TY - JOUR
T1 - Vertical sampling scales for atmospheric boundary layer measurements from small unmanned aircraft systems (sUAS)
AU - Hemingway, Benjamin L.
AU - Frazier, Amy E.
AU - Elbing, Brian R.
AU - Jacob, Jamey D.
N1 - Funding Information:
Acknowledgments: This research is supported by a grant from the U.S. National Science Foundation (NSF) [IIA-1539070] “RII Track-2 FEC: Unmanned Aircraft Systems for Atmospheric Physics”. The authors would like to thank Taylor Mitchell, Jordan Feight, and Geoffrey Donnell from Oklahoma State University and Dr. Phil Chilson from the University of Oklahoma for helping with data collection and useful discussions.
Publisher Copyright:
© 2017 by the authors.
PY - 2017/9/13
Y1 - 2017/9/13
N2 - The lowest portion of the Earth's atmosphere, known as the atmospheric boundary layer (ABL), plays an important role in the formation of weather events. Simple meteorological measurements collected from within the ABL, such as temperature, pressure, humidity, and wind velocity, are key to understanding the exchange of energy within this region, but conventional surveillance techniques such as towers, radar, weather balloons, and satellites do not provide adequate spatial and/or temporal coverage for monitoring weather events. Small unmanned aircraft, or aerial, systems (sUAS) provide a versatile, dynamic platform for atmospheric sensing that can provide higher spatio-temporal sampling frequencies than available through most satellite sensing methods. They are also able to sense portions of the atmosphere that cannot be measured from ground-based radar, weather stations, or weather balloons and have the potential to fill gaps in atmospheric sampling. However, research on the vertical sampling scales for collecting atmospheric measurements from sUAS and the variabilities of these scales across atmospheric phenomena (e.g., temperature and humidity) is needed. The objective of this study is to use variogram analysis, a common geostatistical technique, to determine optimal spatial sampling scales for two atmospheric variables (temperature and relative humidity) captured from sUAS. Results show that vertical sampling scales of approximately 3 m for temperature and 1.5-2 m for relative humidity were sufficient to capture the spatial structure of these phenomena under the conditions tested. Future work is needed to model these scales across the entire ABL as well as under variable conditions.
AB - The lowest portion of the Earth's atmosphere, known as the atmospheric boundary layer (ABL), plays an important role in the formation of weather events. Simple meteorological measurements collected from within the ABL, such as temperature, pressure, humidity, and wind velocity, are key to understanding the exchange of energy within this region, but conventional surveillance techniques such as towers, radar, weather balloons, and satellites do not provide adequate spatial and/or temporal coverage for monitoring weather events. Small unmanned aircraft, or aerial, systems (sUAS) provide a versatile, dynamic platform for atmospheric sensing that can provide higher spatio-temporal sampling frequencies than available through most satellite sensing methods. They are also able to sense portions of the atmosphere that cannot be measured from ground-based radar, weather stations, or weather balloons and have the potential to fill gaps in atmospheric sampling. However, research on the vertical sampling scales for collecting atmospheric measurements from sUAS and the variabilities of these scales across atmospheric phenomena (e.g., temperature and humidity) is needed. The objective of this study is to use variogram analysis, a common geostatistical technique, to determine optimal spatial sampling scales for two atmospheric variables (temperature and relative humidity) captured from sUAS. Results show that vertical sampling scales of approximately 3 m for temperature and 1.5-2 m for relative humidity were sufficient to capture the spatial structure of these phenomena under the conditions tested. Future work is needed to model these scales across the entire ABL as well as under variable conditions.
KW - Atmospheric physics
KW - Drones
KW - Geostatistics
KW - Meteorology
KW - Spatial sampling
KW - Unmanned aerial vehicles (UAV)
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U2 - 10.3390/atmos8090176
DO - 10.3390/atmos8090176
M3 - Article
AN - SCOPUS:85029840541
SN - 2073-4433
VL - 8
JO - ATMOSPHERE
JF - ATMOSPHERE
IS - 9
M1 - 176
ER -