Using the Weather Research and Forecasting (WRF) model with two planetary boundary layer schemes, ACM2 and MYNN, convection-permitting model (CPM) regional climate simulations were conducted for a 6-year period at a 15-km grid spacing covering entire South America and a nested convection-permitting 3-km grid spacing covering the Peruvian central Andes region. These two CPM simulations along with a 4-km simulation covering South America produced by National Center for Atmospheric Research, three gridded global precipitation datasets, and rain gauge data in Peru and Brazil, are used to document the characteristics of precipitation and MCSs in the Peruvian central Andes region. Results show that all km-scale simulations generally capture the spatiotemporal patterns of precipitation and MCSs at both seasonal and diurnal scales, although biases exist in aspects such as precipitation intensity and MCS frequency, size, propagation speed, and associated precipitation intensity. The 3-km simulation using MYNN scheme generally outperforms the other simulations in capturing seasonal and diurnal precipitation over the mountain, while both it and the 4-km simulation demonstrate superior performance in the western Amazon Basin, based on the comparison to the gridded precipitation products and gauge data. Dynamic factors, primarily low-level jet and terrain-induced uplift, are the key drivers for precipitation and MCS genesis along the east slope of the Andes, while thermodynamic factors control the precipitation and MCS activity in the western Amazon Basin and over elevated mountainous regions. The study suggests aspects of the model needing improvement and the choice of better model configurations for future regional climate projections.

Mesoscale convective systems (MCSs) are clusters of thunderstorms that are important in Earth’s water and energy cycle. Additionally, they are responsible for extreme events such as large hail, strong winds, and extreme precipitation. Automated object-based analyses that track MCSs have become popular since they allow us to identify and follow MCSs over their entire life cycle in a Lagrangian framework. This rise in popularity was accompanied by an increasing number of MCS tracking algorithms, however, little is known about how sensitive analyses are concerning the MCS tracker formulation. Here, we assess differences between six MCS tracking algorithms on South American MCS characteristics and evaluating MCSs in kilometer-scale simulations with observational-based MCSs over three years. All trackers are run with a common set of MCS classification criteria to isolate tracker formulation differences. The tracker formulation substantially impacts MCS characteristics such as frequency, size, duration, and contribution to total precipitation. The evaluation of simulated MCS characteristics is less sensitive to the tracker formulation and all trackers agree that the model can capture MCS characteristics well across different South American climate zones. Dominant sources of uncertainty are the segmentation of cloud systems and the treatment of splitting and merging of storms in MCS trackers. Our results highlight that comparing MCS analyses that use different tracking algorithms is challenging. We provide general guidelines on how MCS characteristics compare between trackers to facilitate a more robust assessment of MCS statistics in future studies.

Mesoscale organization of convection is typically not represented in global circulation models, and hence its influence on the global circulation is not accounted for. A parameterization aiming at representing the dynamical and physical effects of the circulation associated with organized convection, referred to as the multiscale coherent structure parameterization (MCSP), is implemented in the Energy Exascale Earth System Model version 1 (E3SMv1). Simulations are conducted to assess its impact on the simulated climate. Besides E3SMv1 simulations, we performed high-resolution (1 km) simulations using the Weather Research and Forecasting (WRF) Model to determine the temperature tendencies induced by mesoscale convective systems embedded in deep convection. We tuned the free parameters of the MCSP based on the WRF simulations. We found that the MCSP enhances Kevin wave spectra in E3SMv1, improves the representation of the Madden-Julian Oscillation, and reduces model precipitation biases over the tropical Pacific.