Abstract Background The purpose of this study was to examine a possible association between standard meteorological variables and their changes and the occurrence and clinical features of SAH. Methods Univariate association between the clinical/radiographic variables of patients with SAH and standard meteorological variables was evaluated. Next, a multivariate analysis was performed to find independent meteorological predictors for the occurrence of SAH by using a binary logistic regression analysis. Results Univariate analysis showed significant differences between bleeding days and non-bleeding days for the number of change days (maximal atmospheric difference of the day >10 hPa) ( P < .001); for the maximal relative humidity ( P < .05); for the maximal difference of vapor pressure of the day 24 hours before the bleeding day ( P < .006) and between cluster days and noncluster days for the number of change days ( P < .001); for the maximal difference of temperature of the day ( P < .035); and for the maximal, minimal, and mean relative humidity ( P < .027, P < .018, and P < .03, respectively). In the multivariate models, the variable “change day” (OR, 3.7; 95% CI, 1.2-11.3) and direction of the atmospheric pressure difference of the day (OR, 2.6; 95% CI, 1.8-7.8) were retained as independent predictors for the occurrence of SAH. For the variable cluster day as dependent variable, only change day was maintained in the model (OR, 6.9; 95% CI, 4.7-10.8). Conclusions Atmospheric pressure changes of more than 10 hPa within 24 hours are an independent predictor of clustering of patients with SAH. Hypertension is an independent risk factor for the occurrence of SAH at change day.