A new OT detection approach over East Asia and its validation using EarthCARE data

Overshooting tops (OTs) are key indicators of severe weather events associated with deep convection, and geostationary satellite observations play a critical role in monitoring OTs with high spatiotemporal resolution. The infrared window texture (IRW-texture) algorithm (Bedka et al., 2010) identifies OTs as localized cold spots relative to the surrounding anvil. This approach overcomes the limitations of traditional brightness temperature difference methods, which tend to overestimate anvil regions as OTs. However, the IRW-texture algorithm involves uncertainties due to its reliance on model-based tropopause information and fixed detection thresholds. To address these limitations, this study proposes a regionally adapted OT detection algorithm for East Asia by incorporating satellite-derived tropopause information from the GK-2A/AMI atmospheric profile product and optimizing key detection thresholds for the target region. The improved algorithm was validated using the Cloud Profiling Radar (CPR) onboard the EarthCARE satellite. The CPR provides enhanced sensitivity and Doppler velocity measurements compared to previous spaceborne radars, enabling precise characterization of the vertical structure of overshooting convection. Taking advantage of these capabilities, we conducted a detailed physical validation of the detected OTs. The results show that the OTs detected by the algorithm align closely with the vertical updrafts captured by the CPR, validating its reliability in identifying active overshooting convection. Although constrained by a limited number of cases, this pioneering validation using EarthCARE observations demonstrates the importance of physically consistent, region-specific adaptations. These results suggest a promising pathway for enhancing next-generation global convection monitoring capabilities.