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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ponce de Leon, Sonia | - |
dc.date.accessioned | 2022-10-27T07:35:19Z | - |
dc.date.available | 2022-10-27T07:35:19Z | - |
dc.date.issued | 2016-03 | - |
dc.identifier.citation | Akpınar, A. ve Ponce de Leon, S. (2016). "An assessment of the wind re-analyses in the modelling of an extreme sea state in the Black Sea". Dynamics of Atmospheres and Oceans, 73, 61-75. | en_US |
dc.identifier.issn | 0377-0265 | - |
dc.identifier.issn | 1872-6879 | - |
dc.identifier.uri | https://doi.org/10.1016/j.dynatmoce.2015.12.002 | - |
dc.identifier.uri | https://www.sciencedirect.com/science/article/pii/S0377026515300129 | - |
dc.identifier.uri | http://hdl.handle.net/11452/29228 | - |
dc.description.abstract | This study aims at an assessment of wind re-analyses for modelling storms in the Black Sea. A wind-wave modelling system (Simulating WAve Nearshore, SWAN) is applied to the Black Sea basin and calibrated with buoy data for three recent re-analysis wind sources, namely the European Centre for Medium-Range Weather Forecasts Reanalysis-Interim (ERA-Interim), Climate Forecast System Reanalysis (CFSR), and Modern Era Retrospective Analysis for Research and Applications (MERRA) during an extreme wave condition that occurred in the north eastern part of the Black Sea. The SWAN model simulations are carried out for default and tuning settings for deep water source terms, especially whitecapping. Performances of the best model configurations based on calibration with buoy data are discussed using data from the JASON2, TOPEX-Poseidon, ENVISAT and GFO satellites. The SWAN model calibration shows that the best configuration is obtained with Janssen and Komen formulations with whitecapping coefficient (C-ds) equal to 1.8e-5 for wave generation by wind and whitecapping dissipation using ERA-Interim. In addition, from the collocated SWAN results against the satellite records, the best configuration is determined to be the SWAN using the CFSR winds. Numerical results, thus show that the accuracy of a wave forecast will depend on the quality of the wind field and the ability of the SWAN model to simulate the waves under extreme wind conditions in fetch limited wave conditions. | en_US |
dc.description.sponsorship | NATO Science for Stability Program | en_US |
dc.language.iso | en | en_US |
dc.publisher | Elsevier | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Geochemistry & geophysics | en_US |
dc.subject | Meteorology & atmospheric sciences | en_US |
dc.subject | Oceanography | en_US |
dc.subject | Wind waves | en_US |
dc.subject | SWAN | en_US |
dc.subject | Satellite altimetry data | en_US |
dc.subject | Calibration | en_US |
dc.subject | Satellite altimetry data | en_US |
dc.subject | Extreme sea states | en_US |
dc.subject | Wave model | en_US |
dc.subject | Numerical-models | en_US |
dc.subject | Performance | en_US |
dc.subject | Calibration | en_US |
dc.subject | Forecasting | en_US |
dc.subject | Geodetic satellites | en_US |
dc.subject | Satellites | en_US |
dc.subject | Weather forecasting | en_US |
dc.subject | Wind | en_US |
dc.subject | Black sea | en_US |
dc.subject | Sea state | en_US |
dc.subject | Wind wave | en_US |
dc.subject | Climate modeling | en_US |
dc.subject | Climate prediction | en_US |
dc.subject | Ensemble forecasting | en_US |
dc.subject | Satellite data | en_US |
dc.subject | Satellite imagery | en_US |
dc.subject | Weather forecasting | en_US |
dc.subject | Ocean currents | en_US |
dc.title | An assessment of the wind re-analyses in the modelling of an extreme sea state in the Black Sea | en_US |
dc.type | Article | en_US |
dc.identifier.wos | 000374368600005 | tr_TR |
dc.identifier.scopus | 2-s2.0-84951859752 | tr_TR |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi | tr_TR |
dc.contributor.department | Uludağ Üniversitesi/Mühendislik Fakültesi/İnşaat Mühendisliği Bölümü. | tr_TR |
dc.contributor.orcid | 0000-0002-9042-6851 | tr_TR |
dc.identifier.startpage | 61 | tr_TR |
dc.identifier.endpage | 75 | tr_TR |
dc.identifier.volume | 73 | tr_TR |
dc.relation.journal | Dynamics of Atmospheres and Oceans | en_US |
dc.contributor.buuauthor | Akpınar, Adem | - |
dc.contributor.researcherid | ABE-8817-2020 | tr_TR |
dc.contributor.researcherid | AAC-6763-2019 | tr_TR |
dc.relation.collaboration | Yurt dışı | tr_TR |
dc.subject.wos | Geochemistry & geophysics | en_US |
dc.subject.wos | Meteorology & atmospheric sciences | en_US |
dc.subject.wos | Oceanography | en_US |
dc.indexed.wos | SCIE | en_US |
dc.indexed.scopus | Scopus | en_US |
dc.wos.quartile | Q3 | en_US |
dc.wos.quartile | Q4 (Meteorology & atmospheric sciences) | en_US |
dc.contributor.scopusid | 23026855400 | tr_TR |
dc.subject.scopus | Wave Energy; Wind Power; Data Buoy | en_US |
Appears in Collections: | Scopus Web of Science |
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