scholarly journals Studies on the Biological Processes in the Lower Trophic Levels in the Subarctic Waters of the North Pacific Ocean.

1992 ◽  
Vol 1 (6) ◽  
pp. 355-367
Author(s):  
Tsuneo Odate
Keyword(s):  
Pacific Ocean ◽  
North Pacific ◽  
North Pacific Ocean ◽  
Trophic Levels ◽  
Biological Processes ◽  
The North ◽  
The North Pacific

scholarly journals Impacts of Physical and Biological Processes on Spatial and Temporal Variability of Particulate Organic Carbon in the North Pacific Ocean during 2003–2017

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Jun Yu ◽  
Xiujun Wang ◽  
Hang Fan ◽  
Rong-Hua Zhang
Keyword(s):  
Pacific Ocean ◽  
Organic Carbon ◽  
North Pacific ◽  
Temporal Variability ◽  
North Pacific Ocean ◽  
Biological Processes ◽  
Subtropical Region ◽  
Subarctic Region ◽  
The North ◽  
The North Pacific

Abstract The North Pacific Ocean is a significant carbon sink region, but little is known about the dynamics of particulate organic carbon (POC) and the influences of physical and biological processes in this region at the basin scale. Here, we analysed high-resolution surface POC data derived from MODIS-Aqua during 2003–2017, together with satellite-derived sea surface chlorophyll and temperature (SST). There are large spatial and temporal variations in surface POC in the North Pacific. Surface POC is much lower in the subtropical region (<50 mg m−3) than in the subarctic region (>100 mg m−3), primarily resulting from the south-to-north variability in biological production. Our analyses show significant seasonal and interannual variability in surface POC. In particular, there is one peak in winter-spring in the western subtropical region and two peaks in late spring and fall in the western subarctic region. Surface POC is positively correlated with chlorophyll (r = ~1) and negatively correlated with SST (r = ~−0.45, P < 0.001) south of 45°N, indicating the strong influence of physically driven biological activity on the temporal variability of POC in the subtropical region. There is a significantly positive but relatively lower correlation coefficient (0.6–0.8) between POC and chlorophyll and an overall non-significantly positive correlation between POC and SST north of 45°N, reflecting the reduction in the POC standing stock due to the fast sinking of large particles. The climate modes of the Pacific Decadal Oscillation, El Niño–Southern Oscillation and North Pacific Gyre Oscillation have large impacts on POC in various seasons in the subtropical region and weak influences in the subarctic region. Surface POC was anomalously high after 2013 (increased by ~15%) across the basin, which might be the result of complex interactions of physical and biological processes associated with an anomalous warming event (the Blob).

scholarly journals Neural Network Approach to Retrieving Ocean Subsurface Temperatures from Surface Parameters Observed by Satellites

Water ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 388
Author(s):  
Hao Cheng ◽  
Liang Sun ◽  
Jiagen Li
Keyword(s):  
Neural Network ◽  
Pacific Ocean ◽  
North Pacific ◽  
North Pacific Ocean ◽  
Sea Surface ◽  
Satellite Measurements ◽  
Surface Parameters ◽  
The North ◽  
The North Pacific ◽  
Bpnn Model

The extraction of physical information about the subsurface ocean from surface information obtained from satellite measurements is both important and challenging. We introduce a back-propagation neural network (BPNN) method to determine the subsurface temperature of the North Pacific Ocean by selecting the optimum input combination of sea surface parameters obtained from satellite measurements. In addition to sea surface height (SSH), sea surface temperature (SST), sea surface salinity (SSS) and sea surface wind (SSW), we also included the sea surface velocity (SSV) as a new component in our study. This allowed us to partially resolve the non-linear subsurface dynamics associated with advection, which improved the estimated results, especially in regions with strong currents. The accuracy of the estimated results was verified with reprocessed observational datasets. Our results show that the BPNN model can accurately estimate the subsurface (upper 1000 m) temperature of the North Pacific Ocean. The corresponding mean square errors were 0.868 and 0.802 using four (SSH, SST, SSS and SSW) and five (SSH, SST, SSS, SSW and SSV) input parameters and the average coefficients of determination were 0.952 and 0.967, respectively. The input of the SSV in addition to the SSH, SST, SSS and SSW therefore has a positive impact on the BPNN model and helps to improve the accuracy of the estimation. This study provides important technical support for retrieving thermal information about the ocean interior from surface satellite remote sensing observations, which will help to expand the scope of satellite measurements of the ocean.

scholarly journals Nursery origin and population connectivity of swordfish Xiphias gladius in the North Pacific Ocean

2021 ◽  
Author(s):  
R. J. David Wells ◽  
Veronica A. Quesnell ◽  
Robert L. Humphreys ◽  
Heidi Dewar ◽  
Jay R. Rooker ◽  
...  
Keyword(s):  
Pacific Ocean ◽  
North Pacific ◽  
North Pacific Ocean ◽  
Population Connectivity ◽  
The North ◽  
Xiphias Gladius ◽  
The North Pacific
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