Kelly M. Núñez Ocasio | Erin M. Dougherty | Lulin Xue | Zachary L. Moon | Antonio Ruiz Núñez | Monica Morrison | Kwesi T. Quagraine | Ye Mu | Carlos Martinez | Veeshan Narinesingh | Tereza Cavazos | Gabriel Rios | Julio Bacmeister | Jorge A. Amador | Dimitris A. Herrera | Cenlin He | Eric D. Maloney | Kristen Rasmussen | Kevin A. Reed | Rich Neale | Christian Domínguez | Alejandro Jaramillo | Kwok P Chun | Leonardo A. Clarke | Santiago Núñez-Mejía | Yang Tian | Rosimar Rios-Berrios | K. Santiago Hernández | Lucía Scaff Fuenzalida | Alan G. Rosales | Patrick Callaghan | Xingchao Chen | Talia G. Anderson
Abstract
Understanding the weather and climate of Mesoamerica and the Caribbean remains challenging due to complex hydroclimate interactions, limited observations, and poor representation of regional processes in global models. We introduce the Mesoamerica Affinity Group (MAAG), an NSF NCAR and community voluntary initiative that fosters research collaboration to advance weather and climate science, develop convection-permitting datasets, and promote knowledge exchange. MAAG’s first major contribution is a two-week convection-permitting simulation of Hurricane Maria (2017) using MPAS-A, featuring a novel regional 15-km to 3-km variable-resolution mesh over the region. Initial evaluation shows that MPAS-A captures key features like
precipitation patterns, the Intertropical Convergence Zone, and low-level jets. Some biases remain, particularly in enhanced land convection and slight deviations in Maria’s track. This novel dataset, now publicly available through NCAR’s Data Archive, supports studies of other extreme events and mesoscale convective systems active during the same period. It offers a valuable resource for the research community. MAAG is a new but rapidly growing initiative achieving notable milestones in a short time. It serves as a collaborative platform for co-designing high-resolution modeling experiments, aimed at producing actionable weather and climate information. We invite the community to join MAAG, explore this initial dataset and advance regional weather and climate research.
precipitation patterns, the Intertropical Convergence Zone, and low-level jets. Some biases remain, particularly in enhanced land convection and slight deviations in Maria’s track. This novel dataset, now publicly available through NCAR’s Data Archive, supports studies of other extreme events and mesoscale convective systems active during the same period. It offers a valuable resource for the research community. MAAG is a new but rapidly growing initiative achieving notable milestones in a short time. It serves as a collaborative platform for co-designing high-resolution modeling experiments, aimed at producing actionable weather and climate information. We invite the community to join MAAG, explore this initial dataset and advance regional weather and climate research.
.
REGRESAR
