The regional diversity of monthly temperature was analyzed based on long-term data obtained for South Dakota (SD) from the High Plains Regional Climate Center. Multidimensional statistical methods were used and the principal results presented as a sequence of 2- and 3-dimensional scatterplot pictures depicting the quantitative results. 
System hierarchical model of landscape was used for research tasks formulation. Initial matrixes for three research tasks were compiled for the state. The first set of initial matrices of time series {Xt*n}, where t = number of years and n = number of meteorological stations, contains two matrixes: X1(67*29) and X2(33*94). The second set -{Xt*m}, where t = number of years and m = number of months in a year: X3(113*12), X4(110*12), and X5(102*12). The third set - {Xn*m}, where n = number of meteorological stations and m = number of months in a year, contains two matrixes: X6(29*12) and X7(94*12). 
Statistical analysis allowed us to differentiate weather stations by temporal trends and spatial distribution for the time interval 1932-1998. The most variable stations (Brookings, Camp Crook, and Highmore) were determined; their seasonality was described (the most variable months and correlation among months during the year) and their seasonal regime determined. The average annual and monthly temperature distributions were presented for South Dakota based on 29 and 94 stations for the time intervals 1932-1998 and 1963-1995.

