{"type": "FeatureCollection", "features": [{"id": "10.1002/2017JD027346", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:14:19Z", "type": "Journal Article", "created": "2017-12-28", "title": "Soil Moisture-Temperature Coupling in a Set of Land Surface Models", "description": "Abstract<p>The land surface controls the partitioning of water and energy fluxes and therefore plays a crucial role in the climate system. The coupling between soil moisture and air temperature, in particular, has been shown to affect the severity and occurrence of temperature extremes and heat waves. Here we study soil moisture\uffe2\uff80\uff90temperature coupling in five land surface models, focusing on the terrestrial segment of the coupling in the warm season. All models are run off\uffe2\uff80\uff90line over a common period with identical atmospheric forcing data, in order to allow differences in the results to be attributed to the models' partitioning of energy and water fluxes. Coupling is calculated according to two semiempirical metrics, and results are compared to observational flux tower data. Results show that the locations of the global hot spots of soil moisture\uffe2\uff80\uff90temperature coupling are similar across all models and for both metrics. In agreement with previous studies, these areas are located in transitional climate regimes. The magnitude and local patterns of model coupling, however, can vary considerably. Model coupling fields are compared to tower data, bearing in mind the limitations in the geographical distribution of flux towers and the differences in representative area of models and in situ data. Nevertheless, model coupling correlates in space with the tower\uffe2\uff80\uff90based results (r = 0.5\uffe2\uff80\uff930.7), with the multimodel mean performing similarly to the best\uffe2\uff80\uff90performing model. Intermodel differences are also found in the evaporative fractions and may relate to errors in model parameterizations and ancillary data of soil and vegetation characteristics.</p>", "keywords": ["ENVIRONMENT SIMULATOR JULES", "FLUXES", "0207 environmental engineering", "02 engineering and technology", "01 natural sciences", "CO2 EXCHANGE", "models", "WATER", "SCALE", "Research Articles", "0105 earth and related environmental sciences", "land surface", "CARBON-DIOXIDE EXCHANGE", "eartH2Observe", "temperature", "15. Life on land", "DECIDUOUS FOREST", "CLIMATE", "EVAPORATION", "VARIABILITY", "13. Climate action", "Earth and Environmental Sciences", "BALANCE", "land surface models", "SENSIBLE HEAT", "land-atmosphere interactions", "soil moisture"]}, "links": [{"href": "https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2017JD027346"}, {"href": "https://doi.org/10.1002/2017JD027346"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Geophysical%20Research%3A%20Atmospheres", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1002/2017JD027346", "name": "item", "description": "10.1002/2017JD027346", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1002/2017JD027346"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-02-01T00:00:00Z"}}, {"id": "10.5194/essd-10-405-2018", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:21:49Z", "type": "Journal Article", "created": "2018-03-12", "title": "Global Carbon Budget 2017", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere \u2013 the global carbon budget \u2013 is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on land-cover change data and bookkeeping models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as \u00b11\u03c3. For the last decade available (2007\u20132016), EFF was 9.4\u202f\u00b1\u202f0.5\u202fGtC\u202fyr\u22121, ELUC 1.3\u202f\u00b1\u202f0.7\u202fGtC\u202fyr\u22121, GATM 4.7\u202f\u00b1\u202f0.1\u202fGtC\u202fyr\u22121, SOCEAN 2.4\u202f\u00b1\u202f0.5\u202fGtC\u202fyr\u22121, and SLAND 3.0\u202f\u00b1\u202f0.8\u202fGtC\u202fyr\u22121, with a budget imbalance BIM of 0.6\u202fGtC\u202fyr\u22121 indicating overestimated emissions and/or underestimated sinks. For year 2016 alone, the growth in EFF was approximately zero and emissions remained at 9.9\u202f\u00b1\u202f0.5\u202fGtC\u202fyr\u22121. Also for 2016, ELUC was 1.3\u202f\u00b1\u202f0.7\u202fGtC\u202fyr\u22121, GATM was 6.1\u202f\u00b1\u202f0.2\u202fGtC\u202fyr\u22121, SOCEAN was 2.6\u202f\u00b1\u202f0.5\u202fGtC\u202fyr\u22121, and SLAND was 2.7\u202f\u00b1\u202f1.0\u202fGtC\u202fyr\u22121, with a small BIM of \u22120.3\u202fGtC. GATM continued to be higher in 2016 compared to the past decade (2007\u20132016), reflecting in part the high fossil emissions and the small SLAND consistent with El Ni\u00f1o conditions. The global atmospheric CO2 concentration reached 402.8\u202f\u00b1\u202f0.1\u202fppm averaged over 2016. For 2017, preliminary data for the first 6\u20139\u00a0months indicate a renewed growth in EFF of +2.0\u202f% (range of 0.8 to 3.0\u202f%) based on national emissions projections for China, USA, and India, and projections of gross domestic product (GDP) corrected for recent changes in the carbon intensity of the economy for the rest of the world. This living data update documents changes in the methods and data sets used in this new global carbon budget compared with previous publications of this data set (Le Qu\u00e9r\u00e9 et al., 2016, 2015b, a, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2017 (GCP, 2017).                     </p></article>", "keywords": ["ENVIRONMENT SIMULATOR JULES", "550", "530 Physics", "[PHYS.PHYS.PHYS-GEO-PH] Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph]", "MIXED-LAYER SCHEME", "INTERNATIONAL-TRADE", "7. Clean energy", "01 natural sciences", "333", "12. Responsible consumption", "FOSSIL-FUEL COMBUSTION", "ANTHROPOGENIC CO2 UPTAKE", "11. Sustainability", "SDG 13 - Climate Action", "Life Science", "GE1-350", "SDG 14 - Life Below Water", "ATMOSPHERIC CO2", "DIOXIDE EMISSIONS", "SDG 15 - Life on Land", "0105 earth and related environmental sciences", "LAND-COVER CHANGE", "QE1-996.5", "info:eu-repo/classification/ddc/550", "EARTH SYSTEM MODEL", "ddc:550", "VEGETATION MODEL", "Geology", "15. Life on land", "Environmental sciences", "Earth sciences", "13. Climate action", "8. Economic growth", "General Earth and Planetary Sciences"]}, "links": [{"href": "https://ueaeprints.uea.ac.uk/id/eprint/66578/1/Published_manuscript.pdf"}, {"href": "http://oceanrep.geomar.de/42391/1/essd-10-405-2018.pdf"}, {"href": "https://boris.unibe.ch/116576/1/lequere18essd.pdf"}, {"href": "https://pure.iiasa.ac.at/id/eprint/15161/1/essd-10-405-2018.pdf"}, {"href": "http://pure.iiasa.ac.at/id/eprint/15161/1/essd-10-405-2018.pdf"}, {"href": "https://essd.copernicus.org/articles/10/405/2018/essd-10-405-2018.pdf"}, {"href": "https://doi.org/10.5194/essd-10-405-2018"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Earth%20System%20Science%20Data", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/essd-10-405-2018", "name": "item", "description": "10.5194/essd-10-405-2018", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/essd-10-405-2018"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-03-12T00:00:00Z"}}, {"id": "1912/10214", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:25:19Z", "type": "Journal Article", "created": "2018-03-12", "title": "Global Carbon Budget 2017", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere \u2013 the global carbon budget \u2013 is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on land-cover change data and bookkeeping models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as \u00b11\u03c3. For the last decade available (2007\u20132016), EFF was 9.4\u202f\u00b1\u202f0.5\u202fGtC\u202fyr\u22121, ELUC 1.3\u202f\u00b1\u202f0.7\u202fGtC\u202fyr\u22121, GATM 4.7\u202f\u00b1\u202f0.1\u202fGtC\u202fyr\u22121, SOCEAN 2.4\u202f\u00b1\u202f0.5\u202fGtC\u202fyr\u22121, and SLAND 3.0\u202f\u00b1\u202f0.8\u202fGtC\u202fyr\u22121, with a budget imbalance BIM of 0.6\u202fGtC\u202fyr\u22121 indicating overestimated emissions and/or underestimated sinks. For year 2016 alone, the growth in EFF was approximately zero and emissions remained at 9.9\u202f\u00b1\u202f0.5\u202fGtC\u202fyr\u22121. Also for 2016, ELUC was 1.3\u202f\u00b1\u202f0.7\u202fGtC\u202fyr\u22121, GATM was 6.1\u202f\u00b1\u202f0.2\u202fGtC\u202fyr\u22121, SOCEAN was 2.6\u202f\u00b1\u202f0.5\u202fGtC\u202fyr\u22121, and SLAND was 2.7\u202f\u00b1\u202f1.0\u202fGtC\u202fyr\u22121, with a small BIM of \u22120.3\u202fGtC. GATM continued to be higher in 2016 compared to the past decade (2007\u20132016), reflecting in part the high fossil emissions and the small SLAND consistent with El Ni\u00f1o conditions. The global atmospheric CO2 concentration reached 402.8\u202f\u00b1\u202f0.1\u202fppm averaged over 2016. For 2017, preliminary data for the first 6\u20139\u00a0months indicate a renewed growth in EFF of +2.0\u202f% (range of 0.8 to 3.0\u202f%) based on national emissions projections for China, USA, and India, and projections of gross domestic product (GDP) corrected for recent changes in the carbon intensity of the economy for the rest of the world. This living data update documents changes in the methods and data sets used in this new global carbon budget compared with previous publications of this data set (Le Qu\u00e9r\u00e9 et al., 2016, 2015b, a, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2017 (GCP, 2017).</p></article>", "keywords": ["ENVIRONMENT SIMULATOR JULES", "550", "530 Physics", "[PHYS.PHYS.PHYS-GEO-PH] Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph]", "MIXED-LAYER SCHEME", "INTERNATIONAL-TRADE", "7. Clean energy", "01 natural sciences", "333", "12. Responsible consumption", "FOSSIL-FUEL COMBUSTION", "ANTHROPOGENIC CO2 UPTAKE", "11. Sustainability", "SDG 13 - Climate Action", "Life Science", "GE1-350", "SDG 14 - Life Below Water", "ATMOSPHERIC CO2", "DIOXIDE EMISSIONS", "SDG 15 - Life on Land", "0105 earth and related environmental sciences", "LAND-COVER CHANGE", "QE1-996.5", "info:eu-repo/classification/ddc/550", "EARTH SYSTEM MODEL", "ddc:550", "VEGETATION MODEL", "Geology", "15. Life on land", "Environmental sciences", "Earth sciences", "13. Climate action", "8. Economic growth", "General Earth and Planetary Sciences"]}, "links": [{"href": "https://ueaeprints.uea.ac.uk/id/eprint/66578/1/Published_manuscript.pdf"}, {"href": "http://oceanrep.geomar.de/42391/1/essd-10-405-2018.pdf"}, {"href": "https://boris.unibe.ch/116576/1/lequere18essd.pdf"}, {"href": "http://pure.iiasa.ac.at/id/eprint/15161/1/essd-10-405-2018.pdf"}, {"href": "https://pure.iiasa.ac.at/id/eprint/15161/1/essd-10-405-2018.pdf"}, {"href": "https://essd.copernicus.org/articles/10/405/2018/essd-10-405-2018.pdf"}, {"href": "https://doi.org/1912/10214"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Earth%20System%20Science%20Data", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "1912/10214", "name": "item", "description": "1912/10214", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1912/10214"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-03-12T00:00:00Z"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=ENVIRONMENT+SIMULATOR+JULES&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=ENVIRONMENT+SIMULATOR+JULES&f=html", "hreflang": "en-US"}, {"rel": "collection", "type": "application/json", "title": "Collection URL", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main", "hreflang": "en-US"}, {"type": "application/geo+json", "rel": "first", "title": "items (first)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=ENVIRONMENT+SIMULATOR+JULES&", "hreflang": "en-US"}, {"rel": "last", "type": "application/geo+json", "title": "items (last)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=ENVIRONMENT+SIMULATOR+JULES&offset=3", "hreflang": "en-US"}], "numberMatched": 3, "numberReturned": 3, "distributedFeatures": [], "timeStamp": "2026-07-26T06:21:58.319887Z"}