Assessing Precipitation Over the Amazon Basin as Simulated by a Storm‐Resolving Model. Issue 4 (11th February 2023) - Paccini, L.; Stevens, B.
Abstract: In this study, we investigate whether a better representation of precipitation in the Amazon basin arises through an explicit representation of convection and whether it is related to the representation of organized systems. In addition to satellite data, we use ensemble simulations of the ICON‐NWP model at storm‐resolving (2.5–5.0 km) scales with explicit convection (E‐CON) and coarse resolutions, with parameterized convection (P‐CON). The main improvements in the representation of Amazon precipitation by E‐CON are in the distribution of precipitation intensity and the spatial distribution in the diurnal cycle. By isolating precipitation from organized convective systems (OCS), it is shown that many of the well simulated precipitation features in the Amazon arise from the distribution of these systems. The simulated and observed OCS are classified into 6 clusters which distinguish nocturnal and diurnal OCS. While the E‐CON ensembles capture the OCS, especially their diurnal cycle, their frequency is reduced compared to observations. Diurnal clusters are influenced by surface processes such as cold pools, which aid to the propagation of OCS. Nocturnal clusters are rather associated with strong low‐level easterlies, possibly related to the Amazonian low‐level jet. Our results also show no systematic improvement with a twofold grid refinement and remaining biases related to stratiform features of OCS suggest that yet unresolved processes play an important role for correctly representing precipitating systems in the Amazon. Plain Language Summary: The Amazon basin is a relevant element of the Earth system because it influences the global water and carbon cycle, as well as it constitutes a unique ecosystem. Over this important region, conventional climate models do not simulate basic features of rainfall given their inability to resolve this physical process due to their coarse spatial resolution. In this study, we use high‐resolution simulations that allow an explicit representation of such physical process (moist convection) and compare them with a set of coarse‐resolution simulations and observed precipitation. We find that improvements in the representation of Amazon rainfall, such as the distribution of light and high intensity rain rates, as well as the spatial variability of the diurnal cycle, are explained by the explicit representation of moist convection. Moreover, these improvements arise from the representation of big and organized systems that produce intense rainfall (OCS). We find that particular environmental conditions are associated with the OCS according to their time of occurrence. Diurnal OCS are mainly influenced by interactions with the surface, while nocturnal OCS are related to strong low‐level winds. Some of the remaining discrepancies with observed OCS do not show improvements when refining the grid by a factor of two. Key Points: An explicit representation of convection enables the emergence of organized systems (OCS) leading to improved simulations of Amazon rainfall Propagating cold‐pools and strong low‐level easterlies are related to the occurrence of diurnal and nocturnal OCS, respectively Systematic biases in the size, intensity and nocturnal precipitation phase of OCS are insensitive to a twofold refinement in resolution