Aeroecology pp 311-343 | Cite as

Inferring the State of the Aerosphere from Weather Radar

  • Eric Jacobsen
  • Valliappa Lakshmanan


Weather surveillance radars (see Chap.  12) are indispensable tools for characterizing the state of the aerosphere—the lower layer of the atmosphere used by flying animals—owing to their ability to remotely sense in-flight insects, birds, and bats at unprecedented temporal and spatial scales. The increasingly worldwide distribution of weather radars, their improving hardware and software, decades-long datasets, and capacity for revealing vertical and horizontal distributions make them well suited to mapping populations and movement from local to continental scales and for correlation with global datasets in other specializations like meteorology and geography. However, doing so requires care in processing the data and removing radar echoes that are unlikely to be biological. Moreover, radar design and the geometrically unique nature of their observations necessitate corrective methods for producing comparable data. Nevertheless, a parallel progression of meteorological and aerecological studies of how best to analyze radar data in spite of these observation inhomogeneities continues to yield fruitful research and new algorithms, continuously enhancing the ability to gain new insight into animal behavior in the aerosphere.



Several of the algorithms described in this chapter have been implemented within the Warning Decision Support System Integrated Information [WDSSII; Lakshmanan et al. (2007b)] as the w2merger and w2birddensity algorithms. WDSS-II is available for download at


  1. Able KP (1970) A radar study of the altitude of nocturnal passerine migration. Bird Band 41(4):282.
  2. Achtemeier GL (1991) The use of insects as tracers for “clear-air” boundary-layer studies by Doppler radar. J Atmos Ocean Technol 8(6):746–765.<0746:TUOIAT<2.0.CO;2
  3. Askelson M, Aubagnac J, Straka J (2000) An adaptation of the Barnes filter applied to the objective analysis of radar data. Mon Weather Rev 128(9):3050–3082CrossRefGoogle Scholar
  4. Beyer W (ed) (1987) CRC standard math tables, 18th edn. CRC Press, Boca RatonGoogle Scholar
  5. Bridge ES, Pletschet SM, Fagin T, Chilson PB, Horton KG, Broadfoot KR, Kelly JF (2015) Persistence and habitat associations of Purple Martin roosts quantified via weather surveillance radar. Landsc Ecol 31(1):43–53.
  6. Buler JJ, Dawson DK (2014) Radar analysis of fall bird migration stopover sites in the northeastern U.S. Condor 116(3):357–370.
  7. Buler J, Diehl R (2009) Quantifying bird density during migratory stopover using weather surveillance radar. IEEE Trans Geosci Remote Sens 47(8):2741–2751CrossRefGoogle Scholar
  8. Buler J, Lakshmanan V, La Puma D (2012) Improving weather radar data processing for biological research applications: final report. Technical report G11AC20489, Patuxent Wildlife Research Center, USGS, Laurel, MDGoogle Scholar
  9. Chilson PB, Frick WF, Kelly JF, Howard KW, Larkin RP, Diehl RH, Westbrook JK, Kelly TA, Kunz TH (2012a) Partly cloudy with a chance of migration: weather, radars, and aeroecology. Bull Am Meteorol Soc 93(5):669–686.
  10. Chilson PB, Frick WF, Stepanian PM, Shipley JR, Kunz TH, Kelly JF (2012b) Estimating animal densities in the aerosphere using weather radar: to Z or not to Z? Ecosphere 3(8):1–19.
  11. Cohen EB, Barrow WC, Buler JJ, Deppe JL, Farnsworth A, Marra PP, McWilliams SR, Mehlman DW, Wilson RR, Woodrey MS, Moore FR (2017) How do en route events around the Gulf of Mexico influence migratory landbird populations? Condor 119(2):327–343.
  12. Contreras RF, Frasier SJ (2008) High-resolution observations of insects in the atmospheric boundary layer. J Atmos Ocean Technol 25(12):2176–2187.
  13. Dean J, Ghemawat S (2008) Mapreduce: simplified data processing on large clusters. Commun ACM 51(1):107–113CrossRefGoogle Scholar
  14. Diehl RH, Larkin RP (2005) Introduction to the WSR-88D (NEXRAD) for ornithological research. In: Ralph CJ, Rich TD (eds) Bird conservation implementation and integration in the Americas: Proceedings of 3rd international partners in flight conference, Asilomar, CA. 20 24 March 2002. Gen. Tech. Rep. PSW-GTR-191, vol 2, U.S. Department of Agriculture, Forest Service, Pacific Southwest Research Station, Albany, NY, pp 876–888Google Scholar
  15. Diehl R, Larkin R, Black J, Moore F (2003) Radar observations of bird migration over the Great Lakes. Auk 120(2):278–290CrossRefGoogle Scholar
  16. Dokter AM, Liechti F, Stark H, Delobbe L, Tabary P, Holleman I (2011) Bird migration flight altitudes studied by a network of operational weather radars. J R Soc Interface 8:30–43CrossRefPubMedGoogle Scholar
  17. Dokter AM, Åkesson S, Beekhuis H, Bouten W, Buurma L, van Gasteren H, Holleman I (2013) Twilight ascents by common swifts, Apus apus, at dawn and dusk: acquisition of orientation cues? Anim Behav 85(3):545–552.
  18. Doviak R, Zrnic D (1993) Doppler radar and weather observations, 2nd edn. Academic Press, Cambridge, MAGoogle Scholar
  19. Drake VA (1984) The vertical distribution of macro-insects migrating in the nocturnal boundary layer: a radar study. Bound Lay Meteorol 28(3–4):353–374.
  20. Drake VA, Farrow RA (1988) The influence of atmospheric structure and motions on insect migration. Annu Rev Entomol 33(1):183–210.
  21. Eastwood E (1967) Radar ornithology. Methuen, LondonGoogle Scholar
  22. Farnsworth A, Van Doren BM, Hochachka WM, Sheldon D, Winner K, Irvine J, Geevarghese J, Kelling S (2016) A characterization of autumn nocturnal migration detected by weather surveillance radars in the northeastern USA. Ecol Appl 26(3):752–770CrossRefPubMedGoogle Scholar
  23. Frick WF, Stepanian PM, Kelly JF, Howard KW, Kuster CM, Kunz TH, Chilson PB (2012) Climate and weather impact timing of emergence of bats. PLoS One 7(8):e42737.
  24. Gauthreaux SA (1991) The flight behavior of migrating birds in changing wind fields. Am Zool 31(1):187–204CrossRefGoogle Scholar
  25. Gauthreaux SA, Belser C (2003) Radar ornithology and biological conservation. Auk 120(2):266–277CrossRefGoogle Scholar
  26. Gauthreaux SA, Belser CG, van Blaricon D (2003) Avian migration. Springer, Berlin.
  27. Gauthreaux SA, Livingston JW, Belser CG (2008) Detection and discrimination of fauna in the aerosphere using Doppler weather surveillance radar. Integr Comp Biol 48(1):12–23CrossRefPubMedGoogle Scholar
  28. Geerts B, Miao Q (2005) Airborne radar observations of the flight behavior of small insects in the atmospheric convective boundary layer. Environ Entomol 34(2):361–377.
  29. Grecu M, Krajewski W (2000) An efficient methodology for detection of anamalous propagation echoes in radar reflectivity data using neural networks. J Atmos Oceanic Tech 17:121–129CrossRefGoogle Scholar
  30. Greene DR, Clark RA (1972) Vertically integrated liquid water – a new analysis tool. Mon Weather Rev 100:548–552CrossRefGoogle Scholar
  31. Horn JW, Kunz TH (2008) Analyzing NEXRAD doppler radar images to assess nightly dispersal patterns and population trends in Brazilian freetailed bats (Tadarida brasiliensis). Integr Comp Biol 48(1):24–39.
  32. Horton KG, Shriver WG, Buler JJ (2016a) An assessment of spatio-temporal relationships between nocturnal bird migration traffic rates and diurnal bird stopover density. Mov Ecol 4:1.
  33. Horton KG, Van Doren BM, Stepanian PM, Farnsworth A, Kelly JF (2016b) Seasonal differences in landbird migration strategies. Auk 133(4):761–769.
  34. Horton KG, Van Doren BM, Stepanian PM, Farnsworth A, Kelly JF (2016c) Where in the air? Aerial habitat use of nocturnally migrating birds. Biol Lett 12(11).
  35. Horton KG, Van Doren BM, Stepanian PM, Hochachka WM, Farnsworth A, Kelly JF (2016d) Nocturnally migrating songbirds drift when they can and compensate when they must. Sci Rep 6:21249.
  36. Joss J, Lee R (1995) The application of radar–gauge comparisons to operational precipitation profile corrections. J Appl Meteorol 34(12):2612–2630.<2612:TAORCT>2.0.CO;2
  37. Kelly JF, Horton KG (2016) Toward a predictive macrosystems framework for migration ecology. Glob Ecol Biogeogr 25(10):1159–1165.
  38. Kelly JF, Horton KG, Stepanian PM, de Beurs KM, Fagin T, Bridge ES, Chilson PB (2016) Novel measures of continental-scale avian migration phenology related to proximate environmental cues. Ecosphere 7(8):e01434.
  39. Kemp M, ShamounBaranes J, Dokter A (2013) The influence of weather on the flight altitude of nocturnal migrants in mid-latitudes. Ibis 155:734–749CrossRefGoogle Scholar
  40. Kessinger C, Ellis S, Van Andel J (2003) The radar echo classifier: a fuzzy logic algorithm for the WSR-88D. In: 3rd conference on artificial applications to the environmental sciences, American Meteor Society, Long Beach, CA, P1.6Google Scholar
  41. Kitchen M (1997) Towards improved radar estimates of surface precipitation rate at long range. Q J R Meteorol Soc 123(537):145–163.
  42. Koistinen J, Pohjola H (2014) Estimation of ground-level reflectivity factor in operational weather radar networks using VPR-based correction ensembles. J Appl Meteorol Climatol 53(10):2394–2411.
  43. Kunz TH, Gauthreaux SA, Hristov NI, Horn JW, Jones G, Kalko EKV, Larkin RP, McCracken GF, Swartz SM, Srygley RB, Dudley R, Westbrook JK, Wikelski M (2008) Aeroecology: probing and modeling the aerosphere. Integr Comp Biol 48(1):1–11. CrossRefPubMedGoogle Scholar
  44. La Sorte FA, Hochachka WM, Farnsworth A, Sheldon D, Van Doren BM, Fink D, Kelling S (2015) Seasonal changes in the altitudinal distribution of nocturnally migrating birds during autumn migration. R Soc Open Sci 2(12):150347.
  45. Lack D, Varley G (1945) Detection of birds by radar. Nature 156(3963):446CrossRefGoogle Scholar
  46. Lakshmanan V, Smith T, Hondl K, Stumpf GJ, Witt A (2006) A real-time, three dimensional, rapidly updating, heterogeneous radar merger technique for reflectivity, velocity and derived products. Weather Forecast 21(5):802–823CrossRefGoogle Scholar
  47. Lakshmanan V, Fritz A, Smith T, Hondl K, Stumpf GJ (2007a) An automated technique to quality control radar reflectivity data. J Appl Meteorol 46(3):288–305CrossRefGoogle Scholar
  48. Lakshmanan V, Smith T, Stumpf GJ, Hondl K (2007b) The warning decision support system – integrated information. Weather Forecast 22(3):596–612CrossRefGoogle Scholar
  49. Lakshmanan V, Zhang J, Howard K (2010) A technique to censor biological echoes in radar reflectivity data. J Appl Meteorol 49(3):435–462Google Scholar
  50. Lakshmanan V, Karstens C, Krause J, Tang L (2014) Quality control of weather radar data using polarimetric variables. J Atmos Oceanic Tech 31:1234–1249CrossRefGoogle Scholar
  51. Lang TJ, Rutledge SA, Stith JL (2004) Observations of quasi-symmetric echo patterns in clear air with the CSUCHILL polarimetric radar. J Atmos Ocean Technol 21(8):1182–1189.<1182:OOQEPI>2.0.CO;2
  52. Leskinen M, Markkula I, Koistinen J, Pylkkö P, Ooperi S, Siljamo P, Ojanen H, Raiskio S, Tiilikkala K (2011) Pest insect immigration warning by an atmospheric dispersion model, weather radars and traps. J Appl Entomol 135:55–67.
  53. Liu H, Chandrasekar V (2000) Classification of hydrometeors based on polarimetric radar measurements: development of fuzzy logic and neuro-fuzzy systems, and in situ verification. J Atmos Oceanic Tech 17(2):140–164CrossRefGoogle Scholar
  54. Melnikov V, Leskinen M, Koistinen J (2013) Doppler velocities at orthogonal polarizations in radar echoes from insects and birds. IEEE Geosci Remote Sens Lett 11(3):592–596. CrossRefGoogle Scholar
  55. Melnikov VM, Istok MJ, Westbrook JK (2015) Asymmetric radar echo patterns from insects. J Atmos Ocean Technol 32(4):659–674.
  56. Mirkovic D, Stepanian PM, Kelly JF, Chilson PB (2016) Electromagnetic model reliably predicts radar scattering characteristics of airborne organisms. Sci Rep 6:35637.
  57. Mueller EA, Larkin RP (1985) Insects observed using dual-polarization radar. J Atmos Ocean Technol 2(1):49–54.<0049:IOUDPR>2.0.CO;2
  58. Nebuloni R, Capsoni C, Vigorita V (2008) Quantifying bird migration by a high-resolution weather radar. IEEE Trans Geosci Remote Sens 46(6):1867–1875CrossRefGoogle Scholar
  59. Park H, Ryzhkov A, Zrnic D, Kim K (2009) The hydrometeor classification algorithm for the polarimetric WSR-88D: description and application to a mcs. Weather Forecast 24(3):730–748CrossRefGoogle Scholar
  60. Rinehart R (1991) Radar for meteorologists, or, You, too, can be a radar meteorologist, 2nd edn. Rinehart Pubilcations, Grand Forks, NDGoogle Scholar
  61. Russell KR, Gauthreaux SA (1998) Use of weather radar to characterize movements of roosting Purple martins. Wildl Soc Bull 26(1):5–16Google Scholar
  62. Russell KR, Mizrahi DS, Gauthreaux SA (1998) Large-scale mapping of Purple martin pre-migratory roosts using WSR-88D weather surveillance radar. J Field Ornithol 69(2):316–325Google Scholar
  63. Schmaljohann H, Liechti F, Bruderer B (2007) Songbird migration across the Sahara: the non-stop hypothesis rejected! Proc Biol Sci 274(1610):735–739.
  64. Shamoun-Baranes J, Bouten W, van Loon EE (2010) Integrating meteorology into research on migration. Integr Comp Biol 50(3):280–292.
  65. Shamoun-Baranes J, Dokter AM, van Gasteren H, van Loon EE, Leijnse H, Bouten W (2011) Birds flee en mass from New Year’s Eve fireworks. Behav Ecol 22(6):1173–1177.
  66. Shamoun-Baranes J, Alves JA, Bauer S, Dokter AM, Hüppop O, Koistinen J, Leijnse H, Liechti F, van Gasteren H, Chapman JW (2014) Continental-scale radar monitoring of the aerial movements of animals. Mov Ecol 2(1):9.
  67. Shamoun-Baranes J, Liechti F, Vansteelant WMG (2017) Atmospheric conditions create freeways, detours and tailbacks for migrating birds. J Comp Physiol A 203(6–7):509–529.
  68. Smyth TJ, Illingworth AJ (1998) Radar estimates of rainfall rates at the ground in bright band and non-bright band events. Q J R Meteorol Soc 124(551):2417–2434.
  69. Steiner M, Smith J (2002) Use of three-dimensional reflectivity structure for automated detection and removal of non-precipitating echoes in radar data. J Atmos Oceanic Tech 19:673–686CrossRefGoogle Scholar
  70. Stepanian PM, Horton KG (2015) Extracting migrant flight orientation profiles using polarimetric radar. IEEE Trans Geosci Remote Sens 53(12):6518–6528.
  71. Stepanian PM, Horton KG, Melnikov VM, Zrnić DS, Gauthreaux SA (2016) Dual-polarization radar products for biological applications. Ecosphere 7(11):e01539.
  72. Trapp RJ, Doswell CA (2000) Radar data objective analysis. J Atmos Ocean Tech 17:105–120CrossRefGoogle Scholar
  73. Van Doren BM, Horton KG, Stepanian PM, Mizrahi DS, Farnsworth A (2016) Wind drift explains the reoriented morning flights of songbirds. Behav Ecol 27(4):1122–1131.
  74. Vignal B, Andrieu H, Creutin JD (1999) Identification of vertical profiles of reflectivity from volume scan radar data. J Appl Meteorol 38:1214–1228CrossRefGoogle Scholar
  75. Vignal B, Galli G, Joss J, Germann U (2000) Three methods to determine profiles of reflectivity from volumetric radar data to correct precipitation estimates. J Appl Meteorol 39(10):1715–1726.
  76. Wainwright CE, Stepanian PM, Horton KG (2016) The role of the US great plains low-level jet in nocturnal migrant behavior. Int J Biometeorol 60(10):1531–1542.
  77. Warning Decision Training Division (2016) VCP training.
  78. Westbrook J, Eyster R (2017) Doppler weather radar detects emigratory flights of noctuids during a major pest outbreak. Remote Sens Appl Soc Environ 8:64–70.
  79. Westbrook J, Isard S (1999) Atmospheric scales of biotic dispersal. Agric For Meteorol 97(4):263–274.
  80. Westbrook JK, Eyster RS, Wolf WW (2014) WSR-88D Doppler radar detection of corn earworm moth migration. Int J Biometeorol 58(5):931–940.
  81. Zrnic D, Ryzhkov A (1998) Observations of insects and birds with a polarimetric radar. IEEE Trans Geosci Remote Sens 36:661–668CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2017

Authors and Affiliations

  1. 1.University of Oklahoma School of MeteorologyNormanUSA
  2. 2.Cooperative Institute for Mesoscale Meteorological StudiesThe University of OklahomaNormanUSA
  3. 3.Google Inc.SeattleUSA

Personalised recommendations