Fifteen-minute precipitation data from 173 stations covering a nine-state region of the southeastern United States is analyzed to produce a monthly and seasonal rainfall rate climatology of the region for the period 1971-1995. As measures of the rainfall rate, both the monthly rainfall intensity as measured by the fraction of rainfall occurring in heavy showers and the averaged monthly maximum fifteen-minute rainfall rate are used. In constrast to the results for the northeastern United States done previously, the southeastern region has much higher values of the rainfall intensity during the non-summer months and shows a much smaller variation between coastal and inland areas and much smaller month-to-month changes. Both rainfall intensity and maximum rate generally increase and decrease with the annual temperature cycle but significant monthly anomalies of the maximum rate occur in March (values higher than in April) and November (values higher than in October), particularly in Mississippi, Alabama and Georgia. Both the dominant hour and the purity of the diurnal distributions of heavy showers are much more uniform than in the northeastern region. Except for Florida, the purity is strong only during the summer season, and is strongest in the flat plains between the coast and the higher inland areas.
The effect of the El Niņo-Southern Oscillation phenomenon on total precipitation, rainfall intensity and maximum rate are also determined. Changes in total precipitation (El Niņo minus La Niņa months) are: positive near the coast and in Florida and negative inland during the winter season; generally positive but decreasing toward the south during the spring; and generally negative but more scattered during the summer and fall. Significant differences in rainfall intensity and maximum rate occur only during the winter season and are generally negative with magnitudes decreasing toward the coast and values becoming positive toward the east and toward southern Florida.
Plausible physical origins of the results as well as their applications to long-range weather forecasting are discussed