Unmanned aircraft systems (UASs) offer innovative capabilities for
providing new perspectives on the atmosphere, and therefore atmospheric
scientists are rapidly expanding their use, particularly for studying the
planetary boundary layer. In support of this expansion, from 14 to 20 July 2018
the International Society for Atmospheric Research using Remotely piloted
Aircraft (ISARRA) hosted a community flight week, dubbed the Lower
Atmospheric Profiling Studies at Elevation – a Remotely-piloted Aircraft
Team Experiment (LAPSE-RATE; de Boer et al., 2020a). This field campaign
spanned a 1-week deployment to Colorado's San Luis Valley, involving over
100 students, scientists, engineers, pilots, and outreach coordinators.
These groups conducted intensive field operations using unmanned aircraft
and ground-based assets to develop comprehensive datasets spanning a variety
of scientific objectives, including a total of nearly 1300 research flights
totaling over 250 flight hours. This article introduces this campaign and
lays the groundwork for a special issue on the LAPSE-RATE project. The
remainder of the special issue provides detailed overviews of the datasets
collected and the platforms used to collect them. All of the datasets
covered by this special issue have been uploaded to a LAPSE-RATE community
set up at the Zenodo data archive (https://zenodo.org/communities/lapse-rate/, last access: 3 December 2020).
Background
Over the past decade there has been a significant expansion of the use of
unmanned aircraft systems (UASs) to make measurements of the atmosphere and
its interactions with the surface of the Earth. Rapid miniaturization and
cost reductions of instrumentation, other hardware, and the aircraft
platforms used to carry them have brought UAS-based atmospheric science to
many reaches of the globe. Specific advancements such as vertical takeoff
and landing capabilities offered by rotary-wing and hybrid UAS platforms
that limit the footprints required for launch and recovery (e.g., McGonigle
et al., 2008; Brady et al., 2016; Hemingway et al., 2017; Wildmann et al.,
2017) have made meteorological observations in focused areas feasible.
Scientifically, UAS-based atmospheric science campaigns have focused on
evaluating the planetary boundary layer (PBL) and atmospheric turbulence
(e.g., Reuder et al., 2012; Bonin et al., 2013; Lothon et al., 2014;
Altstädter et al., 2015; Lawrence and Balsley, 2013).
Together, fixed- and rotary-wing UASs have expanded observations beyond those
from operational meteorological observing networks (Hemmingway et al.,
2017), offering high-resolution insight into key parameters in locations
where surface observations may be challenging. Specific examples of
difficult-to-observe areas that have been sampled using UASs include in
tropical cyclones (e.g., Cione et al., 2016, 2019), over the
Arctic Ocean (e.g., Curry et al., 2004), in distant Antarctic regimes (e.g.
Knuth et al., 2013), during a total solar eclipse (Bailey, et al., 2019), and
in and around supercell thunderstorms (e.g., Elston et al., 2011). Beyond the
PBL, data gathered by UASs have shed light on interactions between the
atmosphere and other components of the Earth system (e.g., oceans, ice, land
surface), with campaigns covering both lower latitudes (e.g., Corrigan et
al., 2006; Ramanathan et al., 2007; van den Kroonenberg et al., 2008;
Houston et al., 2012) and higher latitudes (e.g., Curry et al., 2004; Cassano
et al., 2010; Knuth and Cassano, 2014; de Boer et al., 2018; Kral et al.,
2018).
With this rise in the popularity of the use of UASs in atmospheric science,
in 2008 the European Union funded a COST (Cooperation in Science and
Technology) action to advance and support the community of researchers
focused on using UASs for atmospheric science. From this COST action, the
International Society for Atmospheric Research using Remotely piloted
Aircraft (ISARRA) emerged. ISARRA has met annually since 2012, with five
meetings in Europe (2013, 2014, 2016, 2017, 2019) and two in the United
States (2015, 2018). The 2018 meeting, hosted by a joint committee of
representatives from The University of Colorado, the National Center for
Atmospheric Research (NCAR), and the National Oceanic and Atmospheric
Administration (NOAA), was held in Boulder, Colorado, USA, between 9 and 12 July 2018 (de Boer et al., 2019). Since 2012, several ISARRA conferences have
featured coordinated flight activities to offer a field-based opportunity
for participants to share information on platforms and sensing capabilities
and promote collaboration between individual groups working towards similar
goals. The 2018 conference offered participants a field experience
highlighting Colorado-specific science topics and leveraging ongoing work
within the state of Colorado to foster community relations surrounding the
use of UASs. This week-long flight event, named Lower Atmospheric Profiling
Studies at Elevation – a Remotely-piloted Aircraft Team Experiment
(LAPSE-RATE) was held in the San Luis Valley (SLV) of south-central
Colorado from 14 to 21 July 2018, immediately following the 2018 ISARRA
conference.
Prior ISARRA flight campaigns generally focused on system intercomparison
and demonstrations. However, LAPSE-RATE set out to increase the coordination
and scientific value of this significant effort, shifting the focus to not
only offer opportunities for aircraft and sensor comparisons but also
target data collection on specific science themes identified collaboratively
by the community, including the following:
The morning boundary-layer transition. The diurnal cycle in temperature in the SLV can be substantial, making for
large swings between stable and convective boundary layers, with
near-surface temperatures changing by up to nearly 25 ∘C as part of the
diurnal cycle. This topic was sampled using a distributed profiling
approach, with measurement sites located geographically across different
surface types and across different parts of the valley.
Aerosol properties. A variety of particle sources in the SLV, including agriculture, the Great
Sand Dunes National Park, wildfires, biogenic emissions, and advection, make
this an interesting area to study aerosol properties and their variability.
Routine lower-atmospheric profiling allowed teams to document particle sizes
and concentrations and their connections to boundary-layer and synoptic-wind
regimes.
Valley drainage flows. The SLV itself is very broad and of a substantial scale (see Fig. 1), with
several smaller valleys feeding into it. Clear nights often result in
distinct density currents from these smaller valleys into the main SLV.
Targeted sampling within the Saguache Valley and its outflow area captured
the evolution of such a density current and provided data to map its outflow
into the SLV.
Deep convection initiation. Thunderstorms routinely form over the mountains surrounding the SLV, with
storms sometimes advecting into or forming over the central part of the
valley. Storm life cycles are thought to be impacted by local sources of
potential energy and/or coherent circulations tied to gradients of surface
types. Distributing teams throughout the northern portion of the valley to
make detailed measurements of the thermodynamic state and its evolution with
time across a variety of surface gradients offered data to evaluate whether
the surface plays a role in the development and evolution of valley storms.
Atmospheric turbulence profiling. Understanding atmospheric turbulence in the lower atmosphere is key to the
development of numerical models. Furthermore, turbulence can undermine the
performance of communication systems due to its impact on signal integrity.
Teams deployed a variety of measurement platforms to characterize the
diurnal cycle of turbulence intensity in the “high desert” environment of
SLV to provide a unique dataset on variability within the valley, terrain
effects, and the impact of low water vapor amounts on turbulence generation.
The current special issue provides information on datasets collected during
the LAPSE-RATE campaign. This introductory article provides background
information on the campaign itself and the general conditions that were
sampled throughout the week, with additional details on the campaign and
associated activities available in de Boer et al. (2020a). The subsequent
articles in the special issue describe, in detail, the datasets that were
collected by the various teams participating in the event. These details
include information on completed flights, platforms used for data
collection, specific flight permissions, the sensors deployed and their
expected accuracy, interesting conditions encountered, and an overview of
statistics related to the scientific objectives and individual datasets
obtained.
Campaign overview and logistics
The SLV is a high-altitude depositional basin located in south-central
Colorado (USA) with an average elevation of 2336 m above sea level (a.s.l.). The
full valley stretches approximately 200 km north to south and 120 km east to
west. It is surrounded by mountains, with the Sangre de Cristo mountain
range to the east and the San Juan mountain range to the west. Both of these
mountain ranges have peaks rising over 4200 m a.s.l., resulting in
an altitude difference of up to 2000 m above the valley floor. The central
valley is primarily flat, and land cover comprises mostly agriculture and
shrub or scrublands. The agricultural areas are irrigated using groundwater
and streams fed by snowmelt from the surrounding mountain ranges. The shrub
and scrubland areas include very arid regions, as well as areas that
are seasonally flooded and marshy. Another unique feature in the valley is
the approximately 600 km2 Great Sand Dunes National Park, which
includes a large area with expansive sand dunes, the tallest of which, Star
Dune, is approximately 230 m tall from the valley floor.
To collect measurements targeting the primary objectives discussed above,
teams deployed both UASs and surface-based instrumentation across the
northern half of the SLV (entire area shown on map in Fig. 1). Potential
sites were identified during scouting trips to the valley prior to the
flight event. The identified sites were spatially distributed and
represented a variety of different land cover and terrain conditions. Flight
permissions were secured from the Federal Aviation Administration (FAA), and
site access was secured from landowners prior to the flight event. On any given day, the
assembled flight teams (up to 22) from the participating organizations would
set up their flight and sampling operations at one of the preselected
sites. While the deployment configuration changed somewhat from day to day
based on the specific sampling objectives, many teams spent the majority of
the campaign sampling a single location. Additional details on which
specific teams were distributed to each individual sampling location are
provided in the remainder of the articles in this special issue. However, in
the current article we provide some insight into the general motivation
behind the selection of sampling locations for the different objectives
covered above.
Weather conditions experienced during the LAPSE-RATE campaign were excellent
for the operation of UASs and for studying the above-mentioned phenomena of
interest. Broadly speaking, the SLV was under the influence of a developing
North American Monsoon flow, whereby moisture from the Gulf of Mexico and
Pacific Ocean were periodically injected into a general region of
anticyclonic flow that varied in strength during the week-long field
experiment. High pressure was prevalent over the region during 14 July,
resulting in limited convection forming over the mountains surrounding the
SLV. A cold front passed through the region on 15 July and early on
16 July. This time period also featured upper-level advection of air
from the southwest, including moisture from the Pacific Ocean. In
combination, these conditions resulted in the development of more widespread
convective clouds and offered favorable conditions for evaluating convective
initiation. These storms produced only limited precipitation but did result
in lightning and significant and gusty winds. On 17 July, the
upper-level anticyclonic circulation re-established itself over the region,
reducing convective storm activity. This quieter flow regime persisted
through the rest of the campaign, resulting in generally dry conditions,
with only a limited number of thunderstorms occurring in the mountains
surrounding the SLV through the end of the experiment.
Each day of LAPSE-RATE featured well-defined diurnal cycles in temperature,
humidity, and winds. Mornings were characterized by calm winds and elevated
humidities with temperatures between 10 and 15 ∘C. Localized areas of fog were
observed early in the morning, particularly along the western portion of the
valley. Winds were generally stronger and gustier in the afternoon after
development of the convective boundary layer, with sustained wind speeds
reaching around 10 m s-1 at times. Higher gusts associated with
thunderstorm outflows were also observed locally. The weak winds that
occurred overnight into the late morning resulted in excellent conditions for
evaluating atmospheric variability forced by local phenomena, including
assessment of how surface property variability impacts boundary-layer
evolution and the evolution of density currents resulting from differential
cooling across the valley. The spatiotemporal variability in meteorological
conditions throughout the field experiment is evident in Fig. 2.
An overview of meteorological conditions observed in the San Luis
Valley during LAPSE-RATE. The two leftmost figures illustrate temperature
(a) and dew point (b) profiles obtained from radiosondes
launched at Leach Airport, with the colors representing the date of launch.
The center and righthand panels illustrate surface meteorology at three
different sites across the valley over the course of the week. These include
surface pressure (c), air temperature (d), relative
humidity (e), and wind speed (f). These observations were
obtained by the MURC vehicle (red), the Saguache Airport AWOS station (blue),
and the CLAMPS trailer (yellow).
LAPSE-RATE flights began on 14 July. This first day involved an
intercomparison of platforms and sensors performed at Leach Airport,
near the center of our operations area (point “E” in Fig. 1). This site
was chosen in part because the site features open space without nearby
structures, vegetation, or topography, allowing multiple UAS teams to safely
conduct flight operations at the same time. Additionally, the surrounding
surface was relatively homogeneous, with the site being largely surrounded
by irrigated agricultural lands and little in the way of nearby topography.
Finally, there was easy access for the University of Colorado's Mobile UAS
Research Collaboratory (MURC) vehicle, a platform that includes a suite of
meteorological instrumentation mounted on a 15 m tower (see de Boer et al.,
2020b, in this special issue) that was used for the intercomparison. Teams
were assigned specific flight times in proximity to the MURC instrumentation
throughout the course of 14 July. Results of this intercomparison can be
found in Barbieri et al. (2019) and largely showed good agreement between
the various platforms. Additional intercomparison work was carried out using
measurements obtained by the University of Oklahoma's Collaborative Lower
Atmospheric Mobile Profiling System (CLAMPS) and Doppler lidar systems
deployed by the University of Colorado (Bell et al., 2020a, b, in this special issue); one of the University of Colorado lidars is
pictured in the foreground of Fig. 1, point B.
For the remainder of LAPSE-RATE, participating teams were distributed based
on the specific science objective that was deemed most attractive based on
daily forecasts. This was largely decided the day before during an all-teams
briefing in which weather forecasts and platform readiness were discussed.
Forecast guidance for planning came through joint input from the National
Weather Service and high-resolution simulations from the Weather Research
and Forecasting (WRF) model (Pinto et al., 2020; Nolan et al., 2018).
Generally, days were divided into two basic categories: days where
convection was expected and days where it was not. Below, we provide
overviews of the sampling completed on each day of the campaign.
On 15 and 16 July, teams were deployed to collect data to understand the
development of convection over the valley. For the convective initiation and
development days, teams were instructed to fly from sites covering a variety
of surface types. The general idea was for all teams to conduct nearly
continuous profiling at these sites to capture the thermodynamic evolution
of the boundary layer and provide information on winds and turbulence (where
available) resulting in the organization of convection. In addition to the
teams deploying UASs, there were the previously mentioned surface-based
remote-sensing instruments (CLAMPS, Doppler lidars) deployed to Moffat
School, Saguache Airport, and Leach Airport (see Bell et al., 2020b, in this
special issue) as well as a variety of mobile systems that were deployed on
transects throughout the valley (de Boer et al., 2020b, in this special
issue).
On 17 July, teams were offered time to complete flight activities matching
their own primary objectives, without coordinated organization by the larger
group. Some teams conducted additional intercomparison flights, while others
conducted equipment evaluation flights to improve their sensing capabilities
and expand their operational envelopes.
Sampling on 18 July focused on the morning boundary-layer transition. During
this day, teams aimed to arrive at their distributed sampling sites at
sunrise (around 06:00 local time) to initiate flights and capture the
transition between the nighttime stable regime and the development of a
surface-radiation-driven convective boundary layer, with sampling continuing
until around midday. Teams were once again distributed across the valley at
sites featuring a variety of surface types, with some teams operating on
eastward-slanting slopes and others on westward-slanting slopes.
Surface-based assets were again located at Moffat School, Leach Airport, and
Saguache Airport.
A list of data-generating entities participating in LAPSE-RATE and
the individual roles that each entity filled during the campaign.
OrganizationPrimary roleRelevant publications (all in this ESSD special issue)University of Colorado BoulderCampaign coordination, operation of unmanned aircraft, deployment of surface-based Doppler lidar systems and mobile measurement systemde Boer et al. (2020b) de Boer et al. (2020c) Bell et al. (2020b)University of OklahomaOperation of unmanned aircraft, deployment ofCLAMPS surface observatoryPillar-Little et al. (2020)University of KentuckyOperation of unmanned aircraft, deployment of surface flux towerBailey et al. (2020)Oklahoma State UniversityOperation of unmanned aircraftNatalie et al. (2020)University of Nebraska–LincolnOperation of unmanned aircraft, deployment ofmobile measurement systemsIslam et al. (2020)Virginia TechOperation of unmanned aircraftNot applicableKansas State UniversityOperation of unmanned aircraft, deployment ofsurface aerosol instrumentationBrus et al. (2020)National Oceanic and Atmospheric Administration (Physical Sciences Laboratory, National Severe Storms Laboratory, Chemical Sciences Laboratory)Campaign coordination, campaign forecasting,launching of weather balloons, deployment ofmobile measurement systemde Boer et al. (2020c) Bell et al. (2020b)National Center for Atmospheric ResearchCampaign forecasting, production of numerical forecast products, modeling and postcampaign supportPinto et al. (2020)Finnish Meteorological InstituteOperation of unmanned aircraftBrus et al. (2020)Black Swift TechnologiesOperation of unmanned aircraftde Boer et al. (2020b)
Finally, 19 July focused on cold-air drainage flows that were set up during the
nighttime. For this effort, teams were distributed with a focus on the
Saguache Valley that feeds into the northwest corner of the SLV (around
point “B” in Fig. 1). Several teams were distributed in the Saguache
Valley itself, including at the Saguache Airport which has an automated
weather observing system (AWOS). An additional array of UAS platforms was
deployed in the block of agricultural fields situated at the outflow region
(near point “C” in Fig. 1). Further, some teams were situated within
different parts of the main valley, and two teams were assigned to conduct
flights in the valley feeding into the northern portion of the SLV (near
point “A” in Fig. 1).
The final day of the LAPSE-RATE campaign, 20 July, was once again open for
teams to conduct their own sampling activities throughout the SLV as needed
to accomplish individual goals and tasks. Some teams conducted additional
comparison flights with the MURC on this date.
Finally, given that only a limited number of teams were interested in
studying aerosol processes during the campaign, these measurements were made
continuously at a single site approximately 15 km north of Leach Airport, using UAS-based sensors as well as from the surface (see Brus et al.,
2020, in this special issue).
Overview of datasets
Participants in the LAPSE-RATE campaign spanned a variety of organizations
including various US and international universities, US federal
agencies, US and international institutes, and various companies in the
private sector. An overview of the groups responsible for the collection of
data during LAPSE-RATE, along with their specific roles and the special-issue publications that are connected to those activities, is provided in
Table 1. As mentioned above, these groups include operators of unmanned
aircraft, surface-based in situ and remote sensor systems, radiosondes, and
surface vehicles. Additionally, they include modelers, forecasters, and
outreach teams.
All of the datasets have been quality-controlled based on protocols
established by the individual teams. The details behind this quality control
are outlined in the individual articles and will not be explained in detail
here. However, our common goal was to provide a quality dataset that could
be leveraged by the community for scientific studies. Data are provided in
NetCDF format with a common file name structure. This structure is
xxx.ppppp.lv.yyyymmdd.hhmmss.cdf
using the following definitions:
xxx – institute
ppppp – a five-letter platform identifier
lv – the data file processing level
yyyymmdd – the file date (UTC) in year, month, day format
hhmmss – the file start time (UTC) in hours, minutes, seconds format
cdf – the NetCDF file extension.
As an example, a NetCDF file produced by the University of Colorado Boulder from the DataHawk UAS that includes non-quality-controlled data (in geophysical
units) collected starting at 11:30:54 UTC on 17 July 2018 would be named
UCB.DATHK.a1.20180717.113054.cdf.
The groups provided files at various levels of processing. These include
a0 – raw data converted to netCDF
a1 – calibration factors applied and converted to geophysical units
b1 – quality control (QC) checks applied to measurements to ensure that they are “in
bounds”; missing data points or those with bad values should be set to
-9999.9
c1 – derived or calculated value-added data product (VAP) using one or more
measured or modeled data products (a0 to c1) as input.
Note that it was not required (or expected) that all groups would submit all
data levels. For example, a0 data may be deemed too detailed, too large,
and without sufficient quality control to be useful to many interested users
and therefore may not be made available by many of the participating
groups. All groups sought to provide a1 or b1 data products where possible
as this level of processing offers the greatest potential for community
consumption and ensures some level of quality control.
Participating teams were requested to provide sufficient metadata in their
NetCDF files to allow users to understand and interpret the data stream.
This includes information that could be included in global metadata (i.e.
specific to the entire file) such as
location of sensor or platform (if stationary platform)
QC checks and flags applied
calibration procedural information as appropriate
principal investigator contact information.
Additionally, for individual variables, it was requested that teams provide
metadata to help the user understand how the measurement was obtained and
what it represents. This type of information could include
orientation – downwelling, upwelling, or dependent on the installation as
appropriate
missing data value applied to a given variable (e.g., -9999.9)
key information to characterize the measurement
the instrument or sensor used for the measurement (occasionally important
especially if it comes from a data stream containing results from several
instruments)
time interval information (e.g., averaging time and measurement intervals)
the units of the measurement
an indication that the data are best-estimate data or a calculated value
data stream; unless indicated otherwise, it is implicit that the measurement
is observed.
Data availability
Files from all teams are archived under individual DOIs at the Zenodo data
archive (https://www.zenodo.org/, last access: 3 December 2020), where a dedicated community has been established
for LAPSE-RATE (https://zenodo.org/communities/lapse-rate/, last access: 3 December 2020).
This community houses the data files along with additional metadata on the
datasets. In total, these files cover nearly 1300 flights and 250 flight
hours, along with data from related ground-based observing systems,
radiosondes, and numerical model output.
Summary
During the summer of 2018, a large group of atmospheric scientists and
engineers came together in the San Luis Valley of Colorado to conduct a
coordinated atmospheric measurement program using unmanned aircraft. This
group deployed fixed- and rotary-wing UASs, in combination with surface-based
in situ and remote sensors, and radiosondes to make comprehensive
measurements to demonstrate the utility of these platforms in understanding
a variety of boundary-layer phenomena including the morning boundary-layer
transition, density currents, convection initiation, aerosol processes, and
turbulence. Additionally, intercomparison efforts were undertaken to
evaluate to what extent these types of measurements can be used together. In
the end, a large number (> 1200) of flights were completed. This
article provides an overview of the campaign, the conditions sampled, and
the general structure of data collection. This overview introduces this
special issue on the LAPSE-RATE campaign, which hosts individual articles
from the teams involved that provide additional details on their platforms,
sensors, and flights. We hope that this issue will encourage widespread use
of the data, and we encourage individuals to reach out to the teams who
collected the datasets if they have interest in using them for their own
scientific purposes.
Author contributions
GB coordinated the logistics of the LAPSE-RATE field campaign and oversaw its completion. Additionally, GB led the formulation of this paper and wrote draft text and assembled figures. All other authors contributed to the development and execution of LAPSE-RATE and contributed to the development of this paper by providing information and editing text.
Competing interests
GB is the lead editor for the special issue in which this manuscript appears. Additionally, GB works as a consultant for Black Swift Technologies, who participated in LAPSE-RATE and contributed to the development of this paper.
Disclaimer
The views expressed in the article do not necessarily
represent the views of the Department of Energy (DOE) or the US Government. The US Government
retains and the publisher, by accepting the article for publication,
acknowledges that the US Government retains a nonexclusive, paid-up,
irrevocable, worldwide license to publish or reproduce the published form of
this work, or allow others to do so, for US Government purposes.
Special issue statement
This article is part of the special issue “Observational and model data from the 2018 Lower Atmospheric Process Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE) campaign”. It is a result of the International Society for Atmospheric Research using Remotely piloted Aircraft (ISARRA 2018) conference, Boulder, USA, 9–12 July 2018.
Acknowledgements
LAPSE-RATE was made possible by the active participation of
over 100 people. Limited financial support, specifically for participant
travel, was provided by the US National Science Foundation (NSF; AGS
1807199) and the US Department of Energy (DE-SC0018985). Partial support
was also provided by the US National Science Foundation through award
no. 1539070, Collaboration Leading Operational UAS Development for
Meteorology and Atmospheric Physics (CLOUDMAP), and award no.
CBET-1351411. Further, this work was authored in part by the National
Renewable Energy Laboratory, operated by Alliance for Sustainable Energy,
LLC, for the US Department of Energy (DOE) under contract no.
DE-AC36-08GO28308.
We
appreciate and acknowledge the long hours dedicated to this effort by
numerous participants not included in the author list of this overview
document, including many undergraduate and graduate students and other
early-career participants. We would also like to thank the San Luis Valley
community for welcoming us and providing access to land to conduct flight
operations, and we recognize the sponsors indicated in the acknowledgement
sections of the remaining special-issue articles for their support of this
effort.
Financial support
This research has been supported by the National Science Foundation (grant nos. AGS 1807199, 1539070, and CBET-1351411) and the US Department of Energy (grant nos. DE-SC0018985 and DE-AC36-08GO28308).
Review statement
This paper was edited by David Carlson and reviewed by two anonymous referees.
ReferencesAltstädter, B., Platis, A., Wehner, B., Scholtz, A., Wildmann, N., Hermann, M., Käthner, R., Baars, H., Bange, J., and Lampert, A.: ALADINA – an unmanned research aircraft for observing vertical and horizontal distributions of ultrafine particles within the atmospheric boundary layer, Atmos. Meas. Tech., 8, 1627–1639, 10.5194/amt-8-1627-2015, 2015.Bailey, S. C. C., Sama, M. P., Canter, C. A., Pampolini, L. F., Lippay, Z. S., Schuyler, T. J., Hamilton, J. D., MacPhee, S. B., Rowe, I. S., Sanders, C. D., Smith, V. G., Vezzi, C. N., Wight, H. M., Hoagg, J. B., Guzman, M. I., and Smith, S. W.: University of Kentucky measurements of wind, temperature, pressure and humidity in support of LAPSE-RATE using multisite fixed-wing and rotorcraft unmanned aerial systems, Earth Syst. Sci. Data, 12, 1759–1773, 10.5194/essd-12-1759-2020, 2020.Bailey, S. C. C., Canter, C., Sama, M., Houston, A. L., and Smith, S. W.:
Unmanned aerial vehicles reveal impact of total solar eclipse on atmospheric
surface layer, Proc. R. Soc. A., 475, 20190212, 10.1098/rspa.2019.0212, 2019.Barbieri, L., Kral, S. T., Bailey, S. C. C., Frazier, A. E., Jacob, J. D.,
Reuder, J., Brus, D., Chilson, P. B., Crick, C., Detweiler, C., Doddi, A.,
Elston, J., Foroutan, H., González-Rocha, J., Greene, B. R., Guzman,
M. I., Houston, A. L., Islam, A., Kemppinen, O., Lawrence, D., Pillar-Little,
E. A., Ross, S. D., Sama, M. P., Schmale, D. G., Schuyler, T. J., Shankar, A.,
Smith, S. W., Waugh, S., Dixon, C., Borenstein, S., and de Boer, G.:
Intercomparison of Small Unmanned Aircraft System (sUAS) Measurements for
Atmospheric Science during the LAPSE-RATE Campaign, Sensors, 19, 2179,
10.3390/s19092179, 2019.Bell, T. M., Greene, B. R., Klein, P. M., Carney, M., and Chilson, P. B.: Confronting the boundary layer data gap: evaluating new and existing methodologies of probing the lower atmosphere, Atmos. Meas. Tech., 13, 3855–3872, 10.5194/amt-13-3855-2020, 2020a.
Bell, T. M., Klein, P. M., Lundquist J. K., and Waugh, S.: Remote sensing and
radiosonde datasets collected in the San Luis Valley during the LAPSE-RATE
campaign, Earth Sys. Sci. Data, in preparation, 2020b.Bonin, T., Chilson, P., Zielke, B., and Fedorovich, E.: Observations of the
Early Evening Boundary-Layer Transition Using a Small Unmanned Aerial
System, Bound.-Lay. Meteorol. 146, 119-132. 10.1007/s10546-012-9760-3, 2013.Brady, J. M., Stokes, M. D., Bonnardel, J., and Bertram, T. H.: Characterization
of a quadrotor unmanned aircraft system for aerosol particle concentration
measurements, Environ. Sci. Technol., 50, 1376–1383, 10.1021/acs.est.5b05320, 2016.Brus, D., Gustafsson, J., Kempinen, O., de Boer, G., and Hirsikko, A.: Atmospheric aerosol, gases and meteorological parameters measured during the LAPSE-RATE campaign, Earth Syst. Sci. Data Discuss., 10.5194/essd-2020-251, in review, 2020.Cassano, J. J., Maslanik, J. A., Zappa, C. J., Gordon, A. L., Cullather, R.
I., and Knuth, S. L.: Observations of Antarctic polynya with unmanned
aircraft systems, Eos Trans. AGU, 91, 245–246, 10.1029/2010EO280001, 2010.Cione, J. J., Kalina, E. A., Uhlhorn, E. W., Farber, A. M., and Damiano, B.:
Coyote unmanned aircraft system observations in hurricane Edouard (2014),
Earth Space Sci., 3, 370–380, 10.1002/2016EA000187, 2016.Cione, J. J., Bryan, G. H., Dobosy, R., Zhang, J. A., de Boer, G., Aksoy, A.,
Wadler, J. B., Kalina, E. A., Dahl, B. A., Ryan, K., Dumas, E., Marks, F. D.,
Farber, A. M., and Chen, X.: Eye of the storm: Observing hurricanes with a
small unmanned aircraft system, B. Am. Meteorol. Soc., 101, E186–E205, 10.1175/BAMS-D-19-0169.1, 2019.
Corrigan, C., Ramanathan, V., Ramana, M. V., Kim, D., and Roberts, G.: Chasing black carbon using autonomous unmanned aerial vehicles, Eos, Trans. Amer. Geophys. Union, 87 (Fall Meeting Suppl.), Abstract A43A-0106, 2006.Curry, J. A., Maslanik, J., Holland, G. J., and Pinto, J.: Applications of
aerosondes in the Arctic, B. Am. Meteorol. Soc., 85, 1855–1861, 10.1175/BAMS-85-12-1855, 2004.de Boer, G., Ivey, M., Schmid, B., Lawrence, D., Dexheimer, D., Mei, F., Hubbe, J., Bendure, A., Hardesty, J., Shupe, M. D., McComiskey, A., Telg, H., Schmitt, C., Matrosov, S. Y., Brooks, I., Creamean, J., Solomon, A., Turner, D. D., Williams, C., Maahn, M., Argrow, B., Palo, S., Long, C. N., Gao, R., and Mather, J.: A Bird’s-Eye View: Development of an Operational ARM Unmanned Aerial Capability for Atmospheric Research in Arctic Alaska, B. Am. Meteorol. Soc., 99, 1197–1212, 10.1175/BAMS-D-17-0156.1, 2018.de Boer, G., Diehl, C., Jacob, J., Houston, A., Smith, S. W., Chilson, P.,
Schmale III, D. G., Intrieri, J., Pinto, J., Elston, J., Brus, D., Kemppinen,
O., Clark, A., Lawrence, D., Bailey, S. C. C., Sama, M. P., Frazier, A., Crick,
C., Natalie, V., Pillar-Little, E. A., Klein, P., Waugh, S., Lundquist, J. K.,
Barbieri, L., Kral, S. T., Jensen, A. A., Dixon, C., Borenstein, S.,
Hesselius, D., Human, K., Hall, P., Argrow, B., Thornberry, T., Wright, R.,
and Kelly, J. T.: Development of community, capabilities and understanding
through unmanned aircraft-based atmospheric research: The LAPSE-RATE
campaign, B. Am. Meteorol. Soc., 101, E684–E699, 10.1175/BAMS-D-19-0050.1, 2020a.de Boer, G., Waugh, S., Erwin, A., Borenstein, S., Dixon, C., Shanti, W., Houston, A., and Argrow, B.: Measurements from mobile surface vehicles during LAPSE-RATE, Earth Syst. Sci. Data Discuss., 10.5194/essd-2020-173, in review, 2020b.
de Boer, G., Dixon, C., Borenstein, S., Lawrence, D. A., Elston, J.,
Hesselius, D., Stachura, M., Laurence III, R., Swenson, S., Choate, C. M.,
Doddi, A., Sesnic, A., Glasheen, K., Laouar, Z., Quimby, F., Frew, E., and
Argrow, B. M.: UAS-based observations of the lower atmosphere during
LAPSE-RATE: University of Colorado and Black Swift Technologies
contributions, Earth Sys. Sci. Data, submitted, 2020c.de Boer, G., Argrow, B., Cassano, J., Cione, J., Frew, E., Lawrence, D.,
Wick, G., and Wolff, C.: Advancing unmanned aerial capabilities for
atmospheric research, B. Am. Meteorol. Soc., 100, ES105–ES108, 10.1175/BAMS-D-18-0254.1, 2019.Elston, J. S., Roadman, J., Stachura, M., Argrow, B., Houston, A., and Frew,
E.: The tempest unmanned aircraft system for in situ observations of
tornadic supercells: Design and VORTEX2 flight results, J. Field Robotics,
28, 461-483, 10.1002/rob.20394, 2011.Hemingway, B. L., Frazier, A. E., Elbing, B. R., and Jacob, J. D.: Vertical
Sampling Scales for Atmospheric Boundary Layer Measurements from Small
Unmanned Aircraft Systems (sUAS), Atmosphere, 8, 176, 10.3390/atmos8090176, 2017.Houston, A. L., Argrow, B., Elston, J., Lahowetz, J., Frew, E. W., and Kennedy, P. C.: The Collaborative Colorado–Nebraska Unmanned Aircraft System Experiment, B. Am. Meteorol. Soc., 93, 39–54, 10.1175/2011BAMS3073.1, 2012.
Islam, A., Shankar, A., Houston, A. L., and Detweiler, C.: University of
Nebraska UAS profiling during LAPSE-RATE, Earth Syst. Sci. Data Discuss., submitted, 2020.Knuth, S. L., Cassano, J. J., Maslanik, J. A., Herrmann, P. D., Kernebone, P. A., Crocker, R. I., and Logan, N. J.: Unmanned aircraft system measurements of the atmospheric boundary layer over Terra Nova Bay, Antarctica, Earth Syst. Sci. Data, 5, 57–69, 10.5194/essd-5-57-2013, 2013.Knuth, S. L. and Cassano, J. J.: Estimating sensible and latent heat fluxes
using the integral method from in situ aircraft measurements, J. Atmos. Ocean. Tech., 31,
1964–1981, 10.1175/JTECH-D-14-00008.1, 2014.Kral, S., Reuder, J., Vihma, T., Suomi, I., O'Connor, E., Kouznetsov, R.,
Wrenger, B., Rautenberg, A., Urbancic, G., Jonassen, M., Båserud, L.,
Maronga, B., Mayer, S., Lorenz, T., Holtslag, A., Steeneveld, G.-J., Seidl,
A., Müller, M., Lindenberg, C., Langohr, C., Voss, H., Bange, J.,
Hundhausen, M., Hilsheimer, P., and Schygulla, M.: Innovative Strategies for
Observations in the Arctic Atmospheric Boundary Layer (ISOBAR) – The
Hailuoto 2017 Campaign, Atmosphere, 9, 268, 10.3390/atmos9070268, 2018.Lawrence, D. A. and Balsley, B. B.: High-Resolution Atmospheric Sensing of
Multiple Atmospheric Variables Using the DataHawk Small Airborne Measurement
System, J. Atmos. Ocean. Tech., 30, 2352–2366, 10.1175/JTECH-D-12-00089.1, 2013.Lothon, M., Lohou, F., Pino, D., Couvreux, F., Pardyjak, E. R., Reuder, J., Vilà-Guerau de Arellano, J., Durand, P., Hartogensis, O., Legain, D., Augustin, P., Gioli, B., Lenschow, D. H., Faloona, I., Yagüe, C., Alexander, D. C., Angevine, W. M., Bargain, E., Barrié, J., Bazile, E., Bezombes, Y., Blay-Carreras, E., van de Boer, A., Boichard, J. L., Bourdon, A., Butet, A., Campistron, B., de Coster, O., Cuxart, J., Dabas, A., Darbieu, C., Deboudt, K., Delbarre, H., Derrien, S., Flament, P., Fourmentin, M., Garai, A., Gibert, F., Graf, A., Groebner, J., Guichard, F., Jiménez, M. A., Jonassen, M., van den Kroonenberg, A., Magliulo, V., Martin, S., Martinez, D., Mastrorillo, L., Moene, A. F., Molinos, F., Moulin, E., Pietersen, H. P., Piguet, B., Pique, E., Román-Cascón, C., Rufin-Soler, C., Saïd, F., Sastre-Marugán, M., Seity, Y., Steeneveld, G. J., Toscano, P., Traullé, O., Tzanos, D., Wacker, S., Wildmann, N., and Zaldei, A.: The BLLAST field experiment: Boundary-Layer Late Afternoon and Sunset Turbulence, Atmos. Chem. Phys., 14, 10931–10960, 10.5194/acp-14-10931-2014, 2014.McGonigle, A. J. S., Aiuppa, A., Giudice, G., Tamburello, G., Hodson, A.
J., and Gurrieri, S.: Unmanned aerial vehicle measurements of volcanic
carbon dioxide fluxes, Geophys. Res. Lett., 35, L06303, 10.1029/2007GL032508,
2008.
Natalie, V., Avery, A., Hemingway, B., Frazier, A., Crick, C., and Jacob, J.:
Kinematic and thermodynamic atmospheric boundary layer observations in the
San Luis Valley, CO via unmanned aircraft systems during the LAPSE-RATE
field campaign, Earth Syst. Sci. Data, in preparation, 2020.Nolan, P., Pinto, J., Gonzalez-Rocha, J., Jensen, A., Vezzi, C. N., Bailey, S. C. C., de Boer, G., Diehl, C., Laurence III, R., Powers, C. W., Foroutan, H., Ross, S. D., and Schmale III, D. G.: Coordinated unmanned aircraft system (UAS) and ground-based weather measurements to predict lagrangian coherent structures (LCSs), Sensors, 18, 4448, 10.3390/s18124448, 2018.Pillar-Little, E. A., Greene, B. R., Lappin, F. M., Bell, T. M., Segales, A. R., de Azevedo, G. B. H., Doyle, W., Kanneganti, S. T., Tripp, D. D., and Chilson, P. B.: Observations of the thermodynamic and kinematic state of the atmospheric boundary layer over the San Luis Valley, CO using remotely piloted aircraft systems during the LAPSE-RATE field campaign, Earth Syst. Sci. Data Discuss., 10.5194/essd-2020-194, in review, 2020.Pinto, J. O., Jensen, A. A., Jiménez, P. A., Hertneky, T., Muñoz-Esparza, D., Dumont, A., and Steiner, M.: Realtime WRF LES Simulations to Support UAS Flight Planning and Operations During 2018 LAPSE-RATE, Earth Syst. Sci. Data Discuss., 10.5194/essd-2020-242, in review, 2020.Ramanathan, V., Ramana, M. V., Roberts, G., Kim, D., Corrigan, C., Chung, C., and Winker, D.: Warming trends in Asia amplified by brown cloud solar absorption, Nature, 448, 575–579, 10.1038/nature06019, 2007.
Reuder, J., Jonassen, M. O., and Ólafsson, H.: The Small Unmanned
Meteorological Observer SUMO: Recent developments and applications of a
micro-UAS for atmospheric boundary layer research, Acta Geophys., 60, 1454–1473, 10.2478/s11600-012-0042-8, 2012.Van den Kroonenberg, A., Martin, T., Buschmann, M., Bange, J., and Vorsmann, P.: Measuring the wind vector using the autonomous mini aerial vehicle M2AV, J. Atmos. Ocean. Tech., 25, 1969–1982, 10.1175/2008JTECHA1114.1, 2008.Wildmann, N., Bernard, S., and Bange, J.: Measuring the local wind field at
an escarpment using small remotely-piloted aircraft, Renew. Energ., 103, 613–619,
10.1016/j.renene.2016.10.073, 2017.