TY - JOUR
T1 - Advancing Weather and Climate Science in Mesoamerica and the Caribbean
T2 - A Novel Regional Multiweek Convection-Permitting Simulation
AU - Núñez Ocasio, Kelly M.
AU - Dougherty, Erin M.
AU - Xue, Lulin
AU - Moon, Zachary L.
AU - Núñez, Antonio Ruiz
AU - Morrison, Monica
AU - Quagraine, Kwesi T.
AU - Mu, Ye
AU - Martinez, Carlos
AU - Narinesingh, Veeshan
AU - Cavazos, Tereza
AU - Rios, Gabriel
AU - Bacmeister, Julio
AU - Amador, Jorge A.
AU - Herrera, Dimitris A.
AU - He, Cenlin
AU - Maloney, Eric D.
AU - Rasmussen, Kristen
AU - Reed, Kevin A.
AU - Neale, Rich
AU - Domínguez, Christian
AU - Jaramillo, Alejandro
AU - Chun, Kwok P.
AU - Clarke, Leonardo A.
AU - Núñez-Mejía, Santiago
AU - Tian, Yang
AU - Rios-Berrios, Rosimar
AU - Santiago Hernández, K.
AU - Fuenzalida, Lucía Scaff
AU - Rosales, Alan G.
AU - Callaghan, Patrick
AU - Chen, Xingchao
AU - Anderson, Talia G.
N1 - Publisher Copyright:
© 2026 American Meteorological Society.
PY - 2026/4
Y1 - 2026/4
N2 - 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), a National Science Foundation (NSF) National Center for Atmospheric Research (NCAR) and community 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 2-week convection-permitting simulation of Hurricane Maria (2017) using Model for Prediction Across Scales–Atmosphere (MPAS-A), featuring a novel regional 15-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 codesigning 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.
AB - 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), a National Science Foundation (NSF) National Center for Atmospheric Research (NCAR) and community 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 2-week convection-permitting simulation of Hurricane Maria (2017) using Model for Prediction Across Scales–Atmosphere (MPAS-A), featuring a novel regional 15-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 codesigning 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.
KW - Atmosphere
KW - Central America
KW - Complex terrain
KW - Hindcasts
KW - Hydrologic cycle
KW - Tropical cyclones
UR - https://www.scopus.com/pages/publications/105037116943
U2 - 10.1175/BAMS-D-25-0023.1
DO - 10.1175/BAMS-D-25-0023.1
M3 - Article
AN - SCOPUS:105037116943
SN - 0003-0007
VL - 107
SP - E836-E852
JO - Bulletin of the American Meteorological Society
JF - Bulletin of the American Meteorological Society
IS - 4
ER -