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Monte Carlo Atmosphere Model

Monte Carlo Atmosphere Model. Dana Crider, CUA Rosemary Killen, U. Md. Mecury’s Exosphere. Surface bounded exosphere The atmosphere is collisionless The surface is the exobase

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Monte Carlo Atmosphere Model

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  1. Monte Carlo Atmosphere Model Dana Crider, CUA Rosemary Killen, U. Md.

  2. Mecury’s Exosphere • Surface bounded exosphere • The atmosphere is collisionless • The surface is the exobase • Since individual particles do not interact, Monte Carlo modeling is an excellent tool. Different scenarios can be run separately, and co-added in whatever proportion is physically appropriate.

  3. Mecury’s Exosphere

  4. SOURCES • Comets • Micrometeorites • Solar Wind • Regolith • Hermean Interior

  5. RELEASE MECHANISMS • Ion sputtering • Mid-to-high latitude • Impact vaporization • Isotropic unless there is an assumed surface distribution of the element released • Thermal vaporization • Highly dependent on the assumed time-dependent distribution of materials in the regolith

  6. BALLISTIC HOPS • Once released from the surface, particles follow a trajectory under the influence of gravity and radiation pressure • Mercury’s eccentricity leads to high radial velocity at some true anomaly angles, causing annual differences in the effectiveness of radiation pressure.

  7. SURFACE PROCESSES • What happens when the particle encounters the surface? • Rebound (elastic or inelastic) • Thermalize and reemit • Partial thermalization • Stick (either permanently or until dawn)

  8. SINKS • Photoionization • Products can either return to surface or escape. Returned products can be followed in simulations • Gravitational escape • Aided by radiation pressure • Sticking to surface • Long-duration cold traps exist at high latitude

  9. NUMERICAL NEEDS Random seed Number of particles Box size Time steps PHYSICAL VARIABLES Release mechanism Spatial distribution Initial velocity Sticking module Rerelease velocity Spatial distribution True anomaly angle Radiation pressure Photoionization Monte Carlo ModelINPUT

  10. Monte Carlo ModelOUTPUT • Statistics for a set of physical inputs • Dominant loss mechanism • Average hop parameters (distance, height, number of hops) • Particle lifetime

  11. Monte Carlo ModelOUTPUT • 3-D atmospheric distribution given source • Position and velocity of particles in the atmosphere • Model abundance can be scaled to real abundance by multiplying by the source rate • Multiple sources can be co-added in proportion to get cumulative atmosphere • Flexible to allow any cut through simulated atmosphere for comparison with viewing geometry for comparison with observations

  12. Monte Carlo ModelOUTPUT • Spatial distribution of loss processes, which can feed additional source processes • Magnetospheric recycling • Nightside sticking, dawn desorption

  13. Photon stimulated desorption source

  14. Conclusions • Our Monte Carlo exosphere model paired with upcoming observations will provide insight into hermean surface, atmosphere, and magnetosphere interactions: • Understand surface-atmosphere interactions especially in terms of sticking and re-release • Compare atmospheric distribution for different release mechanisms

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