Title: A Framework for Relating the Structures and Recovery Statistics in Pressure Time-Series Surveys for Dust Devils,
Abstract: Dust devils are likely the dominant source of dust for the martian
atmosphere, but the amount and frequency of dust-lifting depend on the
statistical distribution of dust devil parameters. Dust devils exhibit pressure
perturbations and, if they pass near a barometric sensor, they may register as
a discernible dip in a pressure time-series. Leveraging this fact, several
surveys using barometric sensors on landed spacecraft have revealed dust devil
structures and occurrence rates. However powerful they are, though, such
surveys suffer from non-trivial biases that skew the inferred dust devil
properties. For example, such surveys are most sensitive to dust devils with
the widest and deepest pressure profiles, but the recovered profiles will be
distorted, broader and shallow than the actual profiles. In addition, such
surveys often do not provide wind speed measurements alongside the pressure
time series, and so the durations of the dust devil signals in the time series
cannot be directly converted to profile widths. Fortunately, simple statistical
and geometric considerations can de-bias these surveys, allowing conversion of
the duration of dust devil signals into physical widths, given only a
distribution of likely translation velocities, and the recovery of the
underlying distributions of physical parameters. In this study, we develop a
scheme for de-biasing such surveys. Applying our model to an in-situ survey
using data from the Phoenix lander suggests a larger dust flux and a dust devil
occurrence rate about ten times larger than previously inferred. Comparing our
results to dust devil track surveys suggests only about one in five
low-pressure cells lifts sufficient dust to leave a visible track.