Surface refractivity gradient data for radio system design

Abstract

Reliable information about the cumulative distribution of surface refractivity gradient is often required in the design of radio systems. Strong negative gradients, or super-refraction, may lead to interference between terrestrial stations, both terrestrial links and satellite earth stations. Predicted positive or sub-refractive gradients are taken into account in determining the minimum antenna heights, to ensure terrestrial links achieve their required availability. This paper reviews sources of refractivity gradient data, and considers how refractivity gradient at a point may relate to an effective value over a terrestrial path.

How real are observed trends in small correlated datasets?

“…The most significant predictor of fade depth A0.01% was found [27] to be a composite parameter v 1 , in terms of path length D (km), mean rayline height at standard refractivity gradient H 8500 , and N sA90−10 , the interdecile range of the time-series of surface refractivity anomaly N sA [24]: v1=(NsA90−100.3)(D0.5)H85000.25.…”

“…Ideally, we may imagine this problem being solved by numerical weather prediction (NWP) estimating the state of the lower atmosphere with sufficient resolution, of the order of 1 m vertically, and accuracy, to predict the radio propagation with a technique such as the parabolic equation model [23]. However NWP models do not yet have sufficient resolution, or accuracy in many locations [24], so empirical regression models are used. The current accepted prediction model [25] is an OLS estimate from a number of climatic and physical parameters [26].…”