We also constructed random populations from WOA18 to determine how variability in sitespecific trends affected their median values. First, we randomly selected a potential monthly nutricline depth for each geographic coordinate with nutricline depths observed for two or more years in the GO-SHIP collection. We then paired these to another random, potential monthly nutricline depth to simulate a 50-year trend for each geographical coordinate. We repeated this procedure until 10,000 random populations of the conglomerate data set were made. Second, we performed a similar procedure where we paired one set of monthly values to another set, but here we imposed a ubiquitous site-specific trend by changing the second set of monthly values by a rate equivalent to the median trend from observations. These two analyses determined if the median trend was controlled by monthly variability in sampling. Third, we imposed a variable site-specific trend by changing each monthly value in the second set by a rate of change randomly selected from a normal distribution of rates. We altered the mean and standard deviation of this normal distribution until the median trend and the variance of simulated nutricline depths (i.e., IQR) both matched the observations. This analysis determined if the median trend actually captured an underlying tendency of the site-specific trends despite their high variability. In summary, these analyses with WOA18 determined if variability in the site-specific trends had considerable influence on their median values.