Dynamical Ocean Responses to Typhoon Malakas (2016) in the Vicinity of Taiwan

Shen, Dongliang; Li, Xiaofeng; Wang, Jia; Bao, Shaowu; Pietrafesa, Leonard J.

doi:10.1029/2020jc016663

Cited by 15 publications

(14 citation statements)

References 73 publications

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“…Both are not conductive to the growth of phytoplankton. When typhoons pass though the northern SCS, their winds also generate upper ocean Ekman transport and trigger upwelling or downwelling, further enhancing or destroying the two upwelling regions [43] depending on the direction of the typhoon path relative to the coastline [44]. This probably results in increased or decreased Chl-a concentrations, which can be partially attributed to nutrient transportation.…”

Section: Introductionmentioning

confidence: 99%

Effect of Summer Typhoon Linfa on the Chlorophyll-a Concentration in the Continental Shelf Region of Northern South China Sea

Wang

Zhang

2021

JMSE

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Based on both physical and biological data collected from multi-source satellite during summer typhoon Linfa, we found that the typhoon triggered two phytoplankton declines and three phytoplankton blooms in the northern South China Sea (SCS), where the waters were influenced by coastal upwelling and the input of terrigenous materials from the Pearl River estuary (PRE). One phytoplankton decline (about a 3-fold reduction) in the continental shelf region can probably be attribute to the limited nutrient supply induced by the decayed coastal northeastern current and onshore Ekman transport (OET) and Kuroshio intrusion water, as well as the uplifted subsurface’s low chlorophyll-a (Chl-a) concentration driven by vertical mixing and upwelling. Another phytoplankton decline (about a 3.5-fold reduction) in the eastern Leizhou Peninsula-coastal upwelling region is probably caused by OET and a decayed coastal northern current. Conversely, the decayed coastal current, OET, and the vertical mixing and upwelling could lead to the transport of nutrient-rich water from the PRE to the nearshore region of the southwestern PRE mouth, and from the subsurface layer to the surface, respectively, thereby stimulating the growth of phytoplankton in the nearshore region (increased by about 4-fold) and the open ocean (increased by about 2.3-fold). In the Shantou (the coastal upwelling region), the phytoplankton responses to nutrient supply were feeble when phytoplankton was already growing in nutrient replete conditions. In addition, the OET and the high turbidity barely resulted in moderate phytoplankton bloom (increased by 38%). In summary, the physical driving forces associated with typhoons that modulates phytoplankton dynamics are the nutrient and phytoplankton transportation in the northern SCS during the wet season.

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Section: Introductionmentioning

confidence: 99%

Effect of Summer Typhoon Linfa on the Chlorophyll-a Concentration in the Continental Shelf Region of Northern South China Sea

Wang

Zhang

2021

JMSE

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“…The Regional Ocean Modeling System, a free‐surface, terrain‐following, primitive‐equation, hydrostatic approximation ocean model with a built‐in Lagrangian tracking module (Shchepetkin & McWilliams, 2005) was used to simulate ocean currents (Bao et al., 2017; Shen et al., 2021) and float trajectories. In the Lagrangian tracking module, a float is treated as a small neutrally buoyant particle.…”

Section: Data and Model Setupmentioning

confidence: 99%

Improving Numerical Model Predicted Float Trajectories by Deep Learning

Shen

Bao

Pietrafesa

et al. 2022

Earth and Space Science

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The Lagrangian tracking approach is often used in numerical modeling (NM) to simulate and predict the movement of marine particles such as plastic, oil spills, and floating wreckage. The uncertainties in NM reduce prediction accuracy as a result of the coarse temporal and spatial resolution, along with waves, winds, and currents. From 29 August to 22 December 2020, the United States Defense Advanced Research Projects Agency's Ocean of Things program deployed 422 floating drifters in the Gulf of Mexico, providing an opportunity of using the observed trajectories as ground truth to train Artificial Intelligence (AI) models to correct NM float trajectory predictions. A Regional Ocean Model System (ROMS) and AI Hybrid model was developed to implement AI to correct the ROMS‐predicted 1‐day float trajectories. The AI model is built on a convolutional neural network and Gated Recurrent Unit. The results of the ROMS‐AI Hybrid model show that 82.0% of the trajectory predictions were improved at the 24 hr, with the corresponding overall mean separation error decreasing by 11.82 km, from 20.56 to 8.74 km, which is a 57% improvement, and the error growth rate decreasing from 5.06 km per 6 hr to 1.95 km per 6 hr. The evident improvement indicates that the ROMS‐AI Hybrid model can correct the ROMS simulation to improve the 1‐day prediction of the float trajectories and shows great potential to predict the cluster of the floats.

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“…Shen, Li, et al. (2021) showed that typhoon Malakas triggered two eddies with different mechanisms along the ECS Kuroshio path, which caused the chlorophyll‐a increase. Chen et al.…”

Section: Introductionmentioning

confidence: 99%

“…The super typhoon Soudelor in 2015 caused an abnormal reverse intrusion of the Kuroshio branch current due to the break of the potential vorticity barrier on both sides of KC (Lü et al, 2021). Shen, Li, et al (2021) showed that typhoon Malakas triggered two eddies with different mechanisms along the ECS Kuroshio path, which caused the chlorophyll-a increase. Chen et al (2003) pointed out that the cross-shelf upwelling of nutrient-rich KSSW due to buoyancy forcing was responsible for new productivity during typhoon Herb.…”

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confidence: 99%

Three Types of Typhoon‐Induced Upwellings Enhance Coastal Algal Blooms: A Case Study

Yang

et al. 2022

JGR Oceans

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Satellite data show that typhoon Chan‐hom did trigger an algal bloom several days after passing by the East China Sea. To investigate dynamic connections between this enhanced chlorophyll‐a and phosphate‐rich Kuroshio subsurface water (KSSW), we set up a fine‐resolution coupled physical‐biological model, which effectively reproduced the oceanic conditions during this typhoon. Furthermore, we released a passive tracer along a zonal transect northeast of Taiwan. The modeled surface tracer variations along the coast of Zhejiang agreed very well with satellite data and chlorophyll‐a changes in the biological model. The lowest structural similarity index between chlorophyll‐a and KSSW was 0.77. Model results along a coastal section imply that typhoon Chan‐hom induced additional upwellings and enhanced vertical mixing, leading to more KSSW outcropping. Through horizontal dynamic diagnostic and vertical velocity decomposition, we distinguished three types of dynamical mechanisms for the upward motions. At first, the linear wind Ekman effect existed around the coastal areas and led to intense Ekman pumping. Second, a pronounced nonlinear effect led to upwellings, and spectrum analysis revealed that this nonlinearity consisted of high‐frequency near‐inertial waves and low‐frequency coastal shelf waves. At last, an eddy field remained after the typhoon, continuously supplying nutrients upward to the surface layer by eddy‐induced Ekman pumping. This study reveals that these mechanisms may be general on the continental shelf, where typhoons can pump phosphate‐rich bottom water into the upper layer and enhance primary productivity there. The results also prove typhoon‐induced nonlinear wave motions on the continental shelf contribute to the outcrop of nutrients.

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Dynamical Ocean Responses to Typhoon Malakas (2016) in the Vicinity of Taiwan

Cited by 15 publications

References 73 publications

Effect of Summer Typhoon Linfa on the Chlorophyll-a Concentration in the Continental Shelf Region of Northern South China Sea

Effect of Summer Typhoon Linfa on the Chlorophyll-a Concentration in the Continental Shelf Region of Northern South China Sea

Improving Numerical Model Predicted Float Trajectories by Deep Learning

Three Types of Typhoon‐Induced Upwellings Enhance Coastal Algal Blooms: A Case Study

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