| description abstract | Satellite estimates and weather forecast models have made it possible to observe and predict precipitation over large spatial scales. Despite substantial progress in observing patterns of precipitation, characterization of spatial patterns is still a challenge. Quantitative assessment methods for spatial patterns are essential for future developments in prediction of the spatial extent and patterns of precipitation. In this study, precipitation patterns are characterized using three geometrical indices: (i) a connectivity index, (ii) a shape index, and (iii) a dispersiveness index. Using multiple examples, the application of the proposed indices is explored in pattern analysis of satellite precipitation images and validation of numerical atmospheric models with respect to geometrical properties. The results indicate that the presented indices can be reasonably employed for a relative comparison of different patterns (e.g., multiple fields against spatial observations) with respect to their connectivity, organization, and shape. | |
