10:00 AM - 10:15 AM
[PPS01-05] Estimation of the Ejection Velocity Distribution of Plume Particles on Enceladus
Observations by Cassini have provided compelling evidence for the existence of a subsurface ocean on Enceladus. This ocean may host prebiotic chemical evolution, making it a key target for astrobiological investigations (Postberg et al., 2018). Since the progress of chemical evolution depends on the longevity of the subsurface ocean, understanding its duration is crucial for evaluating the habitability of Enceladus.
However, constraints on the duration of the subsurface ocean rely on the moon’s orbital and thermal evolution, both of which involve significant uncertainties. Estimates of the ocean’s existence span a wide range, from as short as a few million years to as long as 1 billion years (Roberts & Nimmo, 2008). Plume activity near Enceladus’s south pole, likely from the subsurface ocean, provides a lower bound on the ocean’s duration (Porco et al., 2006; Thomas et al., 2016).
Some of the particles emitted from the plumes escape Enceladus and contribute to Saturn’s E-ring. Deposits of these particles have been confirmed on other moons, indicating that measuring the total accumulated material could provide an estimate of the cumulative plume activity(Hirata et al.,2014). By comparing the deposition rate on these moons with the present-day supply rate from the plumes, we can infer the duration of the plume.
Plume models focus on gas dynamics, while particle acceleration and velocity dispersion remain unclear (Schimit et al., 2009). High-velocity particles control escape rates, making velocity distribution key to material transport from Enceladus to the E-ring.
Objectives and Methods
This study aims to characterize the velocity distribution of particles in the Enceladus plume. To achieve this, we conducted numerical simulations of particle motion, assuming various velocity distributions. We then compared the results with the observed spatial brightness distribution of the plume as captured by Cassini’s imaging system.
First, we performed one-dimensional motion calculations to estimate the velocity distribution of particles by comparing the results with observations. We considered three velocity distribution models:
Model1:Mono-velocity model: All particles are ejected at the same velocity, v0.
Model2:Exponential decay model: The number of particles decreases with increasing velocity, following N(v)∝exp(−v/v0).
Model3:Maxwellian-like model: The number of particles decreases following N(v)∝exp(−v^2/v0^2), resembling a thermal distribution.
We varied the characteristic velocity v0 and simulated the motion of plume particles under Enceladus’s gravitational field to determine the number of particles present at various altitudes. These results were compared to the altitude-dependent brightness distribution of the plume observed by Cassini.
Results and Discussion
The mono-velocity model failed to reproduce the observed altitude dependence of plume brightness, as it did not account for the significant decrease in particle density with increasing altitude. This suggests that the initial velocities of plume particles vary widely.
In contrast, both Model 2 and Model 3 produced altitude distributions where particle density decreased exponentially at lower altitudes and dropped off sharply at higher altitudes, making them more consistent with observations. Model 3, in particular, provided the best match to the observed brightness distribution when the characteristic velocity v0 was approximately 200 m/s. This velocity is comparable to the speed of sound in the plume’s gas, supporting the hypothesis that ice particles are accelerated by interactions with water vapor in the plume. Notably, the presence of a significant fraction of supersonic particles suggests that gas-driven acceleration continues even beyond the vent region.
To further investigate the relationship between the 3D structure of the plume and the observed brightness distribution, we performed 3D simulations of particle motion. We modeled particle ejection from the south pole, using the two best-fitting velocity distributions from our one-dimensional analysis. The results demonstrated that the altitude distribution of particles is primarily controlled by velocity distribution rather than the spatial configuration of the fissures.
This study highlights the importance of distinguishing between Model 2 and Model 3, as the particle supply to the E ring in Model 2 is approximately three times greater. This distinction is essential for accurately estimating the age of the plume based on deposition rates on other satellites.
However, constraints on the duration of the subsurface ocean rely on the moon’s orbital and thermal evolution, both of which involve significant uncertainties. Estimates of the ocean’s existence span a wide range, from as short as a few million years to as long as 1 billion years (Roberts & Nimmo, 2008). Plume activity near Enceladus’s south pole, likely from the subsurface ocean, provides a lower bound on the ocean’s duration (Porco et al., 2006; Thomas et al., 2016).
Some of the particles emitted from the plumes escape Enceladus and contribute to Saturn’s E-ring. Deposits of these particles have been confirmed on other moons, indicating that measuring the total accumulated material could provide an estimate of the cumulative plume activity(Hirata et al.,2014). By comparing the deposition rate on these moons with the present-day supply rate from the plumes, we can infer the duration of the plume.
Plume models focus on gas dynamics, while particle acceleration and velocity dispersion remain unclear (Schimit et al., 2009). High-velocity particles control escape rates, making velocity distribution key to material transport from Enceladus to the E-ring.
Objectives and Methods
This study aims to characterize the velocity distribution of particles in the Enceladus plume. To achieve this, we conducted numerical simulations of particle motion, assuming various velocity distributions. We then compared the results with the observed spatial brightness distribution of the plume as captured by Cassini’s imaging system.
First, we performed one-dimensional motion calculations to estimate the velocity distribution of particles by comparing the results with observations. We considered three velocity distribution models:
Model1:Mono-velocity model: All particles are ejected at the same velocity, v0.
Model2:Exponential decay model: The number of particles decreases with increasing velocity, following N(v)∝exp(−v/v0).
Model3:Maxwellian-like model: The number of particles decreases following N(v)∝exp(−v^2/v0^2), resembling a thermal distribution.
We varied the characteristic velocity v0 and simulated the motion of plume particles under Enceladus’s gravitational field to determine the number of particles present at various altitudes. These results were compared to the altitude-dependent brightness distribution of the plume observed by Cassini.
Results and Discussion
The mono-velocity model failed to reproduce the observed altitude dependence of plume brightness, as it did not account for the significant decrease in particle density with increasing altitude. This suggests that the initial velocities of plume particles vary widely.
In contrast, both Model 2 and Model 3 produced altitude distributions where particle density decreased exponentially at lower altitudes and dropped off sharply at higher altitudes, making them more consistent with observations. Model 3, in particular, provided the best match to the observed brightness distribution when the characteristic velocity v0 was approximately 200 m/s. This velocity is comparable to the speed of sound in the plume’s gas, supporting the hypothesis that ice particles are accelerated by interactions with water vapor in the plume. Notably, the presence of a significant fraction of supersonic particles suggests that gas-driven acceleration continues even beyond the vent region.
To further investigate the relationship between the 3D structure of the plume and the observed brightness distribution, we performed 3D simulations of particle motion. We modeled particle ejection from the south pole, using the two best-fitting velocity distributions from our one-dimensional analysis. The results demonstrated that the altitude distribution of particles is primarily controlled by velocity distribution rather than the spatial configuration of the fissures.
This study highlights the importance of distinguishing between Model 2 and Model 3, as the particle supply to the E ring in Model 2 is approximately three times greater. This distinction is essential for accurately estimating the age of the plume based on deposition rates on other satellites.