A dynamical history of the inner Neptunian satellites and Martian weather : Viking observations and M.O. data assimilation techniques

• Main Author: Banfield, Donald J.
• Format: Others
• Language: en
• Published: 1994
• Online Access: https://thesis.library.caltech.edu/836/1/Banfield_dj_1994.pdf; Banfield, Donald J. (1994) A dynamical history of the inner Neptunian satellites and Martian weather : Viking observations and M.O. data assimilation techniques. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/07dr-qq38. https://resolver.caltech.edu/CaltechETD:etd-03022006-132818 <https://resolver.caltech.edu/CaltechETD:etd-03022006-132818>

We examine a scenario involving the capture origin of Triton, and infer the dynamical history of the Neptune satellite system. Triton's post-capture orbit forced chaotic perturbations on the original inner satellites of Neptune, leading to their mutual collisions and self-destruction. Neptune's current inner satellite system re-formed equatorially after Triton's orbital circularization. The 4.7° inclination of 1989N6 is probably due to a temporary inclination resonance. The 2:1 secondary resonance of the 1989N6-1989N3 12:10 resonance would eject 1989N6 at 4.7°, matching the observations. We have established limits for Neptune's Q: 12,000 < QN < 330,000. We examine a steady-state scheme for data assimilation in the context of a single, sun-synchronous, polar-orbiting satellite. The optimal (Wiener) gains are steady in time, and equivalent to those of a Kalman filter. The gains are computed by iteration using prior estimates to assimilate simulated observations of one model run ('Truth') into another run. The resulting prediction errors then form the next estimate of the gains. In model tests, the scheme works well even if only the mass field is observed. Although the scheme was developed for Mars Observer, it should be applicable to data retrieved from Earth atmosphere satellites, e.g., UARS. Spring and fall Viking IRTM T15 observations are used to estimate the Martian weather correlation length scale in the range 0.5-1 mbar. The results are important in providing a benchmark for validating Martian GCMs, determining the optimal placement of a network of landers, and guiding data assimilation efforts. Atmospheric temperature observations are used to compute an atmospheric mean state, which is subtracted from the observations to yield weather temperature residuals. These residuals are correlated with each other to determine the weather temperature correlation length scale (~ 1500km) and the weather temperature variance (~ 4-11K2). This work suggests that ~110 landers are needed to globally observe Mars' weather.