Of late, significant changes in climate with their grave consequences have posed great challenges on humankind. Thus, the detection and assessment of climatic changes on a regional scale is gaining importance, since it helps to adopt adequate mitigation and adaptation measures. In this paper, we have presented a novel approach for detecting spatio-temporal pattern of regional climate change by exploiting the theory of <i>mathematical morphology</i>. At first, the various climatic zones in the region have been identified by using <i>multifractal cross-correlation analysis</i> (MF-DXA) of different climate variables of interest. Then, the <i>directional granulometry</i> with four different structuring elements has been studied to detect the temporal changes in spatial distribution of the identified climatic zones in the region and further insights have been drawn with respect to <i>morphological uncertainty index</i> and <i>Hurst exponent</i>. The approach has been evaluated with the daily time series data of <i>land surface temperature</i> (LST) and <i>precipitation rate</i>, collected from <i>Microsoft Research - Fetch Climate Explorer</i>, to analyze the spatio-temporal climatic pattern-change in the <i>Eastern</i> and <i>North-Eastern</i> regions of <i>India</i> throughout four quarters of the 20th century.