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Best Practices for Computing Backtrajectories with WRF

ffrntic

New member
Hello everyone,


I am currently working on a case study and would like to compute air parcel backtrajectories using WRF output. However, I'm running into some confusion regarding the recommended approach.

Is there a supported, internal option in WRF for computing backward trajectories (not forward)? The documentation only mentions traj_opt = 1 for forward trajectories.

I’ve considered using HYSPLIT, but was told the resolution may be too coarse for our needs. Would a custom Python script using 3D wind fields (e.g., with Runge-Kutta integration) be a viable alternative? Has anyone implemented this and validated the output?

If anyone can share references or workflows they’ve used for high-resolution backtrajectory analysis from WRF output, I’d be grateful.
 
Thank you for you answer. I’m trying to determine the best tool for high-resolution backward trajectory analysis. Between RIP and HYSPLIT (using WRF output), which tool is likely to provide better spatial and temporal resolution in the computed trajectories?
 
Unfortunately I don't have any experience with HYSPLIT, so I can't provide a fair assessment of the two tools. Perhaps someone else on this forum will be able to respond.
 
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