Assimilation of high-resolution sea surface temperature data into an operational nowcast/forecast system around Japan using a multi-scale three-dimensional variational scheme

Miyazawa, Yasumasa; Varlamov, Sergey M.; Miyama, Toru; Guo, Xinyu; Hihara, Tsutomu; Kiyomatsu, Keiji; Kachi, Misako; Kurihara, Yukio; Murakami, Hiroshi

doi:10.1007/s10236-017-1056-1

Cited by 88 publications

(64 citation statements)

References 40 publications

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“…By using this operational model (JCOPE_EC), we have already launched a trial to perform a nowcast/forecast experiment targeting ocean acidification indices (pH insitu and Ω arg ), which are reproduced with the nowcast/forecast operational ocean model products [35,36,38]. A website (https: //www.marinecrisiswatch.jp/mcwatch/prediction/jcope/index.html) experimentally shows up-to-date results of the nowcast/forecast system to demonstrate our studies effectively.…”

Section: Discussionmentioning

confidence: 99%

“…The JCOPE_EC was constructed on an offline tracer model driven by physical processes simulated by the model outputs of the JCOPE2M, and an operational eddy-resolving ocean general circulation model based on the Princeton Ocean Model, with a generalized sigma coordinate [38]. The JCOPE_EC is a three-dimensional high-resolution regional model that covers the western North Pacific (10.5 • -62 • N, 108 • -180 • E) at a horizontal resolution of 1/12 • (9.1-4.4 km) and has 46 vertical active levels.…”

Section: Model Formationmentioning

confidence: 99%

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Development of a Biogeochemical and Carbon Model Related to Ocean Acidification Indices with an Operational Ocean Model Product in the North Western Pacific

et al. 2019

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We developed a biogeochemical and carbon model (JCOPE_EC) coupled with an operational ocean model for the North Western Pacific. JCOPE_EC represents ocean acidification indices on the background of the risks due to ocean acidification and our model experiences. It is an off-line tracer model driven by a high-resolution regional ocean general circulation model (JCOPE2M). The results showed that the model adequately reproduced the general patterns in the observed data, including the seasonal variability of chlorophyll-a, dissolved inorganic nitrogen/phosphorus, dissolved inorganic carbon, and total alkalinity. We provide an overview of this system and the results of the model validation based on the available observed data. Sensitivity analysis using fixed values for temperature, salinity, dissolved inorganic carbon and total alkalinity helped us identify which variables contributed most to seasonal variations in the ocean acidification indices, pH and Ωarg. The seasonal variation in the pHinsitu was governed mainly by balances of the change in temperature and dissolved inorganic carbon. The seasonal increase in Ωarg from winter to summer was governed mainly by dissolved inorganic carbon levels.

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Section: Discussionmentioning

confidence: 99%

Section: Model Formationmentioning

confidence: 99%

Development of a Biogeochemical and Carbon Model Related to Ocean Acidification Indices with an Operational Ocean Model Product in the North Western Pacific

et al. 2019

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“…(a) Masses of free‐floating Ulva prolifera thalli were collected and cleaned by special cargo ships and fishing boats from the sea along the coast of Qingdao during the occurrence of green tide; (b) Although many barrier cables were built on the surface of the sea to prevent invasion of U. prolifera thalli, a large amount of thalli still could been seen in the famous tourism zone of Qingdao; (c) Green tides and hydrological conditions in the south Yellow Sea (Miyazawa et al, ). Blue solid arrows represent the main direction of current during green tides migration; Black hollow arrows represent the main direction of wind during green tides migration.…”

Section: Ulva and Green Tides In The Yellow Seamentioning

confidence: 99%

Macroalgal blooms caused by marine nutrient changes resulting from human activities

Wang

2020

Journal of Applied Ecology

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Macroalgal blooms (green tides) are occurring more frequently in many regions of the world, leading to significant impacts on marine ecology and economies. Although many studies and hypotheses have been proposed, the exact mechanism of green tide formation remains unclear. The world's largest green tides recur in the Yellow Sea and this area is representative for studying the origin and mechanism of green tide formation. We conducted a meta‐analysis of studies related to green tides and associated hypotheses for their formation. Rapid industrialization/urbanization and environmental protection actions in coastal zones have led to an increase in nitrate (nitrite) and decline in ammonium (ammonia), and this has resulted in increasing levels of dissolved inorganic nitrogen in seawater. We found that presence of appropriate attachment substrates for Ulva including laver culture rafts and certain hydrological conditions are supplementary factors to green tide formation in the Yellow Sea. Changes in marine nutrient levels promote the production of nitric oxide, which is essential for Ulva sporulation. Consequently, numerous spores are created and attach to substrates including laver culture rafts and parent Ulva thalli. These spores then develop into new thalli that are capable of producing further spores. As a result, Ulva thalli rapidly occupy vast areas of the sea and develop into green tides. Synthesis and applications. Our synthesis identifies that escalating marine nitric oxide generation caused by various factors and its essential role in Ulva sporulation are underlying and significant components in the mechanism of green tide formation. We provide solutions such as the improvement of comprehensive management of aquaculture and strict restriction of marine nitrate pollution, to prevent green tides. Furthermore, we propose an innovative wastewater treatment programme combined with Ulva application to fulfil the standard of sustainable development and circular economy.

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“…Thus, techniques aiming at improving the way sea surface observations from satellite-borne sensors correct the sub-surface ocean state are required to advance. Here, we focus our investigation on the optimal assimilation of daytime sea surface temperature (SST) retrievals at high temporal frequency, which has the potential to correct the mixed layer depth [4][5][6], with obvious advantages for several oceanographic applications, ranging from biogeochemistry to underwater acoustic propagation [7].…”

Section: Introductionmentioning

confidence: 99%

Optimal Assimilation of Daytime SST Retrievals from SEVIRI in a Regional Ocean Prediction System

Storto

Oddo

2019

Remote Sensing

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Exploiting the potential of space-borne oceanic measurements to characterize the sub-surface structure of the ocean becomes critical in areas where deployment of in situ sensors might be difficult or expensive. Sea Surface Temperature (SST) observations potentially provide enormous amounts of information about the upper ocean variability. However, the assimilation of daytime SST retrievals, e.g., from infrared sensors into ocean prediction systems, requires a specific treatment of the diurnal cycle of skin SST, which is generally under-estimated in current ocean models due to poor vertical resolution at the air–sea interface and lack of proper parameterizations. To this end, a simple off-line bias correction scheme is proposed, where the bias predictors include, among others, the warm layer and cool skin warming/cooling deduced from a prognostic model. Furthermore, a localization procedure that limits the vertical penetration of the SST information in a hybrid variational-ensemble data assimilation system is formulated. These two novelties are implemented and assessed within a regional ocean prediction system in the Ligurian Sea for the assimilation of daytime SST data retrieved with hourly frequency from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the geostationary satellite Meteosat-10. Experiments are validated against independent measurements collected by gliders, moorings, and drifters during the Long-term Glider Missions for Environmental Characterization (LOGCMEC17) sea trial. Results suggest that the simple bias correction scheme is effective in improving both the sea surface and mixed layer accuracy, correctly thinning the mixed layer compared to the control experiment, outperforming experiments with night-only data assimilation, and improving the forecast skill scores. Localization further improves the prediction of the mixed layer depth. It is therefore recommended that sophisticated bias correction and localization procedures are adopted for fruitfully assimilating daytime SST data in operational oceanographic analysis systems.

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Assimilation of high-resolution sea surface temperature data into an operational nowcast/forecast system around Japan using a multi-scale three-dimensional variational scheme

Cited by 88 publications

References 40 publications

Development of a Biogeochemical and Carbon Model Related to Ocean Acidification Indices with an Operational Ocean Model Product in the North Western Pacific

Development of a Biogeochemical and Carbon Model Related to Ocean Acidification Indices with an Operational Ocean Model Product in the North Western Pacific

Macroalgal blooms caused by marine nutrient changes resulting from human activities

Optimal Assimilation of Daytime SST Retrievals from SEVIRI in a Regional Ocean Prediction System

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