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| Eyring, Veronika; Bock, Lisa; Lauer, Axel; Righi, Mattia; Schlund, Manuel; Andela, Bouwe; Arnone, Enrico; Bellprat, Omar; Broetz, Bjorn; Caron, Louis-philippe; Carvalhais, Nuno; Cionni, Irene; Cortesi, Nicola; Crezee, Bas; Davin, Edouard L.; Davini, Paolo; Debeire, Kevin; De Mora, Lee; Deser, Clara; Docquier, David; Earnshaw, Paul; Ehbrecht, Carsten; Gier, Bettina K.; Gonzalez-reviriego, Nube; Goodman, Paul; Hagemann, Stefan; Hardiman, Steven; Hassler, Birgit; Hunter, Alasdair; Kadow, Christopher; Kindermann, Stephan; Koirala, Sujan; Koldunov, Nikolay; Lejeune, Quentin; Lembo, Valerio; Lovato, Tomas; Lucarini, Valerio; Massonnet, Francois; Mueller, Benjamin; Pandde, Amarjiit; Perez-zanon, Nuria; Phillips, Adam; Predoi, Valeriu; Russell, Joellen; Sellar, Alistair; Serva, Federico; Stacke, Tobias; Swaminathan, Ranjini; Torralba, Veronica; Vegas-regidor, Javier; Von Hardenberg, Jost; Weigel, Katja; Zimmermann, Klaus. |
| The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool designed to improve comprehensive and routine evaluation of Earth system models (ESMs) participating in the Coupled Model Intercomparison Project (CMIP). It has undergone rapid development since the first release in 2016 and is now a well-tested tool that provides end-to-end provenance tracking to ensure reproducibility. It consists of (1) an easy-to-install, well-documented Python package providing the core functionalities (ESMValCore) that performs common preprocessing operations and (2) a diagnostic part that includes tailored diagnostics and performance metrics for specific scientific applications. Here we describe large-scale diagnostics of the... |
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| Ano: 2020 |
URL: https://archimer.ifremer.fr/doc/00676/78832/81119.pdf |
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| Lee, Younjoo J.; Matrai, Patricia A.; Friedrichs, Marjorie A. M.; Saba, Vincent S.; Aumont, Olivier; Babin, Marcel; Buitenhuis, Erik T.; Chevallier, Matthieu; De Mora, Lee; Dessert, Morgane; Dunne, John P.; Ellingsen, Ingrid H.; Feldman, Doron; Frouin, Robert; Gehlen, Marion; Gorgues, Thomas; Ilyina, Tatiana; Jin, Meibing; John, Jasmin G.; Lawrence, Jon; Manizza, Manfredi; Menkes, Christophe E.; Perruche, Coralie; Le Fouest, Vincent; Popova, Ekaterina E.; Romanou, Anastasia; Samuelsen, Annette; Schwinger, Jorg; Seferian, Roland; Stock, Charles A.; Tjiputra, Jerry; Tremblay, Bruno; Ueyoshi, Kyozo; Vichi, Marcello; Yool, Andrew; Zhang, Jinlun. |
| The relative skill of 21 regional and global biogeochemical models was assessed in terms of how well the models reproduced observed net primary productivity (NPP) and environmental variables such as nitrate concentration (NO3), mixed layer depth (MLD), euphotic layer depth (Z(eu)), and sea ice concentration, by comparing results against a newly updated, quality-controlled in situ NPP database for the Arctic Ocean (1959-2011). The models broadly captured the spatial features of integrated NPP (iNPP) on a pan-Arctic scale. Most models underestimated iNPP by varying degrees in spite of overestimating surface NO3, MLD, and Z(eu) throughout the regions. Among the models, iNPP exhibited little difference over sea ice condition (ice-free versus ice-influenced)... |
| Tipo: Text |
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| Ano: 2016 |
URL: https://archimer.ifremer.fr/doc/00373/48441/69564.pdf |
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