Tropical rainfall exhibits considerable heterogeneity in the scales smaller than mesoscale. It is important to be able to model rainfall at this scale with a great deal of accuracy. The meteorological models available today, are however, limited in their accuracy at these scales.
In order to understand the stochastic characteristics of rainfall at the sub-grid scales, many scaling methods have been developed. However, none have been applied to tropical rainfall. This study approaches the above problem using wavelets, to dis-aggregate tropical radar rainfall data to study the sub-grid scale behavior.
Dis-aggregation of available rainfall data into small scales and statistical reconstruction of the small-scale features (variations), is carried out using wavelets, assuming certain types of scalability. This study is undertaken at the Environmental Verification and Analysis Center (EVAC), at the University of Oklahoma. Initial analysis and modeling is performed using the Kwajalein radar data and TOGA COARE data sets.