How domain-specific languages in Python can bridge the software productivity gap in weather and climate science: Demonstration with the SHiELD Atmospheric Model

Wu, Elynn

How domain-specific languages in Python can bridge the software productivity gap in weather and climate science: Demonstration with the SHiELD Atmospheric Model

Elynn Wu¹, Johann Dahm¹, Florian Deconinck¹, Oliver Elbert¹, Jeremy McGibbon¹, Tobias Wicky¹, Lucas Harris², Rusty Benson³ and Oliver Fuhrer^1,4, (1)Allen Institute for Artificial Intelligence, Seattle, United States, (2)Geophysical Fluid Dynamics Laboratory, NOAA, Princeton, United States, (3)Geophysical Fluid Dynamics Laboratory, Princeton, NJ, United States, (4)MeteoSwiss Federal Office of Meteorology and Climatology, Zurich, Switzerland