Validation of the SAMOA Operational Forecasting System in Spanish Mediterranean Ports Article Swipe
María Liste Muñoz
,
Marc Mestres
,
Manuel Espino
,
Manel Grifoll
,
Agustín Sánchez‐Arcilla
,
Manuel García-León
,
Marcos García Sotillo
,
Enrique Ãlvarez Fanjul
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.5194/egusphere-egu2020-20429
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.5194/egusphere-egu2020-20429
<p>Working in the coastal marine environment is highly challenging, among other reasons, due to the variety of extreme, seasonal, short and long-term environmental conditions that affect the coastline, beaches, infrastructures and port operations. The maritime climate directly affects the construction and maintenance of port infrastructures, the access of ships to ports, the safety of cargo handling operations, emergency response or the environmental management of effects of port operations. Currently, the ability to predict the sea state from a few hours to days has reached levels of precision and reliability unbelievable a few years ago. And all this, in combination with numerical measurements and predictions, has enabled significant advances in knowledge about meteorological and oceanographic conditions, making possible the development of forecasting systems to provide real, accurate and safe support in decision making in ports.</p><p>SAMOA initiative (System of Meteorological and Oceanographic Support for Port Authorities), developed by Spanish Port System (Puertos del Estado), in cooperation with Spanish Port Authorities, provides high-resolution coastal operational prediction systems in domains such as harbours and nearby coastal waters.</p><p>We present a high-resolution coastal operational prediction system which simulates the hydrodynamic in the Spanish Mediterranean Ports from April to September 2019. Bathymetry was built using a combination of bathymetric data from GEBCO (General Bathymetric Chart of the Oceans), and specific local high-resolution sources provided by port authorities. Daily updated hourly winds and heat and water fluxes from the Spanish Meteorological Agency forecast services were used as a surface forcing. The Regional Ocean Modelling System, ROMS, was used to investigate the hydrodynamics.</p><p>Three-day forecast of three-dimensional currents and other oceanographic variables, such as temperature, salinity, and sea level, were produced. These results were compared with field campaigns data, displaying agreements between model outputs and in-situ observations. Finally, a look ahead to the future of the operational prediction systems is provided as a useful tool to make informed decisions around port safety and efficiency.</p><p>We would like to acknowledge financial support from ECOSISTEMA-BC Project (CTM2017-84275-R), funded by the Spanish State Research Agency.</p>
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Metadata
- Type
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- Language
- en
- Landing Page
- https://doi.org/10.5194/egusphere-egu2020-20429
- OA Status
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- Related Works
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- OpenAlex ID
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All OpenAlex metadata
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https://doi.org/10.5194/egusphere-egu2020-20429Digital Object Identifier
- Title
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Validation of the SAMOA Operational Forecasting System in Spanish Mediterranean PortsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2020Year of publication
- Publication date
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2020-03-10Full publication date if available
- Authors
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María Liste Muñoz, Marc Mestres, Manuel Espino, Manel Grifoll, Agustín Sánchez‐Arcilla, Manuel García-León, Marcos García Sotillo, Enrique Ãlvarez FanjulList of authors in order
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https://doi.org/10.5194/egusphere-egu2020-20429Publisher landing page
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.5194/egusphere-egu2020-20429Direct OA link when available
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Port (circuit theory), Bathymetry, Environmental science, Mediterranean climate, Oceanography, Environmental resource management, Mediterranean sea, Meteorology, Geography, Engineering, Geology, Electrical engineering, ArchaeologyTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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| abstract_inverted_index.ROMS, | 247 |
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| abstract_inverted_index.model | 282 |
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| abstract_inverted_index.highly | 7 |
| abstract_inverted_index.hourly | 222 |
| abstract_inverted_index.level, | 268 |
| abstract_inverted_index.levels | 84 |
| abstract_inverted_index.making | 115, 131 |
| abstract_inverted_index.marine | 4 |
| abstract_inverted_index.nearby | 170 |
| abstract_inverted_index.ports, | 50 |
| abstract_inverted_index.safety | 52, 311 |
| abstract_inverted_index.system | 179 |
| abstract_inverted_index.useful | 303 |
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| abstract_inverted_index.Project | 322 |
| abstract_inverted_index.Spanish | 146, 155, 186, 231, 327 |
| abstract_inverted_index.Support | 140 |
| abstract_inverted_index.System, | 246 |
| abstract_inverted_index.ability | 70 |
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| abstract_inverted_index.between | 281 |
| abstract_inverted_index.climate | 35 |
| abstract_inverted_index.coastal | 3, 160, 171, 176 |
| abstract_inverted_index.domains | 165 |
| abstract_inverted_index.effects | 64 |
| abstract_inverted_index.enabled | 105 |
| abstract_inverted_index.in-situ | 285 |
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| abstract_inverted_index.sources | 215 |
| abstract_inverted_index.support | 128, 319 |
| abstract_inverted_index.surface | 240 |
| abstract_inverted_index.systems | 121, 163, 298 |
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| abstract_inverted_index.(Puertos | 149 |
| abstract_inverted_index.Estado), | 151 |
| abstract_inverted_index.Finally, | 287 |
| abstract_inverted_index.Oceans), | 210 |
| abstract_inverted_index.Regional | 243 |
| abstract_inverted_index.Research | 329 |
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| abstract_inverted_index.advances | 107 |
| abstract_inverted_index.beaches, | 28 |
| abstract_inverted_index.compared | 274 |
| abstract_inverted_index.currents | 257 |
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| abstract_inverted_index.extreme, | 17 |
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| abstract_inverted_index.forecast | 234, 254 |
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| abstract_inverted_index.harbours | 168 |
| abstract_inverted_index.informed | 307 |
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| abstract_inverted_index.campaigns | 277 |
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| abstract_inverted_index.emergency | 57 |
| abstract_inverted_index.financial | 318 |
| abstract_inverted_index.knowledge | 109 |
| abstract_inverted_index.long-term | 21 |
| abstract_inverted_index.numerical | 100 |
| abstract_inverted_index.precision | 86 |
| abstract_inverted_index.produced. | 270 |
| abstract_inverted_index.salinity, | 265 |
| abstract_inverted_index.seasonal, | 18 |
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| abstract_inverted_index.Bathymetry | 194 |
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| abstract_inverted_index.agreements | 280 |
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| abstract_inverted_index.displaying | 279 |
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| abstract_inverted_index.management | 62 |
| abstract_inverted_index.prediction | 162, 178, 297 |
| abstract_inverted_index.variables, | 261 |
| abstract_inverted_index.Bathymetric | 206 |
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| abstract_inverted_index.forecasting | 120 |
| abstract_inverted_index.investigate | 251 |
| abstract_inverted_index.maintenance | 41 |
| abstract_inverted_index.operational | 161, 177, 296 |
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| abstract_inverted_index.operations. | 32, 67 |
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| abstract_inverted_index.significant | 106 |
| abstract_inverted_index.Authorities, | 157 |
| abstract_inverted_index.authorities. | 219 |
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| abstract_inverted_index.hydrodynamic | 183 |
| abstract_inverted_index.measurements | 101 |
| abstract_inverted_index.predictions, | 103 |
| abstract_inverted_index.temperature, | 264 |
| abstract_inverted_index.unbelievable | 89 |
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| abstract_inverted_index.ECOSISTEMA-BC | 321 |
| abstract_inverted_index.Mediterranean | 187 |
| abstract_inverted_index.Oceanographic | 139 |
| abstract_inverted_index.environmental | 22, 61 |
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| abstract_inverted_index.meteorological | 111 |
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| abstract_inverted_index.infrastructures, | 44 |
| abstract_inverted_index.three-dimensional | 256 |
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| abstract_inverted_index.efficiency.&lt;/p&gt;&lt;p&gt;We | 313 |
| abstract_inverted_index.hydrodynamics.&lt;/p&gt;&lt;p&gt;Three-day | 253 |
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| corresponding_author_ids | https://openalex.org/A5001820301, https://openalex.org/A5085185460 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 8 |
| corresponding_institution_ids | https://openalex.org/I9617848 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/14 |
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| sustainable_development_goals[0].display_name | Life below water |
| citation_normalized_percentile.value | 0.12355621 |
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| citation_normalized_percentile.is_in_top_10_percent | False |