3 resultados para Arabian Sea warm pool

em DigitalCommons - The University of Maine Research


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The Princeton Ocean Model is used to study the circulation in the South China Sea (SCS) and its seasonal transition. Kuroshio enters ( leaves) the SCS through the southern ( northern) portion of the Luzon Strait. The annually averaged net volume flux through the Luzon Strait is similar to2 Sv into the SCS with seasonal reversals. The inflow season is from May to January with the maximum intrusion of Kuroshio water reaching the western SCS during fall in compensation of summertime surface offshore transport associated with coastal upwelling. From February to April the net transport reverses from the SCS to the Pacific. The intruded Kuroshio often forms an anticyclonic current loop west of the Luzon Strait. The current loop separates near the Dongsha Islands with the northward branch continuously feeding the South China Sea Warm Current (SCSWC) near the shelf break and the westward branch becoming the South China Sea Branch of Kuroshio on the slope, which is most apparent in the fall. The SCSWC appears from December to February on the seaward side of the shelf break, flowing eastward against the prevailing wind. Diagnosis shows that the onshore Ekman transport due to northeasterly monsoon generates upwelling when moving upslope, and the particular distributions of the density and sea level associated with the cross shelf motion supports the SCSWC.

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The complex effects of light, nutrients and temperature lead to a variable carbon to chlorophyll (C:Chl) ratio in phytoplankton cells. Using field data collected in the Equatorial Pacific, we derived a new dynamic model with a non-steady C:Chl ratio as a function of irradiance, nitrate, iron, and temperature. The dynamic model is implemented into a basin-scale ocean circulation-biogeochemistry model and tested in the Equatorial Pacific Ocean. The model reproduces well the general features of phytoplankton dynamics in this region. For instance, the simulated deep chlorophyll maximum (DCM) is much deeper in the western warm pool (similar to 100 m) than in the Eastern Equatorial Pacific (similar to 50 m). The model also shows the ability to reproduce chlorophyll, including not only the zonal, meridional and vertical variations, but also the interannual variability. This modeling study demonstrates that combination of nitrate and iron regulates the spatial and temporal variations in the phytoplankton C:Chl ratio in the Equatorial Pacific. Sensitivity simulations suggest that nitrate is mainly responsible for the high C:Chl ratio in the western warm pool while iron is responsible for the frontal features in the C:Chl ratio between the warm pool and the upwelling region. In addition, iron plays a dominant role in regulating the spatial and temporal variations of the C:Chl ratio in the Central and Eastern Equatorial Pacific. While temperature has a relatively small effect on the C:Chl ratio, light is primarily responsible for the vertical decrease of phytoplankton C:Chl ratio in the euphotic zone.

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Application of biogeochemical models to the study of marine ecosystems is pervasive, yet objective quantification of these models' performance is rare. Here, 12 lower trophic level models of varying complexity are objectively assessed in two distinct regions (equatorial Pacific and Arabian Sea). Each model was run within an identical one-dimensional physical framework. A consistent variational adjoint implementation assimilating chlorophyll-a, nitrate, export, and primary productivity was applied and the same metrics were used to assess model skill. Experiments were performed in which data were assimilated from each site individually and from both sites simultaneously. A cross-validation experiment was also conducted whereby data were assimilated from one site and the resulting optimal parameters were used to generate a simulation for the second site. When a single pelagic regime is considered, the simplest models fit the data as well as those with multiple phytoplankton functional groups. However, those with multiple phytoplankton functional groups produced lower misfits when the models are required to simulate both regimes using identical parameter values. The cross-validation experiments revealed that as long as only a few key biogeochemical parameters were optimized, the models with greater phytoplankton complexity were generally more portable. Furthermore, models with multiple zooplankton compartments did not necessarily outperform models with single zooplankton compartments, even when zooplankton biomass data are assimilated. Finally, even when different models produced similar least squares model-data misfits, they often did so via very different element flow pathways, highlighting the need for more comprehensive data sets that uniquely constrain these pathways.