Development of SuperEnsemble Techniques for the Mediterranean Ocean Forecasting System
This research activity studied how the uncertainties are concerned and interrelated through the multi-model approach, since it seems to be the bigger challenge of ocean and weather forecasting. Moreover, we tried to reduce model error throughout the superensemble approach. In order to provide this a...
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Alma Mater Studiorum - Università di Bologna
2012
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Online Access: | http://amsdottorato.unibo.it/4303/ |
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ndltd-unibo.it-oai-amsdottorato.cib.unibo.it-43032014-03-24T16:29:45Z Development of SuperEnsemble Techniques for the Mediterranean Ocean Forecasting System Pistoia, Jenny <1983> FIS/06 Fisica per il sistema terra e il mezzo circumterrestre This research activity studied how the uncertainties are concerned and interrelated through the multi-model approach, since it seems to be the bigger challenge of ocean and weather forecasting. Moreover, we tried to reduce model error throughout the superensemble approach. In order to provide this aim, we created different dataset and by means of proper algorithms we obtained the superensamble estimate. We studied the sensitivity of this algorithm in function of its characteristics parameters. Clearly, it is not possible to evaluate a reasonable estimation of the error neglecting the importance of the grid size of ocean model, for the large amount of all the sub grid-phenomena embedded in space discretizations that can be only roughly parametrized instead of an explicit evaluation. For this reason we also developed a high resolution model, in order to calculate for the first time the impact of grid resolution on model error. Alma Mater Studiorum - Università di Bologna Pinardi, Nadia 2012-03-28 Doctoral Thesis PeerReviewed application/pdf en http://amsdottorato.unibo.it/4303/ info:eu-repo/semantics/openAccess |
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en |
format |
Doctoral Thesis |
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FIS/06 Fisica per il sistema terra e il mezzo circumterrestre |
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FIS/06 Fisica per il sistema terra e il mezzo circumterrestre Pistoia, Jenny <1983> Development of SuperEnsemble Techniques for the Mediterranean Ocean Forecasting System |
description |
This research activity studied how the uncertainties are concerned and interrelated through the multi-model approach, since it seems to be the bigger challenge of ocean and weather forecasting. Moreover, we tried to reduce model error throughout the superensemble approach. In order to provide this aim, we created different dataset and by means of proper algorithms we obtained the superensamble estimate. We studied the sensitivity of this algorithm in function of its characteristics parameters. Clearly, it is not possible to evaluate a reasonable estimation of the error neglecting the importance of the grid size of ocean model, for the large amount of all the sub grid-phenomena embedded in space discretizations that can be only roughly parametrized instead of an explicit evaluation. For this reason we also developed a high resolution model, in order to calculate for the first time the impact of grid resolution on model error. |
author2 |
Pinardi, Nadia |
author_facet |
Pinardi, Nadia Pistoia, Jenny <1983> |
author |
Pistoia, Jenny <1983> |
author_sort |
Pistoia, Jenny <1983> |
title |
Development of SuperEnsemble Techniques for the Mediterranean Ocean Forecasting System |
title_short |
Development of SuperEnsemble Techniques for the Mediterranean Ocean Forecasting System |
title_full |
Development of SuperEnsemble Techniques for the Mediterranean Ocean Forecasting System |
title_fullStr |
Development of SuperEnsemble Techniques for the Mediterranean Ocean Forecasting System |
title_full_unstemmed |
Development of SuperEnsemble Techniques for the Mediterranean Ocean Forecasting System |
title_sort |
development of superensemble techniques for the mediterranean ocean forecasting system |
publisher |
Alma Mater Studiorum - Università di Bologna |
publishDate |
2012 |
url |
http://amsdottorato.unibo.it/4303/ |
work_keys_str_mv |
AT pistoiajenny1983 developmentofsuperensembletechniquesforthemediterraneanoceanforecastingsystem |
_version_ |
1716654477829734400 |