deletions | additions       diff --git a/section_Formulating_the_Recovery_Biases__.tex b/section_Formulating_the_Recovery_Biases__.tex  index d2e25f9..a9754f8 100644  --- a/section_Formulating_the_Recovery_Biases__.tex  +++ b/section_Formulating_the_Recovery_Biases__.tex 
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\item A dust devil is carried past the sensor with the ambient wind field at a velocity $\upsilon$. For simplicity, we will assume the wind velocity vector is constant in magnitude and direction, while in reality, the ambient wind field carrying a devil can be complex, even causing multiple encounters between devil and sensor and consequently more complex pressure signals \citep{Lorenz_2013}. The upshot of this assumption is that a devil whose center passes directly over the sensor will register a pressure dip with a full-width at half-max in time $\Gamma^\prime_{\rm act} = \Gamma_{\rm act}/\upsilon$. For a more distant encounter, the profile width in time observed is $\Gamma^\prime_{\rm obs}$.  \item Many dust devil surveys (refs) impose a minimum pressure threshold $P_{\rm min}$, below which a putative pressure fluctuation is deemed statistically insignificant. For distant encounters with a devil, the observed pressure will fall below $P_{\rm min}$, and the devil will not be recovered. At the other end of the scale, basic thermodynamical limits likely restrict the maximum pressure depth a devil can have to some finite value, $P_{\rm max}$. Thus, we will assume the pressure signals for detected devils fall between these two limits. Likewise the $\Gamma_{\rm act}$-values fall between $\Gamma_{\rm min}$ and $\Gamma_{\rm max}$.  \item The distributions of $P_{\rm act}$ and $\Gamma_{\rm act}$, $n(P_{\rm act})$ and $n(\Gamma_{\rm act})$ respectively, are integrable and differentiable. The same is true for the distributions of observed dust devil parameters. 
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