  The correlation dimension and limit capacity serve theoretically as lower and
upper bounds, respectively, of the fractal dimension of attractors of dynamic
systems. In this paper, we show that estimates of the correlation dimension
grow rapidly with increasing noise level in the time-series, while estimates of
the limit capacity remain relatively unaffected. It is therefore proposed that
the limit capacity be used in studies of noisy data, despite its heavier
computational requirements. An analysis of Singapore wind data with the limit
capacity estimate revealed a surprisingly low dimension (~2.5). It is suggested
that further studies be made with comprehensive equatorial weather data.
