• Baars, H., A. Ansmann, R. Engelmann, and D. Althausen, 2008: Continuous monitoring of the boundary-layer top with lidar. Atmos. Chem. Phys., 8, 72817296, https://doi.org/10.5194/acp-8-7281-2008.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Baars, H., and et al. , 2016: An overview of the first decade of PollyNET: An emerging network of automated Raman-polarization lidars for continuous aerosol profiling. Atmos. Chem. Phys., 16, 51115137, https://doi.org/10.5194/acp-16-5111-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Biavati, G., D. G. Feist, C. Gerbig, and R. Kretschmer, 2015: Error estimation for localized signal properties: Application to atmospheric mixing height retrievals. Atmos. Meas. Tech., 8, 42154230, https://doi.org/10.5194/amt-8-4215-2015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bonin, T. A., B. J. Carroll, R. M. Hardesty, W. A. Brewer, K. Hajny, O. E. Salmon, and P. B. Shepson, 2018: Doppler lidar observations of the mixing height in Indianapolis using an automated composite fuzzy logic approach. J. Atmos. Oceanic Technol., 35, 473490, https://doi.org/10.1175/JTECH-D-17-0159.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bradley, R. S., F. T. Keimig, and H. F. Diaz, 1993: Recent changes in the North American Arctic boundary layer in winter. J. Geophys. Res., 98, 88518858, https://doi.org/10.1029/93JD00311.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Brooks, I. M., 2003: Finding boundary layer top: Application of a wavelet covariance transform to lidar backscatter profiles. J. Atmos. Oceanic Technol., 20, 10921105, https://doi.org/10.1175/1520-0426(2003)020<1092:FBLTAO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Caicedo, V., B. Rappenglück, B. Lefer, G. Morris, D. Toledo, and R. Delgado, 2017: Comparison of aerosol lidar retrieval methods for boundary layer height detection using ceilometer aerosol backscatter data. Atmos. Meas. Tech., 10, 16091622, https://doi.org/10.5194/amt-10-1609-2017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Caicedo, V., and et al. , 2019: Bay breeze and sea breeze circulation impacts on the planetary boundary layer and air quality from an observed and modeled DISCOVER-AQ Texas case study. J. Geophys. Res. Atmos., 124, 73597378, https://doi.org/10.1029/2019JD030523.

    • Search Google Scholar
    • Export Citation
  • Cohn, S., and W. Angevine, 2000: Boundary layer height and entrainment zone thickness measured by lidars and wind-profiling radars. J. Appl. Meteor., 39, 12331247, https://doi.org/10.1175/1520-0450(2000)039<1233:BLHAEZ>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Compton, J. C., R. Delgado, T. A. Berkoff, and R. M. Hoff, 2013: Determination of planetary boundary layer height on short spatial and temporal scales: A demonstration of the covariance wavelet transform in ground-based wind profiler and lidar measurements. J. Atmos. Oceanic Technol., 30, 15661575, https://doi.org/10.1175/JTECH-D-12-00116.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dang, R., Y. Yang, X.-M. Hu, Z. Wang, and S. Zhang, 2019: A review of techniques for diagnosing the atmospheric boundary layer height (ABLH) using aerosol lidar data. Remote Sens., 11, 1590, https://doi.org/10.3390/rs11131590.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Davis, K. J., N. Gamage, C. R. Hagelberg, C. Kiemle, D. H. Lenschow, and P. P. Sullivan, 2000: An objective method for deriving atmospheric structure from airborne lidar observations. J. Atmos. Oceanic Technol., 17, 14551468, https://doi.org/10.1175/1520-0426(2000)017<1455:AOMFDA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • de Bruine, M., A. Apituley, D. Donovan, H. Klein Baltink, and M. de Haij, 2017: Pathfinder: Applying graph theory for consistent tracking of daytime mixed layer height with backscatter lidar. Atmos. Meas. Tech., 10, 18931909, https://doi.org/10.5194/amt-10-1893-2017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • de Haij, M., W. Wauben, and H. Klein Baltink, 2006: Determination of mixing layer height from ceilometer backscatter profiles. Proc. SPIE, 6362, 63620R, https://doi.org/10.1117/12.691050.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Delle Monache, L., K. D. Perry, R. T. Cederwall, and J. A. Ogren, 2004: In situ aerosol profiles over the Southern Great Plains and cloud and radiation test bed site: 2. Effects of mixing height on aerosol properties. J. Geophys. Res., 109, D06209, https://doi.org/10.1029/2003JD004024.

    • Search Google Scholar
    • Export Citation
  • De Wekker, S. F. J., D. G. Steyn, and S. Nyeki, 2004: A comparison of aerosol-layer and convective boundary-layer structure over a mountain range during STAAARTE ’97. Bound.-Layer Meteor., 113, 249271, https://doi.org/10.1023/B:BOUN.0000039371.41823.37.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Di Giuseppe, F., A. Riccio, L. Caporaso, G. Bonafé, G. P. Gobbi, and F. Angelini, 2012: Automatic detection of atmospheric boundary layer height using ceilometer backscatter data assisted by a boundary layer model. Quart. J. Roy. Meteor. Soc., 138, 649663, https://doi.org/10.1002/qj.964.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Emeis, S., K. Schäfer, and C. Münkel, 2008a: Long-term observations of the urban mixing-layer height with ceilometers. IOP Conf. Ser. Earth Environ. Sci., 1, 012027, https://doi.org/10.1088/1755-1315/1/1/012027.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Emeis, S., K. Schäfer, and C. Münkel, 2008b: Surface-based remote sensing of the mixing-layer height—A review. Meteor. Z., 17, 621630, https://doi.org/10.1127/0941-2948/2008/0312.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • EPA, 2019: Technical assistance document for sampling and analysis of ozone precursors for the Photochemical Assessment Monitoring Stations program—Revision 2—April 2019. EPA Doc. EPA-454/B-19-004, 226 pp.

  • Eresmaa, N., A. Karppinen, S. M. Joffre, J. Räsänen, and H. Talvitie, 2006: Mixing height determination by ceilometer. Atmos. Chem. Phys., 6, 14851493, https://doi.org/10.5194/acp-6-1485-2006.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Garratt, J. R., 1992: The Atmospheric Boundary Layer. Cambridge University Press, 335 pp.

  • Geiß, A., 2016: Automated calibration of ceilometer data and its applicability for quantitative aerosol monitoring. Ph.D. thesis, Ludwig-Maximilians-Universität München, 185 pp.

  • Geiß, A., and et al. , 2017: Mixing layer height as an indicator for urban air quality? Atmos. Meas. Tech., 10, 29692988, https://doi.org/10.5194/amt-10-2969-2017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Haeffelin, M., and et al. , 2012: Evaluation of mixing-height retrievals from automatic profiling lidars and ceilometers in view of future integrated networks in Europe. Bound.-Layer Meteor., 143, 4975, https://doi.org/10.1007/s10546-011-9643-z.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Haman, C. L., B. Lefer, and G. A. Morris, 2012: Seasonal variability in the diurnal evolution of the boundary layer in a near-coastal urban environment. J. Atmos. Oceanic Technol., 29, 697710, https://doi.org/10.1175/JTECH-D-11-00114.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Haman, C. L., E. Couzo, J. H. Flynn, W. Vizuete, B. Heffron, and B. L. Lefer, 2014: Relationship between boundary layer heights and growth rates with ground-level ozone in Houston, Texas. J. Geophys. Res. Atmos., 119, 62306245, https://doi.org/10.1002/2013JD020473.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Heffter, J. L., 1980: Transport layer depth calculations. Second Joint Conf. on Applications of Air Pollution Meteorology, New Orleans, LA, Amer. Meteor. Soc., 787–791.

  • Hervo, M., Y. Poltera, and A. Haefele, 2016: An empirical method to correct for temperature-dependent variations in the overlap function of CHM15k ceilometers. Atmos. Meas. Tech., 9, 29472959, https://doi.org/10.5194/amt-9-2947-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hicks, M., R. Sakai, and E. Joseph, 2015: The evaluation of a new method to detect mixing layer heights using lidar observations. J. Atmos. Oceanic Technol., 32, 20412051, https://doi.org/10.1175/JTECH-D-14-00103.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hicks, M., B. Demoz, K. Vermeesch, and D. Atkinson, 2019: Intercomparison of mixing layer heights from the National Weather Service ceilometer test sites and collocated radiosondes. J. Atmos. Oceanic Technol., 36, 129137, https://doi.org/10.1175/JTECH-D-18-0058.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Holzworth, G. C., 1964: Estimates of mean maximum mixing depths in the contiguous United States. Mon. Wea. Rev., 92, 235242, https://doi.org/10.1175/1520-0493(1964)092<0235:EOMMMD>2.3.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hopkin, E., A. J. Illingworth, C. Charlton-Perez, C. D. Westbrook, and S. Ballard, 2019: A robust automated technique for operational calibration of ceilometers using the integrated backscatter from totally attenuating liquid clouds. Atmos. Meas. Tech., 12, 41314147, https://doi.org/10.5194/amt-12-4131-2019.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Knepp, T. N., and et al. , 2017: Assessment of mixed-layer height estimation from single-wavelength ceilometer profiles. Atmos. Meas. Tech., 10, 39633983, https://doi.org/10.5194/amt-10-3963-2017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kotthaus, S., and C. S. B. Grimmond, 2018a: Atmospheric boundary layer characteristics from ceilometer measurements. Part 1: A new method to track mixed layer height and classify clouds. Quart. J. Roy. Meteor. Soc., 144, 15251538, https://doi.org/10.1002/qj.3299.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kotthaus, S., and C. S. B. Grimmond, 2018b: Atmospheric boundary layer characteristics from ceilometer measurements. Part 2: Application to London’s urban boundary layer. Quart. J. Roy. Meteor. Soc., 144, 15111524, https://doi.org/10.1002/qj.3298.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kotthaus, S., E. O’Connor, C. Münkel, C. Charlton-Perez, M. Haeffelin, A. M. Gabey, and C. S. B. Grimmond, 2016: Recommendations for processing atmospheric attenuated backscatter profiles from Vaisala CL31 ceilometers. Atmos. Meas. Tech., 9, 37693791, https://doi.org/10.5194/amt-9-3769-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lammert, A., and J. Bösenberg, 2006: Determination of the convective boundary-layer height with laser remote sensing. Bound.-Layer Meteor., 119, 159170, https://doi.org/10.1007/s10546-005-9020-x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lewis, J. R., E. J. Welton, A. M. Molod, and E. Joseph, 2013: Improved boundary layer depth retrievals from MPLNET. J. Geophys. Res. Atmos., 118, 98709879, https://doi.org/10.1002/JGRD.50570.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liu, S., and X.-Z. Liang, 2010: Observed diurnal cycle climatology of planetary boundary layer height. J. Climate, 23, 57905809, https://doi.org/10.1175/2010JCLI3552.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lotteraner, C., and M. Piringer, 2016: Mixing-height time series from operational ceilometer aerosol-layer heights. Bound.-Layer Meteor., 161, 265287, https://doi.org/10.1007/s10546-016-0169-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Madonna, F., F. Amato, J. Vande Hey, and G. Pappalardo, 2015: Ceilometer aerosol profiling versus Raman lidar in the frame of the INTERACT campaign of ACTRIS. Atmos. Meas. Tech., 8, 22072223, https://doi.org/10.5194/amt-8-2207-2015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Madonna, F., and et al. , 2018: Intercomparison of aerosol measurements performed with multiwavelength Raman lidars, automatic lidars and ceilometers in the framework of INTERACT-II campaign. Atmos. Meas. Tech., 11, 24592475, https://doi.org/10.5194/amt-11-2459-2018.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Marsik, F. J., K. W. Fischer, T. D. McDonald, and P. J. Samson, 1995: Comparison of methods for estimating mixing height used during the 1992 Atlanta field intensive. J. Appl. Meteor., 34, 18021814, https://doi.org/10.1175/1520-0450(1995)034<1802:COMFEM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Martucci, G., R. Matthey, V. Mitev, and H. Richner, 2007: Comparison between backscatter lidar and radiosonde measurements of the diurnal and nocturnal stratification in the lower troposphere. J. Atmos. Oceanic Technol., 24, 12311244, https://doi.org/10.1175/JTECH2036.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Martucci, G., R. Matthey, V. Mitev, and H. Richner, 2010: Frequency of boundary-layer-top fluctuations in convective and stable conditions using laser remote sensing. Bound.-Layer Meteor., 135, 313331, https://doi.org/10.1007/s10546-010-9474-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mather, P., 1987: Computer Processing of Remotely-Sensed Images. John Wiley and Sons, 353 pp.

    • Crossref
    • Export Citation
  • McElroy, J. L., and T. B. Smith, 1991: Lidar descriptions of mixing-layer thickness characteristics in a complex terrain/coastal environment. J. Appl. Meteor., 30, 585597, https://doi.org/10.1175/1520-0450(1991)030<0585:LDOMLT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Morille, Y., M. Haeffelin, P. Drobinski, and J. Pelon, 2007: STRAT: An automated algorithm to retrieve the vertical structure of the atmosphere from single-channel lidar data. J. Atmos. Oceanic Technol., 24, 761775, https://doi.org/10.1175/JTECH2008.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Münkel, C., and R. Roininen, 2010: Automatic monitoring of boundary layer structures with ceilometers. Vaisala News, No. 184, 7–9, https://www.vaisala.com/sites/default/files/documents/vn184_07_AutomaticMonitoringofBoundaryLayerStructureswithCeilometers.pdf.

  • Münkel, C., N. Eresmaa, J. Räsänen, and A. Karppinen, 2007: Retrieval of mixing height and dust concentration with lidar ceilometer. Bound.-Layer Meteor., 124, 117128, https://doi.org/10.1007/s10546-006-9103-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • O’Connor, E. J., A. J. Illingworth, and R. J. Hogan, 2004: A technique for autocalibration of cloud lidar. J. Atmos. Oceanic Technol., 21, 777786, https://doi.org/10.1175/1520-0426(2004)021<0777:ATFAOC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pal, S., M. Haeffelin, and E. Batchvarova, 2013: Exploring a geophysical process based attribution technique for the determination of the atmospheric boundary layer depth using aerosol lidar and near-surface meteorological measurements. J. Geophys. Res. Atmos., 118, 92779295, https://doi.org/10.1002/JGRD.50710.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Peng, J., and et al. , 2017: Ceilometer based analysis of Shanghai’s boundary layer height (under rain and fog free conditions). J. Atmos. Oceanic Technol., 34, 749764, https://doi.org/10.1175/JTECH-D-16-0132.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Piringer, M., K. Baumann, and M. Langer, 1998: Summertime mixing heights at Vienna, Austria, estimated from vertical soundings and by a numerical model. Bound.-Layer Meteor., 89, 2545, https://doi.org/10.1023/A:1001565319487.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Poltera, Y., G. Martucci, M. Collaud Coen, M. Hervo, L. Emmenegger, S. Henne, D. Brunner, and A. Haefele, 2017: PathfinderTURB: An automatic boundary layer algorithm. Development, validation and application to study the impact on in situ measurements at the Jungfraujoch. Atmos. Chem. Phys., 17, 10 05110 070, https://doi.org/10.5194/acp-17-10051-2017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rappenglück, B., R. Perna, S. Zhong, and G. A. Morris, 2008: An analysis of the vertical structure of the atmosphere and the upper-level meteorology and their impact on surface ozone levels in Houston, Texas. J. Geophys. Res., 113, D17315, https://doi.org/10.1029/2007JD009745.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Scarino, A. J., and et al. , 2014: Comparison of mixed layer heights from airborne high spectral resolution lidar, ground-based measurements, and the WRFChem model during CalNex and CARES. Atmos. Chem. Phys., 14, 55475560, https://doi.org/10.5194/acp-14-5547-2014.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schäfer, K., S. M. Emeis, A. Rauch, C. Munkel, and S. Vogt, 2004: Determination of mixing layer heights from ceilometer data. Proc. SPIE, 5571, 248259, https://doi.org/10.1117/12.565592.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Seibert, P., F. Beyrich, S. E. Gryning, S. Joffre, A. Rasmussen, and P. Tercier, 2000: Review and intercomparison of operational methods for the determination of the mixing height. Atmos. Environ., 34, 10011027, https://doi.org/10.1016/S1352-2310(99)00349-0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Seidel, D. J., C. O. Ao, and K. Li, 2010: Estimating climatological planetary boundary layer heights from radiosonde observations: Comparison of methods and uncertainty analysis. J. Geophys. Res., 115, D16113, https://doi.org/10.1029/2009JD013680.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Seidel, D. J., Y. Zhang, A. Beljaars, J.-C. Golaz, A. R. Jacobson, and B. Medeiros, 2012: Climatology of the planetary boundary layer over the continental United States and Europe. J. Geophys. Res., 117, D17106, https://doi.org/10.1029/2012JD018143.

    • Search Google Scholar
    • Export Citation
  • Sivaraman, C., S. McFarlane, E. Chapman, M. Jensen, T. Toto, S. Liu, and M. Fischer, 2013: Planetary boundary layer (PBL) height value added product (VAP): Radiosonde retrievals. U.S. Department of Energy Rep. DOE/SC-ARM-TR-132, 36 pp., https://www.arm.gov/publications/tech_reports/doe-sc-arm-tr-132.pdf.

  • Smith, R. B., S. T. Skubis, J. D. Doyle, A. Broad, C. Kiemle, and H. Volkert, 2002: Mountain waves over Mont Blanc: Influence of a stagnant boundary layer. J. Atmos. Sci., 59, 20732092, https://doi.org/10.1175/1520-0469(2002)059<2073:MWOMBI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Snyder, B. J., and K. B. Strawbridge, 2004: Meteorological analysis of the Pacific 2001 Air Quality Field Study. Atmos. Environ., 38, 57335743, https://doi.org/10.1016/j.atmosenv.2004.02.068.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sokół, P., I. S. Stachlewska, I. Ungureanu, and S. Stefan, 2014: Evaluation of the boundary layer morning transition using the CL-31 ceilometer signals. Acta Geophys., 62, 367380, https://doi.org/10.2478/s11600-013-0158-5.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sørensen, J. H., A. Rasmussen, T. Ellermann, and E. Lyck, 1998: Mesoscale influence on long-range transport, evidence from ETEX modelling and observations. Atmos. Environ., 32, 42074217, https://doi.org/10.1016/S1352-2310(98)00183-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Steyn, D. G., M. Baldi, and R. M. Hoff, 1999: The detection of mixed layer depth and entrainment zone thickness from lidar backscatter profiles. J. Atmos. Oceanic Technol., 16, 953959, https://doi.org/10.1175/1520-0426(1999)016<0953:TDOMLD>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stull, R. B., 1988: An Introduction to Boundary Layer Meteorology. Kluwer Academic, 666 pp.

    • Crossref
    • Export Citation
  • Tang, G., and et al. , 2016: Mixing layer height and its implications for air pollution over Beijing, China. Atmos. Chem. Phys., 16, 24592475, https://doi.org/10.5194/acp-16-2459-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Toledo, D., C. Córdoba-Jabonero, and M. Gil-Ojeda, 2014: Cluster analysis: A new approach applied to lidar measurements for atmospheric boundary layer height estimation. J. Atmos. Oceanic Technol., 31, 422436, https://doi.org/10.1175/JTECH-D-12-00253.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Troen, I., and L. Mahrt, 1986: A simple model of the atmospheric boundary layer; sensitivity to surface evaporation. Bound.-Layer Meteor., 37, 129148, https://doi.org/10.1007/BF00122760.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Uzan, L., S. Egert, and P. Alpert, 2016: Ceilometer evaluation of the eastern Mediterranean summer boundary layer height—First study of two Israeli sites. Atmos. Meas. Tech., 9, 43874398, https://doi.org/10.5194/amt-9-4387-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vande Hey, J., J. Coupland, J. Richards, and A. Sandford, 2012: Design and implementation of a divided lens lidar ceilometer prototype for manufacture. IEEE Int. Geoscience and Remote Sensing Symp., Munich, Germany, IEEE, 5002–5005, https://doi.org/10.1109/IGARSS.2012.6352488.

    • Crossref
    • Export Citation
  • van der Kamp, D., and I. McKendry, 2010: Diurnal and seasonal trends in convective mixed-layer heights estimated from two years of continuous ceilometer observations in Vancouver, BC. Bound.-Layer Meteor., 137, 459475, https://doi.org/10.1007/s10546-010-9535-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wagner, P., and K. Schäfer, 2017: Influence of mixing layer height on air pollutant concentrations in an urban street canyon. Urban Climate, 22, 6479, https://doi.org/10.1016/j.uclim.2015.11.001.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, Z., X. Cao, L. Zhang, J. Notholt, B. Zhou, R. Liu, and B. Zhang, 2012: Lidar measurement of planetary boundary layer height and comparison with microwave profiling radiometer observation. Atmos. Meas. Tech., 5, 19651972, https://doi.org/10.5194/amt-5-1965-2012.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wiegner, M., and A. Geiß, 2012: Aerosol profiling with the Jenoptik ceilometer CHM15kx. Atmos. Meas. Tech., 5, 19531964, https://doi.org/10.5194/amt-5-1953-2012.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wiegner, M., and et al. , 2019: Aerosol backscatter profiles from ceilometers: Validation of water vapor correction in the framework of CeiLinEx2015. Atmos. Meas. Tech., 12, 471490, https://doi.org/10.5194/amt-12-471-2019.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhang, J., H. Chen, Z. Li, X. Fan, L. Peng, Y. Yu, and M. Cribb, 2010: Analysis of cloud layer structure in Shouxian, China using RS92 radiosonde aided by 95 GHz cloud radar. J. Geophys. Res., 115, D00K30, https://doi.org/10.1029/2010JD014030.

    • Search Google Scholar
    • Export Citation
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An Automated Common Algorithm for Planetary Boundary Layer Retrievals Using Aerosol Lidars in Support of the U.S. EPA Photochemical Assessment Monitoring Stations Program

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  • 1 a Joint Center of Earth Systems Technology, Baltimore, Maryland
  • | 2 b University of Maryland, Baltimore County, Baltimore, Maryland
  • | 3 c Howard University, Washington, D.C.
  • | 4 d Science Systems and Applications, Inc., Hampton, Virginia
  • | 5 e National Aeronautics and Space Administration Langley Research Center, Hampton, Virginia
  • | 6 f Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina
  • | 7 g Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina
  • | 8 h National Aeronautics and Space Administration Headquarters, Washington, D.C.
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Abstract

A unique automated planetary boundary layer (PBL) retrieval algorithm is proposed as a common cross-platform method for use with commercially available ceilometers for implementation under the redesigned U.S. Environmental Protection Agency Photochemical Assessment Monitoring Stations program. This algorithm addresses instrument signal quality and screens for precipitation and cloud layers before the implementation of the retrieval method using the Haar wavelet covariance transform. Layer attribution for the PBL height is supported with the use of continuation and time-tracking parameters, and uncertainties are calculated for individual PBL height retrievals. Commercial ceilometer retrievals are tested against radiosonde PBL height and cloud-base height during morning and late-afternoon transition times, critical to air quality model prediction and when retrieval algorithms struggle to identify PBL heights. A total of 58 radiosonde profiles were used, and retrievals for nocturnal stable layers, residual layers, and mixing layers were assessed. Overall good agreement was found for all comparisons, with one system showing limitations for the cases of nighttime surface stable layers and daytime mixing layer. It is recommended that nighttime shallow stable-layer retrievals be performed with a recommended minimum height or with additional verification. Retrievals of residual-layer heights and mixing-layer comparisons revealed overall good correlations with radiosonde heights (square of correlation coefficients r2 ranging from 0.89 to 0.96, and bias ranging from approximately −131 to +63 m for the residual layer and r2 from 0.88 to 0.97 and bias from −119 to +101 m for the mixing layer).

Corresponding author: Vanessa Caicedo, caicedo.vanessa@gmail.com

Abstract

A unique automated planetary boundary layer (PBL) retrieval algorithm is proposed as a common cross-platform method for use with commercially available ceilometers for implementation under the redesigned U.S. Environmental Protection Agency Photochemical Assessment Monitoring Stations program. This algorithm addresses instrument signal quality and screens for precipitation and cloud layers before the implementation of the retrieval method using the Haar wavelet covariance transform. Layer attribution for the PBL height is supported with the use of continuation and time-tracking parameters, and uncertainties are calculated for individual PBL height retrievals. Commercial ceilometer retrievals are tested against radiosonde PBL height and cloud-base height during morning and late-afternoon transition times, critical to air quality model prediction and when retrieval algorithms struggle to identify PBL heights. A total of 58 radiosonde profiles were used, and retrievals for nocturnal stable layers, residual layers, and mixing layers were assessed. Overall good agreement was found for all comparisons, with one system showing limitations for the cases of nighttime surface stable layers and daytime mixing layer. It is recommended that nighttime shallow stable-layer retrievals be performed with a recommended minimum height or with additional verification. Retrievals of residual-layer heights and mixing-layer comparisons revealed overall good correlations with radiosonde heights (square of correlation coefficients r2 ranging from 0.89 to 0.96, and bias ranging from approximately −131 to +63 m for the residual layer and r2 from 0.88 to 0.97 and bias from −119 to +101 m for the mixing layer).

Corresponding author: Vanessa Caicedo, caicedo.vanessa@gmail.com
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