilation method. Independent evaluation using AERONET dust-filtered optical depth retrievals indicates that the reanalysis data set is highly accurate (mean bias\u2009=\u2009\u22120.05, RMSE\u2009=\u20090.12, r\u2009=\u20090.81 when compared to retrievals from the spectral de-convolution algorithm on a 3-hourly basis). Verification statistics are broadly homogeneous in space and time with regional differences that can be partly attributed to model limitations (e.g., poor representation of small-scale emission processes), presence of aerosols other than dust in the observations used in the evaluation, and differences in the number of observations among seasons. Such a reliable high-resolution historical record of atmospheric desert dust will allow a better quantification of dust impacts upon key sectors of society and economy, including health, solar energy production and transportation. The reanalysis data set (Di Tomaso et al., 2021) is distributed via a Thematic Real-time Environmental Distributed Data Service (THREDDS) at BSC and freely available at http://hdl.handle.net/21.12146/c6d4a608-5de3-47f6-a004-67cb1d498d98.

", "keywords": ["Desert dust aerosol", "550", "Climate", "MINERAL-COMPOSITION", "Aerosols atmosf\u00e8rics", "01 natural sciences", "Dust emission", "[SDU] Sciences of the Universe [physics]", "LETKF", "Local ensemble transform Kalman filter", "DATA ASSIMILATION", "\u00c0rees tem\u00e0tiques de la UPC::Enginyeria agroaliment\u00e0ria::Ci\u00e8ncies de la terra i de la vida::Climatologia i meteorologia", "Pols -- Control", "SDG 3 - Good Health and Well-being", "MONARCH", "SAHARAN DUST", "SDG 13 - Climate Action", "SIZE DISTRIBUTION", "GE1-350", "Desert", "CONVECTIVE ADJUSTMENT SCHEME", "Aerosol measurements", "Multiscale Online Nonhydrostatic AtmospheRe CHemistry model", "0105 earth and related environmental sciences", "QE1-996.5", "info:eu-repo/classification/ddc/550", ":Enginyeria agroaliment\u00e0ria::Ci\u00e8ncies de la terra i de la vida::Climatologia i meteorologia [\u00c0rees tem\u00e0tiques de la UPC]", "ddc:550", "Geology", "1 MODEL DESCRIPTION", "OPTICAL-PROPERTIES", "MONARCH modeling system", "Atmospheric aerosols", "Environmental sciences", "Earth sciences", "PM10 CONCENTRATIONS", "900", "Dust aerosol", "13. Climate action", "[SDU.STU] Sciences of the Universe [physics]/Earth Sciences", "SINGLE-SCATTERING ALBEDO", "MEDITERRANEAN BASIN", "Dust control"]}, "links": [{"href": "https://iris.cnr.it/bitstream/20.500.14243/417480/1/prod_471097-doc_191235.pdf"}, {"href": "https://essd.copernicus.org/articles/14/2785/2022/essd-14-2785-2022.pdf"}, {"href": "https://doi.org/10.5194/essd-2021-358"}, {"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-2021-358", "name": "item", "description": "10.5194/essd-2021-358", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/essd-2021-358"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-10-28T00:00:00Z"}}, {"id": "10.5194/gmd-10-3821-2017", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:20:17Z", "type": "Journal Article", "created": "2017-10-23", "title": "ORCHILEAK (revision 3875): a new model branch to simulate carbon transfers along the terrestrial\u2013aquatic continuum of the Amazon basin", "description": "

Abstract. Lateral transfer of carbon (C) from terrestrial ecosystems into the inland water network is an important component of the global C cycle, which sustains a large aquatic CO2 evasion flux fuelled by the decomposition of allochthonous C inputs. Globally, estimates of the total C exports through the terrestrial\u2013aquatic interface range from 1.5 to 2.7\u202fPg\u202fC\u202fyr\u22121 (Cole et al., 2007; Battin et al., 2009; Tranvik et al., 2009), i.e. of the order of 2\u20135\u202f% of the terrestrial NPP. Earth system models (ESMs) of the climate system ignore these lateral transfers of C, and thus likely overestimate the terrestrial C sink. In this study, we present the implementation of fluvial transport of dissolved organic carbon (DOC) and CO2 into ORCHIDEE (Organising Carbon and Hydrology in Dynamic Ecosystems), the land surface scheme of the Institut Pierre-Simon Laplace ESM. This new model branch, called ORCHILEAK, represents DOC production from canopy and soils, DOC and CO2 leaching from soils to streams, DOC decomposition, and CO2 evasion to the atmosphere during its lateral transport in rivers, as well as exchange with the soil carbon and litter stocks on floodplains and in swamps. We parameterized and validated ORCHILEAK for the Amazon basin, the world's largest river system with regard to discharge and one of the most productive ecosystems in the world. With ORCHILEAK, we are able to reproduce observed terrestrial and aquatic fluxes of DOC and CO2 in the Amazon basin, both in terms of mean values and seasonality. In addition, we are able to resolve the spatio-temporal variability in C fluxes along the canopy\u2013soil\u2013water continuum at high resolution (1\u00b0, daily) and to quantify the different terrestrial contributions to the aquatic C fluxes. We simulate that more than two-thirds of the Amazon's fluvial DOC export are contributed by the decomposition of submerged litter. Throughfall DOC fluxes from canopy to ground are about as high as the total DOC inputs to inland waters. The latter, however, are mainly sustained by litter decomposition. Decomposition of DOC and submerged plant litter contributes slightly more than half of the CO2 evasion from the water surface, while the remainder is contributed by soil respiration. Total CO2 evasion from the water surface equals about 5\u202f% of the terrestrial NPP. Our results highlight that ORCHILEAK is well suited to simulate carbon transfers along the terrestrial\u2013aquatic continuum of tropical forests. It also opens the perspective that provided parameterization, calibration and validation is performed for other biomes, the new model branch could improve the quantification of the global terrestrial C sink and help better constrain carbon cycle\u2013climate feedbacks in future projections.

", "keywords": ["[SDU] Sciences of the Universe [physics]", "Sciences de la terre et du cosmos", "570", "QE1-996.5", "550", "[SDU]Sciences of the Universe [physics]", "13. Climate action", "Geology", "Sciences pharmaceutiques", "15. Life on land"]}, "links": [{"href": "https://gmd.copernicus.org/articles/10/3821/2017/gmd-10-3821-2017.pdf"}, {"href": "https://dipot.ulb.ac.be/dspace/bitstream/2013/261804/4/doi_245431.pdf"}, {"href": "https://doi.org/10.5194/gmd-10-3821-2017"}, {"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-10-3821-2017", "name": "item", "description": "10.5194/gmd-10-3821-2017", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/gmd-10-3821-2017"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-10-23T00:00:00Z"}}, {"id": "10.5194/gmd-14-6403-2021", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:20:18Z", "type": "Journal Article", "created": "2021-10-25", "title": "Mineral dust cycle in the Multiscale Online Nonhydrostatic AtmospheRe CHemistry model (MONARCH) Version 2.0", "description": "

Abstract. We present the dust module in the Multiscale Online Non-hydrostatic AtmospheRe CHemistry model (MONARCH) version 2.0, a chemical weather prediction system that can be used for regional and global modeling at a range of resolutions. The representations of dust processes in MONARCH were upgraded with a focus on dust emission (emission parameterizations, entrainment thresholds, considerations of soil moisture and surface cover), lower boundary conditions (roughness, potential dust sources), and dust\u2013radiation interactions. MONARCH now allows modeling of global and regional mineral dust cycles using fundamentally different paradigms, ranging from strongly simplified to physics-based parameterizations. We present a detailed description of these updates along with four global benchmark simulations, which use conceptually different dust emission parameterizations, and we evaluate the simulations against observations of dust optical depth. We determine key dust parameters, such as global annual emission/deposition flux, dust loading, dust optical depth, mass-extinction efficiency, single-scattering albedo, and direct radiative effects. For dust-particle diameters up to 20\u2009\u00b5m, the total annual dust emission and deposition fluxes obtained with our four experiments range between about 3500 and 6000\u2009Tg, which largely depend upon differences in the emitted size distribution. Considering ellipsoidal particle shapes and dust refractive indices that account for size-resolved mineralogy, we estimate the global total (longwave and shortwave) dust direct radiative effect (DRE) at the surface to range between about \u22120.90 and \u22120.63\u2009W\u2009m\u22122 and at the top of the atmosphere between \u22120.20 and \u22120.28\u2009W\u2009m\u22122. Our evaluation demonstrates that MONARCH is able to reproduce key features of the spatiotemporal variability of the global dust cycle with important and insightful differences between the different configurations.

", "keywords": ["Mineral dusts", "Previsi\u00f3 del temps", "QE1-996.5", "info:eu-repo/classification/ddc/550", "550", "ddc:550", "Geology", "15. Life on land", "01 natural sciences", ":Enginyeria qu\u00edmica::Qu\u00edmica del medi ambient::Qu\u00edmica atmosf\u00e8rica [\u00c0rees tem\u00e0tiques de la UPC]", "Weather forecasting", "Climate Action", "[SDU] Sciences of the Universe [physics]", "Earth sciences", "[SDU]Sciences of the Universe [physics]", "13. Climate action", "Earth Sciences", "Pols", "\u00c0rees tem\u00e0tiques de la UPC::Enginyeria qu\u00edmica::Qu\u00edmica del medi ambient::Qu\u00edmica atmosf\u00e8rica", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://gmd.copernicus.org/articles/14/6403/2021/gmd-14-6403-2021.pdf"}, {"href": "https://escholarship.org/content/qt2r39x8b5/qt2r39x8b5.pdf"}, {"href": "https://doi.org/10.5194/gmd-14-6403-2021"}, {"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-14-6403-2021", "name": "item", "description": "10.5194/gmd-14-6403-2021", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/gmd-14-6403-2021"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-04-01T00:00:00Z"}}, {"id": "10.5194/gmd-2017-172", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:20:18Z", "type": "Journal Article", "created": "2017-07-24", "title": "Representation of dissolved organic carbon in the JULES land surface model (vn4.4_JULES-DOCM)", "description": "

Abstract. Current global models of the carbon (C) cycle consider only vertical gas exchanges between terrestrial or oceanic reservoirs and the atmosphere, thus not considering lateral transport of carbon from the continents to the oceans. Therefore, those models implicitly consider that all the C which is not respired to the atmosphere is stored on land, hence overestimating the land C sink capability. A model that represents the whole continuum from atmosphere to land and into the ocean would provide better understanding of the Earth's C cycle and hence more reliable historical or future projections. We present an original representation of Dissolved Organic C (DOC) processes in the Joint UK Land Environment Simulator (JULES-DOCM). The standard version of JULES represents energy, water and carbon dynamics between vegetation, soil and atmosphere, while lateral fluxes only account for water run-off. Here we integrate a representation of DOC production in terrestrial ecosystems based on incomplete decomposition of organic matter, DOC decomposition within the soil column, and DOC export to the river network via leaching. The model performance is evaluated in five specific sites for which observations of soil DOC concentration are available. Results show that the model is able to reproduce the DOC concentration and controlling processes including leaching to the riverine system which is fundamental for integrating terrestrial and aquatic ecosystems.

", "keywords": ["QE1-996.5", "Multidisciplinary", "550", "Physics", "[SDU.STU]Sciences of the Universe [physics]/Earth Sciences", "/dk/atira/pure/sustainabledevelopmentgoals/life_on_land; name=SDG 15 - Life on Land", "Geology", "/dk/atira/pure/core/keywords/biology; name=Ecosystems Research", "15. Life on land", "[SDU] Sciences of the Universe [physics]", "Sciences de la terre et du cosmos", "Environmental Sciences related to Agriculture and Land-use", "/dk/atira/pure/sustainabledevelopmentgoals/affordable_and_clean_energy; name=SDG 7 - Affordable and Clean Energy", "[SDU]Sciences of the Universe [physics]", "/dk/atira/pure/subjectarea/asjc/1900; name=Earth and Planetary Sciences(all)", "13. Climate action", "[SDU.STU] Sciences of the Universe [physics]/Earth Sciences", "14. Life underwater", "Geosciences", " Multidisciplinary", "Geosciences", "/dk/atira/pure/subjectarea/asjc/2600/2611; name=Modelling and Simulation"]}, "links": [{"href": "https://pub.epsilon.slu.se/15362/1/Nakhavali_et_al_180507.pdf"}, {"href": "https://gmd.copernicus.org/articles/11/593/2018/gmd-11-593-2018.pdf"}, {"href": "https://dipot.ulb.ac.be/dspace/bitstream/2013/282704/1/doi_266331.pdf"}, {"href": "https://doi.org/10.5194/gmd-2017-172"}, {"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-2017-172", "name": "item", "description": "10.5194/gmd-2017-172", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/gmd-2017-172"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-07-24T00:00:00Z"}}, {"id": "10.5194/hess-2019-105", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:20:19Z", "type": "Journal Article", "created": "2019-04-23", "title": "An evapotranspiration model self-calibrated from remotely sensed surface soil moisture, land surface temperature and vegetation cover fraction: application to disaggregated SMOS and MODIS data", "description": "

Abstract. Thermal-based two-source energy balance modeling is very useful for estimating the land evapotranspiration (ET) at a wide range of spatial and temporal scales. However, the land surface temperature (LST) is not sufficient for constraining simultaneously both soil and vegetation flux components in such a way that assumptions (on either the soil or the vegetation fluxes) are commonly required. To avoid such assumptions, a new energy balance model (TSEB-SM) was recently developed in Ait Hssaine et al. (2018a) to integrate the microwave-derived near-surface soil moisture (SM), in addition to the thermal-derived LST and vegetation cover fraction (fc). Whereas, TSEB-SM has been recently tested using in-situ measurements, the objective of this paper is to evaluate the performance of TSEB-SM in real-life using 1\u2009km resolution MODIS (Moderate resolution imaging spectroradiometer) LST and fc data and the 1\u2009km resolution SM data disaggregated from SMOS (Soil Moisture and Ocean Salinity) observations by using DisPATCh. The approach is applied during a four-year period (2014\u20132018) over a rainfed wheat field in the Tensift basin, central Morocco, during a four-year period (2014\u20132018). The field was seeded for the 2014\u20132015 (S1), 2016\u20132017 (S2) and 2017\u20132018 (S3) agricultural season, while it was not ploughed (remained as bare soil) during the 2015\u20132016 (B1) agricultural season. The mean retrieved values of (arss, brss) calculated for the entire study period using satellite data are (7.32, 4.58). The daily calibrated \u03b1PT ranges between 0 and 1.38 for both S1 and S2. Its temporal variability is mainly attributed to the rainfall distribution along the agricultural season. For S3, the daily retrieved \u03b1PT remains at a mostly constant value (\u223c\u20090.7) throughout the study period, because of the lack of clear sky disaggregated SM and LST observations during this season. Compared to eddy covariance measurements, TSEB driven only by LST and fc data significantly overestimates latent heat fluxes for the four seasons. The overall mean bias values are 119, 94, 128 and 181\u2009W/m2 for S1, S2, S3 and B1 respectively. In contrast, these errors are much reduced when using TSEB-SM (SM and LST combined data) with the mean bias values estimated as 39, 4, 7 and 62\u2009W/m2 for S1, S2, S3 and B1 respectively.

", "keywords": ["Technology", "Atmospheric sciences", "550", "Soil Moisture", "0208 environmental biotechnology", "02 engineering and technology", "Environmental technology. Sanitary engineering", "01 natural sciences", "Engineering", "Geography. Anthropology. Recreation", "Pathology", "GE1-350", "TD1-1066", "2. Zero hunger", "Global and Planetary Change", "Water content", "Evapotranspiration", "Geography", "Ecology", "T", "Soil Water Retention", "Moderate-resolution imaging spectroradiometer", "Hydrology (agriculture)", "Geology", "[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces", " environment", "6. Clean water", "Aerospace engineering", "Physical Sciences", "Medicine", "environment", "Vegetation (pathology)", "Latent heat", "Mechanics and Transport in Unsaturated Soils", "Land cover", "Environmental Engineering", "0207 environmental engineering", "Energy balance", "Thermal Effects on Soil", "Environmental science", "[SDU] Sciences of the Universe [physics]", "G", "Meteorology", "Civil engineering", "14. Life underwater", "[SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology", "Biology", "Civil and Structural Engineering", "0105 earth and related environmental sciences", "Global Forest Drought Response and Climate Change", "FOS: Environmental engineering", "FOS: Earth and related environmental sciences", "15. Life on land", "Remote Sensing of Soil Moisture", "Environmental sciences", "Geotechnical engineering", "[SDU]Sciences of the Universe [physics]", "Satellite", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Land use", "[SDU.STU.HY] Sciences of the Universe [physics]/Earth Sciences/Hydrology", "[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces", "FOS: Civil engineering"]}, "links": [{"href": "https://hess.copernicus.org/articles/24/1781/2020/hess-24-1781-2020.pdf"}, {"href": "https://doi.org/10.5194/hess-2019-105"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Hydrology%20and%20Earth%20System%20Sciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/hess-2019-105", "name": "item", "description": "10.5194/hess-2019-105", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/hess-2019-105"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-04-23T00:00:00Z"}}, {"id": "10.5194/hess-24-1781-2020", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:20:19Z", "type": "Journal Article", "created": "2019-04-23", "title": "An evapotranspiration model self-calibrated from remotely sensed surface soil moisture, land surface temperature and vegetation cover fraction: application to disaggregated SMOS and MODIS data", "description": "

Abstract. Thermal-based two-source energy balance modeling is very useful for estimating the land evapotranspiration (ET) at a wide range of spatial and temporal scales. However, the land surface temperature (LST) is not sufficient for constraining simultaneously both soil and vegetation flux components in such a way that assumptions (on either the soil or the vegetation fluxes) are commonly required. To avoid such assumptions, a new energy balance model (TSEB-SM) was recently developed in Ait Hssaine et al. (2018a) to integrate the microwave-derived near-surface soil moisture (SM), in addition to the thermal-derived LST and vegetation cover fraction (fc). Whereas, TSEB-SM has been recently tested using in-situ measurements, the objective of this paper is to evaluate the performance of TSEB-SM in real-life using 1\uffe2\uff80\uff89km resolution MODIS (Moderate resolution imaging spectroradiometer) LST and fc data and the 1\uffe2\uff80\uff89km resolution SM data disaggregated from SMOS (Soil Moisture and Ocean Salinity) observations by using DisPATCh. The approach is applied during a four-year period (2014\uffe2\uff80\uff932018) over a rainfed wheat field in the Tensift basin, central Morocco, during a four-year period (2014\uffe2\uff80\uff932018). The field was seeded for the 2014\uffe2\uff80\uff932015 (S1), 2016\uffe2\uff80\uff932017 (S2) and 2017\uffe2\uff80\uff932018 (S3) agricultural season, while it was not ploughed (remained as bare soil) during the 2015\uffe2\uff80\uff932016 (B1) agricultural season. The mean retrieved values of (arss, brss) calculated for the entire study period using satellite data are (7.32, 4.58). The daily calibrated \uffce\uffb1PT ranges between 0 and 1.38 for both S1 and S2. Its temporal variability is mainly attributed to the rainfall distribution along the agricultural season. For S3, the daily retrieved \uffce\uffb1PT remains at a mostly constant value (\uffe2\uff88\uffbc\uffe2\uff80\uff890.7) throughout the study period, because of the lack of clear sky disaggregated SM and LST observations during this season. Compared to eddy covariance measurements, TSEB driven only by LST and fc data significantly overestimates latent heat fluxes for the four seasons. The overall mean bias values are 119, 94, 128 and 181\uffe2\uff80\uff89W/m2 for S1, S2, S3 and B1 respectively. In contrast, these errors are much reduced when using TSEB-SM (SM and LST combined data) with the mean bias values estimated as 39, 4, 7 and 62\uffe2\uff80\uff89W/m2 for S1, S2, S3 and B1 respectively.

", "keywords": ["Technology", "Atmospheric sciences", "550", "Soil Moisture", "0208 environmental biotechnology", "02 engineering and technology", "Environmental technology. Sanitary engineering", "01 natural sciences", "Engineering", "Geography. Anthropology. Recreation", "Pathology", "GE1-350", "TD1-1066", "2. Zero hunger", "Global and Planetary Change", "Water content", "Evapotranspiration", "Geography", "Ecology", "T", "Soil Water Retention", "Moderate-resolution imaging spectroradiometer", "Hydrology (agriculture)", "Geology", "[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces", " environment", "6. Clean water", "Aerospace engineering", "Physical Sciences", "Medicine", "environment", "Vegetation (pathology)", "Latent heat", "Mechanics and Transport in Unsaturated Soils", "Land cover", "Environmental Engineering", "0207 environmental engineering", "Energy balance", "Thermal Effects on Soil", "Environmental science", "[SDU] Sciences of the Universe [physics]", "G", "Meteorology", "Civil engineering", "14. Life underwater", "[SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology", "Biology", "Civil and Structural Engineering", "0105 earth and related environmental sciences", "Global Forest Drought Response and Climate Change", "FOS: Environmental engineering", "FOS: Earth and related environmental sciences", "15. Life on land", "Remote Sensing of Soil Moisture", "Environmental sciences", "Geotechnical engineering", "[SDU]Sciences of the Universe [physics]", "Satellite", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Land use", "[SDU.STU.HY] Sciences of the Universe [physics]/Earth Sciences/Hydrology", "[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces", "FOS: Civil engineering"]}, "links": [{"href": "https://hess.copernicus.org/articles/24/1781/2020/hess-24-1781-2020.pdf"}, {"href": "https://doi.org/10.5194/hess-24-1781-2020"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Hydrology%20and%20Earth%20System%20Sciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/hess-24-1781-2020", "name": "item", "description": "10.5194/hess-24-1781-2020", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/hess-24-1781-2020"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-04-23T00:00:00Z"}}, {"id": "10261/281211", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:18Z", "type": "Journal Article", "created": "2022-10-10", "title": "Women in limnology: From a historical perspective to a present\u2010day evaluation", "description": "Abstract

Research in limnology is nurtured by the work of many fascinating and passionate women, who have contributed enormously to our understanding of inland waters. Female limnologists have promoted and established the bases of our knowledge about inland waters and fostered the need of protecting the values of those ecosystems. However, on numerous occasions, their contribution to the advancement of limnology has not been duly recognized. Here, we review the presence of women in limnology through the history of the discipline: from the pioneers who contributed to the origins to present day' developments. We aim at visibilizing those scientists and establish them as role models. We also analyze in a simple and illustrative way the current situation of women in limnology, the scientific barriers they must deal with, and their future prospects. Multiple aspects fostering the visibility of a scientist, such as their presence in conferences, awards, or representation in societal or editorial boards show a significant gap, with none of those aspects showing a similar visibility of women and men in limnology. This article raises awareness of the obstacles that women in limnology faced and still face, and encourages to embrace models of leadership, scientific management, and assessment of research performance far from those commonly established.

This article is categorized under:

Science of Water > Methods

Water and Life > Methods

Abstract. Current global models of the carbon (C) cycle consider only vertical gas exchanges between terrestrial or oceanic reservoirs and the atmosphere, thus not considering lateral transport of carbon from the continents to the oceans. Therefore, those models implicitly consider that all the C which is not respired to the atmosphere is stored on land, hence overestimating the land C sink capability. A model that represents the whole continuum from atmosphere to land and into the ocean would provide better understanding of the Earth's C cycle and hence more reliable historical or future projections. We present an original representation of Dissolved Organic C (DOC) processes in the Joint UK Land Environment Simulator (JULES-DOCM). The standard version of JULES represents energy, water and carbon dynamics between vegetation, soil and atmosphere, while lateral fluxes only account for water run-off. Here we integrate a representation of DOC production in terrestrial ecosystems based on incomplete decomposition of organic matter, DOC decomposition within the soil column, and DOC export to the river network via leaching. The model performance is evaluated in five specific sites for which observations of soil DOC concentration are available. Results show that the model is able to reproduce the DOC concentration and controlling processes including leaching to the riverine system which is fundamental for integrating terrestrial and aquatic ecosystems.

", "keywords": ["QE1-996.5", "Multidisciplinary", "550", "Physics", "[SDU.STU]Sciences of the Universe [physics]/Earth Sciences", "/dk/atira/pure/sustainabledevelopmentgoals/life_on_land; name=SDG 15 - Life on Land", "Geology", "/dk/atira/pure/core/keywords/biology; name=Ecosystems Research", "15. Life on land", "[SDU] Sciences of the Universe [physics]", "Sciences de la terre et du cosmos", "Environmental Sciences related to Agriculture and Land-use", "/dk/atira/pure/sustainabledevelopmentgoals/affordable_and_clean_energy; name=SDG 7 - Affordable and Clean Energy", "[SDU]Sciences of the Universe [physics]", "/dk/atira/pure/subjectarea/asjc/1900; name=Earth and Planetary Sciences(all)", "13. Climate action", "[SDU.STU] Sciences of the Universe [physics]/Earth Sciences", "14. Life underwater", "Geosciences", " Multidisciplinary", "Geosciences", "/dk/atira/pure/subjectarea/asjc/2600/2611; name=Modelling and Simulation"]}, "links": [{"href": "https://pub.epsilon.slu.se/15362/1/Nakhavali_et_al_180507.pdf"}, {"href": "https://gmd.copernicus.org/articles/11/593/2018/gmd-11-593-2018.pdf"}, {"href": "https://dipot.ulb.ac.be/dspace/bitstream/2013/282704/1/doi_266331.pdf"}, {"href": "https://doi.org/10871/31936"}, {"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": "10871/31936", "name": "item", "description": "10871/31936", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10871/31936"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-07-24T00:00:00Z"}}, {"id": "10.5445/ir/1000160199", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:21:42Z", "type": "Journal Article", "created": "2023-06-14", "title": "A new process-based and scale-aware desert dust emission scheme for global climate models \u2013 Part I: Description and evaluation against inverse modeling emissions", "description": "

Abstract. Desert dust accounts for most of the atmosphere's aerosol burden by mass and produces numerous important impacts on the Earth system. However, current global climate models (GCMs) and land-surface models (LSMs) struggle to accurately represent key dust emission processes, in part because of inadequate representations of soil particle sizes that affect the dust emission threshold, surface roughness elements that absorb wind momentum, and boundary-layer characteristics that control wind fluctuations. Furthermore, because dust emission is driven by small-scale (\u223c\u20091\u2009km or smaller) processes, simulating the global cycle of desert dust in GCMs with coarse horizontal resolutions (\u223c\u2009100\u2009km) presents a fundamental challenge. This representation problem is exacerbated by dust emission fluxes scaling nonlinearly with wind speed above a threshold wind speed that is sensitive to land-surface characteristics. Here, we address these fundamental problems underlying the simulation of dust emissions in GCMs and LSMs by developing improved descriptions of (1)\u00a0the effect of soil texture on the dust emission threshold, (2)\u00a0the effects of nonerodible roughness elements (both rocks and green vegetation) on the surface wind stress, and (3)\u00a0the effects of boundary-layer turbulence on driving intermittent dust emissions. We then use the resulting revised dust emission parameterization to simulate global dust emissions in a standalone model forced by reanalysis meteorology and land-surface fields. We further propose (4)\u00a0a simple methodology to rescale lower-resolution dust emission simulations to match the spatial variability of higher-resolution emission simulations in GCMs. The resulting dust emission simulation shows substantially improved agreement against regional dust emissions observationally constrained by inverse modeling. We thus find that our revised dust emission parameterization can substantially improve dust emission simulations in GCMs and\u00a0LSMs.

", "keywords": ["Atmospheric sciences", "info:eu-repo/classification/ddc/550", "550", "Climate change science", "ddc:550", "Physics", "QC1-999", "15. Life on land", "Atmospheric Sciences", "Climate Action", "[SDU] Sciences of the Universe [physics]", "Earth sciences", "Chemistry", "13. Climate action", "[SDU]Sciences of the Universe [physics]", "Earth Sciences", "Meteorology & Atmospheric Sciences", "QD1-999", "Astronomical and Space Sciences"]}, "links": [{"href": "https://acp.copernicus.org/articles/23/6487/2023/acp-23-6487-2023.pdf"}, {"href": "https://escholarship.org/content/qt2fk4w0h1/qt2fk4w0h1.pdf"}, {"href": "https://doi.org/10.5445/ir/1000160199"}, {"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": "10.5445/ir/1000160199", "name": "item", "description": "10.5445/ir/1000160199", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5445/ir/1000160199"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-06-14T00:00:00Z"}}, {"id": "10.5772/63887", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:21:57Z", "type": "Report", "created": "2016-09-29", "title": "Remote Sensing Studies of Urban Canopies: 3D Radiative Transfer Modeling", "description": "Need for better understanding and more accurate estimation of radiative fluxes in urban environments, specifically urban surface albedo and exitance, motivates development of new remote sensing and three\u2010dimensional (3D) radiative transfer (RT) modeling methods. The discrete anisotropic radiative transfer (DART) model, one of the most comprehensive physically based 3D models simulating Earth/atmosphere radiation interactions, was used in combination with satellite data (e.g., Landsat\u20108 observations) to better parameterize the radiative budget components of cities, such as Basel in Switzerland. After presenting DART and its recent RT modeling functions, we present a methodological concept for estimating urban fluxes using any satellite image data.", "keywords": ["[SDU] Sciences of the Universe [physics]", "[SDU]Sciences of the Universe [physics]", "13. Climate action", "11. Sustainability"]}, "links": [{"href": "http://www.intechopen.com/download/pdf/pdfs_id/51179"}, {"href": "http://www.intechopen.com/download/pdf/51179"}, {"href": "https://edoc.unibas.ch/44287/1/51179.pdf"}, {"href": "https://doi.org/10.5772/63887"}, {"rel": "self", "type": "application/geo+json", "title": "10.5772/63887", "name": "item", "description": "10.5772/63887", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5772/63887"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-09-28T00:00:00Z"}}, {"id": "10.60692/g4rcv-eqz54", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:00Z", "type": "Journal Article", "created": "2019-04-23", "title": "An evapotranspiration model self-calibrated from remotely sensed surface soil moisture, land surface temperature and vegetation cover fraction: application to disaggregated SMOS and MODIS data", "description": "

Abstract. Thermal-based two-source energy balance modeling is very useful for estimating the land evapotranspiration (ET) at a wide range of spatial and temporal scales. However, the land surface temperature (LST) is not sufficient for constraining simultaneously both soil and vegetation flux components in such a way that assumptions (on either the soil or the vegetation fluxes) are commonly required. To avoid such assumptions, a new energy balance model (TSEB-SM) was recently developed in Ait Hssaine et al. (2018a) to integrate the microwave-derived near-surface soil moisture (SM), in addition to the thermal-derived LST and vegetation cover fraction (fc). Whereas, TSEB-SM has been recently tested using in-situ measurements, the objective of this paper is to evaluate the performance of TSEB-SM in real-life using 1\u2009km resolution MODIS (Moderate resolution imaging spectroradiometer) LST and fc data and the 1\u2009km resolution SM data disaggregated from SMOS (Soil Moisture and Ocean Salinity) observations by using DisPATCh. The approach is applied during a four-year period (2014\u20132018) over a rainfed wheat field in the Tensift basin, central Morocco, during a four-year period (2014\u20132018). The field was seeded for the 2014\u20132015 (S1), 2016\u20132017 (S2) and 2017\u20132018 (S3) agricultural season, while it was not ploughed (remained as bare soil) during the 2015\u20132016 (B1) agricultural season. The mean retrieved values of (arss, brss) calculated for the entire study period using satellite data are (7.32, 4.58). The daily calibrated \u03b1PT ranges between 0 and 1.38 for both S1 and S2. Its temporal variability is mainly attributed to the rainfall distribution along the agricultural season. For S3, the daily retrieved \u03b1PT remains at a mostly constant value (\u223c\u20090.7) throughout the study period, because of the lack of clear sky disaggregated SM and LST observations during this season. Compared to eddy covariance measurements, TSEB driven only by LST and fc data significantly overestimates latent heat fluxes for the four seasons. The overall mean bias values are 119, 94, 128 and 181\u2009W/m2 for S1, S2, S3 and B1 respectively. In contrast, these errors are much reduced when using TSEB-SM (SM and LST combined data) with the mean bias values estimated as 39, 4, 7 and 62\u2009W/m2 for S1, S2, S3 and B1 respectively.

", "keywords": ["Technology", "Atmospheric sciences", "550", "Soil Moisture", "0208 environmental biotechnology", "02 engineering and technology", "Environmental technology. Sanitary engineering", "01 natural sciences", "Engineering", "Geography. Anthropology. Recreation", "Pathology", "GE1-350", "TD1-1066", "2. Zero hunger", "Global and Planetary Change", "Water content", "Evapotranspiration", "Geography", "Ecology", "T", "Soil Water Retention", "Moderate-resolution imaging spectroradiometer", "Hydrology (agriculture)", "Geology", "[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces", " environment", "6. Clean water", "Aerospace engineering", "Physical Sciences", "Medicine", "environment", "Vegetation (pathology)", "Latent heat", "Mechanics and Transport in Unsaturated Soils", "Land cover", "Environmental Engineering", "0207 environmental engineering", "Energy balance", "Thermal Effects on Soil", "Environmental science", "[SDU] Sciences of the Universe [physics]", "G", "Meteorology", "Civil engineering", "14. Life underwater", "[SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology", "Biology", "Civil and Structural Engineering", "0105 earth and related environmental sciences", "Global Forest Drought Response and Climate Change", "FOS: Environmental engineering", "FOS: Earth and related environmental sciences", "15. Life on land", "Remote Sensing of Soil Moisture", "Environmental sciences", "Geotechnical engineering", "[SDU]Sciences of the Universe [physics]", "Satellite", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Land use", "[SDU.STU.HY] Sciences of the Universe [physics]/Earth Sciences/Hydrology", "[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces", "FOS: Civil engineering"]}, "links": [{"href": "https://hess.copernicus.org/articles/24/1781/2020/hess-24-1781-2020.pdf"}, {"href": "https://doi.org/10.60692/g4rcv-eqz54"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Hydrology%20and%20Earth%20System%20Sciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.60692/g4rcv-eqz54", "name": "item", "description": "10.60692/g4rcv-eqz54", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.60692/g4rcv-eqz54"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-04-23T00:00:00Z"}}, {"id": "10067/1897670151162165141", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:13Z", "type": "Journal Article", "created": "2022-07-01", "title": "Global stocks and capacity of mineral-associated soil organic carbon", "description": "Abstract

Soil is the largest terrestrial reservoir of organic carbon and is central for climate change mitigation and carbon-climate feedbacks. Chemical and physical associations of soil carbon with minerals play a critical role in carbon storage, but the amount and global capacity for storage in this form remain unquantified. Here, we produce spatially-resolved global estimates of mineral-associated organic carbon stocks and carbon-storage capacity by analyzing 1144 globally-distributed soil profiles. We show that current stocks total 899 Pg C to a depth of 1\uffe2\uff80\uff89m in non-permafrost mineral soils. Although this constitutes 66% and 70% of soil carbon in surface and deeper layers, respectively, it is only 42% and 21% of the mineralogical capacity. Regions under agricultural management and deeper soil layers show the largest undersaturation of mineral-associated carbon. Critically, the degree of undersaturation indicates sequestration efficiency over years to decades. We show that, across 103 carbon-accrual measurements spanning management interventions globally, soils furthest from their mineralogical capacity are more effective at accruing carbon; sequestration rates average 3-times higher in soils at one tenth of their capacity compared to soils at one half of their capacity. Our findings provide insights into the world\uffe2\uff80\uff99s soils, their capacity to store carbon, and priority regions and actions for soil carbon management.

Abstract. We present the Copernicus Atmosphere Monitoring Service TEMPOral profiles (CAMS-TEMPO), a dataset of global and European emission temporal profiles that provides gridded monthly, daily, weekly and hourly weight factors for atmospheric chemistry modelling. CAMS-TEMPO includes temporal profiles for the priority air pollutants (NOx; SOx; NMVOC, non-methane volatile organic compound; NH3; CO; PM10; and PM2.5) and the greenhouse gases (CO2 and CH4) for each of the following anthropogenic source categories: energy industry (power plants), residential combustion, manufacturing industry, transport (road traffic and air traffic in airports) and agricultural activities (fertilizer use and livestock). The profiles are computed on a global 0.1\u2009\u00d7\u20090.1\u2218 and regional European 0.1\u2009\u00d7\u20090.05\u2218 grid following the domain and sector classification descriptions of the global and regional emission inventories developed under the CAMS programme. The profiles account for the variability of the main emission drivers of each sector. Statistical information linked to emission variability (e.g. electricity production and traffic counts) at national and local levels were collected and combined with existing meteorology-dependent parametrizations to account for the influences of sociodemographic factors and climatological conditions. Depending on the sector and the temporal resolution (i.e. monthly, weekly, daily and hourly) the resulting profiles are pollutant-dependent, year-dependent (i.e. time series from 2010 to 2017) and/or spatially dependent (i.e. the temporal weights vary per country or region). We provide a complete description of the data and methods used to build the CAMS-TEMPO profiles, and whenever possible, we evaluate the representativeness of the proxies used to compute the temporal weights against existing observational data. We find important discrepancies when comparing the obtained temporal weights with other currently used datasets. The CAMS-TEMPO data product including the global (CAMS-GLOB-TEMPOv2.1, https://doi.org/10.24380/ks45-9147, Guevara et al., 2020a) and regional European (CAMS-REG-TEMPOv2.1, https://doi.org/10.24380/1cx4-zy68, Guevara et al., 2020b) temporal profiles are distributed from the Emissions of atmospheric Compounds and Compilation of Ancillary Data (ECCAD) system (https://eccad.aeris-data.fr/, last access: February 2021).

", "keywords": ["China", "Atmospheric chemistry", "550", "Anthropogenic emissions", "Ammonia emissions", "Urbanisation", "Environment", "7. Clean energy", "[SDU] Sciences of the Universe [physics]", "11. Sustainability", "Air-pollution", "GE1-350", "Gridded emissions", "Fuel use", "QE1-996.5", "[SDU.OCEAN] Sciences of the Universe [physics]/Ocean", " Atmosphere", "Inventory", "Geology", "Environmental sciences", "Data product", "Qu\u00edmica atmosf\u00e8rica", "13. Climate action", "Air quality", "Transport model", "Data sets", "Bottom-up", "\u00c0rees tem\u00e0tiques de la UPC::Desenvolupament hum\u00e0 i sostenible::Degradaci\u00f3 ambiental::Contaminaci\u00f3 atmosf\u00e8rica", ":Desenvolupament hum\u00e0 i sostenible::Degradaci\u00f3 ambiental::Contaminaci\u00f3 atmosf\u00e8rica [\u00c0rees tem\u00e0tiques de la UPC]", "Air pollutants"]}, "links": [{"href": "https://essd.copernicus.org/articles/13/367/2021/essd-13-367-2021.pdf"}, {"href": "https://doi.org/3129610671"}, {"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": "3129610671", "name": "item", "description": "3129610671", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3129610671"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-02-12T00:00:00Z"}}, {"id": "10459.1/60556", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:24Z", "type": "Journal Article", "created": "2017-11-10", "title": "Disaggregation of SMOS Soil Moisture to 100 m Resolution Using MODIS Optical/Thermal and Sentinel-1 Radar Data: Evaluation over a Bare Soil Site in Morocco", "description": "

The 40 km resolution SMOS (Soil Moisture and Ocean Salinity) soil moisture, previously disaggregated at a 1 km resolution using the DISPATCH (DISaggregation based on Physical And Theoretical scale CHange) method based on MODIS optical/thermal data, is further disaggregated to 100 m resolution using Sentinel-1 backscattering coefficient (\u03c3\u00b0). For this purpose, three distinct radar-based disaggregation methods are tested by linking the spatio-temporal variability of \u03c3\u00b0 and soil moisture data at the 1 km and 100 m resolution. The three methods are: (1) the weight method, which estimates soil moisture at 100 m resolution at a certain time as a function of \u03c3\u00b0 ratio (100 m to 1 km resolution) and the 1 km DISPATCH products of the same time; (2) the regression method which estimates soil moisture as a function of \u03c3\u00b0 where the regression parameters (e.g., intercept and slope) vary in space and time; and (3) the Cumulative Distribution Function (CDF) method, which estimates 100 m resolution soil moisture from the cumulative probability of 100 m resolution backscatter and the maximum to minimum 1 km resolution (DISPATCH) soil moisture difference. In each case, disaggregation results are evaluated against in situ measurements collected between 1 January 2016 and 11 October 2016 over a bare soil site in central Morocco. The determination coefficient (R2) between 1 km resolution DISPATCH and localized in situ soil moisture is 0.31. The regression and CDF methods have marginal effect on improving the DISPATCH accuracy at the station scale with a R2 between remotely sensed and in situ soil moisture of 0.29 and 0.34, respectively. By contrast, the weight method significantly improves the correlation between remotely sensed and in situ soil moisture with a R2 of 0.52. Likewise, the soil moisture estimates show low root mean square difference with in situ measurements (RMSD= 0.032 m3 m\u22123).

", "keywords": ["soil moisture and ocean salinity satellite (SMOS)", "Atmospheric Science", "Artificial intelligence", "Environmental Engineering", "550", "Science", "Soil Moisture", "0211 other engineering and technologies", "Aerospace Engineering", "FOS: Mechanical engineering", "02 engineering and technology", "01 natural sciences", "Environmental science", "[SDU] Sciences of the Universe [physics]", "Engineering", "Meteorology", "DISPATCH", "Image resolution", "Arctic Permafrost Dynamics and Climate Change", "14. Life underwater", "Moisture", "0105 earth and related environmental sciences", "Soil science", "Water content", "Radar", "Geography", "soil moisture and ocean salinity satellite (SMOS); DISPATCH; radar; Sentinel-1; disaggregation; soil moisture", "Soilmoisture and ocean salinity satellite (SMOS)", "Synthetic Aperture Radar Interferometry", "Q", "FOS: Environmental engineering", "Geology", "FOS: Earth and related environmental sciences", "Remote sensing", "Remote Sensing of Soil Moisture", "Surface Deformation Monitoring", "Computer science", "Earth and Planetary Sciences", "Groundwater Extraction", "Geotechnical engineering", "[SDU]Sciences of the Universe [physics]", "disaggregation", "Environmental Science", "Physical Sciences", "Sentinel-1", "soil moisture", "radar"]}, "links": [{"href": "http://www.mdpi.com/2072-4292/9/11/1155/pdf"}, {"href": "https://doi.org/10459.1/60556"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Remote%20Sensing", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10459.1/60556", "name": "item", "description": "10459.1/60556", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10459.1/60556"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-11-10T00:00:00Z"}}, {"id": "11386/4857971", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:31Z", "type": "Journal Article", "created": "2023-08-23", "title": "Observing Mineral Dust in Northern Africa, the Middle East, and Europe: Current Capabilities and Challenges ahead for the Development of Dust Services", "description": "Abstract

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

Abstract. Climate\u00a0change contributes to the increased frequency and intensity of wildfires globally, with significant impacts on society and the environment. However, our understanding of the global distribution of extreme fires remains skewed, primarily influenced by media coverage and regionalised research efforts. This inaugural State of Wildfires report systematically analyses fire activity worldwide, identifying extreme events from the March 2023\u2013February 2024 fire season. We assess the causes, predictability, and attribution of these events to climate change and land use and forecast future risks under different climate scenarios. During the 2023\u20132024 fire season, 3.9\u00d7106\u2009km2 burned globally, slightly below the average of previous seasons, but fire carbon (C) emissions were 16\u2009% above average, totalling 2.4\u2009Pg\u2009C. Global fire C emissions were increased by record emissions in Canadian boreal forests (over 9 times the average) and reduced by low emissions from African savannahs. Notable events included record-breaking fire extent and emissions in Canada, the largest recorded wildfire in the European Union (Greece), drought-driven fires in western Amazonia and northern parts of South America, and deadly fires in Hawaii (100 deaths) and Chile (131 deaths). Over 232\u2009000 people were evacuated in Canada alone, highlighting the severity of human impact. Our analyses revealed that multiple drivers were needed to cause areas of extreme fire activity. In Canada and Greece, a combination of high fire weather and an abundance of dry fuels increased the probability of fires, whereas burned area anomalies were weaker in regions with lower fuel loads and higher direct suppression, particularly in Canada. Fire weather prediction in Canada showed a mild anomalous signal 1 to 2 months in advance, whereas events in Greece and Amazonia had shorter predictability horizons. Attribution analyses indicated that modelled anomalies in burned area were up to 40\u2009%, 18\u2009%, and 50\u2009% higher due to climate change in Canada, Greece, and western Amazonia during the 2023\u20132024 fire season, respectively. Meanwhile, the probability of extreme fire seasons of these magnitudes has increased significantly due to anthropogenic climate change, with a 2.9\u20133.6-fold increase in likelihood of high fire weather in Canada and a 20.0\u201328.5-fold increase in Amazonia. By the end of the century, events of similar magnitude to 2023 in Canada are projected to occur 6.3\u201310.8 times more frequently under a medium\u2013high emission scenario (SSP370). This report represents our first annual effort to catalogue extreme wildfire events, explain their occurrence, and predict future risks. By consolidating state-of-the-art wildfire science and delivering key insights relevant to policymakers, disaster management services, firefighting agencies, and land managers, we aim to enhance society's resilience to wildfires and promote advances in preparedness, mitigation, and adaptation. New datasets presented in this work are available from https://doi.org/10.5281/zenodo.11400539 (Jones et al., 2024) and https://doi.org/10.5281/zenodo.11420742 (Kelley et al., 2024a).

", "keywords": ["QE1-996.5", "info:eu-repo/classification/ddc/550", "550", "Geology", "15. Life on land", "7. Clean energy", "wildfire", "[SDU] Sciences of the Universe [physics]", "Environmental sciences", "climate change", "[SDU]Sciences of the Universe [physics]", "13. Climate action", "11. Sustainability", "Life Science", "GE1-350"]}, "links": [{"href": "https://ueaeprints.uea.ac.uk/id/eprint/96389/1/essd_16_3601_2024.pdf"}, {"href": "https://essd.copernicus.org/articles/16/3601/2024/essd-16-3601-2024.pdf"}, {"href": "https://doi.org/10871/137179"}, {"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": "10871/137179", "name": "item", "description": "10871/137179", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10871/137179"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-08-14T00:00:00Z"}}, {"id": "1854/LU-8528923", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:40Z", "type": "Journal Article", "created": "2017-03-23", "title": "A review of spatial downscaling of satellite remotely sensed soil moisture", "description": "Abstract

Satellite remote sensing technology has been widely used to estimate surface soil moisture. Numerous efforts have been devoted to develop global soil moisture products. However, these global soil moisture products, normally retrieved from microwave remote sensing data, are typically not suitable for regional hydrological and agricultural applications such as irrigation management and flood predictions, due to their coarse spatial resolution. Therefore, various downscaling methods have been proposed to improve the coarse resolution soil moisture products. The purpose of this paper is to review existing methods for downscaling satellite remotely sensed soil moisture. These methods are assessed and compared in terms of their advantages and limitations. This review also provides the accuracy level of these methods based on published validation studies. In the final part, problems and future trends associated with these methods are analyzed.

Abstract. One of the challenges in studying desert dust aerosol along with its numerous interactions and impacts is the paucity of direct in-situ measurements, particularly in the areas most affected by dust storms. Satellites typically provide columnintegrated aerosol measurements, but observationally-constrained continuous 3D dust fields are needed to assess dust variability, climate effects and impacts upon a variety of socio-economic sectors. Here, we present a high resolution regional reanalysis data set of desert dust aerosols that covers Northern Africa, the Middle East and Europe along with the Mediterranean sea and parts of Central Asia, and the Atlantic and Indian Oceans between 2007 and 2016. The horizontal resolution is 0.1\u00b0 latitude\u2009\u00d7\u20090.1\u00b0 longitude, and the temporal resolution is 3 hours. The reanalysis was produced using Local Ensemble Transform Kalman Filter (LETKF) data assimilation in the Multiscale Online Non-hydrostatic AtmospheRe CHemistry model (MONARCH) developed at the Barcelona Supercomputing Center (BSC). The assimilated data are coarse-mode dust optical depth retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue Level 2 products. The reanalysis data set consists of upper air (dust mass concentrations and extinction coefficient), surface (dust deposition and solar irradiance fields, among them) and total column (e.g., dust optical depth and load) variables. Some dust variables, such as concentrations and wet and dry deposition, are expressed for a binned size distribution that ranges from 0.2 to 20\u2009\u03bcm in particle diameter. Both analysis and first-guess (analysis-initialized simulation) fields are available for the variables that are diagnosed from the state vector. A set of ensemble statistics is archived for each output variable, namely the ensemble mean, standard deviation, maximum and median. The spatial and temporal distribution of the dust fields follows well-known dust cycle features controlled by seasonal changes in meteorology and vegetation cover. The analysis is statistically closer to the assimilated retrievals than the first-guess, which proves the consistency of the data assimilation method. Independent evaluation using AERONET dust-filtered optical depth retrievals indicates that the reanalysis data set is highly accurate (mean bias\u2009=\u2009\u22120.05, RMSE\u2009=\u20090.12, r\u2009=\u20090.81 when compared to retrievals from the spectral de-convolution algorithm on a 3-hourly basis). Verification statistics are broadly homogeneous in space and time with regional differences that can be partly attributed to model limitations (e.g., poor representation of small-scale emission processes), presence of aerosols other than dust in the observations used in the evaluation, and differences in the number of observations among seasons. Such a reliable high-resolution historical record of atmospheric desert dust will allow a better quantification of dust impacts upon key sectors of society and economy, including health, solar energy production and transportation. The reanalysis data set (Di Tomaso et al., 2021) is distributed via a Thematic Real-time Environmental Distributed Data Service (THREDDS) at BSC and freely available at http://hdl.handle.net/21.12146/c6d4a608-5de3-47f6-a004-67cb1d498d98.

", "keywords": ["Desert dust aerosol", "550", "Climate", "MINERAL-COMPOSITION", "Aerosols atmosf\u00e8rics", "01 natural sciences", "Dust emission", "[SDU] Sciences of the Universe [physics]", "LETKF", "Local ensemble transform Kalman filter", "DATA ASSIMILATION", "\u00c0rees tem\u00e0tiques de la UPC::Enginyeria agroaliment\u00e0ria::Ci\u00e8ncies de la terra i de la vida::Climatologia i meteorologia", "Pols -- Control", "SDG 3 - Good Health and Well-being", "MONARCH", "SAHARAN DUST", "SIZE DISTRIBUTION", "GE1-350", "Desert", "CONVECTIVE ADJUSTMENT SCHEME", "Aerosol measurements", "Multiscale Online Nonhydrostatic AtmospheRe CHemistry model", "0105 earth and related environmental sciences", "QE1-996.5", "info:eu-repo/classification/ddc/550", ":Enginyeria agroaliment\u00e0ria::Ci\u00e8ncies de la terra i de la vida::Climatologia i meteorologia [\u00c0rees tem\u00e0tiques de la UPC]", "ddc:550", "Geology", "1 MODEL DESCRIPTION", "OPTICAL-PROPERTIES", "MONARCH modeling system", "Atmospheric aerosols", "Environmental sciences", "Earth sciences", "PM10 CONCENTRATIONS", "900", "Dust aerosol", "13. Climate action", "[SDU.STU] Sciences of the Universe [physics]/Earth Sciences", "SINGLE-SCATTERING ALBEDO", "MEDITERRANEAN BASIN", "Dust control"]}, "links": [{"href": "https://iris.cnr.it/bitstream/20.500.14243/417480/1/prod_471097-doc_191235.pdf"}, {"href": "https://essd.copernicus.org/articles/14/2785/2022/essd-14-2785-2022.pdf"}, {"href": "https://doi.org/20.500.14243/417480"}, {"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": "20.500.14243/417480", "name": "item", "description": "20.500.14243/417480", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/20.500.14243/417480"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-10-28T00:00:00Z"}}, {"id": "20.500.14352/123440", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:53Z", "type": "Journal Article", "created": "2022-10-10", "title": "Women in limnology: From a historical perspective to a present\u2010day evaluation", "description": "Abstract

Research in limnology is nurtured by the work of many fascinating and passionate women, who have contributed enormously to our understanding of inland waters. Female limnologists have promoted and established the bases of our knowledge about inland waters and fostered the need of protecting the values of those ecosystems. However, on numerous occasions, their contribution to the advancement of limnology has not been duly recognized. Here, we review the presence of women in limnology through the history of the discipline: from the pioneers who contributed to the origins to present day' developments. We aim at visibilizing those scientists and establish them as role models. We also analyze in a simple and illustrative way the current situation of women in limnology, the scientific barriers they must deal with, and their future prospects. Multiple aspects fostering the visibility of a scientist, such as their presence in conferences, awards, or representation in societal or editorial boards show a significant gap, with none of those aspects showing a similar visibility of women and men in limnology. This article raises awareness of the obstacles that women in limnology faced and still face, and encourages to embrace models of leadership, scientific management, and assessment of research performance far from those commonly established.

This article is categorized under:

Science of Water > Methods

Water and Life > Methods

Abstract. Lateral transfer of carbon (C) from terrestrial ecosystems into the inland water network is an important component of the global C cycle, which sustains a large aquatic CO2 evasion flux fuelled by the decomposition of allochthonous C inputs. Globally, estimates of the total C exports through the terrestrial\u2013aquatic interface range from 1.5 to 2.7\u202fPg\u202fC\u202fyr\u22121 (Cole et al., 2007; Battin et al., 2009; Tranvik et al., 2009), i.e. of the order of 2\u20135\u202f% of the terrestrial NPP. Earth system models (ESMs) of the climate system ignore these lateral transfers of C, and thus likely overestimate the terrestrial C sink. In this study, we present the implementation of fluvial transport of dissolved organic carbon (DOC) and CO2 into ORCHIDEE (Organising Carbon and Hydrology in Dynamic Ecosystems), the land surface scheme of the Institut Pierre-Simon Laplace ESM. This new model branch, called ORCHILEAK, represents DOC production from canopy and soils, DOC and CO2 leaching from soils to streams, DOC decomposition, and CO2 evasion to the atmosphere during its lateral transport in rivers, as well as exchange with the soil carbon and litter stocks on floodplains and in swamps. We parameterized and validated ORCHILEAK for the Amazon basin, the world's largest river system with regard to discharge and one of the most productive ecosystems in the world. With ORCHILEAK, we are able to reproduce observed terrestrial and aquatic fluxes of DOC and CO2 in the Amazon basin, both in terms of mean values and seasonality. In addition, we are able to resolve the spatio-temporal variability in C fluxes along the canopy\u2013soil\u2013water continuum at high resolution (1\u00b0, daily) and to quantify the different terrestrial contributions to the aquatic C fluxes. We simulate that more than two-thirds of the Amazon's fluvial DOC export are contributed by the decomposition of submerged litter. Throughfall DOC fluxes from canopy to ground are about as high as the total DOC inputs to inland waters. The latter, however, are mainly sustained by litter decomposition. Decomposition of DOC and submerged plant litter contributes slightly more than half of the CO2 evasion from the water surface, while the remainder is contributed by soil respiration. Total CO2 evasion from the water surface equals about 5\u202f% of the terrestrial NPP. Our results highlight that ORCHILEAK is well suited to simulate carbon transfers along the terrestrial\u2013aquatic continuum of tropical forests. It also opens the perspective that provided parameterization, calibration and validation is performed for other biomes, the new model branch could improve the quantification of the global terrestrial C sink and help better constrain carbon cycle\u2013climate feedbacks in future projections.

", "keywords": ["[SDU] Sciences of the Universe [physics]", "Sciences de la terre et du cosmos", "570", "QE1-996.5", "550", "[SDU]Sciences of the Universe [physics]", "13. Climate action", "Geology", "Sciences pharmaceutiques", "15. Life on land"]}, "links": [{"href": "https://gmd.copernicus.org/articles/10/3821/2017/gmd-10-3821-2017.pdf"}, {"href": "https://dipot.ulb.ac.be/dspace/bitstream/2013/261804/4/doi_245431.pdf"}, {"href": "https://doi.org/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/261804"}, {"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": "2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/261804", "name": "item", "description": "2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/261804", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/261804"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-10-23T00:00:00Z"}}, {"id": "2117/342239", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:57Z", "type": "Journal Article", "created": "2021-03-17", "title": "Quantifying the range of the dust direct radiative effect due to source mineralogy uncertainty", "description": "

Abstract. The large uncertainty in the mineral dust direct radiative effect (DRE) hinders projections of future climate change due to anthropogenic activity. Resolving modeled dust mineral speciation allows for spatially and temporally varying refractive indices consistent with dust aerosol composition. Here, for the first time, we quantify the range in dust DRE at the top of the atmosphere (TOA) due to current uncertainties in the surface soil mineralogical content using a dust mineral-resolving climate model. We propagate observed uncertainties in soil mineral abundances from two soil mineralogy atlases along with the optical properties of each mineral into the DRE and compare the resultant range with other sources of uncertainty across six climate models. The shortwave DRE responds region-specifically to the dust burden depending on the mineral speciation and underlying shortwave surface albedo: positively when the regionally averaged annual surface albedo is larger than 0.28 and negatively otherwise. Among all minerals examined, the shortwave TOA DRE and single scattering albedo at the 0.44\u20130.63\u2009\u00b5m band are most sensitive to the fractional contribution of iron oxides to the total dust composition. The global net (shortwave plus longwave) TOA DRE is estimated to be within \u22120.23 to +0.35\u2009W\u2009m\u22122. Approximately 97\u2009% of this range relates to uncertainty in the soil abundance of iron oxides. Representing iron oxide with solely hematite optical properties leads to an overestimation of shortwave DRE by +0.10\u2009W\u2009m\u22122 at the TOA, as goethite is not as absorbing as hematite in the shortwave spectrum range. Our study highlights the importance of iron oxides to the shortwave DRE: they have a disproportionally large impact on climate considering their small atmospheric mineral mass fractional burden (\u223c2\u2009%). An improved description of iron oxides, such as those planned in the Earth Surface Mineral Dust Source Investigation (EMIT), is thus essential for more accurate estimates of the dust DRE.

", "keywords": ["Mineral dusts", "Atmospheric sciences", "550", "QC1-999", "Iron oxides", "01 natural sciences", "Atmospheric Sciences", ":Enginyeria qu\u00edmica::Qu\u00edmica del medi ambient::Qu\u00edmica atmosf\u00e8rica [\u00c0rees tem\u00e0tiques de la UPC]", "[SDU] Sciences of the Universe [physics]", "\u00d2xids de ferro", "Pols", "Meteorology & Atmospheric Sciences", "\u00c0rees tem\u00e0tiques de la UPC::Enginyeria qu\u00edmica::Qu\u00edmica del medi ambient::Qu\u00edmica atmosf\u00e8rica", "QD1-999", "0105 earth and related environmental sciences", "info:eu-repo/classification/ddc/550", "Climate change science", "ddc:550", "Physics", "Climatic changes", "15. Life on land", "Climate Action", "Earth sciences", "Chemistry", "[SDU]Sciences of the Universe [physics]", "13. Climate action", "Earth Sciences", "Astronomical and Space Sciences", "Canvis clim\u00e0tics"]}, "links": [{"href": "https://acp.copernicus.org/articles/21/3973/2021/acp-21-3973-2021.pdf"}, {"href": "https://escholarship.org/content/qt27c9p2v2/qt27c9p2v2.pdf"}, {"href": "https://doi.org/2117/342239"}, {"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": "2117/342239", "name": "item", "description": "2117/342239", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2117/342239"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-09-15T00:00:00Z"}}, {"id": "2117/342462", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:57Z", "type": "Journal Article", "created": "2021-02-13", "title": "Copernicus Atmosphere Monitoring Service TEMPOral profiles (CAMS-TEMPO): global and European emission temporal profile maps for atmospheric chemistry modelling", "description": "

Abstract. We present the Copernicus Atmosphere Monitoring Service TEMPOral profiles (CAMS-TEMPO), a dataset of global and European emission temporal profiles that provides gridded monthly, daily, weekly and hourly weight factors for atmospheric chemistry modelling. CAMS-TEMPO includes temporal profiles for the priority air pollutants (NOx; SOx; NMVOC, non-methane volatile organic compound; NH3; CO; PM10; and PM2.5) and the greenhouse gases (CO2 and CH4) for each of the following anthropogenic source categories: energy industry (power plants), residential combustion, manufacturing industry, transport (road traffic and air traffic in airports) and agricultural activities (fertilizer use and livestock). The profiles are computed on a global 0.1\u2009\u00d7\u20090.1\u2218 and regional European 0.1\u2009\u00d7\u20090.05\u2218 grid following the domain and sector classification descriptions of the global and regional emission inventories developed under the CAMS programme. The profiles account for the variability of the main emission drivers of each sector. Statistical information linked to emission variability (e.g. electricity production and traffic counts) at national and local levels were collected and combined with existing meteorology-dependent parametrizations to account for the influences of sociodemographic factors and climatological conditions. Depending on the sector and the temporal resolution (i.e. monthly, weekly, daily and hourly) the resulting profiles are pollutant-dependent, year-dependent (i.e. time series from 2010 to 2017) and/or spatially dependent (i.e. the temporal weights vary per country or region). We provide a complete description of the data and methods used to build the CAMS-TEMPO profiles, and whenever possible, we evaluate the representativeness of the proxies used to compute the temporal weights against existing observational data. We find important discrepancies when comparing the obtained temporal weights with other currently used datasets. The CAMS-TEMPO data product including the global (CAMS-GLOB-TEMPOv2.1, https://doi.org/10.24380/ks45-9147, Guevara et al., 2020a) and regional European (CAMS-REG-TEMPOv2.1, https://doi.org/10.24380/1cx4-zy68, Guevara et al., 2020b) temporal profiles are distributed from the Emissions of atmospheric Compounds and Compilation of Ancillary Data (ECCAD) system (https://eccad.aeris-data.fr/, last access: February 2021).

", "keywords": ["China", "Atmospheric chemistry", "550", "Anthropogenic emissions", "Ammonia emissions", "Urbanisation", "Environment", "7. Clean energy", "[SDU] Sciences of the Universe [physics]", "11. Sustainability", "Air-pollution", "GE1-350", "Gridded emissions", "Fuel use", "QE1-996.5", "[SDU.OCEAN] Sciences of the Universe [physics]/Ocean", " Atmosphere", "Inventory", "Geology", "Environmental sciences", "Data product", "Qu\u00edmica atmosf\u00e8rica", "13. Climate action", "Air quality", "Transport model", "Data sets", "Bottom-up", "\u00c0rees tem\u00e0tiques de la UPC::Desenvolupament hum\u00e0 i sostenible::Degradaci\u00f3 ambiental::Contaminaci\u00f3 atmosf\u00e8rica", ":Desenvolupament hum\u00e0 i sostenible::Degradaci\u00f3 ambiental::Contaminaci\u00f3 atmosf\u00e8rica [\u00c0rees tem\u00e0tiques de la UPC]", "Air pollutants"]}, "links": [{"href": "https://essd.copernicus.org/articles/13/367/2021/essd-13-367-2021.pdf"}, {"href": "https://doi.org/2117/342462"}, {"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": "2117/342462", "name": "item", "description": "2117/342462", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2117/342462"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-02-12T00:00:00Z"}}, {"id": "2164/21071", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:59Z", "type": "Journal Article", "created": "2023-05-24", "title": "Microbial carbon use efficiency promotes global soil carbon storage", "description": "Abstract

Soils store more carbon than other terrestrial ecosystems1,2. How soil organic carbon (SOC) forms and persists remains uncertain1,3, which makes it challenging to understand how it will respond to climatic change3,4. It has been suggested that soil microorganisms play an important role in SOC formation, preservation and loss5\uffe2\uff80\uff937. Although microorganisms affect the accumulation and loss of soil organic matter through many pathways4,6,8\uffe2\uff80\uff9311, microbial carbon use efficiency (CUE) is an integrative metric that can capture the balance of these processes12,13. Although CUE has the potential to act as a predictor of variation in SOC storage, the role of CUE in SOC persistence remains unresolved7,14,15. Here we examine the relationship between CUE and the preservation of SOC, and interactions with climate, vegetation and edaphic properties, using a combination of global-scale datasets, a microbial-process explicit model, data assimilation, deep learning and meta-analysis. We find that CUE is at least four times as important as other evaluated factors, such as carbon input, decomposition or vertical transport, in determining SOC storage and its spatial variation across the globe. In addition, CUE shows a positive correlation with SOC content. Our findings point to microbial CUE as a major determinant of global SOC storage. Understanding the microbial processes underlying CUE and their environmental dependence may help the prediction of SOC feedback to a changing climate.

The 40 km resolution SMOS (Soil Moisture and Ocean Salinity) soil moisture, previously disaggregated at a 1 km resolution using the DISPATCH (DISaggregation based on Physical And Theoretical scale CHange) method based on MODIS optical/thermal data, is further disaggregated to 100 m resolution using Sentinel-1 backscattering coefficient (\u03c3\u00b0). For this purpose, three distinct radar-based disaggregation methods are tested by linking the spatio-temporal variability of \u03c3\u00b0 and soil moisture data at the 1 km and 100 m resolution. The three methods are: (1) the weight method, which estimates soil moisture at 100 m resolution at a certain time as a function of \u03c3\u00b0 ratio (100 m to 1 km resolution) and the 1 km DISPATCH products of the same time; (2) the regression method which estimates soil moisture as a function of \u03c3\u00b0 where the regression parameters (e.g., intercept and slope) vary in space and time; and (3) the Cumulative Distribution Function (CDF) method, which estimates 100 m resolution soil moisture from the cumulative probability of 100 m resolution backscatter and the maximum to minimum 1 km resolution (DISPATCH) soil moisture difference. In each case, disaggregation results are evaluated against in situ measurements collected between 1 January 2016 and 11 October 2016 over a bare soil site in central Morocco. The determination coefficient (R2) between 1 km resolution DISPATCH and localized in situ soil moisture is 0.31. The regression and CDF methods have marginal effect on improving the DISPATCH accuracy at the station scale with a R2 between remotely sensed and in situ soil moisture of 0.29 and 0.34, respectively. By contrast, the weight method significantly improves the correlation between remotely sensed and in situ soil moisture with a R2 of 0.52. Likewise, the soil moisture estimates show low root mean square difference with in situ measurements (RMSD= 0.032 m3 m\u22123).

", "keywords": ["soil moisture and ocean salinity satellite (SMOS)", "Atmospheric Science", "Artificial intelligence", "Environmental Engineering", "550", "Science", "Soil Moisture", "0211 other engineering and technologies", "Aerospace Engineering", "FOS: Mechanical engineering", "02 engineering and technology", "01 natural sciences", "Environmental science", "[SDU] Sciences of the Universe [physics]", "Engineering", "Meteorology", "DISPATCH", "Image resolution", "Arctic Permafrost Dynamics and Climate Change", "14. Life underwater", "Moisture", "0105 earth and related environmental sciences", "Soil science", "Water content", "Radar", "Geography", "soil moisture and ocean salinity satellite (SMOS); DISPATCH; radar; Sentinel-1; disaggregation; soil moisture", "Soilmoisture and ocean salinity satellite (SMOS)", "Synthetic Aperture Radar Interferometry", "Q", "FOS: Environmental engineering", "Geology", "FOS: Earth and related environmental sciences", "Remote sensing", "Remote Sensing of Soil Moisture", "Surface Deformation Monitoring", "Computer science", "Earth and Planetary Sciences", "Groundwater Extraction", "Geotechnical engineering", "[SDU]Sciences of the Universe [physics]", "disaggregation", "Environmental Science", "Physical Sciences", "Sentinel-1", "soil moisture", "radar"]}, "links": [{"href": "http://www.mdpi.com/2072-4292/9/11/1155/pdf"}, {"href": "https://doi.org/2767588274"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Remote%20Sensing", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2767588274", "name": "item", "description": "2767588274", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2767588274"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-11-10T00:00:00Z"}}, {"id": "3084540378", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:23:20Z", "type": "Journal Article", "created": "2021-03-17", "title": "Quantifying the range of the dust direct radiative effect due to source mineralogy uncertainty", "description": "

Abstract. The large uncertainty in the mineral dust direct radiative effect (DRE) hinders projections of future climate change due to anthropogenic activity. Resolving modeled dust mineral speciation allows for spatially and temporally varying refractive indices consistent with dust aerosol composition. Here, for the first time, we quantify the range in dust DRE at the top of the atmosphere (TOA) due to current uncertainties in the surface soil mineralogical content using a dust mineral-resolving climate model. We propagate observed uncertainties in soil mineral abundances from two soil mineralogy atlases along with the optical properties of each mineral into the DRE and compare the resultant range with other sources of uncertainty across six climate models. The shortwave DRE responds region-specifically to the dust burden depending on the mineral speciation and underlying shortwave surface albedo: positively when the regionally averaged annual surface albedo is larger than 0.28 and negatively otherwise. Among all minerals examined, the shortwave TOA DRE and single scattering albedo at the 0.44\u20130.63\u2009\u00b5m band are most sensitive to the fractional contribution of iron oxides to the total dust composition. The global net (shortwave plus longwave) TOA DRE is estimated to be within \u22120.23 to +0.35\u2009W\u2009m\u22122. Approximately 97\u2009% of this range relates to uncertainty in the soil abundance of iron oxides. Representing iron oxide with solely hematite optical properties leads to an overestimation of shortwave DRE by +0.10\u2009W\u2009m\u22122 at the TOA, as goethite is not as absorbing as hematite in the shortwave spectrum range. Our study highlights the importance of iron oxides to the shortwave DRE: they have a disproportionally large impact on climate considering their small atmospheric mineral mass fractional burden (\u223c2\u2009%). An improved description of iron oxides, such as those planned in the Earth Surface Mineral Dust Source Investigation (EMIT), is thus essential for more accurate estimates of the dust DRE.

", "keywords": ["Mineral dusts", "Atmospheric sciences", "550", "QC1-999", "Iron oxides", "01 natural sciences", "Atmospheric Sciences", ":Enginyeria qu\u00edmica::Qu\u00edmica del medi ambient::Qu\u00edmica atmosf\u00e8rica [\u00c0rees tem\u00e0tiques de la UPC]", "[SDU] Sciences of the Universe [physics]", "\u00d2xids de ferro", "Pols", "Meteorology & Atmospheric Sciences", "\u00c0rees tem\u00e0tiques de la UPC::Enginyeria qu\u00edmica::Qu\u00edmica del medi ambient::Qu\u00edmica atmosf\u00e8rica", "QD1-999", "0105 earth and related environmental sciences", "info:eu-repo/classification/ddc/550", "Climate change science", "ddc:550", "Physics", "Climatic changes", "15. Life on land", "Climate Action", "Earth sciences", "Chemistry", "[SDU]Sciences of the Universe [physics]", "13. Climate action", "Earth Sciences", "Astronomical and Space Sciences", "Canvis clim\u00e0tics"]}, "links": [{"href": "https://acp.copernicus.org/articles/21/3973/2021/acp-21-3973-2021.pdf"}, {"href": "https://escholarship.org/content/qt27c9p2v2/qt27c9p2v2.pdf"}, {"href": "https://doi.org/3084540378"}, {"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": "3084540378", "name": "item", "description": "3084540378", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3084540378"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-09-15T00:00:00Z"}}, {"id": "2914742561", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:23:10Z", "type": "Journal Article", "created": "2019-02-05", "title": "Current state of the global operational aerosol multi\u2010model ensemble: An update from the International Cooperative for Aerosol Prediction (ICAP)", "description": "

Since the first International Cooperative for Aerosol Prediction (ICAP) multi\u2010model ensemble (MME) study, the number of ICAP global operational aerosol models has increased from five to nine. An update of the current ICAP status is provided, along with an evaluation of the performance of ICAP\u2010MME over 2012\u20132017, with a focus on June 2016\u2013May 2017. Evaluated with ground\u2010based Aerosol Robotic Network (AERONET) aerosol optical depth (AOD) and data assimilation quality MODerate\u2010resolution Imaging Spectroradiometer (MODIS) retrieval products, the ICAP\u2010MME AOD consensus remains the overall top\u2010scoring and most consistent performer among all models in terms of root\u2010mean\u2010square error (RMSE), bias and correlation for total, fine\u2010 and coarse\u2010mode AODs as well as dust AOD; this is similar to the first ICAP\u2010MME study. Further, over the years, the performance of ICAP\u2010MME is relatively stable and reliable compared to more variability in the individual models. The extent to which the AOD forecast error of ICAP\u2010MME can be predicted is also examined. Leading predictors are found to be the consensus mean and spread. Regression models of absolute forecast errors were built for AOD forecasts of different lengths for potential applications. ICAP\u2010MME performance in terms of modal AOD RMSEs of the 21 regionally representative sites over 2012\u20132017 suggests a general tendency for model improvements in fine\u2010mode AOD, especially over Asia. No significant improvement in coarse\u2010mode AOD is found overall for this time period.

", "keywords": ["[SDU] Sciences of the Universe [physics]", "Special Supplement on 25 Years of Ensemble Forecasting", "01 natural sciences", "[PHYS.PHYS.PHYS-AO-PH] Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph]", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/qj.3497"}, {"href": "https://doi.org/2914742561"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Quarterly%20Journal%20of%20the%20Royal%20Meteorological%20Society", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2914742561", "name": "item", "description": "2914742561", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2914742561"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-04-02T00:00:00Z"}}, {"id": "2940609395", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:23:11Z", "type": "Journal Article", "created": "2019-04-23", "title": "An evapotranspiration model self-calibrated from remotely sensed surface soil moisture, land surface temperature and vegetation cover fraction: application to disaggregated SMOS and MODIS data", "description": "

Abstract. Thermal-based two-source energy balance modeling is very useful for estimating the land evapotranspiration (ET) at a wide range of spatial and temporal scales. However, the land surface temperature (LST) is not sufficient for constraining simultaneously both soil and vegetation flux components in such a way that assumptions (on either the soil or the vegetation fluxes) are commonly required. To avoid such assumptions, a new energy balance model (TSEB-SM) was recently developed in Ait Hssaine et al. (2018a) to integrate the microwave-derived near-surface soil moisture (SM), in addition to the thermal-derived LST and vegetation cover fraction (fc). Whereas, TSEB-SM has been recently tested using in-situ measurements, the objective of this paper is to evaluate the performance of TSEB-SM in real-life using 1\u2009km resolution MODIS (Moderate resolution imaging spectroradiometer) LST and fc data and the 1\u2009km resolution SM data disaggregated from SMOS (Soil Moisture and Ocean Salinity) observations by using DisPATCh. The approach is applied during a four-year period (2014\u20132018) over a rainfed wheat field in the Tensift basin, central Morocco, during a four-year period (2014\u20132018). The field was seeded for the 2014\u20132015 (S1), 2016\u20132017 (S2) and 2017\u20132018 (S3) agricultural season, while it was not ploughed (remained as bare soil) during the 2015\u20132016 (B1) agricultural season. The mean retrieved values of (arss, brss) calculated for the entire study period using satellite data are (7.32, 4.58). The daily calibrated \u03b1PT ranges between 0 and 1.38 for both S1 and S2. Its temporal variability is mainly attributed to the rainfall distribution along the agricultural season. For S3, the daily retrieved \u03b1PT remains at a mostly constant value (\u223c\u20090.7) throughout the study period, because of the lack of clear sky disaggregated SM and LST observations during this season. Compared to eddy covariance measurements, TSEB driven only by LST and fc data significantly overestimates latent heat fluxes for the four seasons. The overall mean bias values are 119, 94, 128 and 181\u2009W/m2 for S1, S2, S3 and B1 respectively. In contrast, these errors are much reduced when using TSEB-SM (SM and LST combined data) with the mean bias values estimated as 39, 4, 7 and 62\u2009W/m2 for S1, S2, S3 and B1 respectively.

", "keywords": ["Technology", "Atmospheric sciences", "550", "Soil Moisture", "0208 environmental biotechnology", "02 engineering and technology", "Environmental technology. Sanitary engineering", "01 natural sciences", "Engineering", "Geography. Anthropology. Recreation", "Pathology", "GE1-350", "TD1-1066", "2. Zero hunger", "Global and Planetary Change", "Water content", "Evapotranspiration", "Geography", "Ecology", "T", "Soil Water Retention", "Moderate-resolution imaging spectroradiometer", "Hydrology (agriculture)", "Geology", "[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces", " environment", "6. Clean water", "Aerospace engineering", "Physical Sciences", "Medicine", "environment", "Vegetation (pathology)", "Latent heat", "Mechanics and Transport in Unsaturated Soils", "Land cover", "Environmental Engineering", "0207 environmental engineering", "Energy balance", "Thermal Effects on Soil", "Environmental science", "[SDU] Sciences of the Universe [physics]", "G", "Meteorology", "Civil engineering", "14. Life underwater", "[SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology", "Biology", "Civil and Structural Engineering", "0105 earth and related environmental sciences", "Global Forest Drought Response and Climate Change", "FOS: Environmental engineering", "FOS: Earth and related environmental sciences", "15. Life on land", "Remote Sensing of Soil Moisture", "Environmental sciences", "Geotechnical engineering", "[SDU]Sciences of the Universe [physics]", "Satellite", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Land use", "[SDU.STU.HY] Sciences of the Universe [physics]/Earth Sciences/Hydrology", "[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces", "FOS: Civil engineering"]}, "links": [{"href": "https://hess.copernicus.org/articles/24/1781/2020/hess-24-1781-2020.pdf"}, {"href": "https://doi.org/2940609395"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Hydrology%20and%20Earth%20System%20Sciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2940609395", "name": "item", "description": "2940609395", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2940609395"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-04-23T00:00:00Z"}}, {"id": "3154587330", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:23:24Z", "type": "Journal Article", "created": "2021-10-25", "title": "Mineral dust cycle in the Multiscale Online Nonhydrostatic AtmospheRe CHemistry model (MONARCH) Version 2.0", "description": "

Abstract. We present the dust module in the Multiscale Online Non-hydrostatic AtmospheRe CHemistry model (MONARCH) version 2.0, a chemical weather prediction system that can be used for regional and global modeling at a range of resolutions. The representations of dust processes in MONARCH were upgraded with a focus on dust emission (emission parameterizations, entrainment thresholds, considerations of soil moisture and surface cover), lower boundary conditions (roughness, potential dust sources), and dust\u2013radiation interactions. MONARCH now allows modeling of global and regional mineral dust cycles using fundamentally different paradigms, ranging from strongly simplified to physics-based parameterizations. We present a detailed description of these updates along with four global benchmark simulations, which use conceptually different dust emission parameterizations, and we evaluate the simulations against observations of dust optical depth. We determine key dust parameters, such as global annual emission/deposition flux, dust loading, dust optical depth, mass-extinction efficiency, single-scattering albedo, and direct radiative effects. For dust-particle diameters up to 20\u2009\u00b5m, the total annual dust emission and deposition fluxes obtained with our four experiments range between about 3500 and 6000\u2009Tg, which largely depend upon differences in the emitted size distribution. Considering ellipsoidal particle shapes and dust refractive indices that account for size-resolved mineralogy, we estimate the global total (longwave and shortwave) dust direct radiative effect (DRE) at the surface to range between about \u22120.90 and \u22120.63\u2009W\u2009m\u22122 and at the top of the atmosphere between \u22120.20 and \u22120.28\u2009W\u2009m\u22122. Our evaluation demonstrates that MONARCH is able to reproduce key features of the spatiotemporal variability of the global dust cycle with important and insightful differences between the different configurations.

", "keywords": ["Mineral dusts", "Previsi\u00f3 del temps", "QE1-996.5", "info:eu-repo/classification/ddc/550", "550", "ddc:550", "Geology", "15. Life on land", "01 natural sciences", ":Enginyeria qu\u00edmica::Qu\u00edmica del medi ambient::Qu\u00edmica atmosf\u00e8rica [\u00c0rees tem\u00e0tiques de la UPC]", "Weather forecasting", "Climate Action", "[SDU] Sciences of the Universe [physics]", "Earth sciences", "[SDU]Sciences of the Universe [physics]", "13. Climate action", "Earth Sciences", "Pols", "\u00c0rees tem\u00e0tiques de la UPC::Enginyeria qu\u00edmica::Qu\u00edmica del medi ambient::Qu\u00edmica atmosf\u00e8rica", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://gmd.copernicus.org/articles/14/6403/2021/gmd-14-6403-2021.pdf"}, {"href": "https://escholarship.org/content/qt2r39x8b5/qt2r39x8b5.pdf"}, {"href": "https://doi.org/3154587330"}, {"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": "3154587330", "name": "item", "description": "3154587330", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3154587330"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-04-01T00:00:00Z"}}, {"id": "PMC6876662", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:25:01Z", "type": "Journal Article", "created": "2019-02-05", "title": "Current state of the global operational aerosol multi\u2010model ensemble: An update from the International Cooperative for Aerosol Prediction (ICAP)", "description": "

Since the first International Cooperative for Aerosol Prediction (ICAP) multi\u2010model ensemble (MME) study, the number of ICAP global operational aerosol models has increased from five to nine. An update of the current ICAP status is provided, along with an evaluation of the performance of ICAP\u2010MME over 2012\u20132017, with a focus on June 2016\u2013May 2017. Evaluated with ground\u2010based Aerosol Robotic Network (AERONET) aerosol optical depth (AOD) and data assimilation quality MODerate\u2010resolution Imaging Spectroradiometer (MODIS) retrieval products, the ICAP\u2010MME AOD consensus remains the overall top\u2010scoring and most consistent performer among all models in terms of root\u2010mean\u2010square error (RMSE), bias and correlation for total, fine\u2010 and coarse\u2010mode AODs as well as dust AOD; this is similar to the first ICAP\u2010MME study. Further, over the years, the performance of ICAP\u2010MME is relatively stable and reliable compared to more variability in the individual models. The extent to which the AOD forecast error of ICAP\u2010MME can be predicted is also examined. Leading predictors are found to be the consensus mean and spread. Regression models of absolute forecast errors were built for AOD forecasts of different lengths for potential applications. ICAP\u2010MME performance in terms of modal AOD RMSEs of the 21 regionally representative sites over 2012\u20132017 suggests a general tendency for model improvements in fine\u2010mode AOD, especially over Asia. No significant improvement in coarse\u2010mode AOD is found overall for this time period.

", "keywords": ["[SDU] Sciences of the Universe [physics]", "Special Supplement on 25 Years of Ensemble Forecasting", "01 natural sciences", "[PHYS.PHYS.PHYS-AO-PH] Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph]", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/qj.3497"}, {"href": "https://doi.org/PMC6876662"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Quarterly%20Journal%20of%20the%20Royal%20Meteorological%20Society", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "PMC6876662", "name": "item", "description": "PMC6876662", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/PMC6876662"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-04-02T00:00:00Z"}}, {"id": "f99d796fd14a4f5cc0ee80d086e1fcdb", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:26:40Z", "type": "Report", "title": "Effect of varying the proportion of crystalline-amorphous phases in a lunar regolith analog and resulting physical properties for isru selective laser melting", "keywords": ["[SDU] Sciences of the Universe [physics]", "Selective Laser melting", "ISRU", "[SPI] Engineering Sciences [physics]", "3D pritning", "[SPI.MAT] Engineering Sciences [physics]/Materials", "lunar regolith"], "contacts": [{"organization": "Granier, Julien, Cutard, Thierry, Pinet, P.C., Le Maoult, Yannick, Sentenac, Thierry, Chevrel, Serge,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/f99d796fd14a4f5cc0ee80d086e1fcdb"}, {"rel": "self", "type": "application/geo+json", "title": "f99d796fd14a4f5cc0ee80d086e1fcdb", "name": "item", "description": "f99d796fd14a4f5cc0ee80d086e1fcdb", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/f99d796fd14a4f5cc0ee80d086e1fcdb"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-01-01T00:00:00Z"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=%5BSDU%5D+Sciences+of+the+Universe+%5Bphysics%5D&offset=50&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=%5BSDU%5D+Sciences+of+the+Universe+%5Bphysics%5D&offset=50&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": "prev", "title": "items (prev)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=%5BSDU%5D+Sciences+of+the+Universe+%5Bphysics%5D&offset=0", "hreflang": "en-US"}, {"rel": "last", "type": "application/geo+json", "title": "items (last)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=%5BSDU%5D+Sciences+of+the+Universe+%5Bphysics%5D&offset=85", "hreflang": "en-US"}], "numberMatched": 85, "numberReturned": 35, "distributedFeatures": [], "timeStamp": "2026-10-25T15:59:56.904673Z"}