| Advances in satellite technology have led to the development of many remote-sensing algorithms to estimate precipitation at quasi-global scales. A number of satellite precipitation products are provided at high spatial and temporal resolutions that are suitable for short-term hydrologic applications. Several coordinated validation activities have been established to evaluate the accuracy of satellite precipitation. Traditional verification measures summarize pixel-to-pixel differences between observation and estimates. Object-based verification methods, however, extend pixel based validation to address errors related to spatial patterns and storm structure, such as the shape, volume, and distribution of precipitation rain-objects.;In this study, an image processing approach known as watershed transformation, being capable of detect the local/individual storm systems, is adopted in the object-based validation framework. After image segmentation, several key attributes of the segmented storm systems are selected and membership scores of those attributes are estimated based on the distance measurement of the estimated and reference images. An overall membership score is estimated from all the selected attributes and their membership values.;The proposed object-based validation framework was used to evaluate PERSIANN, PERSIANN-CCS, CMORPH, 3B42RT against NOAA stage IV MPE multi-sensor composite rain analysis. All estimates are evaluated at 0.25° by 0.25° on a daily-scale in the summer of 2008 and winter of 2010 over the contiguous United States (CONUS). The results show that CMORPH outperforms the other three satellite products in both seasons. Different satellite products present different characteristics of precipitation. For example, the sizes of storm objects acquired from PERSIANN-CCS are smaller, while storm objects obtained from PERSIANN typically cover larger area. Furthermore, the satellite-based precipitation products perform differently in different seasons, and the seasonal variability can be captured by the framework for each product. It is concluded that the discrepancies between various satellite precipitation estimates can be identified through the proposed verification framework. |
