Jet streams are fast-moving bands of air that steer storms, influence regional weather, and help shape long-term climate patterns. Yet scientists have long faced a challenge in determining exactly where these atmospheric rivers are located. Traditional methods identify jets by looking for regions of strong wind at a particular moment in time, but this "snapshot" view can miss persistent pathways and produce inconsistent results when comparing climates, seasons, or computer models.
In a recent paper, researchers from Harvard and collaborators developed a new approach called JetLag, which treats jet streams as moving transport pathways rather than simply locations of maximum wind speed. Instead of focusing on instantaneous winds, the method tracks how air parcels travel through the atmosphere over time. This Lagrangian perspective identifies jet streams as coherent structures that organize large-scale transport and atmospheric mixing. Applying JetLag to more than eight decades of atmospheric data, the team found that it reproduces known jet-stream behavior while providing a more continuous, robust, and physically meaningful description of jet position and variability.
The advance matters because jet streams influence extreme weather, storm tracks, and climate variability. By improving how scientists identify and monitor these features, the new framework may help researchers better understand climate change impacts and improve comparisons between observations and climate model simulations. Harvard research computing enabled the large-scale analysis of historical atmospheric datasets and the trajectory calculations required to track millions of air-parcel movements across decades of global records.
Rivoire, L., Curbelo, J., & Linz, M. (2026), Tracking jet streams as Lagrangian objects, Communications Earth & Environment, doi: 10.1038/s43247-026-03262-z
