South China Sea warm pool detected in spring from the Navy's Master Oceanographic Observational Data Set (MOODS)

Chu, Peter C.; Tseng, Hsing-Chia; Chang, C. P.; Chen, J. M.

doi:10.1029/97jc00628

Cited by 53 publications

(45 citation statements)

References 6 publications

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“…In this study, we analyze temperature and salinity profiles measured from a variety of instruments. Due to the shear size (more than six million profiles) and enormous influx of data to the Naval Oceanographic Office from various sources, quality control is a difficult task (Chu et al, 1997c). Our study domain lies inside the area 24…”

Section: Hydrographic Datasetmentioning

confidence: 99%

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Seasonal variability of the Yellow Sea/East China Sea surface fluxes and thermohaline structure

2005

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We use the U.S. Navy's Master Oceanographic Observation Data Set (MOODS) for the Yellow Sea/East China Sea (YES) to investigate the climatological water mass features and the seasonal and non-seasonal variabilities of the thermohaline structure, and use the Comprehensive Ocean-Atmosphere Data Set (COADS) from 1945 to 1989 to investigate the linkage between the fluxes (momentum, heat, and moisture) across the air-ocean interface and the formation of the water mass features. After examining the major current systems and considering the local bathymetry and water mass properties, we divide YES into five regions: East China Sea (ECS) shelf, Yellow Sea (YS) Basin, Cheju bifurcation (CB) zone, Taiwan Warm Current (TWC) region, Kuroshio Current (KC) region. The long term mean surface heat balance corresponds to a heat loss of 30 W m −2 in the ESC and CB regions, a heat loss of 65 W m −2 in the KC and TWC regions, and a heat gain of 15 W m −2 in the YS region. The surface freshwater balance is defined by precipitation minus evaporation. The annual water loss from the surface for the five subareas ranges from 1.8 to 4 cm month −1 . The fresh water loss from the surface should be compensated for from the river run-off. The entire water column of the shelf region (ECS, YS, and CB) undergoes an evident seasonal thermal cycle with maximum values of temperature during summer and maximum mixed layer depths during winter. However, only the surface waters of the TWC and KC regions exhibit a seasonal thermal cycle. We also found two different relations between surface salinity and the Yangtze River run-off, namely, out-of-phase in the East China Sea shelf and in-phase in the Yellow Sea. This may confirm an earlier study that the summer fresh water discharge from the Yangtze River forms a relatively shallow, low salinity plume-like structure extending offshore on average towards the northeast.

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Section: Hydrographic Datasetmentioning

confidence: 99%

“…9d). Spatial and temporal irregularities along with the lack of data in certain regions must be carefully weighed in order to avoid statistically-induced variability (Chu et al, 1997c).…”

Section: Hydrographic Datasetmentioning

confidence: 99%

Seasonal variability of the Yellow Sea/East China Sea surface fluxes and thermohaline structure

2005

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“…Conventional EOF analysis is able to decompose oceanic/atmospheric signals into spatial and temporal components, but does not allow one to diagnose propagating (or moving) signals (e.g., Chu et al, 1997Chu et al, , 1998. The CEOF analysis is an alternative method for detecting propagating signals (Shriver et al, 1991).…”

Section: General Descriptionmentioning

confidence: 99%

Interannual SST variability in the Japan/East Sea and relationship with environmental variables

Park

Chu

2006

J Oceanogr

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“…cording errors and outliers, checking duplicate profiles, checking depth inversion and depth duplication for individual profiles, checking temperature range, checking large temperature inversions and gradients, checking standard deviation, interpolation to standard levels, and post objective analysis checks (Teague, 1986;Jugan and Beresford, 1992;Boyer and Levitus, 1994;Chu et al, 1997bChu et al, , 1998. The accuracy of the data depends on the accuracy of conversion equations, which transform frequency into temperature and elapsed fall time into depth: the AXBT does not measure depth directly.…”

Section: Datamentioning

confidence: 99%

South China Sea warm pool detected in spring from the Navy's Master Oceanographic Observational Data Set (MOODS)

Cited by 53 publications

References 6 publications

Seasonal variability of the Yellow Sea/East China Sea surface fluxes and thermohaline structure

Seasonal variability of the Yellow Sea/East China Sea surface fluxes and thermohaline structure

Interannual SST variability in the Japan/East Sea and relationship with environmental variables

Characteristics of Thermal Finestructure in the Southern Yellow Sea and the East China Sea from Airborne Expendable Bathythermograph Measurements

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