Kilometer-Scale Modeling of Amazonian Mesoscale Convective Systems - Characterizing Precipitation Extremes in a Changing Climate

Mesoscale convective systems (MCS) are organized clusters of deep convective cells that occur frequently in the tropical Amazon basin. Here, MCS constitute an important source of precipitation, contributing by ~40 – 60 % to the total. This makes MCS vital for the Amazonian water balance, which is dependent on the westward moisture transport from the Atlantic Ocean. During the transport, moisture is recycled in multiple precipitation-evaporation cycles, including the precipitation generated by the MCS. Nevertheless, extreme precipitation related to MCS systems can cause substantial economic damage through extreme rainfall, flash flooding, debris flows, severe winds and hail. Therefore, the effect of the warming climate and changing land-atmosphere interactions on MCS frequency and intensity will have important implications. However, research does not show consensus on the intensity changes in MCS in the Amazon rainforest, and whether MCSs will become more extreme due to changes in physical processes under warming climate conditions. The main shortcoming is that the current global models’ resolution is too coarse (>25 km) to explicitly resolve turbulence and moist convection. Because of this, the intensity of the changes is jeopardized by the sensitivity of these changes to the physical representation of moist deep convection. In the EU Next Generation Earth System models (NextGEMS) project, high-resolution (9 km) earth system experiments covering the Earth were performed. The novelty of these experiments is that they partly resolve the deep convection and capture the large-scale dynamics on a global scale. In this study, we analyze the Integrated Forecasting System coupled to the Finite-volumE Sea ice-Ocean Model (IFS-FESOM) of the NextGEMS project, to characterize the Amazonian MCS in the current climate (1990-2020) and project their future changes (2020-2050; SSP3-7). We do the MCS characterization in a systematic manner: To study the MCS systems, we track them based on brightness temperature and precipitation intensity with the Python FLEXible object TRacKeR (PyFLEXTKRK). Determining these MCS tracks provides insight into the current frequency, duration, and precipitation intensity of MCSs across regions and seasons. Once we have characterized the current climate, we do the same characterization for the projected future climate to determine the main climate change effects on MCS occurrence in the Amazon and their contribution to the water cycle. In the future characterizations, we emphasize extreme scenarios that produce large amounts of precipitation (95th percentile) because of their significant environmental impact.