Pub Date : 2021-11-08DOI: 10.1080/1755876X.2021.1999107
Javier García-Alba, Javier F. Bárcena, Luis Pedraz, Felipe Fernández, Andrés García, Marcos Mecías, Javier Costas-Veigas, M. L. Samano, D. Szpilman
ABSTRACT People still drown on beaches in unacceptable numbers due to the lack of knowledge about the risks taking place in them. The proposed methodology forecasts electronic bathing flags in beaches by integrating the benefits of metocean operational systems, machine learning and web-based decision support technologies into a 24/7 risk assessment service that could be easily implemented at any beach worldwide with low costs of maintenance. Firstly, a crosscutting analysis between metocean conditions, beach characteristics and flag records was performed. Secondly, an expert system, based on Deep Learning, was developed to obtain electronic bathing flags as an indicator of the dynamic risk of drowning on beaches. The input variables of the Deep Neural Network were significant wave height, mean wave period, wind velocity, marine current velocity, incidence angle, and beach modal state. Finally, the application of the method to the Santa Catarina’s beaches (Brazil) conveniently reproduced the status flag of beaches.
{"title":"SOSeas Web App: An assessment web-based decision support tool to predict dynamic risk of drowning on beaches using deep neural networks","authors":"Javier García-Alba, Javier F. Bárcena, Luis Pedraz, Felipe Fernández, Andrés García, Marcos Mecías, Javier Costas-Veigas, M. L. Samano, D. Szpilman","doi":"10.1080/1755876X.2021.1999107","DOIUrl":"https://doi.org/10.1080/1755876X.2021.1999107","url":null,"abstract":"ABSTRACT People still drown on beaches in unacceptable numbers due to the lack of knowledge about the risks taking place in them. The proposed methodology forecasts electronic bathing flags in beaches by integrating the benefits of metocean operational systems, machine learning and web-based decision support technologies into a 24/7 risk assessment service that could be easily implemented at any beach worldwide with low costs of maintenance. Firstly, a crosscutting analysis between metocean conditions, beach characteristics and flag records was performed. Secondly, an expert system, based on Deep Learning, was developed to obtain electronic bathing flags as an indicator of the dynamic risk of drowning on beaches. The input variables of the Deep Neural Network were significant wave height, mean wave period, wind velocity, marine current velocity, incidence angle, and beach modal state. Finally, the application of the method to the Santa Catarina’s beaches (Brazil) conveniently reproduced the status flag of beaches.","PeriodicalId":50105,"journal":{"name":"Journal of Operational Oceanography","volume":"1 1","pages":"155 - 174"},"PeriodicalIF":3.1,"publicationDate":"2021-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91159417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-20DOI: 10.1080/1755876X.2021.1946240
K. von Schuckmann, P. Le Traon, N. Smith, A. Pascual, S. Djavidnia, J. Gattuso, M. Grégoire, S. Aaboe, V. Alari, B. E. Alexander, A. Alonso-Martirena, A. Aydoğdu, J. Azzopardi, M. Bajo, F. Barbariol, M. Batistić, A. Behrens, S. B. Ismail, A. Benetazzo, I. Bitetto, M. Borghini, L. Bray, A. Capet, R. Carlucci, S. Chatterjee, J. Chiggiato, S. Ciliberti, G. Cipriano, E. Clementi, P. Cochrane, G. Cossarini, L. D’Andrea, Silvio Davison, Emily Down, A. Drago, J. Druon, G. Engelhard, I. Federico, R. Garić, A. Gauci, R. Gerin, G. Geyer, R. Giesen, Simon Good, Richard Graham, M. Grégoire, E. Greiner, Kjell Gundersen, P. Hélaouët, S. Hendricks, J. Heymans, Jason D. Holt, M. Hure, M. Juzà, D. Kassis, P. Kellett, Maaike Knol-Kauffman, P. Kountouris, M. Kõuts, P. Lagemaa, T. Lavergne, J. Legeais, P. L. Traon, S. Libralato, V. Lien, Leonardo Lima, S. Lind, Ye Liu, D. Macias, I. Maljutenko, A. Mangin, A. Männik, V. Marinova, R. Martellucci, Francesco Masnadi, E. Mauri, M. Mayer, M. Menna, C. Meulders, Jane S. Møgster, M
{"title":"Copernicus Marine Service Ocean State Report, Issue 5","authors":"K. von Schuckmann, P. Le Traon, N. Smith, A. Pascual, S. Djavidnia, J. Gattuso, M. Grégoire, S. Aaboe, V. Alari, B. E. Alexander, A. Alonso-Martirena, A. Aydoğdu, J. Azzopardi, M. Bajo, F. Barbariol, M. Batistić, A. Behrens, S. B. Ismail, A. Benetazzo, I. Bitetto, M. Borghini, L. Bray, A. Capet, R. Carlucci, S. Chatterjee, J. Chiggiato, S. Ciliberti, G. Cipriano, E. Clementi, P. Cochrane, G. Cossarini, L. D’Andrea, Silvio Davison, Emily Down, A. Drago, J. Druon, G. Engelhard, I. Federico, R. Garić, A. Gauci, R. Gerin, G. Geyer, R. Giesen, Simon Good, Richard Graham, M. Grégoire, E. Greiner, Kjell Gundersen, P. Hélaouët, S. Hendricks, J. Heymans, Jason D. Holt, M. Hure, M. Juzà, D. Kassis, P. Kellett, Maaike Knol-Kauffman, P. Kountouris, M. Kõuts, P. Lagemaa, T. Lavergne, J. Legeais, P. L. Traon, S. Libralato, V. Lien, Leonardo Lima, S. Lind, Ye Liu, D. Macias, I. Maljutenko, A. Mangin, A. Männik, V. Marinova, R. Martellucci, Francesco Masnadi, E. Mauri, M. Mayer, M. Menna, C. Meulders, Jane S. Møgster, M","doi":"10.1080/1755876X.2021.1946240","DOIUrl":"https://doi.org/10.1080/1755876X.2021.1946240","url":null,"abstract":"","PeriodicalId":50105,"journal":{"name":"Journal of Operational Oceanography","volume":"26 1","pages":"1 - 185"},"PeriodicalIF":3.1,"publicationDate":"2021-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82310435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-05-19DOI: 10.1080/1755876X.2021.1928394
D. Greenslade, M. Hemer, Ian R. Young, Craig Steinberg
ABSTRACT This work revisits and extends an analysis of the Australian wave observing network. The method is based on calculating correlations between modelled wave variables at observation sites and the Australian coastal domain and identifying areas of low correlation. This gives an indication of the areas where variability of the wave fields is poorly captured by existing observation locations, i.e. the network gaps. It is found that the gaps in the network that had been identified in previous work are to a large part reduced by the recent deployment of new infrastructure, but not eliminated. It is also found that the network does less well at observing the synoptic scale wave field than it does at observing the monthly wave climate. Lagged correlations are also considered but found to have only a modest impact on the ability of the network to observe the wave field variability.
{"title":"Structured design of Australia’s in situ wave observing network","authors":"D. Greenslade, M. Hemer, Ian R. Young, Craig Steinberg","doi":"10.1080/1755876X.2021.1928394","DOIUrl":"https://doi.org/10.1080/1755876X.2021.1928394","url":null,"abstract":"ABSTRACT This work revisits and extends an analysis of the Australian wave observing network. The method is based on calculating correlations between modelled wave variables at observation sites and the Australian coastal domain and identifying areas of low correlation. This gives an indication of the areas where variability of the wave fields is poorly captured by existing observation locations, i.e. the network gaps. It is found that the gaps in the network that had been identified in previous work are to a large part reduced by the recent deployment of new infrastructure, but not eliminated. It is also found that the network does less well at observing the synoptic scale wave field than it does at observing the monthly wave climate. Lagged correlations are also considered but found to have only a modest impact on the ability of the network to observe the wave field variability.","PeriodicalId":50105,"journal":{"name":"Journal of Operational Oceanography","volume":"93 1","pages":"140 - 154"},"PeriodicalIF":3.1,"publicationDate":"2021-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73228673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-04-07DOI: 10.1080/1755876X.2021.1911125
M. Alimohammadi, H. Malakooti, M. Rahbani
ABSTRACT The seven simulations were performed to investigate the role of the sea surface temperature (SST) in numerical prediction of tropical cyclones (TCs). The TC Gonu, formed over the Arabian Sea in 2007, was selected for this study. The first five simulations were performed using WRF model. In the first simulation as control simulation (CTL), the SST derived from NCEP-MMAB was used. In the second simulation, 1°C was added to input SST, and in the third simulation, 1°C was subtracted to input SST. It was found that the deviation between the simulated track of simulation SST +1 and CTL is more significant than that between simulation SST −1 and CTL. For the fourth simulation, a homogeneous SST field over the entire basin was used. For the fifth simulation, SST anomaly was calculated, and its values were added to the entire domain. Removing the temperature gradient caused TC intensity to decrease and deviation of the track to the northeast; the increasing temperature gradient had a lower impact on the TC intensity but with a significant deviation of the track to the north with respect to the CTL simulation. In the sixth simulation to consider cyclone-induced SST cooling, a one-dimensional oceanic mixed layer scheme was applied. Results showed no significant reduction in TC intensity. In the seventh simulation, the COAWST modelling system was used. The simulated SST of the COAWST model was consistent with the satellite observations, which finally led to improve the simulation of track and intensity of TC Gonu.
{"title":"Sea surface temperature effects on the modelled track and intensity of tropical cyclone Gonu","authors":"M. Alimohammadi, H. Malakooti, M. Rahbani","doi":"10.1080/1755876X.2021.1911125","DOIUrl":"https://doi.org/10.1080/1755876X.2021.1911125","url":null,"abstract":"ABSTRACT The seven simulations were performed to investigate the role of the sea surface temperature (SST) in numerical prediction of tropical cyclones (TCs). The TC Gonu, formed over the Arabian Sea in 2007, was selected for this study. The first five simulations were performed using WRF model. In the first simulation as control simulation (CTL), the SST derived from NCEP-MMAB was used. In the second simulation, 1°C was added to input SST, and in the third simulation, 1°C was subtracted to input SST. It was found that the deviation between the simulated track of simulation SST +1 and CTL is more significant than that between simulation SST −1 and CTL. For the fourth simulation, a homogeneous SST field over the entire basin was used. For the fifth simulation, SST anomaly was calculated, and its values were added to the entire domain. Removing the temperature gradient caused TC intensity to decrease and deviation of the track to the northeast; the increasing temperature gradient had a lower impact on the TC intensity but with a significant deviation of the track to the north with respect to the CTL simulation. In the sixth simulation to consider cyclone-induced SST cooling, a one-dimensional oceanic mixed layer scheme was applied. Results showed no significant reduction in TC intensity. In the seventh simulation, the COAWST modelling system was used. The simulated SST of the COAWST model was consistent with the satellite observations, which finally led to improve the simulation of track and intensity of TC Gonu.","PeriodicalId":50105,"journal":{"name":"Journal of Operational Oceanography","volume":"1 1","pages":"89 - 105"},"PeriodicalIF":3.1,"publicationDate":"2021-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87028275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-04-05DOI: 10.1080/1755876X.2021.1911126
Emre Çalışır, Mehmet Burak Soran, A. Akpınar
ABSTRACT This study aims to investigate the quality of ERA5, a recent reanalysis wind product, and its contribution to wave modelling performance in a semi-closed sea, the Black Sea. This investigation includes a comparison of ERA5 surface wind fields with the ones from the CFSR to assess if this latest reanalysis improved the representation of the surface winds. Wind speeds from both reanalyses were validated with measurements at Gloria, the only sea wind measurement station on the Black Sea. Validations were also conducted using altimeter and scatterometer satellite data after which results were later compared against each other. The second aim of this study investigates whether a wave hindcast model forced with the ERA5 wind fields has improved prediction of wave parameters. A SWAN model with default settings was used to compare the results under the same conditions. Performance analyzes of the default SWAN wave estimates with both ERA5 and CFSR winds were conducted using three offshore buoy measurements and altimeter data of satellites over the Black Sea. Results show that ERA5 winds are more biased compared to CFSR winds at Gloria location. Both CFSR and ERA5 underestimate wind speeds. ERA5 performs better than the CFSR in lower wind speeds and worse in higher wind speeds. However, ERA5 winds have less bias and are more scattered than the CFSR winds against the satellite data. SWAN driven by CFSR winds performs better than the one driven by ERA5 winds against both buoy and satellite data.
{"title":"Quality of the ERA5 and CFSR winds and their contribution to wave modelling performance in a semi-closed sea","authors":"Emre Çalışır, Mehmet Burak Soran, A. Akpınar","doi":"10.1080/1755876X.2021.1911126","DOIUrl":"https://doi.org/10.1080/1755876X.2021.1911126","url":null,"abstract":"ABSTRACT This study aims to investigate the quality of ERA5, a recent reanalysis wind product, and its contribution to wave modelling performance in a semi-closed sea, the Black Sea. This investigation includes a comparison of ERA5 surface wind fields with the ones from the CFSR to assess if this latest reanalysis improved the representation of the surface winds. Wind speeds from both reanalyses were validated with measurements at Gloria, the only sea wind measurement station on the Black Sea. Validations were also conducted using altimeter and scatterometer satellite data after which results were later compared against each other. The second aim of this study investigates whether a wave hindcast model forced with the ERA5 wind fields has improved prediction of wave parameters. A SWAN model with default settings was used to compare the results under the same conditions. Performance analyzes of the default SWAN wave estimates with both ERA5 and CFSR winds were conducted using three offshore buoy measurements and altimeter data of satellites over the Black Sea. Results show that ERA5 winds are more biased compared to CFSR winds at Gloria location. Both CFSR and ERA5 underestimate wind speeds. ERA5 performs better than the CFSR in lower wind speeds and worse in higher wind speeds. However, ERA5 winds have less bias and are more scattered than the CFSR winds against the satellite data. SWAN driven by CFSR winds performs better than the one driven by ERA5 winds against both buoy and satellite data.","PeriodicalId":50105,"journal":{"name":"Journal of Operational Oceanography","volume":"14 1","pages":"106 - 130"},"PeriodicalIF":3.1,"publicationDate":"2021-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85088252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-04-02DOI: 10.1080/1755876X.2021.1911485
M. Hart-Davis, B. Backeberg
ABSTRACT The ability to provide rapid decision support and more precise search area coordinates for rescuers to conduct search and rescue operations at sea are of high impact value for marine and maritime stakeholders. Search and rescue operations rely on accurate information about metocean conditions to locate objects in the ocean. These include local knowledge, operational ocean and wind forecasts and empirical drift relationships between ocean currents, ocean surface winds and the objects being searched for. To provide more accurate decision support for rescuers looking for persons or objects lost at sea, a virtual particle tracking tool was combined with an empirical Leeway drift model. The Lagrangian Ocean Search Targets (LOST) application builds on a Lagrangian ocean analysis framework which has been adapted to provide real-time estimates of the positions of objects based on operational ocean and wind forecasts. LOST incorporates the impact of ocean currents, surface winds and stochastic motion, the latter being critical in accounting for sub-grid scale processes that are not resolved in the ocean and wind forecasts. This study assesses the accuracy of LOST, demonstrating its feasibility as a decision support tool for search and rescue operations by applying it to three use cases in the South African regional ocean. These use cases are real-life scenarios that highlight the value of combining state-of-the-art ocean and wind forecasting systems with Lagrangian ocean analyses frameworks and sub-grid scale parameterisation to support global operational oceanography.
{"title":"Towards a particle trajectory modelling approach in support of South African search and rescue operations at sea","authors":"M. Hart-Davis, B. Backeberg","doi":"10.1080/1755876X.2021.1911485","DOIUrl":"https://doi.org/10.1080/1755876X.2021.1911485","url":null,"abstract":"ABSTRACT The ability to provide rapid decision support and more precise search area coordinates for rescuers to conduct search and rescue operations at sea are of high impact value for marine and maritime stakeholders. Search and rescue operations rely on accurate information about metocean conditions to locate objects in the ocean. These include local knowledge, operational ocean and wind forecasts and empirical drift relationships between ocean currents, ocean surface winds and the objects being searched for. To provide more accurate decision support for rescuers looking for persons or objects lost at sea, a virtual particle tracking tool was combined with an empirical Leeway drift model. The Lagrangian Ocean Search Targets (LOST) application builds on a Lagrangian ocean analysis framework which has been adapted to provide real-time estimates of the positions of objects based on operational ocean and wind forecasts. LOST incorporates the impact of ocean currents, surface winds and stochastic motion, the latter being critical in accounting for sub-grid scale processes that are not resolved in the ocean and wind forecasts. This study assesses the accuracy of LOST, demonstrating its feasibility as a decision support tool for search and rescue operations by applying it to three use cases in the South African regional ocean. These use cases are real-life scenarios that highlight the value of combining state-of-the-art ocean and wind forecasting systems with Lagrangian ocean analyses frameworks and sub-grid scale parameterisation to support global operational oceanography.","PeriodicalId":50105,"journal":{"name":"Journal of Operational Oceanography","volume":"132 1","pages":"131 - 139"},"PeriodicalIF":3.1,"publicationDate":"2021-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87617062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-03-23DOI: 10.1080/1755876X.2021.1903221
J. Röhrs, G. Sutherland, G. Jeans, M. Bedington, A. Sperrevik, K. Dagestad, Y. Gusdal, C. Mauritzen, A. Dale, J. LaCasce
ABSTRACT This paper reviews physical mechanisms, observation techniques and modelling approaches dealing with surface currents on short time scales (hours to days) relevant for operational oceanography. Key motivations for this article include fundamental difficulties in reliable measurements and the persistent lack of a widely held consensus on the definition of surface currents. These problems are augmented by the fact that various methods to observe and model ocean currents yield very different representations of a surface current. We distinguish between four applicable definitions for surface currents; (i) the interfacial surface current, (ii) the direct wind-driven surface current, (iii) the surface boundary layer current, and (iv) an effective drift current. Finally, we discuss challenges in synthesising various data sources of surface currents - i.e. observational and modelling – and take a view on the predictability of surface currents concluding with arguments that parts of the surface circulation exhibit predictability useful in an operational context.
{"title":"Surface currents in operational oceanography: Key applications, mechanisms, and methods","authors":"J. Röhrs, G. Sutherland, G. Jeans, M. Bedington, A. Sperrevik, K. Dagestad, Y. Gusdal, C. Mauritzen, A. Dale, J. LaCasce","doi":"10.1080/1755876X.2021.1903221","DOIUrl":"https://doi.org/10.1080/1755876X.2021.1903221","url":null,"abstract":"ABSTRACT This paper reviews physical mechanisms, observation techniques and modelling approaches dealing with surface currents on short time scales (hours to days) relevant for operational oceanography. Key motivations for this article include fundamental difficulties in reliable measurements and the persistent lack of a widely held consensus on the definition of surface currents. These problems are augmented by the fact that various methods to observe and model ocean currents yield very different representations of a surface current. We distinguish between four applicable definitions for surface currents; (i) the interfacial surface current, (ii) the direct wind-driven surface current, (iii) the surface boundary layer current, and (iv) an effective drift current. Finally, we discuss challenges in synthesising various data sources of surface currents - i.e. observational and modelling – and take a view on the predictability of surface currents concluding with arguments that parts of the surface circulation exhibit predictability useful in an operational context.","PeriodicalId":50105,"journal":{"name":"Journal of Operational Oceanography","volume":"3 1","pages":"60 - 88"},"PeriodicalIF":3.1,"publicationDate":"2021-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72764715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-03-21DOI: 10.1080/1755876X.2021.1902680
Hailong Liu, P. Lin, Weipeng Zheng, Y. Luan, Jinfeng Ma, M. Ding, H. Mo, L. Wan, Tiejun Ling
ABSTRACT A global eddy-resolving forecast system LFS is developed based on a primitive ocean general circulation model. The system's configuration, forecast experiments, and a preliminary evaluation of the preoperational system are shown. In the preoperational stage, since the full data assimilation has not yet been set up for LFS, the initial state is obtained by nudging the ocean temperature and salinity from an ocean analysis dataset. Despite this, the LFS demonstrates a generally good performance in short-term oceanography forecasting, except for sea level anomaly (SLA). The median values of the 1-day forecast leading root mean square error (RMSE) for the sea surface temperature (SST), SLA, upper 2000 m temperature, and salinity are approximately 0.52°C, 0.10 m, 0.57°C and 0.13 psu, respectively. Although there are slight warm biases in the forecasted SST, the forecasts of temperature and salinity in the thermocline by the LFS are comparable with the results of operational oceanography systems under the framework of the Intercomparison and Validation Task Team. However, the forecast SLA has a relatively large RMSE related to the absence of direct observational constraints in the initial state. Further investigations are needed to improve the performance of LFS.
{"title":"A global eddy-resolving ocean forecast system in China – LICOM Forecast System (LFS)","authors":"Hailong Liu, P. Lin, Weipeng Zheng, Y. Luan, Jinfeng Ma, M. Ding, H. Mo, L. Wan, Tiejun Ling","doi":"10.1080/1755876X.2021.1902680","DOIUrl":"https://doi.org/10.1080/1755876X.2021.1902680","url":null,"abstract":"ABSTRACT A global eddy-resolving forecast system LFS is developed based on a primitive ocean general circulation model. The system's configuration, forecast experiments, and a preliminary evaluation of the preoperational system are shown. In the preoperational stage, since the full data assimilation has not yet been set up for LFS, the initial state is obtained by nudging the ocean temperature and salinity from an ocean analysis dataset. Despite this, the LFS demonstrates a generally good performance in short-term oceanography forecasting, except for sea level anomaly (SLA). The median values of the 1-day forecast leading root mean square error (RMSE) for the sea surface temperature (SST), SLA, upper 2000 m temperature, and salinity are approximately 0.52°C, 0.10 m, 0.57°C and 0.13 psu, respectively. Although there are slight warm biases in the forecasted SST, the forecasts of temperature and salinity in the thermocline by the LFS are comparable with the results of operational oceanography systems under the framework of the Intercomparison and Validation Task Team. However, the forecast SLA has a relatively large RMSE related to the absence of direct observational constraints in the initial state. Further investigations are needed to improve the performance of LFS.","PeriodicalId":50105,"journal":{"name":"Journal of Operational Oceanography","volume":"630 1","pages":"15 - 27"},"PeriodicalIF":3.1,"publicationDate":"2021-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77656904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-03-18DOI: 10.1080/1755876X.2021.1902682
J. Triñanes, N. Putman, G. Goñi, C. Hu, M. Wang
ABSTRACT Pelagic Sargassum is a buoyant macroalgae that forms rafts at the ocean surface and serves as a biologically rich habitat for hundreds of diverse marine species. Since 2011, massive blooms of Sargassum have occurred in the tropical Atlantic and swept through the western tropical Atlantic, Caribbean Sea, and Gulf of Mexico. These recurring annual events have caused significant disruptions to coastal communities throughout the region, negatively impacting human health, tourism, fishing, navigation, and nearshore ecosystems. We present here the Sargassum Inundation Report (SIR), a product that uses satellite-based methodology to estimate and predict the future coastal inundation of pelagic Sargassum. Results from one year of SIRs show strong spatiotemporal differences in the potential of coastal inundation across the Intra-American Seas, and provide a comprehensive method for assessing its geographic distribution and temporal variation. Comparisons of SIRs to opportunistically collected photographs indicate a qualitative concordance between satellite and in situ observations. This work highlights the value of satellite observations, basin-wide and seasonal monitoring, and emphasises the need for sub-regional and weekly forecasting. SIRs show considerable promise as a tool that can eventually incorporate improved spatiotemporal resolution Sargassum imagery, ocean circulation, wind, and wave conditions to forecast the movement of Sargassum into coastal areas.
{"title":"Monitoring pelagic Sargassum inundation potential for coastal communities","authors":"J. Triñanes, N. Putman, G. Goñi, C. Hu, M. Wang","doi":"10.1080/1755876X.2021.1902682","DOIUrl":"https://doi.org/10.1080/1755876X.2021.1902682","url":null,"abstract":"ABSTRACT Pelagic Sargassum is a buoyant macroalgae that forms rafts at the ocean surface and serves as a biologically rich habitat for hundreds of diverse marine species. Since 2011, massive blooms of Sargassum have occurred in the tropical Atlantic and swept through the western tropical Atlantic, Caribbean Sea, and Gulf of Mexico. These recurring annual events have caused significant disruptions to coastal communities throughout the region, negatively impacting human health, tourism, fishing, navigation, and nearshore ecosystems. We present here the Sargassum Inundation Report (SIR), a product that uses satellite-based methodology to estimate and predict the future coastal inundation of pelagic Sargassum. Results from one year of SIRs show strong spatiotemporal differences in the potential of coastal inundation across the Intra-American Seas, and provide a comprehensive method for assessing its geographic distribution and temporal variation. Comparisons of SIRs to opportunistically collected photographs indicate a qualitative concordance between satellite and in situ observations. This work highlights the value of satellite observations, basin-wide and seasonal monitoring, and emphasises the need for sub-regional and weekly forecasting. SIRs show considerable promise as a tool that can eventually incorporate improved spatiotemporal resolution Sargassum imagery, ocean circulation, wind, and wave conditions to forecast the movement of Sargassum into coastal areas.","PeriodicalId":50105,"journal":{"name":"Journal of Operational Oceanography","volume":"4 1","pages":"48 - 59"},"PeriodicalIF":3.1,"publicationDate":"2021-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88609951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-03-17DOI: 10.1080/1755876X.2021.1902681
C. J. Gonzalez, J. R. Torres, P. Bernárdez, Rodolfo J. Ramos
ABSTRACT Sea-level reanalysis data fields from the Iberia-Biscay-Ireland Monitoring and Forecasting Center (IBIre) were analysed and validated with coastal tide-gauge and vertical positioning data from 110 experimental stations, complemented with the Technical University of Denmark global ocean tide model and mean dynamic topography DTU10, in order to establish the reference hydrographic surface (RHS) for Spanish waters. IBIre fitting to experimental tidal ranges, with mean errors about 10 cm, improves the DTU10 results along the Iberian Mediterranean shore due to an adequate reproduction of the ‘radiational’ tides. Regarding the mean dynamic topography, errors were also about 10 cm both for IBIre and DTU10 fields, and about 50% of them is plausibly related to the experimental uncertainness arising from the different averaging periods of observed series. Fitting of IBIre results to experimental data provides orthometric/ellipsoidal heights of the lowest astronomical tide with mean errors between 7 and 10 cm. IBIre sea-level data have enough quality to constitute a reliable basis for an operative RHS in Spanish waters, and plausibly in other regions within its spatial coverage. Moreover, IBIre sea-level data have other potential applications to the study of climate/sea-level trends, and improvements of the accuracy in de-tiding satellite-altimetry data in the western Mediterranean Sea.
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