An objective identification technique for potential vorticity structures associated with African Easterly Waves

Abstract. Tropical Africa and the North Atlantic Ocean are significantly influenced by African Easterly Waves (AEWs), which play a fundamental role in tropical rainfall and cyclogenesis in that region. The dynamics of AEWs can be described in a PV framework and redistribution of PV by latent heat release links PV to the important cloud and rain processes within the waves. This paper introduces an innovative approach for a comprehensive identification and tracking of potential vorticity (PV) structures within AEWs. By employing AEW tracking and computing the wave phase of each point within the AEW domain using a Hilbert transform, we are able to effectively identify and collect 3-D PV structures associated with specific AEWs. To facilitate a climatological analysis, these structures are subsequently characterized by low-dimensional descriptors, including spatial information, intensity, and geometric approximations.

A climatological analysis reveals the seasonal evolution and the structural attributes of PV anomalies within AEWs over the study domain. PV feature locations closely align with the African Easterly Jet's latitudinal shift during the summer season. Analysis of the mean pressure level of the 3-D PV structures shows a remarkable shift during their life-cycle, indicating deep moist convection characteristics over land, and more shallow convection characteristics over the ocean. Both, composite data centered around identified AEW troughs and statistical analysis of main axes agree on an downshear tilt of the PV feature over land, and a tilt to the south over the ocean. The trough-centered analysis reveals distinct differences between satellite-estimated and model-predicted rainfall. The agreement between the results of the composite analysis and the feature analysis provides confidence in our feature approach as a novel diagnostic tool. The low-dimensional representation of PV features enables the research on further statistical analyses, for example the relationship of these features with tropical cyclogenesis or as predictor for rainfall in the tropics.