Statistical Methods for Climate and Resilience Research: A Framework for Enhanced Interdisciplinary Collaboration and National Impact

Climate science and national resilience research demands unprecedented coordination between statistical methodologies and interdisciplinary collaboration to address complex, multi-scale challenges. Climate and weather impact every aspect of the daily lives of U.S. residents, from immediate threats to personal safety, to secure food supplies, to affordable insurance and housing, and to stable financial markets. This paper synthesizes key findings from a series of three workshops focused on the role of statistics in climate science, proposing a comprehensive framework for enhanced data quality, methodological innovation, and collaborative research practices. We identify eight critical areas requiring immediate attention: data quality and accessibility, interdisciplinary collaboration, methodological approaches, scale and complexity management, national security framing, population dynamics integration, education and outreach, and policy communication. Our analysis reveals that while the statistical community possesses the necessary expertise and methodological tools, success requires scientific coordination, strategic communication, and focused efforts on high impact climate applications (Lemos et al., Citation2025). This framework provides actionable recommendations for researchers, educators, business leaders, and policymakers to strengthen the statistical foundation of climate science and national resilience.