Director's Message

Welcome to the Research Applications Laboratory's Annual Report for FY2019. RAL strives to be a world leader in performing collaborative end-to-end scientific research, development, and technology transfer, expanding the reach of atmospheric and related sciences and bringing them to bear in addressing important societal problems. Achieving this vision requires the willingness and ability to work in an interdisciplinary way with internal and external colleagues, collaborators and stakeholders in the public and private sectors.

William Mahoney, RAL Director
William Mahoney, RAL Director

NCAR’s new strategic plan focuses on NCAR’s unique national and international role of performing fundamental science through technology transfer to address critical scientific challenges facing society. RAL plays a key role in ensuring that NCAR’s science is actionable science – science that informs decision making to save lives, property, and contributes to a strong economy.

RAL is an organization with annual expenditures of approximately $34M (FY19) and a transdisciplinary staff composed of approximately 180 scientists, software engineers, mathematicians, geographers, physicists, managers/administrators, and numerous personnel bringing expertise across many other disciplines. RAL is substantially a “soft-funded" laboratory. RAL’s NSF base funding represented 8% of RAL’s total budget and NSF special funds, and one-time NCAR reinvestments added another 4%. The NSF funds are highly leveraged with external sponsor funding used for advancing our scientific research, development, and societal impact mission.

RAL continues to make substantial contributions to the atmospheric science research community and the capabilities we develop support the global weather, water, and climate enterprise. Research areas that gained momentum in 2019 include the development and application of machine learning methods, meso- to microscale numerical weather prediction, large eddy simulation (LES) acceleration using graphical processing units (GPUs), wildland fire behavior prediction, air quality prediction, and the application of LES models to support unmanned aerial systems (UAS) and wind energy prediction.

I hope you will enjoy this year’s Report as it describes many of our exciting scientific accomplishments over the past year and plans for the future.