IEEE Robotics & Automation Magazine - March 2012 - 86

penetration (Figure 1) [10], water condition mapping [11],
and harmful algal bloom tracking [12].
The National Oceanic and Atmospheric Administration (NOAA) and the National Aeronautics and Space
Administration (NASA) have recognized the benefits that
UASs provide for atmospheric sampling [13]. Based on
field experience utilizing a diverse set of measurement
capabilities [7], [13]-[16], NOAA has suggested that current efforts with UASs should be expanded to further
enhance climate study and characterize meteorological
processes [3]. UASs are potentially useful for the study of a
wide variety of atmospheric phenomena and processes,
including thunderstorm outflows and gust fronts, landfalling hurricane boundary-layer circulations, planetary
boundary-layer fluxes (particularly those relevant to climate dynamics), atmospheric responses to fires, pollutant
dispersion, and terrain-driven circulation systems.
While UASs have primarily been deployed to study
atmospheric phenomena that persist for days or longer [7],
[9], [13]-[16], there is an immediate utility in UASs for
facilitating new knowledge through observations of atmospheric phenomena with representative timescales on the
order of hours or minutes [17]. Severe local storms are
good examples of such phenomena [18]. These types of
storms and the phenomena that they produce are challenging to observe and study because of their intensity,
small spatial scale, and tendency for rapid development
[18]. Two examples of severe local storm phenomena are
presented below.
Tornadogenesis
Effective advanced warning systems could drastically
reduce the loss of life and damage caused by tornadoes.
Unfortunately, the understanding of tornadogenesis will
not progress until there are in situ measurements of thermodynamic and microphysical properties aloft in the
vitally important rear-flank region of supercell storms

Figure 1. The Tempest unmanned aircraft with a funnel cloud
on the horizon, aligned with the aircraft midpoint.

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[17]. The process of tornado formation occurs in regions
that are 1-10 km wide, within a few kilometers of the
ground, and in less than 20 min after the first manifestation of tornado potential. Recent hypotheses suggest that
thunderstorm downdrafts must be negatively buoyant aloft
but should arrive at the ground with nearly neutral buoyancy through compressional warming to promote tornado
formation [19], [20]. UASs are exceptionally well suited to
measure these buoyancy characteristics in an environment
with flow variations that are too extreme for manned aircraft observations.
Airmass Boundaries
Airmass boundaries (e.g., drylines, cold fronts, and thunderstorm gust fronts) are ubiquitous phenomena in the
atmosphere and can play a significant role in the development of supercell thunderstorms and tornadoes [21].
Previous methods for collecting in situ measurements of
airmass boundaries do not provide significant spatiotemporal sampling [22]. Airmass boundaries are characterized
by an along-boundary scale (hundreds to thousands of
kilometers), that enables tracking via existing observation
networks. However, the processes associated with airmass
boundaries that are relevant to storm initiation and intensification are mainly dependent on approximately 10-km
scale cross-boundary gradients of density and moisture
[23], [24] that are amenable to sampling with UASs [25].
The autonomous targeted observation of complex environmental phenomena is enabled by a planning framework
that combines real-time science-driven control with online
high-resolution modeling and data assimilation. For severe
local storms, targeted observation can be enabled by the
integration of multiple sensor systems (Figure 2) such as
mobile Doppler radar that can provide three-dimensional
(3-D) wind fields [26] for energy-aware path planning by in
situ aircraft and data assimilation in online models. Underwater [8], [12], terrestrial/surface [11], and airborne [7], [9],
[10] domains present unique challenges for the robotic sampling systems performing targeted observations that can be
broken down into three main categories: regulatory, logistical, and technical.
This article discusses specific challenges in developing
UASs for sampling severe local storms and related phenomena [27]. The development of the Tempest UAS [10]
will be used as a guiding example (Figure 1) throughout
this article. The Tempest UAS was deployed as part of the
second verification of the origins of rotation in tornadoes
experiment (VORTEX2) [17] to sample the rear-flank
gust front of supercell thunderstorms [10]. The Tempest
represents the state of the art in airborne sampling systems
due to its networked command and control architecture
and concept of operations (CONOPS) for flight in the
U.S. National Airspace System (NAS). The major challenges described here played a role in the design of the
Tempest UAS and will shape future robotic airborne sampling systems.



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