Logo

Massive-Parallel Trajectory Calculations

Web Runner for Air Parcel Trajectory Calculations

Explore the MPTRAC Web Runner: Simulate and visualize air parcel trajectories to study atmospheric transport. Configure simulations with key parameters and download results for analysis and further studies. This service is under active development. Please feel free to contact us with feedback or issues!

📘 MPTRAC Documentation 💻 GitHub Repository 📬 Contact Us

Simulation Parameters

Please specify simulation parameters below including meteorological data, initialization, physics, and output options. You can also load predefined case studies from the “Examples” menu.

Select a case study from the available examples below to auto-fill simulation parameters.

Natural Events
Anthropogenic Events

Select the meteorological dataset for the trajectory calculations.

Forecasts
Reanalyses

Simulation Time: Enter the simulation start and stop times in YYYY-MM-DD HH:MM (UTC). Simulations can run forward or backward in time but must not exceed 30 days.


Initial Position: Specify the mean initial location of the air parcels. Heights are in kilometers above sea level and converted to pressure internally.


Random Perturbations: Define uniform or Gaussian spreads (Full Width at Half Maximum, FWHM) to randomly perturb the initial positions of air parcels in longitude, latitude, and height.


Number of Parcels: Specify the total number of air parcels to be released. The maximum allowed is 10,000.

Define the stochastic perturbations of air parcel locations along trajectories by setting the horizontal and vertical diffusivity values for the PBL, troposphere, and stratosphere. Additionally, specify the subgrid-scale winds for both horizontal and vertical directions.


Select thresholds for extreme convection parametrization, and choose whether to enable vertical mixing throughout the planetary boundary layer (PBL).


Select the output interval to determine how frequently simulation results are recorded.



Select parameters for quick look plot.