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

• 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.

Mecury’s Exosphere

SOURCES• Comets

• Micrometeorites

• Solar Wind

• Regolith

• Hermean Interior

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

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.

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)

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

Monte Carlo ModelINPUT

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 ModelOUTPUT

• Statistics for a set of physical inputs– Dominant loss mechanism– Average hop parameters (distance, height,

number of hops)– Particle lifetime

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

Monte Carlo ModelOUTPUT

• Spatial distribution of loss processes, which can feed additional source processes– Magnetospheric recycling– Nightside sticking, dawn desorption

Photon stimulated desorption source

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