TY - JOUR
T1 - Earth System Predictability Across Time Scales for a Resilient Society
T2 - A Research Community Perspective
AU - Richter, Jadwiga H.
AU - Joseph, Everette
AU - Arcodia, Marybeth
AU - Berner, Judith
AU - Demuth, Julie L.
AU - Falloon, Pete D
AU - Romine, Glen S.
AU - Cohen, Jacob T.
AU - Gonzalez-Cruz, Jorge
AU - El Gharamti, Mohamad
AU - Hoppe, Brenda
AU - Kumar, Sanjiv
AU - Mariotti, Annarita
AU - Mishra, Debasish
AU - Pegion, Kathleen
AU - Pu, Zhaoxia
AU - Quagraine, Kwesi A.
AU - Roychoudhury, Chayan
AU - Ryan, James
AU - Stone, Zeljka
AU - Das, Debanjana
AU - Gaubert, Benjamin
AU - Kapnick, Sarah
AU - Zarzycki, Colin
N1 - Publisher Copyright:
© 2026 American Meteorological Society.
PY - 2026/1/13
Y1 - 2026/1/13
N2 - With extreme weather events becoming more frequent and severe, accelerating progress in Earth system predictability is urgently needed to deepen fundamental understanding, improve predictive tools, and provide reliable, actionable information for societal resilience. Building on prior and ongoing efforts by the broader community and informed by discussions at an NSF National Center for Atmospheric Research (NSF NCAR) workshop on Earth System Predictability Across Timescales, this essay articulates a perspective on the scientific and structural priorities needed to advance Earth system predictability from short-range weather forecasts to century-scale projections, underscoring the urgency of a comprehensive, integrative approach capable of meeting emerging societal needs. Three scientific grand challenges are highlighted: understanding interactions across spatial and temporal scales, across interconnected Earth system components, and the influence of external forcing on predictability. To address these grand challenges, we identify potential implementation priorities across five key areas: a) enhancing observations and data accessibility, b) advancing data assimilation techniques, c) improving modeling frameworks, d) developing artificial intelligence and machine learning (AI/ML) methods, e) and applying convergence research. To support these areas, we outline four intersecting pillars of an integrated strategy: i) a multiscale and multidisciplinary approach; ii) closer coordination across modeling, observations, data assimilation, and AI/ML; iii) intentional convergence research; and iv) co-development of science with users. We also propose a collaborative path forward focused on strengthening scientific and technical connections, rewarding interdisciplinary and team-based science, expanding support for engagement with users, and investing in relationship-building, shared language, and trust across scientific and societal domains.
AB - With extreme weather events becoming more frequent and severe, accelerating progress in Earth system predictability is urgently needed to deepen fundamental understanding, improve predictive tools, and provide reliable, actionable information for societal resilience. Building on prior and ongoing efforts by the broader community and informed by discussions at an NSF National Center for Atmospheric Research (NSF NCAR) workshop on Earth System Predictability Across Timescales, this essay articulates a perspective on the scientific and structural priorities needed to advance Earth system predictability from short-range weather forecasts to century-scale projections, underscoring the urgency of a comprehensive, integrative approach capable of meeting emerging societal needs. Three scientific grand challenges are highlighted: understanding interactions across spatial and temporal scales, across interconnected Earth system components, and the influence of external forcing on predictability. To address these grand challenges, we identify potential implementation priorities across five key areas: a) enhancing observations and data accessibility, b) advancing data assimilation techniques, c) improving modeling frameworks, d) developing artificial intelligence and machine learning (AI/ML) methods, e) and applying convergence research. To support these areas, we outline four intersecting pillars of an integrated strategy: i) a multiscale and multidisciplinary approach; ii) closer coordination across modeling, observations, data assimilation, and AI/ML; iii) intentional convergence research; and iv) co-development of science with users. We also propose a collaborative path forward focused on strengthening scientific and technical connections, rewarding interdisciplinary and team-based science, expanding support for engagement with users, and investing in relationship-building, shared language, and trust across scientific and societal domains.
U2 - 10.1175/BAMS-D-24-0155.1
DO - 10.1175/BAMS-D-24-0155.1
M3 - Article (Academic Journal)
SN - 0003-0007
JO - Bulletin of the American Meteorological Society
JF - Bulletin of the American Meteorological Society
ER -