Geomagnetic secular acceleration

Summary. A spherical harmonic model of the second time-derivative of the geomagnetic field is determined, for the first time, directly from measures of the secular acceleration based on observatory annual mean data. The data span the interval 1964.5–1975.5, and 165 observatories are included. The model comprises the 32 coefficients of degree and order up to 6 that are significant at the 5 per cent level. Its primary purpose is to aid in the reduction of data to epoch for the 1980 series of navigational charts. The model is compared with earlier estimates of secular acceleration, derived by less direct methods.     

Chemical composition of glacial meltwaters and river waters within the Aktru river basin (Gornyi Altai)

An assessment was made of the mean levels of major and trace elements and of biogenic and organic matter in glacial and river waters within the Aktru river basin (Gornyi Altai, Russia). The analysis showed a general tendency for an increase in mineralization along the direction from the region of alimentation of glaciers to the mouth of the river. A relatively abrupt increase was revealed in Al, Zn, Cu, Pb, Si, NO₂ ^? and NH₄ ⁺ concentrations in the source of the Aktru river and its glacial tributaries, with their subsequent decrease downstream. The mechanism for such changes is governed by the conditions of interaction of rocks with meltwaters and river waters.     

Stochastic model-based methods for handling uncertainty in areal interpolation

Handling of uncertainty in the estimation of values from source areas to target areas poses a challenge in areal interpolation research. Stochastic model-based methods offer a basis for incorporating such uncertainty, but to date they have not been widely adopted by the GIS community. In this article, we propose one use of such methods based in the problem of interpolating count data from a source set of zones (parishes) to a more widely used target zone geography (postcode sectors). The model developed also uses ancillary statistical count data for a third set of areas nested within both source and target zones. The interpolation procedure was implemented within a Bayesian statistical framework using Markov chain Monte Carlo methods, enabling us to take account of all sources of uncertainty included in the model. Distributions of estimated values at the target zone level are presented using both summary statistics and as individual realisations selected to illustrate the degree of uncertainty in the interpolation results. We aim to describe the use of such stochastic approaches in an accessible way and to highlight the need for quantifying estimation uncertainty arising in areal interpolation, especially given the implications arising when interpolated values are used in subsequent analyses of relationships.