deletions | additions       diff --git a/section_Background_Dust_devils_are__.tex b/section_Background_Dust_devils_are__.tex  index 54db27e..45f19a8 100644  --- a/section_Background_Dust_devils_are__.tex  +++ b/section_Background_Dust_devils_are__.tex 
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All these surveys, however, suffer from observational biases that skew the statistical properties inferred for the underlying dust devil population. For example, as noted in \citet{Lorenz_2009}, in-person visual surveys are likely to be biased toward detection of larger, more easily seen devils. On the other hand, single-sensor barometer surveys suffer from a ``miss distance'' bias: a fixed barometric sensor is more likely to have a more distant encounter than a close encounter with a dust devil. Since the pressure perturbation associated with a devil falls off with distance, the deepest point in the observed pressure profile will almost always be less than the actual pressure well at the devil's center. The observed shape of the profile will be distorted as well. These biases are intrinsic to the detection methods, and additional biases can influence the inferred statistical properties. For instance, noise in the pressure time series from a barometer may make more difficult detection of a dust devils with smaller pressure perturbations, depending on the exact detection scheme.  In this kind of survey, one or more barometric sensors deployed in-situ record a pressure time series at a sampling rate $\lesssim 1$ s. As low-pressure convective vortex, a dust devil has an actual pressure depth $P_{\rm act}$ at its center measured against some known background level and a radial profile $P(r)$ resembling a Lorentz function with a full-width half-max $\Gamma_{\rm act}$: $P(r) = -\dfrac{P_{\rm act}}{1 - \left( 2r/\Gamma_{\rm act} \right)^2 }$. Dust devils are usually carried by the background wind with a velocity $\upsilon$. Figure \ref{fig:conditioning_detection_b_inset} from \citet{Jackson_2015} shows a typical profile.  %\citet{Lorenz_2014} investigated biases inherent to single barometer surveys using a phenomenological Monte-Carlo model for dust devils advected through a virtual arena.  %They have been observed to persist from minutes to hours and can travel kilometers, often carried by the ambient wind [Lorenz, 2013a]. On Earth, they are observed in arid locations primarily, where the ground is usually dry enough to provide a ready supply of dust [e.g., Balme and Greeley, 2006]. On Mars, they have been observed ubiquitously, both from the ground [Metzger et al., 1999] and from orbiting spacecraft [Cantor et al., 2006]. On both planets, dust devils contribute to the atmospheric aerosol content, sometimes increasing the dust content over the U.S. Southwest by more than an order of magnitude [Renno et al., 2004]. On Mars, dust devils may be the primary source for atmospheric dust, which plays a role in the radiative balance of the Martian atmosphere and, therefore, on the planet's meteorology [Basu et al., 2004]. Dust devils also seem to have lengthened the operating lifetime of Martian rovers by frequently cleaning their solar panels (http://mars.jpl.nasa.gov/mer/mission/status_opportunityAll.html#sol3603). Since the dust supply from dust devils on both planets may be dominated by the seldom observed larger devils, it is particularly important to study the underlying distribution of dust devils, rather than focusing on the typical devil. Thus, elucidating the origin, evolution, and population statistics of dust devils is critical for understanding important terrestrial and Martian atmospheric properties and for in situ exploration of Mars. 
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%While the pressure dips associated with dust devils have been recorded on Earth [e.g., Wyett, 1954; Lambeth, 1966; Sinclair, 1973], they are actually more systematically documented in studies of dust devils on Mars (e.g., by Mars Pathfinder: Murphy and Nelli, 2002; and by the Phoenix mission: Ellehoj et al., 2010), where landers have recorded meteorological parameters over long periods with a high enough cadence to detect small vortical structures. Most terrestrial meteorological records have cadence too low (canonically, 15 min) to record dust devils, for which a sampling rate of ∼1 Hz or better is typically required.  The plan of this paper is as follow: In Section \ref{sec:miss_distance_effect}, we discuss the influence of the miss distance effect on the observed parameters for dust devil profiles and on their distributions. In