{"type": "FeatureCollection", "features": [{"id": "10.1029/2019ms001776", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:18:30Z", "type": "Journal Article", "created": "2019-12-20", "title": "Mathematical Reconstruction of Land Carbon Models From Their Numerical Output: Computing Soil Radiocarbon From C Dynamics", "description": "Abstract<p>Radiocarbon (14C) is a powerful tracer of the global carbon cycle that is commonly used to assess carbon cycling rates in various Earth system reservoirs and as a benchmark to assess model performance. Therefore, it has been recommended that Earth System Models (ESMs) participating in the Coupled Model Intercomparison Project Phase 6 report predicted radiocarbon values for relevant carbon pools. However, a detailed representation of radiocarbon dynamics may be an impractical burden on model developers. Here, we present an alternative approach to compute radiocarbon values from the numerical output of an ESM that does not explicitly represent these dynamics. The approach requires computed 12C stocks and fluxes among all carbon pools for a particular simulation of the model. From this output, a time\uffe2\uff80\uff90dependent linear compartmental system is computed with its respective state\uffe2\uff80\uff90transition matrix. Using transient atmospheric 14C values as inputs, the state\uffe2\uff80\uff90transition matrix is then applied to compute radiocarbon values for each pool, the average value for the entire system, and component fluxes. We demonstrate the approach with ELMv1\uffe2\uff80\uff90ECA, the land component of an ESM model that explicitly represents 12C, and 14C in 7 soil pools and 10 vertical layers. Results from our proposed method are highly accurate (relative error &lt;0.01%) compared with the ELMv1\uffe2\uff80\uff90ECA 12C and 14C predictions, demonstrating the potential to use this approach in CMIP6 and other model simulations that do not explicitly represent 14C.</p", "keywords": ["3701 Atmospheric sciences (for-2020)", "Life on Land", "3704 Geoinformatics (for-2020)", "Bioengineering", "Earth system models", "dynamical systems", "0401 Atmospheric Sciences (for)", "3701 Atmospheric Sciences (for-2020)", "compartmental systems", "01 natural sciences", "Atmospheric Sciences", "37 Earth Sciences (for-2020)", "13. 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To this end, data needs to be fused with adequate and efficient system models. Such system models should account for the underlying physics and the possibly nonlinear dynamic processes involved. This paper introduces a physics-based parametric formulation for nonlinear structural systems. A Reduced Order Model (ROM) of the high fidelity system is developed, retaining the dependencies on system properties and on temporal and spectral characteristics of the excitation. The ROM formulation relies on i) Proper Orthogonal Decomposition applied to snapshots of the nonlinear response, and ii) manifold interpolation of the resulting projection bases. Its performance is evaluated on a 3D earthquake-excited shear frame with nonlinear couplings. The developed ROM can be exploited for a number of tasks including monitoring, diagnostics and residual life estimation of critical components.", "keywords": ["Parametric modeling", "Reduced order model; Nonlinear dynamical systems; Earthquake ground motions; Parametric modeling", "Reduced order model", "02 engineering and technology", "Nonlinear dynamical systems", "Earthquake ground motions", "0210 nano-technology", "0201 civil engineering"]}, "links": [{"href": "https://doi.org/10.3929/ethz-b-000442909"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/International%20Conference%20on%20Noise%20and%20Vibration%20Engineering%20%28ISMA%202020%29%20and%20International%20Conference%20on%20Uncertainty%20in%20Structural%20Dynamics%20%28USD%202020%29", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3929/ethz-b-000442909", "name": "item", "description": "10.3929/ethz-b-000442909", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3929/ethz-b-000442909"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-01-01T00:00:00Z"}}, {"id": "21.11116/0000-0005-C54E-6", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:27:52Z", "type": "Report", "created": "2020-03-09", "title": "Mathematical Reconstruction of Land Carbon Models From Their Numerical Output: Computing Soil Radiocarbon From 12C Dynamics", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>         &amp;lt;p&amp;gt;Radiocarbon (&amp;lt;sup&amp;gt;14&amp;lt;/sup&amp;gt;C) is a powerful tracer of the global carbon cycle that is commonly used to assess carbon cycling rates in various Earth system reservoirs and as a benchmark to assess model performance. Therefore, it has been recommended that Earth System Models (ESMs) participating in the Coupled Model Intercomparison Project Phase 6 report predicted radiocarbon values for relevant carbon pools. However, a detailed representation of radiocarbon dynamics may be an impractical burden on model developers. Here, we present an alternative approach to compute radiocarbon values from the numerical output of an ESM that does not explicitly represent these dynamics. The approach requires computed &amp;lt;sup&amp;gt;12&amp;lt;/sup&amp;gt;C stocks and fluxes among all carbon pools for a particular simulation of the model. From this output, a time&amp;amp;#8208;dependent linear compartmental system is computed with its respective state&amp;amp;#8208;transition matrix. Using transient atmospheric &amp;lt;sup&amp;gt;14&amp;lt;/sup&amp;gt;C values as inputs, the state&amp;amp;#8208;transition matrix is then applied to compute radiocarbon values for each pool, the average value for the entire system, and component fluxes. We demonstrate the approach with ELMv1&amp;amp;#8208;ECA, the land component of an ESM model that explicitly represents &amp;lt;sup&amp;gt;12&amp;lt;/sup&amp;gt;C, and &amp;lt;sup&amp;gt;14&amp;lt;/sup&amp;gt;C in 7 soil pools and 10 vertical layers. Results from our proposed method are highly accurate (relative error &amp;lt;0.01%) compared with the ELMv1&amp;amp;#8208;ECA &amp;lt;sup&amp;gt;12&amp;lt;/sup&amp;gt;C and &amp;lt;sup&amp;gt;14&amp;lt;/sup&amp;gt;C predictions, demonstrating the potential to use this approach in CMIP6 and other model simulations that do not explicitly represent &amp;lt;sup&amp;gt;14&amp;lt;/sup&amp;gt;C.&amp;lt;/p&amp;gt;         </p></article>", "keywords": ["Physical geography", "Earth system models", "GC1-1581", "dynamical systems", "15. Life on land", "Oceanography", "compartmental systems", "01 natural sciences", "GB3-5030", "13. Climate action", "radiocarbon", "model diagnostics", "carbon cycle models", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/21.11116/0000-0005-C54E-6"}, {"rel": "self", "type": "application/geo+json", "title": "21.11116/0000-0005-C54E-6", "name": "item", "description": "21.11116/0000-0005-C54E-6", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/21.11116/0000-0005-C54E-6"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-03-23T00:00:00Z"}}, {"id": "2994789089", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:28:21Z", "type": "Journal Article", "created": "2019-12-20", "title": "Mathematical Reconstruction of Land Carbon Models From Their Numerical Output: Computing Soil Radiocarbon From C Dynamics", "description": "Abstract<p>Radiocarbon (14C) is a powerful tracer of the global carbon cycle that is commonly used to assess carbon cycling rates in various Earth system reservoirs and as a benchmark to assess model performance. Therefore, it has been recommended that Earth System Models (ESMs) participating in the Coupled Model Intercomparison Project Phase 6 report predicted radiocarbon values for relevant carbon pools. However, a detailed representation of radiocarbon dynamics may be an impractical burden on model developers. Here, we present an alternative approach to compute radiocarbon values from the numerical output of an ESM that does not explicitly represent these dynamics. The approach requires computed 12C stocks and fluxes among all carbon pools for a particular simulation of the model. From this output, a time\uffe2\uff80\uff90dependent linear compartmental system is computed with its respective state\uffe2\uff80\uff90transition matrix. Using transient atmospheric 14C values as inputs, the state\uffe2\uff80\uff90transition matrix is then applied to compute radiocarbon values for each pool, the average value for the entire system, and component fluxes. We demonstrate the approach with ELMv1\uffe2\uff80\uff90ECA, the land component of an ESM model that explicitly represents 12C, and 14C in 7 soil pools and 10 vertical layers. Results from our proposed method are highly accurate (relative error &lt;0.01%) compared with the ELMv1\uffe2\uff80\uff90ECA 12C and 14C predictions, demonstrating the potential to use this approach in CMIP6 and other model simulations that do not explicitly represent 14C.</p", "keywords": ["Atmospheric sciences", "Life on Land", "Bioengineering", "Earth system models", "dynamical systems", "compartmental systems", "01 natural sciences", "Atmospheric Sciences", "13. 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