PyLag is an offline particle tracking model. The model expects as inputs time independent and/or dependent variables that describe the state of a given fluid. These may be measured quantities or the predictions of an analytical or numerical model. Using these, the model computes Lagrangian trajectories for particles released into the fluid at a particular point in time and space. The model is primarily aimed at marine applications, but is versatile enough to be used in other contexts too; for example, in studies of atmospheric dispersion.
PyLag was created with the aim to make available a particle tracking model that is a) fast to run, b) easy to use, c) extensible and d) flexible. The model is written in a mixture of Python and Cython,
How to cite¶
Uncles, R. J., Clark, J. R., Bedington, M., Torres, R. 2020. “On sediment dispersal in the Whitsand Bay Marine Conservation Zone: Neighbor to a closed dredge-spoil disposal site” in Marine Protected Areas: Evidence, Policy and Practise, ed Robert Clark and John Humphreys (Elsevier Inc.).
- Lateral advection
- Lateral advection and diffusion
- Vertical mixing with analytic inputs
- Vertical mixing with numeric inputs
- FVCOM - Forward tracking
- FVCOM - Backward tracking
- Local Arakawa A-grid - Forward tracking
- Global Arakawa A-grid - Forward tracking
- ROMS - Forward tracking
- Individual based modelling - mortality
- API Reference