A New Method of Interpolation and Smooth Curve Fitting Based on Local Procedures

Akima, Hiroshi

doi:10.1145/321607.321609

Cited by 1,767 publications

(878 citation statements)

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“…Potential temperature, salinity, pressure and oxygen data were then interpolated with semi-Hermite splines [Akima, 1970] Fig. 3a) and temperature increases on the surfaces (Fig.…”

mentioning

confidence: 99%

Warming and circulation change in the eastern South Pacific Ocean

Schaffer

Leth

Ulloa

et al. 2000

Geophysical Research Letters

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“…Potential temperature, salinity, pressure and oxygen data were then interpolated with semi-Hermite splines [Akima, 1970] Fig. 3a) and temperature increases on the surfaces (Fig.…”

mentioning

confidence: 99%

Warming and circulation change in the eastern South Pacific Ocean

Schaffer

Leth

Ulloa

et al. 2000

Geophysical Research Letters

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“…The first set of data was originally used by Akima (1970) and is shown in Table 1. The second set of data is shown in Application of the piecewise rational quadratic interpolation scheme to each of these data sets requires some method for choosing the derivative parameters d i ; i = l, .…”

Section: Numerical Results and Discussionmentioning

confidence: 99%

Piecewise Rational Quadratic Interpolation to Monotonic Data

Gregory¹,

Delbourgo²

1982

IMA J Numer Anal

145

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“…The interpolation to the two target isopycnals 26.8 kg m À3 and 27.2 kg m À3 is done by constructing at each grid point high vertical resolution (Dz = 1 m) profiles of all tracers using an Akima spline [Akima, 1970] and subsequently interpolating to density. This procedure minimizes interpolation errors that occur as a result of the nonlinearity of the equation of state.…”

Section: Linear Regression Methods Without Predefinedmentioning

confidence: 99%

Model‐based evaluation of methods to determine C:N and N:P regeneration ratios from dissolved nutrients

Schneider¹,

Karstensen²,

Oschlies³

et al. 2005

Global Biogeochemical Cycles

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[1] Four indirect methods to determine carbon and nutrient regeneration ratios in the ocean are applied to results from a physical-biogeochemical model with prescribed element ratios for organic matter (de-)composition. The aim is to test whether these methods are suitable to reproduce C org :N:P element ratios of organic matter remineralization, which in contrast to the real ocean are exactly known in the model framework. The model experiment is carried out using the classical C:N:P Redfield ratio of 106:16:1 for production and decomposition of organic material under preindustrial atmospheric pCO 2 . Two methods rely on predefined end member values, while the others do not. The first method is a simple linear regression of two parameters, neglecting mixing effects, and yields remineralization signals biased by isopycnal tracer gradients induced by contributions of different water masses. The second method is based on multiple linear regression of three parameters, includes mixing of three, but notprescribed end members. It can, in part, reproduce the prescribed remineralization ratios. However, considerable bias appears as a result of water mass mixing. The third method considers isopycnal mixing of three prescribed end member water masses by using temperature/salinity as conservative tracers on the two density surfaces s Q = 26.8 and s Q = 27.2. On the basis of a mixing triangle approach, the method is able to reproduce the regeneration rates best in the low latitudes, where the integrated signal of remineralization is high. The fourth method uses the full set of available parameters to derive mixing fractions and remineralization and is applied to the density range from s Q = 26.8 to s Q = 27.2, yielding the best reproduction of prescribed remineralization ratios. As expected, results from the last two methods are sensitive to the choice of end member concentrations. In general, best agreement between modeled and reconstructed ratios is found between 20°N and 20°S and deviations occur toward the outcrop regions, which we account to the low amount of remineralized material together with uncertainties in prescribed end member values. Our investigation shows how apparent variability of remineralization ratios can be generated through methodological shortcomings only.Citation: Schneider, B., J. Karstensen, A. Oschlies, and R. Schlitzer (2005), Model-based evaluation of methods to determine C:N and N:P regeneration ratios from dissolved nutrients, Global Biogeochem. Cycles, 19, GB2009,

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A New Method of Interpolation and Smooth Curve Fitting Based on Local Procedures

Cited by 1,767 publications

References 1 publication

Warming and circulation change in the eastern South Pacific Ocean

Warming and circulation change in the eastern South Pacific Ocean

Piecewise Rational Quadratic Interpolation to Monotonic Data

Model‐based evaluation of methods to determine C:N and N:P regeneration ratios from dissolved nutrients

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