1984
DOI: 10.1016/s0422-9894(08)70306-4
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Variability of Monthly Mean Sea Level and its Regional Features Around Japan and Korea

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Cited by 8 publications
(5 citation statements)
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“…A comparison of Figures g and b shows that the seasonal variations in sea surface height caused by SA (amplitude of 0.16 m) are smaller than the spurious seasonal variations arising from the use of a 2 day sampling interval (amplitude of 0.65 m). The seasonal variations in sea surface height caused by SA are consistent with those in the East China Sea [ Tomizawa et al ., ], and are generally believed to be caused by thermobaric effects [ Wakata , ]. We considered the impact of SA during tidal simulations, but did not include it during the harmonic analyses of the ADCP data because the removal of SA might erase the normal seasonal variations of the Kuroshio volume transport.…”
Section: Tidal Harmonic Analysismentioning
confidence: 98%
“…A comparison of Figures g and b shows that the seasonal variations in sea surface height caused by SA (amplitude of 0.16 m) are smaller than the spurious seasonal variations arising from the use of a 2 day sampling interval (amplitude of 0.65 m). The seasonal variations in sea surface height caused by SA are consistent with those in the East China Sea [ Tomizawa et al ., ], and are generally believed to be caused by thermobaric effects [ Wakata , ]. We considered the impact of SA during tidal simulations, but did not include it during the harmonic analyses of the ADCP data because the removal of SA might erase the normal seasonal variations of the Kuroshio volume transport.…”
Section: Tidal Harmonic Analysismentioning
confidence: 98%
“…The spectrum does not have a well-defined peak in this range which indicates that this is not a periodic component but is dominated by random noise. This finding conflicts with Tomizawa et al [1984] who found, by band-pass filtering, that the signal with periods between about 2-10 mths was made up of a periodic and fairly regular 138 d component plus a random component (the numbers are our conversions: they stated that this band was monthly to annual but their data were monthly means and they had a separate band for the annual variation). They attributed the 138 d component to meteorological events and variability of the Kuroshio, but did not present a supporting argument.…”
Section: The Annual Cycle and Biennial Fluctuationsmentioning
confidence: 60%
“…7) shows some irregular variations of about 2-4 yr period but from these data it is not possible to say anything about their cause. Oscillations of this period have been observed by Minobe et al [2004] and references cited therein and attributed to wind pattern anomalies over the North Pacific, while Tomizawa et al [1984] found no regular inter-annual oscillations in records from a wider spread of stations over 1950-1980.…”
Section: Drift Over the 11 Yearsmentioning
confidence: 73%
“…We used in this study monthly MSL data collected by the Korean Hydrologic Agency, monthly mean atmospheric surface pressure (MBP) data collected by the Korea Meteorological Agency, and hydrographic data collected roughly bimonthly by the National Fishery Research and Development Agency of Korea for the 14 year period 1979 – 1992. The monthly mean adjusted sea level (ASL) is computed as the sum of MSL and cMBP, where the conversion factor c = 1 cm mbar –1 minus any linear trend in the sum over the 14 year period as determined by the method of least squares [ Tomizawa et al , 1984].…”
Section: Methodsmentioning
confidence: 99%
“…Mean seasonal variation η s ( j ) and anomaly η ano ( i , j ) are obtained by the following calculations: where i and j are yearly and monthly indices. Following Tomizawa et al [1984], the anomaly η ano ( i , j ) is further divided into an interannual variation and short‐term fluctuation. The interannual variation η 13 ( i , j ) is calculated using a 13 month moving average, which eliminates variations with periods <1 year.…”
Section: Methodsmentioning
confidence: 99%