GAO Feng, CHEN Xinjun, GUAN Wenjiang, LI Gang. A New model to forecast fishing ground of Scomber japonicus in the Yellow Sea and East China Sea[J]. Acta Oceanologica Sinica, 2016, 35(4): 74-81. doi: 10.1007/s13131-015-0767-8
Citation: HE Yan, LIU Na, CHEN Hongxia, TENG Fei, LIN Lina, WANG Huiwu. Observed features of temperature, salinity and current in central Chukchi Sea during the summer of 2012[J]. Acta Oceanologica Sinica, 2015, 34(5): 51-59. doi: 10.1007/s13131-015-0624-7

Observed features of temperature, salinity and current in central Chukchi Sea during the summer of 2012

doi: 10.1007/s13131-015-0624-7
  • Received Date: 2014-05-12
  • Rev Recd Date: 2014-10-08
  • During the summer of 2012, the fifth CHINARE Arctic Expedition was carried out, and a submersible mooring system was deployed in M5 station located at (69°30.155'N,169°00.654'W) and recovered 50d later. A set of temperature, salinity and current profile records was acquired. The characteristics of these observations are analyzed in this paper. Some main results are achieved as below. (1) Temperature generally decreases while salinity generally increases with increasing depth. The average values of all records are 2.98℃ and 32.21 psu. (2) Salinity and temperature are well negatively correlated, and the correlation coefficient between them is -0.84. However, they did not always vary synchronously. Their co-variation featured different characters during different significant periods. (3) The average velocity for the whole water column is 141 mm/s with directional angle of 347.1°. The statistical distribution curve of velocity record number gets narrower with increasing depth. More than 85% of the recorded velocities are northward, and the mean magnitudes of dominated northward velocities are 100-150 mm/s. (4) Rotary spectrum analysis shows that motions with low frequency take a majority of energy in all layers. The most significant energy peaks for all layers are around 0.012 cph (about 3.5 d period), while the tidal motion in mooring area is nonsignificant. (5) Velocities in all layers feature similar and synchronous temporal variations, except for the slight decrease in magnitude and leftward twist from top to bottom. The directions of velocity correspond well to those of surface wind. The average northward volume transport per square meter is 0.1-0.2 m3/s under southerly wind, but about -0.2 m3/s during northerly wind burst.
  • Chen Hongxia, Wang Huiwu, Shu Qi, et al. 2013. Ocean current observation and spectrum analysis in central Chukchi Sea during the summer of 2008. Acta Oceanologica Sinica, 32(3): 10-18
    Coachman L K, Aagaard K. 1981. Re-evaluation of water transports in CHINARE and those who help with the mooring system design. the vicinity of Bering Strait. In: Hood D W, Calder J A, eds. The Eastern Bering Sea Shelf: Oceanography and Resources, Vol. 1. Washington, D C: National Oceanic and Atmospheric Administration, 95-110
    Dickson B. 1999. Oceanography: All change in the Arctic. Nature, 397(6718): 389-391
    Gonella J. 1972. A rotary-component method for analysing meteoro-logical and oceanographic vector time series. Deep Sea Re-search and Oceanographic Abstracts, 19(12): 833-846
    Li Lei, Du Ling, Zhao Jinping, et al. 2005. The fundamental character-istics of current in the Bering Strait and the Chukchi Sea from July to September 2003. Acta Oceanologica Sinica, 24(6): 1-11
    Morison J, Aagaard K, Steele M. 2000. Recent environmental changes in the Arctic: a review. Arctic, 53(4): 359-371
    Roach T A, Aagaard K, Pease H C, et al. 1995. Direct measurements of transport and water properties through the Bering Strait. Journ-al of Geophysical Research: Oceans (1978-2012), 100(C9): 18443-18457
    Simmonds I, Rudeva I. 2012. The great Arctic cyclone of August 2012. Geophysical Research Letters, 39(23): L23709, doi: 10.1029/2012GL054259
    Wang Huiwu, Chen Hongxia, Lü Liangang, et al. 2011. Study of tide and residual current observations in Chukchi Sea in the sum-mer 2008. Haiyang Xuebao (in Chinese), 33(6): 1-8
    Weingartner T, Aagaard K, Woodgate R, et al. 2005. Circulation on the north central Chukchi Sea shelf. Deep-Sea Research Part II: Topical Studies in Oceanography, 52(24-26): 3150-3174
    Weingartner T, Cavalieri D J, Aagaard K, et al. 1998. Circulation, dense water formation, and outflow on the northeast Chukchi shelf. Journal of Geophysical Research: Oceans (1978-2012), 103(C4): 7647-7661
    Woodgate R A, Aagaard K, Weingartner T J. 2005a. A year in the phys-ical oceanography of the Chukchi Sea: Moored measurements from autumn 1990-1991. Deep-Sea Research Part II: Topical Studies in Oceanography, 52(24-26): 3116-3149
    Woodgate R A, Aagaard K, Weingartner T J. 2005b. Monthly temper-ature, salinity, and transport variability of the Bering Strait through flow. Geophysical Research Letters, 32(4): 1-4
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