Given that more than half of the world’s population currently resides in cities, further understanding of the potential impact of future climate change on urban areas is needed. In this regard, we project recent heatwave (HW) episodes in the Metropolitan Area of Barcelona (AMB) with future climate conditions until 2100 using the pseudo global warming (PGW) method. First, we determine all the HWs that occurred in the AMB during the last climatological period of 30 years (1991-2020) and simulate each individual event using the Weather and Research Forecasting (WRF) model at high-resolution. Then, these historical HW events are re-simulated with the modified atmospheric conditions of the mid-century (2041-2070) and the end-of-the-century (2071-2100) according to the scenario SSP370, in which CO2 emissions are projected to almost double from current levels by 2100 following a low emission reduction scenario. HW intensity is expected to increase by 2.5 °C and 4.2 °C in the mid- and end-of-the-century periods, respectively. Higher temperatures are related to stationary and stable synoptic patterns, which are projected to experience the greatest intensification in the future. The geopotential height at 500 hPa could increase up to 100 geopotential meters (gpm) by the end of the century, leading to values up to 6050 gpm, which indicates changes in thermodynamic and dynamic effects resulting in potentially warmer HW episodes. The results obtained can aid in understanding the expected changes for this century, which could facilitate the formulation of heat mitigation and adaptation strategies, particularly for the most exposed areas.

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.