Sentences with phrase «spatial mean of the data»

We refer to an interpolated data set (Schäfer - Neth and Paul 2003) from which we use the variance V = (1.41 °C) 2 as the starting point to estimate an uncertainty range for the spatial mean of the data field.

Not exact matches

However, the Hadley Centre SST data set60, 61 (HadSST3, v3.1.1.0) is not global in coverage: rather than interpolating over all space and time coordinates it consists of spatial means within 5 ° × 5 ° bins, leading to missing values in the absence of data.

Several previous analyses of tide gauge records1, 2,3,4,5,6 — employing different methods to accommodate the spatial sparsity and temporal incompleteness of the data and to constrain the geometry of long - term sea - level change — have concluded that GMSL rose over the twentieth century at a mean rate of 1.6 to 1.9 millimetres per year.

The attribution study was based on series of 5 - yr - mean temperatures and spatial averages of 90 degree sectors (i.e. to four different sectors), where sectors and periods with no valid data were excluded.

The flux estimates presented in previous sections use available estimates from every reservoir where GHG emissions have been reported (and mean estimates from reservoirs where multiple studies or years of data have been collected), but it is important to note that the spatial and temporal coverage of these emission estimates are highly variable.

Analyses of tide gauge and altimetry data by Vinogradov and Ponte (2011), which indicated the presence of considerably small spatial scale variability in annual mean sea level over many coastal regions, are an important factor for understanding the uncertainties in regional sea - level simulations and projections at sub-decadal time scales in coarse - resolution climate models that are also discussed in Chapter 13.

These range from simple averaging of regional data and scaling of the resulting series so that its mean and standard deviation match those of the observed record over some period of overlap (Jones et al., 1998; Crowley and Lowery, 2000), to complex climate field reconstruction, where large - scale modes of spatial climate variability are linked to patterns of variability in the proxy network via a multivariate transfer function that explicitly provides estimates of the spatio - temporal changes in past temperatures, and from which large - scale average temperature changes are derived by averaging the climate estimates across the required region (Mann et al., 1998; Rutherford et al., 2003, 2005).

However, relatively few studies have investigated whether there are differences in brain structure between these subgroups.We acquired diffusion tensor imaging data and used tract - based spatial statistics (TBSS) to compare adolescents with CD and high levels of CU traits (CD / CU +; n = 18, CD and low levels of CU traits (CD / CU -; n = 17) and healthy controls (HC; n = 32) on measures of fractional anisotropy (FA), axial (AD), radial (RD) and mean (MD) diffusivity.