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2003: Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late Nineteenth Century
 J. Geophysical Research
"... data set, HadISST1, and the nighttime marine air temperature (NMAT) data set, HadMAT1. HadISST1 replaces the global sea ice and sea surface temperature (GISST) data sets and is a unique combination of monthly globally complete fields of SST and sea ice concentration on a 1 ° latitudelongitude grid ..."
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data set, HadISST1, and the nighttime marine air temperature (NMAT) data set, HadMAT1. HadISST1 replaces the global sea ice and sea surface temperature (GISST) data sets and is a unique combination of monthly globally complete fields of SST and sea ice concentration on a 1 ° latitudelongitude grid from 1871. The companion HadMAT1 runs monthly from 1856 on a 5 ° latitudelongitude grid and incorporates new corrections for the effect on NMAT of increasing deck (and hence measurement) heights. HadISST1 and HadMAT1 temperatures are reconstructed using a twostage reducedspace optimal interpolation procedure, followed by superposition of qualityimproved gridded observations onto the reconstructions to restore local detail. The sea ice fields are made more homogeneous by compensating satellite microwavebased sea ice concentrations for the impact of surface melt effects on retrievals in the Arctic and for algorithm deficiencies in the Antarctic and by making the historical in situ concentrations consistent with the satellite data. SSTs near sea ice are estimated using statistical relationships between SST and sea ice concentration. HadISST1 compares well with other published analyses, capturing trends in global, hemispheric, and regional SST well,
Version 2.0Software Support for Metrology Best Practice Guide No. 4 Discrete Modelling and Experimental Data Analysis
, 2004
"... Metrology, the science of measurement, involves the determination from experiment of estimates of the values of physical quantities, along with the associated uncertainties. In this endeavour, a mathematical model of the measurement system is required in order to extract information from the experim ..."
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Metrology, the science of measurement, involves the determination from experiment of estimates of the values of physical quantities, along with the associated uncertainties. In this endeavour, a mathematical model of the measurement system is required in order to extract information from the experimental data. Modelling involves model building: developing a mathematical model of the measurement system in terms of equations involving parameters that describe all the relevant aspects of the system, and model solving: determining estimates of the model parameters from the measured data by solving the equations constructed as part of the model. This bestpractice guide covers all the main stages in experimental data analysis: construction of candidate models, model parameterisation, uncertainty structure in the data, uncertainty of measurements, choice of parameter estimation algorithms and their implementation in software, with the concepts illustrated by case studies. The Guide looks at validation techniques for the main components of discrete modelling: building the functional and statistical model, model solving and parameter estimation methods, goodness of fit of model solutions and experimental design and measurement strategy. The techniques are illustrated in detailed case studies.
nag 1d cheb eval (e02aec) evaluates a polynomial from its Chebyshevseries representation. 2. Specification #include <nag.h> #include <nage02.h>
"... This routine evaluates the polynomial ..."
2. Specification #include <nag.h> #include <nage02.h>
"... nag 1d spline evaluate (e02bbc) evaluates a cubic spline from its Bspline representation. ..."
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nag 1d spline evaluate (e02bbc) evaluates a cubic spline from its Bspline representation.
1. Purpose nag 1d cheb eval (e02aec) evaluates a polynomial from its Chebyshevseries representation. 2. Specification #include <nag.h> #include <nage02.h>
"... This routine evaluates the polynomial ..."
1. Purpose nag 1d spline evaluate (e02bbc) evaluates a cubic spline from its Bspline representation. 2. Specification #include <nag.h> #include <nage02.h>
"... This function evaluates the cubic spline s(x) at a prescribed argument x from its augmented knot set λi, for i = 1, 2,..., n̄+7, (see nag 1d spline fit knots (e02bac)) and from the coefficients ci, for i = 1, 2,..., q in its Bspline representation s(x) = q∑ i=1 ciNi(x) Here q = n ̄ +3, where n ̄ is ..."
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This function evaluates the cubic spline s(x) at a prescribed argument x from its augmented knot set λi, for i = 1, 2,..., n̄+7, (see nag 1d spline fit knots (e02bac)) and from the coefficients ci, for i = 1, 2,..., q in its Bspline representation s(x) = q∑ i=1 ciNi(x) Here q = n ̄ +3, where n ̄ is the number of intervals of the spline, and Ni(x) denotes the normalised Bspline of degree 3 defined upon the knots λi, λi+1,..., λi+4. The prescribed argument x must satisfy λ4 ≤ x ≤ λn̄+4. It is assumed that λj ≥ λj−1, for j = 2, 3,..., n ̄ + 7, and λn̄+4> λ4. The method employed is that of evaluation by taking convex combinations due to de Boor (1972). For further details of the algorithm and its use see Cox (1972) and Cox (1978). It is expected that a common use of nag 1d spline evaluate (e02bbc) will be the evaluation of the cubic spline approximations produced by nag 1d spline fit knots (e02bac). A generalization of nag 1d spline evaluate which also forms the derivative of s(x) is nag 1d spline deriv (e02bcc). nag 1d spline deriv (e02bcc) takes about 50 % longer than nag 1d spline evaluate.