The Comparison of Developing and Non-developing Waves during the NAMMA Experiment

The goal of this study is to compare and diagnose the differences in synoptic environments and mesoscale convective systems between developing and non-developing African easterly waves (AEWs) over the African continent and the Eastern Atlantic Ocean. We compare energy transformation, rainfall over western Africa, geographic location (i.e., the location and intensity of the AEWs left the western African coast), and synoptic parameters (i.e., sea surface temperature, conditional instability, and vertical wind shear). Seven waves are studied, including tropical storm Debby, Hurricane Helene, and five other non-developing waves which were identified during the African Monsoon Multidisciplinary Analyses (AMMA) experiment and its downstream NASA extension, NAMMA. Previous studies have investigated these seven waves and determined some differences among them. However, most of them used low-resolution global reanalysis data, in which some important mesoscale features are absent (i.e., mesoscale convective vortices and vortical hot towers). These mesoscale systems have been shown to play an important role in tropical cyclone activities. Therefore, high-resolution data might give insight into the mechanisms that support tropical cyclone genesis and intensification. In this study, high-resolution reanalysis data (64 km, 16 km, 4 km) will be generated using the Weather Research and Forecasting model and its three-dimensional variational data assimilation system. The assimilated observations include conventional data, NAMMA experiment data (e.g., radiosonde, dropsonde, and Meteorological Measurement System), QuikSCAT wind vectors, Special Sensor Microwave/Imager total precipitable water and wind speed, Atmospheric Infrared Sounder temperature soundings, and Global Positioning System refractivity. The global-merged infrared Brightness Temperature, with 4 km resolution, is used to trace the mesoscale convective system associated with each wave and to validate the high-resolution reanalysis data.