Tropical rainfall prediction is a challenge in current numerical weather prediction (NWP) models. To improve rainfall prediction in the tropics, it is essential to understand convective nature of the system and interactions of convection with large-scale features such as convectively coupled to equatorial waves which have potentials to improve rainfall predictions in the tropics as they control a substantial portion of rainfall variability in the tropics. Yet, NWP models often struggle to realistically produce convectively coupled equatorial waves. Resolved convection is thought to be key for the improvement by allowing for multi-scale interactions between convection and large-scale circulations. This presentation will discuss about mean tropical rainfall and its variability by assessing their representations in the ICON-NWP experiments between explicit versus parameterized convection. First, a set of ICON-NWP aquachannel simulations will be introduced, convective treatment of which comprises different combinations of deep and shallow convection, and we show time-mean behaviors of the aquachannel simulations, focusing on mean rainfall. To understand different behaviors among the simulations, we will present a novel diagnostic tool for a physically consistent comparison between simulations with different representations of convection. After demonstrating the time-mean behaviors of the simulations, equatorial waves are identified by using complementary wave identification methods. Finally, we will move onto realistic global ICON-NWP simulations and their ability of producing equatorial waves. These realistic simulations demonstrate that large-scale equatorial waves are fairly robust between explicit and parameterized convection and across various horizontal resolutions. This talk highlights our understanding of how different convective treatment alters mean rainfall and convectively coupled equatorial waves, and ultimately provides implications for forecast skills in the tropics.