The distribution of rain rates (R) is of great concern for many fields. In particular, for hydrological applications such as flood forecasting, which depends on an accurate representation of the excess rainfall--driven by the rain rate--that does not infiltrate to the soil. Better estimation of the spatial probability distribution function (PDF) of R is also crucial for better evaluation of rainfall products from ground and space-based radars. For example, the evaluation of TRMM Ground Validation (GV) products, in particular, the instantaneous ground-based radar rainfall products, are based on comparing PDFs of R derived from the radar estimates above the gauges to those derived from the gauges themselves. Understanding the PDFs of R will be even more important for space-based radars because of the even larger uncertainties due to the satellite sampling errors (e.g., TRMM and GPM). PDFs of R for comparison studies can be obtained by individual rain gauges. However, if rainfall itself varies significantly at scales smaller than that of a radar pixel, a single gauge cannot represent such variability well, and this distorts our evaluation of the radar performance. While better estimation of the true rainfall at the scale of a radar pixel might be obtained utilizing super dense gauge networks, high costs associated with building and maintaining these networks, make them rarely available.

The underwater sound generated by raindrops striking the ocean surface is a signal that allows detection, classification and quantification of rainfall. One of the advantages of the acoustic measurement is that the listening area, an effective catchment area, is defined by a radius that is roughly three times the depth of the acoustic rain gauges (ARGs), and can be orders of magnitude greater than other rain gauges. This feature allows a very high temporal resolution (1-5 sec) and spatial averaging coverage comparable to a radar sampling volume. Measurements based on ARGs deployed at different depths may assist at determining how to convert a point PDF into a spatial PDF and thus help to understand the uncertainties associated with the spatial PDFs from ground and space-based radars.

In this presentation the scale dependence of rain rate distribution is examined from space, ground and underwater observations. Comparisons of PDFs of R from the TRMM Precipitation Radar and collocated data from the GV radar in Florida, will be presented. A PDF analysis using gauge and ground-based radar data from the TRMM GV program in Florida will be used to demonstrate an optimal gauge adjustment technique for improving rain rate distribution estimates for ground-based radars. In addition, the unique field of rainfall measurements by underwater sound will be introduced to the radar community using a series of rain events in Miami, Florida. We will emphasize similarities to radar and the potential use for radar calibration and validation.