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26 results for “The Kuroshio”
Data in support of 'ENSO influences subsurface marine heatwave occurrence in the Kuroshio Extension'
<p>Data in support of 'Chandler M, Sprintall J, Zilberman NV. (2025). ENSO influences subsurface marine heatwave occurrence in the Kuroshio Extension. <em>Journal of Geophysical Research: Oceans</em>. <a href="https://doi.org/10.1029/2025JC022899" target="_blank" rel="noopener">https://doi.org/10.1029/2025JC022899</a>'</p> <p> </p> <p>There are 2 netCDF files:</p> <ol> <li>p40tem1211_2312.nc</li> <li>synthetic_T_10day_px40_kuroshio_chandler2024.nc</li> </ol> <p><strong>p40tem1211_2312.nc </strong>contains the temperature sections from <a href="https://www-hrx.ucsd.edu/px40.html">HR-XBT transect PX40</a> objectively mapped onto a 10-m depth grid and a 0.1° longitudinal grid. <em>[LONGITUDE; LATITUDE; DEPTH; TIME; TEM]</em></p> <p><strong>synthetic_T_10day_px40_kuroshio_chandler2024.nc</strong> contains the synthetic temperature anomaly time series between the surface and 800-m deep at the western end of transect PX40 over the period from January-1993 to April-2023, as well as the temperature annual cycle needed for reconstructing the full synthetic temperature time series. <em>[time; depth; longitude; latitude; T_prime; T_ann]</em></p> <p> </p> <p>There is 1 MATLAB file:</p> <ol> <li>px40_synthetic_T.m</li> </ol> <p><strong>px40_synthetic_T.m</strong> is the MATLAB script used to produce the synthetic temperature anomaly time series saved in synthetic_T_10day_px40_kuroshio_chandler2024.nc.</p> <p> </p> <p>There is 1 Julia file:</p> <ol> <li>px40_synthetic_T_julia.jl</li> </ol> <p><strong>px40_synthetic_T_julia.jl</strong> is a Julia implementation of the MATLAB script px40_synthetic_T.m.</p> <p> </p> <p>There is 1 R file:</p> <ol> <li>px40_synthetic_T_R.R</li> </ol> <p><strong>px40_synthetic_T_R.R</strong> is an R implementation of the MATLAB script px40_synthetic_T.m.</p> <p> </p> <p><code>Version history:</code><br><code>v1.0.0 First uploaded (25-November-2024)</code><br><code>v1.0.1 Julia script uploaded (18-January-2025)</code><br><code>v1.0.2 R script uploaded (28-January-2025)</code><br><code>v1.1.0 Updated description of synthetic_T_10day_px40_kuroshio_chandler2024.nc to include reference to accepted publication (21-August-2025)</code></p>
Raw data of "Seasonal fluctuations of ichthyoplankton assemblage in the northeastern South China Sea influenced by the Kuroshio intrusion"
<p>The uploaded data here is the raw data of the manuscript "Seasonal fluctuations of ichthyoplankton assemblage in the northeastern South China Sea influenced by the Kuroshio intrusion" submitted to the Journal of Geophysical Research-Oceans. The CTD file (.cnv) is the data recorded by a Sea-Bird conductivity, temperature and depth (CTD) in the sampling stations. This data is used to analyze the water masses during the study period. It can be analyzed with free software of the Ocean Data View 4 (http://odv.awi.de/) or the MATLAB R2017 (http://www.mathworks.com/products/matlab/). The sequence data (.fasta) is used to evaluate the species composition. The data can be analyzed with free software of the BOLD Identification tool (http://www.boldsystems.org/), the basic local-alignment search tool (BLAST) (https://www.ncbi.nlm.nih.gov/), the Clustal X 2.1 (http://www.clustal.org/) and the MEGA 7 (http://www.megasoftware.net/). In additon, the .nc files are the data of surface temperature during the sampling periods. The data can be analyzed with the MATLAB R2017 (http://www.mathworks.com/products/matlab/).</p>
Data files for figures in "Characteristics of the two types of Kuroshio large meanders in the Shikoku Basin"
<p>Processed data files used to create the figures in the paper "Characteristics of the two types of Kuroshio large meanders in the Shikoku Basin".</p>
Fig. 7 in Species Composition And Distribution Of The Dominant Flyingfishes (Exocoetidae) Associated With The Kuroshio Current, South China Sea
Fig. 7. Monthly median (square dot) with 25 th and 75th quartiles (vertical line) for (a) flyingfishes catch proportion (proportion of catch, adjusted by number of trips in the month, to the overall catches of the sampling year), (b) SST (°C), (c) tide level (cm), and (d) tidal range (cm). Tidal range in the plot is the difference of tide level within one hour. Dashed lines indicate roughly the area with high catch
Fig. 5 in Species Composition And Distribution Of The Dominant Flyingfishes (Exocoetidae) Associated With The Kuroshio Current, South China Sea
Fig. 5. Monthly flyingfish densities by (a) vertical catch layer (upper: Fig. 4. Flyingfish compositions of the six dominant species by 0–1.2 m, middle: 1.2–2.4 m, and bottom: 2.4–3.6 m), and (b) mesh sampling area, collected by in-port sampling and at-sea survey size of net (5.6 cm, 4 cm, and 2.8 cm for large, medium, and small
Dynamics of Alongshore Current in the Taiwan Strait: A Perspective on the Southward Kuroshio Branch in Winter
<p>Data for submitted paper "Dynamics of Alongshore Current in the Taiwan Strait: A Perspective on the Southward Kuroshio Branch in Winter ". Those files "Fig.S1-Fig.S4" contain the data of figures in the Supporting Information.</p>
Backward and forward in time particle-tracking simulation in the Kuroshio Extension re-circulation gyre in 2019
<p>Tracers were released at the targeted mesoscale eddy in September 01 2019, and their surface transport was modeled for the previous 26 days and the forward 72 days. Units are expressed as the number of tracer particles in each glid of 1/12° horizontal resolution. The color shades indicate the number of particles. </p>
Transition of the mesoscale eddy in the Kuroshio Extension re-circulation gyre in 2019
<p>Transition of the mesoscale cyclonic eddy occurred in the Kuroshio Extension re-circulation gyre (KERG) from June to December 2019. Color shades denote sea surface height (SSH) map (color contours, m). The Kuroshio and Kuroshio Extension (KE) are shown by a sharp southward increase in SSH and the recirculation gyre is illustrated by a high-SSH (>1.6 m) region. The SSH map was generated using E.U. Copernicus Marine Service Information.</p>
Exceptional multi-year prediction skill of the Kuroshio Extension in the high-resolution CESM decadal prediction system
The Kuroshio Extension (KE) has far-reaching influences on climate as well as on local marine ecosystems. Thus, skillful multi-year to decadal prediction of the KE state and understanding sources of skill are valuable. Retrospective forecasts using the high-resolution CESM show exceptional skill in predicting KE variability up to lead year 4, substantially higher than the skill found in a similarly configured low-resolution CESM. The higher skill is attained because the high-resolution system can more realistically simulate the westward Rossby wave propagation of initialized ocean anomalies in the central North Pacific and their expression within the sharp KE front, and does not suffer from spurious variability near Japan present in the low-resolution CESM that interferes with the incoming wave propagation. These results argue for the use of high-resolution models for future studies that aim to predict changes in western boundary current systems and associated biological fields.
Plankton community respiration and POC in the Kuroshio east of Taiwan
<p><span>This dataset contains data </span>collected from six shipboard measurements taken from the R/V <em>Ocean Researcher I</em> between April 2014 and November 2015, which covered the entire season: April, July, September, and November 2014 and March, June, September, and November 2015 in the Kuroshio, east of Taiwan described in the paper: "Chung-Chi Chen, Pei-Ji Meng, Chih-hao Hsieh, Sen Jan (2022). Plankton community respiration and particulate organic carbon in the Kuroshio, east of Taiwan. <em>Plants</em>".</p> <p><span>The main results of this study included seven figures, which show: 1). The sampling stations; 2). Typical depth profile contour plots of temperature, nitrate, chlorophyll a and particulate organic carbon within 250 m water depth along the KTV1 transect in September 2015; 3). Temporal and spatial variations of the mean values of nitrate and phosphate across the KTV1 transect of the Kuroshio; 4). Temporal and spatial variations of the mean values of chlorophyll a, particulate organic carbon, and plankton community respiration across the KTV1 transect of the Kuroshio; 5). Relationships between the concentration of plankton community respiration vs. particulate organic carbon, chlorophyll a, heterotrophic bacterioplankton, and all picophytoplankton; 6). Relationships between the concentration of particulate organic carbon vs. chlorophyll a and picophytoplankton for all pooled data; and 7). Temporal and spatial variations of the mean values of picophytoplankton in terms of abundance and biomass across the KTV1 transect of the Kuroshio.</span></p>
Data from: The Kuroshio Current influences genetic diversity and population genetic structure of a tropical seagrass, Enhalus acoroides
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Plankton community respiration and POC in the Kuroshio east of Taiwan
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Data from: Finescale measurements of Kelvin-Helmholtz instabilities at a Kuroshio seamount
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Phytoplankton Community Patterns in the Northeastern South China Sea: Implications of intensified Kuroshio intrusion during the 2015/16 El Niño
<p>Phytoplankton Community Patterns in the Northeastern South China Sea:<br> Implications of intensified Kuroshio intrusion during the 2015/16 El Niño</p>
Changes in the Kuroshio path, surface velocity and transport during the last 35,000 years
<p>The major data for “Changes in the Kuroshio path, surface velocity and transport during the last 35,000 years” are listed as follows:</p> <p>1) The annual mean surface current (0-100m, m/s) in 5 cases. Data are separately saved in MATLAB files (surface_velocity_0ka.mat, surface_velocity_6ka.mat, surface_velocity_lgm.mat, surface_velocity_30ka.mat and surface_velocity_35ka.mat) with variables of longitude, latitude, u and v.</p> <p>2) The Kuroshio paths (longitude and latitude) in 5 cases are saved in MATLAB file of “data_pathxy.mat”.</p> <p>3) Distributions of upper 1000-m integrated volume-transport stream function from model results in 5 cases. Data is saved in the MATLAB file of “VT_model.mat” with variables of longitude, latitude, VT_model and casename.</p> <p>3) Distributions of wind-driven Sverdrup transport stream function calculated by wind stresses in 5 cases. Data is saved in the MATLAB file of “ST_wind.mat” with variables of longitude, latitude, ST_wind and casename.</p>
Coastal uplift in the Kuroshio
<p>The Kuroshio is the western boundary current of the North Pacific Ocean. In the subtropical region of eastern Taiwan, a coastal uplift of the isotherms has occurred. To explore its impact on this oligotrophic ecosystem, hydrographic data along the transect line at 23.75<sup>o</sup>N were measured between September 2012 and September 2014. Results show that the intensity of coastal uplift was positively correlated to the flow volume transport of the Kuroshio. Significant dissolved inorganic nutrients were uplifted to the sunlit zone, especially onshore. This dataset contains data collected from six shipboard measurements taken from the R/V <i>Ocean Researcher I</i> between September of 2012 and 2014: September and November 2012, June and September 2013, and July and September 2014 in the Kuroshio, east of Taiwan described in the paper: "Chung-Chi Chen, Chun-Yi Lu, Sen Jan, Chih-Hao Hsieh, Chih-Ching Chung (2022). Effects of the coastal uplift on the Kuroshio ecosystem, eastern Taiwan, the western boundary current of the North Pacific Ocean. <i>Frontiers in Marine Science</i>".</p> <p>The main results of this study included eight figures as described in the paper, and please refer to it for further details.</p>
Code and data for "Seasonal Surface Eddy Mixing in the Kuroshio Extension: Estimation and Machine Learning Prediction" By Guan et al. Submitted to JGR Oceans.
<p>This repository contains the code and data for the machine learning analysis of "Seasonal Surface Eddy Mixing in the Kuroshio Extension: Estimation and Machine Learning Prediction”By Guan et al. Submitted to JGR Oceans.</p> <p>Specifically, this repository contains the following items:<br> (1) Codes for assessing the representation skill of the machine learning and linear regression (LR) methods. Three machine learning methods are considered: random forest (RF), back-propagation neural network (BP), and convolutional neural network (CNN).<br> (2) Codes for assessing the prediction skill of the machine learning and LR methods. <br> (3) Seasonal-mean and annual-mean input data to run these codes. <br> (4) The package needed to run the random forest code, i.e. the RF_MexStandalone-v0.02 program package from https://code.google.com/archive/p/randomforest-matlab/downloads .</p>
Modulation of Cyclones with Tropical and Extratropical Origins by Mesoscale SSTs in the Kuroshio Extension Region
<p>Datasets for <strong>Modulation of Cyclones with T</strong><strong>ropical and Extratropical </strong><strong>Origins </strong><strong>by Mesoscale SSTs in the Kuroshio Extension Region.</strong></p>
Dataset for the manuscript, "Submesoscale Nitrate Upwelling by Cyclonic Eddies in the Upstream Kuroshio Current"
<p>Data and codes for the manuscript, entitled with "Submesoscale Nitrate Upwelling by Cyclonic Eddies in the Upstream Kuroshio Current" by Gloria Silvana Duran Gomez and Takeyoshi Nagai</p>
Forward in time particle-tracking simulation in the Kuroshio Extension re-circulation gyre in 2019 using GLORYS12
<p>Tracers were released at the targeted mesoscale eddy in September 03 2019, and their surface transport was modeled for the the forward two months. Units are expressed as the number of tracer particles in each glid of 1/12° horizontal resolution. The color shades indicate the number of particles. The particle number 50 indicates that the number of particles in a grid is 50 or more.</p>
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