Vertical sampling scales for atmospheric boundary layer measurements from small unmanned aircraft systems (sUAS)

Atmosphere

Volumn 8, Issue 9, 2017, Pages

  Hemingway, Benjamin L ^a   Frazier, Amy E ^a   Elbing, Brian R ^b   Jacob, Jamey D ^b  

^a OKLAHOMA STATE UNIVERSITY   (United States)

^b Oklahoma State University   (United States)

Author keywords

Atmospheric physics; Drones; Geostatistics; Meteorology; Spatial sampling; Unmanned aerial vehicles (UAV)

Indexed keywords

ATMOSPHERIC BOUNDARY LAYER; ATMOSPHERIC TEMPERATURE; BOUNDARY LAYERS; DRONES; EARTH ATMOSPHERE; FIGHTER AIRCRAFT; GEOPHYSICS; METEOROLOGICAL BALLOONS; METEOROLOGY; RADAR; RADAR MEASUREMENT; RADAR SIGNAL PROCESSING; RADAR STATIONS; SPACE-BASED RADAR; UNMANNED AERIAL VEHICLES (UAV); WEATHER INFORMATION SERVICES; WEATHER SATELLITES;

ATMOSPHERIC PHYSICS; BOUNDARY LAYER MEASUREMENTS; GEO-STATISTICS; GEOSTATISTICAL TECHNIQUES; METEOROLOGICAL MEASUREMENTS; SPATIAL SAMPLING; TEMPERATURE AND HUMIDITIES; TEMPERATURE AND RELATIVE HUMIDITY;

ATMOSPHERIC HUMIDITY;

AIRCRAFT; ATMOSPHERIC DYNAMICS; BALLOON OBSERVATION; BOUNDARY LAYER; GEOSTATISTICS; GROUND-BASED MEASUREMENT; MEASUREMENT METHOD; RELATIVE HUMIDITY; REMOTE SENSING; SAMPLING; UNMANNED VEHICLE;

EID: 85029840541     PISSN: None     EISSN: 20734433     Source Type: Journal    
DOI: 10.3390/atmos8090176     Document Type: Article

References (37)

1. Stull, R.B. An Introduction to Boundary Layer Meteorology, 1st ed.; Kluwer Academic Publishers: Dordrecht, The Netherlands, 1988.
2. Garratt, J.R. The Atmospheric Boundary Layer, 1st ed.; Cambridge University Press: Cambridge, New York, NY, USA, 1994.
3. Mayer, S.; Sandvik, A.; Jonassen, M. O.; Reuder, J. Atmospheric profiling with the UAS SUMO: A new perspective for the evaluation of fine-scale atmospheric models. Meteorol. Atmos. Phys. 2012, 116, 15-26.
4. LaDue, D.S.; Heinselman, P.L.; Newman, J.F. Strengths and limitations of current radar systems for two stakeholder groups in the southern plains. Bull. Am. Meteorol. Soc. 2010, 91, 899-910.
5. Frew, E.W.; Elston, J.; Argrow, B.; Houston, A.; Rasmussen, E. Sampling severe local storms and related phenomena: Using unmanned aircraft systems. IEEE Robot. Autom. Mag. 2012, 19, 85-95.
6. McPherson, R.A.; Fiebrich, C.A.; Crawford, K. C.; Kilby, J.R.; Grimsley, D.L.; Martinez, J.E.; Basara, J.B.; Illston, B.G.; Morris, D.A.; Kloesel, K.A. Statewide monitoring of the mesoscale environment: A technical update on the Oklahoma Mesonet. J. Atmos. Ocean. Tech. 2007, 24, 301-321.
7. Fujita, T.T. A Review of Researches on Analytical Mesometeorology; Mesometeorology Project: Department of the Geophysical Sciences, University of Chicago, Chicago, IL, USA, 1962.
8. Hill, M.; Konrad, T.; Meyer, J.; Rowland, J. A small, radio-controlled aircraft as a platform for meteorological sensors. Appl. Phys. Lab. Tech. Digest 1970, 10, 11-19.
9. Jensen, J.R. Introductory Digital Image Processing: A Remote Sensing Perspective; Prentice Hall, Inc.: Old Tappan, NJ, USA, 1986.
10. Doviak, R.J.; Zrnic, D.S. Doppler Radar & Weather Observations; Academic Press: Cambridge, MA, USA, 2014.
11. Bendix, J.; Fries, A.; Zárate, J.; Trachte, K.; Rollenbeck, R.; Pucha-Cofrep, F.; Paladines, R.; Palacios, I.; Orellana, J.; O'ate-Valdivieso, F. RadarNet-Sur FirstWeather Radar Network In Tropical High Mountains. Bull. Am. Meteorol. Soc. 2017, 98, 1235-1254.
12. RoyChowdhury, A.; Sheldon, D.; Maji, S.; Learned-Miller, E. Distinguishing Weather Phenomena from Bird Migration Patterns in Radar Imagery. In Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Las Vegas, NV, USA, 26 June-1 July 2016; pp. 10-17.
13. Farnsworth, A.; Van Doren, B.M.; Hochachka, W.M.; Sheldon, D.; Winner, K.; Irvine, J.; Geevarghese, J.; Kelling, S. A characterization of autumn nocturnal migration detected by weather surveillance radars in the northeastern USA. Ecol. Appl. 2016, 26, 752-770.
14. Golbon-Haghighi, M.-H.; Zhang, G.; Li, Y.; Doviak, R.J. Detection of Ground Clutter fromWeather Radar Using a Dual-Polarization and Dual-Scan Method. Atmosphere 2016, 7, 83.
15. Frazier, A.E.; Mathews, A.J.; Hemingway, B.; Crick, C.; Martin, E.; Smith, S.W. Integrating unmanned aircraft systems (UAS) into GIScience: Challenges and opportunities. Conference Presentation, GI_Forum, Salzburg, Austria, 3-6 July 2017.
16. Federal Aviation Administration. Part 107 of the Small Unmanned Aircraft Regulations. Available online: https://www.faa.gov/news/fact_sheets/news_story.cfm?newsId=20516 (assessed on 19 March 2017).
17. Elston, J.; Argrow, B.; Stachura, M.; Weibel, D.; Lawrence, D.; Pope, D. Overview of small fixed-wing unmanned aircraft for meteorological sampling. J. Atmos. Ocean. Tech. 2015, 32, 97-115.
18. Houston, A.L.; Argrow, B.; Elston, J.; Lahowetz, J.; Frew, E.W.; Kennedy, P.C. The collaborative Colorado-Nebraska unmanned aircraft system experiment. Bull. Am. Meteorol. Soc. 2012, 93, 39-54.
19. Roadman, J.; Elston, J.; Argrow, B.; Frew, E. Mission Performance of the Tempest Unmanned Aircraft System in Supercell Storms. J. Aircraft. 2012, 49, 1821-1830.
20. Cook, D.; Strong, P.; Garrett, S.; Marshall, R. A small unmanned aerial system (UAS) for coastal atmospheric research: Preliminary results from New Zealand. J. R. Soc. N. Z. 2013, 43, 108-115.
21. Cassano, J.J. Observations of atmospheric boundary layer temperature profiles with a small unmanned aerial vehicle. Antarct. Sci. 2014, 26, 205-213.
22. Bolstad, P. GIS Fundamentals: A First Text on Geographic Information Systems, 2nd ed.; Eider Press: White Bear lake, MN, USA, 2005.
23. Crick, C.; Pfeffer, A. Loopy belief propagation as a basis for communication in sensor networks. In UAI'03, Proceedings of the Nineteenth Conference on Uncertainty in Artificial Intelligence; Morgan Kaufmann Publishers Inc.: San Francisco, CA, USA, 2003; pp. 159-166.
24. Isaaks, E.H.; Srivastava, R.M. Applied Geostatistics; Oxford University Press: England, UK, 1989.
25. Burrough, P.A.; McDonnell, R.; McDonnell, R.A.; Lloyd, C.D. Principles of Geographical Information Systems; Oxford University Press: England, UK, 2015.
26. Oliver, M.A.; Webster, R. Basic Steps in Geostatistics: The Variogram and Kriging; Springer: New York, NY, USA, 2015.
27. Pebesma, E.J. Multivariable geostatistics in S: The gstat package. Comput. Geosci. 2004, 30, 683-691.
28. R Core Team. R: A Language and Environment for Statistical Computing. Available online: https://www.rproject. org/ (accessed on 19 March 2017).
29. Chilson, P.; Huck, R.; Fiebrich, C.; Cornish, D.; Wawrzyniak, T.; Mazuera, S.; Dixon, A.; Burns, E.; Greene, B. Calibration and Validation of Weather Sensors for Rotary-Wing UAS: The Devil is in the Details. In Proceedings of the 97th American Meteorological Society Annual Meeting, Seattle, WA, USA, 21 January 2017.
30. Jacob, J.; Axisa, D.; Oncley, S. Unmanned Aerial Systems for Atmospheric Research: Instrumentation Isues for Atmospheric Measurements. In Proceedings of the NCAR/EOL Community Workshop for Unmanned Aerial Systems for Atmospheric Research, Boulder, CO, USA, 21-24 February 2017.
31. Dyer, A. A review of flux-profile relationships. Bound. Layer Meteorol. 1974, 7, 363-372.
32. Essa, K.S. Estimation of Monin-Obukhov Length Using RIchardson and Bulk Richardson Number. In Proceedings of the 2nd Conference on Nuclear and Particle Physics, Cairo, Egypt, 13-17 November 1999.
33. Businger, J. A.; Wyngaard, J.C.; Izumi, Y.; Bradley, E.F. Flux-profile relationships in the atmospheric surface layer. J. Atmos. Sci. 1971, 28, 181-189.
34. Foken, T. 50 years of the Monin-Obukhov similarity theory. Bound. Layer Meteorol. 2006, 119, 431-447.
35. Yeung, P. Lagrangian investigations of turbulence. Annu. Rev. Fluid Mech. 2002, 34, 115-142.
36. Elbing, B.R.;Winkel, E.S.; Ceccio, S.L.; Perlin, M.; Dowling, D.R. High-reynolds-number turbulent-boundarylayer wall-pressure fluctuations with dilute polymer solutions. Phys. Fluids 2010, 22, 085104.
37. Horn, G.; Ouwersloot, H.; De Arellano, J.V.-G.; Sikma, M. Cloud Shading Effects on Characteristic Boundary-Layer Length Scales. Bound. Layer Meteorol. 2015, 157, 237-263.