Optimizing the Global Observational Network: A Dynamical Approach

Abstract

The global observational network is known to be highly inhomogeneous and fractally distributed in space. In this paper the spatial distribution of stations in a network is studied in connection with the type of dynamics exhibited by the atmospheric fields. The existence of an optimal distribution capable of capturing the complexity of this dynamics with a small prescribed error, and the role of deviations of the network distribution from a homogeneous one in this observational error are explored. For sparsely distributed stations like those of the present-day network, it is found that inhomogeneous distributions may generate a record that is closer to reality than homogeneous ones.