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Combination of modeled short-term angular momentum function forecasts from atmosphere, ocean, and hydrology with 90-day EOP predictions / Robert Dill in Journal of geodesy, vol 87 n° 6 (June 2013)  

Public [article]  inJournal of geodesy > vol 87 n° 6 (June 2013) . - pp 567 - 577 Titre : Combination of modeled short-term angular momentum function forecasts from atmosphere, ocean, and hydrology with 90-day EOP predictions Type de document : Article/Communication Auteurs : Robert Dill, Auteur ; H. Dobslaw, Auteur ; M. Thomas, Auteur Année de publication : 2013 Article en page(s) : pp 567 - 577 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] moment cinétique atmosphérique [Termes IGN] moment cinétique océanique [Termes IGN] orientation de la Terre [Termes IGN] prévision Résumé : (Auteur) Angular momentum forecasts for up to 10 days into the future, modeled from predicted states of the atmosphere, ocean and continental hydrosphere, are combined with the operational IERS EOP prediction bulletin A to reduce the prediction error in the very first day and to improve the subsequent 90-day prediction by exploitation of the revised initial state and trend information. EAM functions derived from ECMWF short-range forecasts and corresponding LSDM and OMCT simulations can account for high-frequency mass variations within the geophysical fluids for up to 7 days into the future primarily limited by the accuracy of the forecasted atmospheric wind fields. Including these wide-band stochastic signals into the first days of the 90-day statistical IERS predictions reduces the mean absolute prediction error even for predictions beyond day 10, especially for polar motion, where the presently used prediction approach does not include geophysical fluids data directly. In a hindcast experiment using 1 year of daily predictions from May 2011 till July 2012, the mean prediction error in polar motion, compared to bulletin A, is reduced by 32, 12, and 3 % for prediction days 10, 30, and 90, respectively. In average, the prediction error for medium-range forecasts (30–90 days) is reduced by 1.3–1.7 mas. Even for UT1-UTC, where AAM forecasts are already included in IERS bulletin A, we obtain slight improvements of up to 5 % (up to 0.5 ms) after day 10 due to the additional consideration of oceanic angular momentum forecasts. The improved 90-day predictions can be generated operationally on a daily basis directly after the publication of the related IERS bulletin A product finals2000A daily. Numéro de notice : A2013-340 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-013-0631-6 Date de publication en ligne : 17/03/2013 En ligne : https://doi.org/10.1007/s00190-013-0631-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32478 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
266-2013061	SL	Revue	Centre de documentation	Revues en salle	Disponible

Assessing the quality of geoscientific simulation models with visual analytics methods: a design study / D. Dransch in International journal of geographical information science IJGIS, vol 24 n° 10 (october 2010)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 24 n° 10 (october 2010) . - pp 1459 - 1479 Titre : Assessing the quality of geoscientific simulation models with visual analytics methods: a design study Type de document : Article/Communication Auteurs : D. Dransch, Auteur ; P. Köthur, Auteur ; S. Schulte, Auteur ; V. Klemann, Auteur ; H. Dobslaw, Auteur Année de publication : 2010 Article en page(s) : pp 1459 - 1479 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse de données [Termes IGN] analyse visuelle [Termes IGN] données hétérogènes [Termes IGN] modèle de simulation Résumé : (Auteur) Simulation models are essential means of scientific knowledge building and also the basis for decision-making. Because of their relevance, they have to be assessed thoroughly with respect to their quality. Simulation model assessment comprises two challenges: (a) modelers have to create a comprehensive mental image of the model's quality despite the massive multidimensional, multivariate, and often heterogeneous data; and (b) the model assessment process should be as efficient as possible. We face these challenges with a visual analytics approach. We aim at developing interactive visual representations which, in combination with present computational analysis methods, support the scientist's reasoning process to enhance the assessment of simulation models. In a design study, we analyzed two exemplary reasoning processes which cover the main model assessment procedures: the evaluation of the internal coherence of the model's structure and behavior and the assessment of its empirical validity. The analysis was conducted by means of a user- and task-centered approach which combines several knowledge elicitation techniques and task analysis concepts. We derived domain tasks as well as cognitive actions and developed and implemented interactive visualization components which supplement the statistical analysis methods already used. An informal qualitative user study shows that our visual analytics approach and tools help gain a more detailed mental image and hence a better understanding of the data and the underlying simulation model and allow for a faster and more comprehensive assessment of the simulation model. Numéro de notice : A2010-461 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658816.2010.510800 En ligne : https://doi.org/10.1080/13658816.2010.510800 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30654 [article]

Exemplaires(2)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-2010061	RAB	Revue	Centre de documentation	En réserve L003	Disponible
079-2010062	RAB	Revue	Centre de documentation	En réserve L003	Disponible