Abstract
Surface meteorological reports of wind components, wind speed, air temperature, and sea surface temperature from buoys located in equatorial and midlatitude regions are used in a simulation of random sampling to determine errors of the calculated means due to inadequate sampling. Subsampling the data with several different sample sizes leads to estimates of the accuracy of the subsampled means. The number N of random observations needed to compute mean winds with chosen accuracies of 0.5 (N0.5) and 1.0(N1.0) m s−1 and mean air and sea surface temperatures with chosen accuracies of 0.1 (N0.1) and 0.2(N0.2)°C were calculated for each 5-day and 30-day period in the buoy datasets. Mean values of N for the various accuracies and datasets are given.
A second-order polynomial relation is established between N and the variability of the data record. This relationship demonstrates that for the same accuracy, N increases as the variability of the data record increases. The relationship is also independent of the data source. Volunteer observing ship data do not satisfy the recommended minimum number of observations for obtaining 0.5 m s−1 and 0.2°C accuracy for most locations. The effect of having remotely sensed data is discussed.
