Global statistical space‐time scales of oceanic variability estimated from the TOPEX/POSEIDON altimeter data

Kuragano, Tsurane; Kamachi, Masafumi

doi:10.1029/1999jc900247

Cited by 107 publications

(69 citation statements)

References 18 publications

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“…[48] Using the time-space optimum interpolation technique [Kuragano and Kamachi, 2000], we created data at 7-day intervals on 1/4°grids from the raw data: satellite SSHAh, satellite SST T 1 0 , and in situ temperature/salinity profiles,…”

Section: Appendix A: Time-space Optimum Interpolationmentioning

confidence: 99%

The Kuroshio large meander formation in 2004 analyzed by an eddy‐resolving ocean forecast system

et al. 2008

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The recent formation of the Kuroshio large meander southeast of the Kii Peninsula during the period from May to July 2004 has been simulated successfully in an eddy‐resolving ocean forecast system (Japanese Coastal Ocean Predictability Experiment). The formation process was examined from the viewpoint of eddy‐Kuroshio interactions using sensitivity experiments that had various initial conditions for eddies in March and May 2004. We confirmed that the large meander does not occur when the trigger meander southeast of the Kyushu Island has small amplitude and that the cyclonic eddy on the offshore side of the Kuroshio contributes to the large meander formation. Our results show that the large amplitude of the trigger meander southeast of Kyushu Island in April 2004 was caused by downstream advection of anticyclonic eddies along the Kuroshio in the East China Sea from east of Taiwan. The results suggest that the successive westward propagation of strong anticyclonic eddies in the subtropical frontal region from 2003 to 2004 was the origin of the formation of the Kuroshio large meander south of Japan in summer 2004.

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Section: Appendix A: Time-space Optimum Interpolationmentioning

confidence: 99%

The Kuroshio large meander formation in 2004 analyzed by an eddy‐resolving ocean forecast system

et al. 2008

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“…This suggests that the vertical motions, i.e., divergence and convergence, are responsible for the changes in the vertical profile of temperature and salinity below the depth of the winter-mixed layer. Such a vertical motion is likely associated with the passage of cyclonic and anticyclonic eddies that are often observed in 20-30°N latitudinal bands [Kuragano and Kamachi, 2000].…”

Section: Seasonal Changes In Hydrography and Concentration Of Tocmentioning

confidence: 94%

Concentration and UV reactivity of total organic carbon in the upper layer in the oligotrophic subtropical western North Pacific

Sangkyun¹,

Hama²,

Ishii³

et al. 2010

J. Geophys. Res.

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[1] Characteristics of temporal variation in the vertical profile of total organic carbon (TOC) were investigated in the upper layer of the ocean at various latitudes (10-30°N) of 137°E in the western North Pacific subtropical gyre. Bulk TOC was divided into labile and stable fractions by the specific UV irradiation to evaluate their contributions to the temporal fluctuation of TOC. Authentic specimens and dissolved organic carbon collected from coastal waters were used to examine the correspondence between the photochemical reactivity to the specific UV irradiation and biological reactivity. The concentration of TOC in the upper layer was higher in summer when the surface layer is well stratified and was lower in winter when the mixed layer deepened. Although the winter mixed layer is shallower in lower latitudes, the amplitude of the seasonal variations in the top 50 m weighted mean TOC concentration (19.5-27.7 mM) did not vary considerably over the subtropical zones we studied. A major fraction (51.9-89.8%) of TOC was stable against specific UV irradiation and was thought to be mainly composed of biologically stable organic compounds, but the seasonal variation of TOC at each latitude was mainly attributable to the variation of UV labile fraction. This finding suggests that the seasonal variation of TOC in the upper layer is explained by the biological production of TOC in summer surface water and its vertical mixing with low UV, labile TOC in winter. Upward advection of subsurface water due to the passage of cyclonic eddies and changes in the geostrophic current are also likely to affect the temporal TOC variation, in particular, in the lower latitudes where winter mixed layer and permanent thermocline are shallower.

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“…The functional form of the autocorrelation depends on the physical properties, the considered scales (e.g., synoptic versus mesoscale) and the area. Many studies have estimated autocorrelation functions through analysis of in situ ocean measurements (e.g., Meyers et al, 1991;Chu et al, 2002;Delcroix et al, 2005) and satellite observations (e.g., Kuragano and Kamachi, 2000;Hosoda and Kawamura, 2004;Tzorti et al, 2016). Generally, the estimated autocorrelation functions have exponential or Gaussian form (Molinari and Festa, 2000).…”

Section: Introductionmentioning

confidence: 99%

Decorrelation scales for Arctic Ocean hydrography – Part I: Amerasian Basin

et al. 2018

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Abstract. Any use of observational data for data assimilation requires adequate information of their representativeness in space and time. This is particularly important for sparse, non-synoptic data, which comprise the bulk of oceanic in situ observations in the Arctic. To quantify spatial and temporal scales of temperature and salinity variations, we estimate the autocorrelation function and associated decorrelation scales for the Amerasian Basin of the Arctic Ocean. For this purpose, we compile historical measurements from 1980 to 2015. Assuming spatial and temporal homogeneity of the decorrelation scale in the basin interior (abyssal plain area), we calculate autocorrelations as a function of spatial distance and temporal lag. The examination of the functional form of autocorrelation in each depth range reveals that the autocorrelation is well described by a Gaussian function in space and time. We derive decorrelation scales of 150-200 km in space and 100-300 days in time. These scales are directly applicable to quantify the representation error, which is essential for use of ocean in situ measurements in data assimilation. We also describe how the estimated autocorrelation function and decorrelation scale should be applied for cost function calculation in a data assimilation system.

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Global statistical space‐time scales of oceanic variability estimated from the TOPEX/POSEIDON altimeter data

Cited by 107 publications

References 18 publications

The Kuroshio large meander formation in 2004 analyzed by an eddy‐resolving ocean forecast system

The Kuroshio large meander formation in 2004 analyzed by an eddy‐resolving ocean forecast system

Concentration and UV reactivity of total organic carbon in the upper layer in the oligotrophic subtropical western North Pacific

Decorrelation scales for Arctic Ocean hydrography – Part I: Amerasian Basin

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