Assessment of object-based indices to identify convective organization

Abstract. The emerging field of convective organization has attracted significant attention due to its potential implications for weather and climate. Numerous indices have been developed to identify organization of convection, serving as essential tools for advancing our understanding in this area. Because of the large number of convective indices, many results on organization are still uncertain and different studies have shown diverging results. The present analysis studies and compares nine object-based indices in order to evaluate their ability to quantify organization. The analysis begins by establishing a set of criteria expected for convective organization and subsequently subjecting the indices to assessment against these benchmarks. The criteria are organized into three categories. The first category tests the robustness of the indices against noise. The second category evaluates their sensitivity to the size and position of the convective objects. The third category assesses their dependency on the specific characteristics of the dataset in use. Among the indices scrutinized, none fulfill all the desired conditions, and some conditions are only marginally satisfied. Therefore, we developed a new index, called Organization Index based on Distance and Relative Area (OIDRA), as an example of a well-behaving index. The unmet conditions and differences between indices can explain the discord between different organization studies. The results come down to a guideline that will help to advance our description of deep convective organization.