Abstract
Abstract The major topic of this paper is the resolvable spatial scales that can be analyzed by statistical interpolation of an undersampled dataset. The inquiry was motivated by the need to design the most appropriate procedures for spatial analysis of the upper-air sounding data from the GARP Atlantic Tropical Experiment. A reliable representation of horizontal scales in the analyzed wind fields was a matter of utmost concern, since the derived fields of vorticity, divergence and vertical motion were also of vital interest. To achieve our goal, it was found that the traditional promise of statistical interpolation had to be reexamined. The main conclusions of this theoretical inquiry are (i) resolvable scales are determined by the geometrical distribution of observing stations; (ii) precise knowledge of the second-moment statistics improves the analysis by de-aliasing the amplitudes of resolvable scales, but has no effect on the definition of resolvable scales; (iii) residual effects of unresolvable sig...
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