Synthesis of short-term time-series of daily averaged surface pressure on Mars
Simulation of the operation of various devices for future robotic or manned expeditions to Mars requires a detailed knowledge of the atmospheric pressure time variation. Martian pressure data records are not continuous and finding means of filling in the gaps is necessary. The short-term time-series of daily average pressure on the surface of Mars have specific sequential and distribution characteristics. Both features were studied here by using data from the Viking Lander Meteorology and Atmospheric Opacity Data Set Archive. As a first step, the surface pressure was separated into a slow-varying term (the average pressure) and a fast-varying term (the excess pressure). The average time variation of the daily pressure was fitted using a formula retaining the first eight harmonics of the annual cycle. In order to obey as much as possible the homoscedasticity criterion the analysis was performed separately for each of the four seasons of the Martian year. A number of intervals with continuous data were selected for both VL1 and VL2 and the first autocorrelation coefficients were evaluated. They were used to develop autoregressive (AR) models of various orders. The excess pressure time-series generated by AR models keep the sequential properties of the measured data quite well. Also, there is reasonable good agreement between the first statistical moments of the measured and synthetic excess pressure data.
mars meteorology data synthesis autoregressive models data reduction techniques