Alton comes to grip with industrial decline

Illinois ; Federal Reserve District, 8th ; Economic development

Tennessee town pins hopes on being transportation hub

Transportation ; Tennessee ; Federal Reserve District, 8th

Bucking the trend in manufacturing in Grenada, Miss.

Community ProfileManufactures - South ; Federal Reserve District, 8th ; Mississippi

Plentiful green space along interstate drives economy of tiny Missouri town

Federal Reserve District, 8th ; Employment ; Missouri

Town hangs on to old economy even as it embraces the new

Federal Reserve District, 8th ; Regional economics

MEME08: A global magnetic field model with satellite data weighting

A new data weighting scheme is introduced for satellite geomagnetic survey data. This scheme allows vector samples of the field to be used at all magnetic latitudes and results in an improved lithospheric model, particularly in the auroral regions. Data weights for 20-second spaced satellite samples are derived from two noise estimators for the sample. Firstly the standard deviation along the 20 seconds of satellite track, centred on each sample, is computed as a measure of local magnetic activity. Secondly a larger-scale noise estimator is defined in terms of a ‘local area vector activity’ (LAVA) index for the sample. This is derived from activity estimated from the geographically nearest magnetic observatories to the sample point. Weighting of satellite data by the inverse-sum-of-squares of these noise estimators leads to a robust model of the field (called ‘Model of Earth’s Magnetic Environment 2008, or ‘MEME08’ - to rhyme with ‘beam’) to about spherical harmonic degree 60. In particular we find that vector data may be used at all latitudes and that there is no need to use particularly complex model parameterizations, regularisation, or prior data correction to remove estimates of un-modelled source fields

Improving time-dependent parameters of magnetic field models

An important part of modelling the Earth's magnetic field is to accurately characterise its temporal variation, in particular the secular variation, and secular acceleration. These quantities are sensitive to the data selection and the time-dependent parameterisation and we present modifications to these strategies. When selecting satellite data for magnetic field modelling it is normal practice to use less disturbed data collected when the local time is between certain hours during the night and perhaps additionally when the data are not sunlit. However this approach results in gaps in the temporal data distribution which are likely to compromise the model parameters that depend on time. If the solar zenith angle is also a selection criterion, parameters which depend on location will also be compromised as an annual signal is introduced into the data distribution at high latitudes. Here we strive for a more continuous coverage in time. Rather than eliminating large amounts of data which are normally considered to be too noisy to include in the model, we downweight these data. This builds on work done previously involving small-scale noise