Articles | Volume 15, issue 5
https://doi.org/10.5194/amt-15-1185-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-15-1185-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Low-level buoyancy as a tool to understand boundary layer transitions
Francesca M. Lappin
CORRESPONDING AUTHOR
School of Meteorology, University of Oklahoma, Norman, OK, USA
Cooperative Institute for Severe and High-Impact Weather Research and Operations, National Weather Center, Norman, OK, USA
Tyler M. Bell
Cooperative Institute for Severe and High-Impact Weather Research and Operations, National Weather Center, Norman, OK, USA
NOAA/OAR National Severe Storms Laboratory, National Weather Center, Norman, OK, USA
Elizabeth A. Pillar-Little
School of Meteorology, University of Oklahoma, Norman, OK, USA
Cooperative Institute for Severe and High-Impact Weather Research and Operations, National Weather Center, Norman, OK, USA
Phillip B. Chilson
School of Meteorology, University of Oklahoma, Norman, OK, USA
Advanced Radar Research Center, University of Oklahoma, Norman, OK, USA
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Cited articles
Ágústsson, H., Ólafsson, H., Jonassen, M. O., and Rögnvaldsson, Ó.: The impact of assimilating data from a remotely piloted aircraft on simulations of weak-wind orographic flow, Tellus A, 66, 25421, https://doi.org/10.3402/tellusa.v66.25421, 2014. a
Angevine, W. M., Edwards, J. M., Lothon, M., LeMone, M. A., and Osborne, S. R.: Transition periods in the diurnally-varying atmospheric boundary layer over land, Bound.-Lay. Meteorol., 177, 205–223,
https://doi.org/10.1007/s10546-020-00515-y, 2020. a, b
Baklanov, A. A., Grisogono, B., Bornstein, R., Mahrt, L., Zilitinkevich, S. S., Taylor, P., Larsen, S. E., Rotach, M. W., and Fernando, H.: The nature, theory, and modeling of atmospheric planetary boundary layers, B. Am. Meteorol. Soc., 92, 123–128, https://doi.org/10.1175/2010BAMS2797.1, 2011. a
Banta, R. M., Pichugina, Y. L., and Newsom, R. K.: Relationship between
low-level jet properties and turbulence kinetic energy in the nocturnal
stable boundary layer, J. Atmos. Sci., 60, 2549–2555,
https://doi.org/10.1175/1520-0469(2003)060<2549:RBLJPA>2.0.CO;2, 2003. a
Barbieri, L., Kral, S. T., Bailey, S. 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, https://doi.org/10.3390/s19092179, 2019. a
Båserud, L., Reuder, J., Jonassen, M. O., Kral, S. T., Paskyabi, M. B., and Lothon, M.: Proof of concept for turbulence measurements with the RPAS SUMO during the BLLAST campaign, Atmos. Meas. Tech., 9, 4901–4913, https://doi.org/10.5194/amt-9-4901-2016, 2016. a
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, https://doi.org/10.5194/amt-13-3855-2020, 2020. a, b, c
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 Syst. Sci. Data, 13, 1041–1051, https://doi.org/10.5194/essd-13-1041-2021, 2021. a
Blackadar, A. K.: Boundary layer wind maxima and their significance for the
growth of nocturnal inversions, B. Am. Meteorol. Soc., 38, 283–290, https://doi.org/10.1175/1520-0477-38.5.283, 1957. a
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, https://doi.org/10.1007/s10546-012-9760-3,
2013. a
Braun, S. A. and Tao, W.-K.: Sensitivity of high-resolution simulations of
Hurricane Bob (1991) to planetary boundary layer parameterizations, Mon. Weather Rev., 128, 3941–3961, https://doi.org/10.1175/1520-0493(2000)129<3941:SOHRSO>2.0.CO;2, 2000. a
Brown, A. R., Cederwall, R. T., Chlond, A., Duynkerke, P. G., Golaz, J.-C., Khairoutdinov, M., Lewellen, D. C., Lock, A. P., MacVean, M. K.,
Moeng, C.-H., Neggers, R. a. J., Siebesma, A. P., and Stevens, B.: Large-eddy simulation of the diurnal cycle of shallow cumulus convection over land, Q. J. Roy. Meteor. Soc., 128, 1075–1093, https://doi.org/10.1256/003590002320373210,
2002. a
Chachere, C. N. and Pu, Z.: Connections between cold air pools and mountain
valley fog events in Salt Lake City, Pure Appl. Geophys., 173,
3187–3196, https://doi.org/10.1007/s00024-016-1316-x, 2016. a
Chilson, P. B., Bell, T. M., Brewster, K. A., Britto Hupsel de Azevedo, G., Carr, F. H., Carson, K., Doyle, W., Fiebrich, C. A., Greene,
B. R., Grimsley, J. L., Kanneganti, S. T., Martin, J., Moore, A., Palmer, R. D., Pillar-Little, E. A., Salazar-Cerreno, J. L., Segales, A. R.,
Weber, M. E., Yeary, M., and Droegemeier, K. K.: Moving towards a network of autonomous UAS atmospheric profiling stations for
observations in the Earth’s lower atmosphere: The 3D Mesonet concept, Sensors, 19, 2720, https://doi.org/10.3390/s19122720, 2019. a
Cohen, A. E., Cavallo, S. M., Coniglio, M. C., and Brooks, H. E.: A review of
planetary boundary layer parameterization schemes and their sensitivity in
simulating southeastern US cold season severe weather environments, Weather
Forecast., 30, 591–612, https://doi.org/10.1175/WAF-D-14-00105.1, 2015. a
Coniglio, M. C., Romine, G. S., Turner, D. D., and Torn, R. D.: Impacts of
targeted AERI and Doppler lidar wind retrievals on short-term forecasts of
the initiation and early evolution of thunderstorms, Mon. Weather Rev.,
147, 1149–1170, https://doi.org/10.1175/MWR-D-18-0351.1, 2019. a
Cuchiara, G. C., Li, X., Carvalho, J., and Rappenglück, B.: Intercomparison of planetary boundary layer parameterization and its impacts on surface ozone concentration in the WRF/Chem model for a case study in Houston/Texas, Atmos. Environ., 96, 175–185, https://doi.org/10.1016/j.atmosenv.2014.07.013, 2014. a
Dai, C., Wang, Q., Kalogiros, J., Lenschow, D., Gao, Z., and Zhou, M.:
Determining boundary-layer height from aircraft measurements, Bound.-Lay.
Meteorol., 152, 277–302, https://doi.org/10.1007/s10546-014-9929-z, 2014. a, b, c
Dang, R., Yang, Y., Hu, X.-M., Wang, Z., and Zhang, S.: 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, 2019. a, b, c
de Boer, G., Diehl, C., Jacob, J., Houston, A., Smith, S. W., Chilson, P., Schmale, 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., 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., Ar-
grow, 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, https://doi.org/10.1175/BAMS-D-19-0050.1, 2020a. a
de Boer, G., Houston, A., Jacob, J., Chilson, P. B., Smith, S. W., Argrow, B., Lawrence, D., Elston, J., Brus, D., Kemppinen, O., Klein, P., Lundquist, J. K., Waugh, S., Bailey, S. C. C., Frazier, A., Sama, M. P., Crick, C., Schmale III, D., Pinto, J., Pillar-Little, E. A., Natalie, V., and Jensen, A.: Data generated during the 2018 LAPSE-RATE campaign: an introduction and overview, Earth Syst. Sci. Data, 12, 3357–3366, https://doi.org/10.5194/essd-12-3357-2020, 2020b. a, b
Degelia, S. K., Wang, X., Stensrud, D. J., and Johnson, A.: Understanding the
impact of radar and in situ observations on the prediction of a nocturnal
convection initiation event on 25 June 2013 using an ensemble-based
multiscale data assimilation system, Mon. Weather Rev., 146, 1837–1859,
https://doi.org/10.1175/MWR-D-17-0128.1, 2018. a
De Wekker, S. F., Ameen, A., Song, G., Stephens, B. B., Hallar, A. G., and
McCUBBIN, I. B.: A preliminary investigation of boundary layer effects on
daytime atmospheric CO2 concentrations at a mountaintop location in the
Rocky Mountains, Acta Geophys., 57, 904–922,
https://doi.org/10.2478/s11600-009-0033-6, 2009. a
Dias, N., Gonçalves, J., Freire, L., Hasegawa, T., and Malheiros, A.:
Obtaining potential virtual temperature profiles, entrainment fluxes, and
spectra from mini unmanned aerial vehicle data, Bound.-Lay. Meteorol.,
145, 93–111, https://doi.org/10.1007/s10546-011-9693-2, 2012. a
Elston, J., Argrow, B., Stachura, M., Weibel, D., Lawrence, D., and Pope, D.:
Overview of small fixed-wing unmanned aircraft for meteorological sampling,
J. Atmos. Ocean. Tech., 32, 97–115, https://doi.org/10.1175/JTECH-D-13-00236.1, 2015. a
Flagg, D. D., Doyle, J. D., Holt, T. R., Tyndall, D. P., Amerault, C. M.,
Geiszler, D., Haack, T., Moskaitis, J. R., Nachamkin, J., and Eleuterio,
D. P.: On the Impact of Unmanned Aerial System Observations on Numerical
Weather Prediction in the Coastal Zone, Mon. Weather Rev., 146,
599–622, https://doi.org/10.1175/MWR-D-17-0028.1, 2018. a
Gebauer, J. G., Fedorovich, E., and Shapiro, A.: A 1D theoretical analysis of
northerly low-level jets over the Great Plains, J. Atmos. Sci., 74, 3419–3431, https://doi.org/10.1175/JAS-D-16-0333.1, 2017. a
Greene, B. R., Segales, A. R., Waugh, S., Duthoit, S., and Chilson, P. B.: Considerations for temperature sensor placement on rotary-wing unmanned aircraft systems, Atmos. Meas. Tech., 11, 5519–5530, https://doi.org/10.5194/amt-11-5519-2018, 2018. a
Greene, B. R., Segales, A. R., Bell, T. M., Pillar-Little, E. A., and Chilson, P. B.: Environmental and sensor integration influences on temperature measurements by rotary-wing unmanned aircraft systems, Sensors, 19, 1470, https://doi.org/10.3390/s19061470, 2019. a, b
Greene, B. R., Bell, T. M., Pillar-Little, E. A., Segales, A. R., Britto Hupsel de Azevedo, G., Doyle, W., Tripp, D. D., Kanneganti, S. T., and Chilson, P. B.: University of Oklahoma CopterSonde Files from LAPSE-RATE (Version v1), Zenodo [data set], https://doi.org/10.5281/zenodo.3737087, 2020. a
Hennemuth, B. and Lammert, A.: Determination of the atmospheric boundary layer height from radiosonde and lidar backscatter, Bound.-Lay. Meteorol.,
120, 181–200, https://doi.org/10.1007/s10546-005-9035-3, 2006. a
Houston, A. L. and Niyogi, D.: The sensitivity of convective initiation to the lapse rate of the active cloud-bearing layer, Mon. Weather Rev., 135,
3013–3032, https://doi.org/10.1175/MWR3449.1, 2007. a
Hu, J., Yussouf, N., Turner, D. D., Jones, T. A., and Wang, X.: Impact of
ground-based remote sensing boundary layer observations on short-term
probabilistic forecasts of a tornadic supercell event, Weather Forecast., 34, 1453–1476, https://doi.org/10.1175/WAF-D-18-0200.1, 2019. a
Hu, X.-M., Nielsen-Gammon, J. W., and Zhang, F.: Evaluation of three planetary boundary layer schemes in the WRF model, J. Appl. Meteorol. Clim., 49, 1831–1844, https://doi.org/10.1175/2010JAMC2432.1, 2010. a
Jonassen, M. O., Ólafsson, H., Ágústsson, H., Rögnvaldsson,
Ó., and Reuder, J.: Improving high-resolution numerical weather
simulations by assimilating data from an unmanned aerial system, Mon.
Weather Rev., 140, 3734–3756, https://doi.org/10.1175/MWR-D-11-00344.1, 2012. a
Jones, T. A., Knopfmeier, K., Wheatley, D., Creager, G., Minnis, P., and
Palikonda, R.: Storm-scale data assimilation and ensemble forecasting with
the NSSL experimental Warn-on-Forecast system. Part II: Combined radar and
satellite data experiments, Weather Forecast., 31, 297–327,
https://doi.org/10.1175/WAF-D-15-0107.1, 2016. a
Koch, S. E., Fengler, M., Chilson, P. B., Elmore, K. L., Argrow, B., Andra Jr., D. L., and Lindley, T.: On the use of unmanned aircraft for sampling mesoscale phenomena in the preconvective boundary layer, J. Atmos. Ocean. Tech., 35, 2265–2288, https://doi.org/10.1175/JTECH-D-18-0101.1, 2018. a
Kral, S. T., Reuder, J., Vihma, T., Suomi, I., Haualand, K. F., Urbancic, G. H., Greene, B. R., Steeneveld, G.-J., Lorenz, T., Maronga, B.,
Jonassen, M. O., Ajosenpää, H., Båserud, L., Chilson, P. B., Holtslag, A. A. M., Jenkins, A. D., Kouznetsov, R., Mayer, S., Pillar-Little,
E. A., Rautenberg, A., Schwenkel, J., Seidl, A. W., and Wrenger, B.: The innovative strategies for observations in the arctic atmospheric boundary layer project (ISOBAR): Unique finescale observations under stable and very stable conditions, B. Am. Meteorol. Soc., 102, E218–E243, https://doi.org/10.1175/BAMS-D-19-0212.1, 2021. a
Lapworth, A.: The morning transition of the nocturnal boundary layer,
Bound.-Lay. Meteorol., 119, 501–526, https://doi.org/10.1007/s10546-005-9046-0,
2006. a
Lenschow, D., Stankov, B., and Mahrt, L.: The rapid morning boundary-layer
transition, J. Atmos. Sci., 36, 2108–2124,
https://doi.org/10.1175/1520-0469(1979)036<2108:TRMBLT>2.0.CO;2, 1979. a
Lewis, W. E., Wagner, T. J., Otkin, J. A., and Jones, T. A.: Impact of AERI
Temperature and Moisture Retrievals on the Simulation of a Central Plains
Severe Convective Weather Event, Atmosphere, 11, 729,
https://doi.org/10.3390/atmos11070729, 2020. a
Martucci, G., Matthey, R., Mitev, V., and Richner, H.: Comparison between
backscatter lidar and radiosonde measurements of the diurnal and nocturnal
stratification in the lower troposphere, J. Atmos. Ocean. Tech., 24, 1231–1244, https://doi.org/10.1175/JTECH2036.1, 2007. a, b
National Research Council: Observing weather and climate from the ground up: A nationwide network of networks, National Academies Press, 2009. a
Nilsson, E., Rannik, Ü., Kumala, M., Buzorius, G., and O’Dowd, C.:
Effects of continental boundary layer evolution, convection, turbulence and
entrainment, on aerosol formation, Tellus B, 53, 441–461, https://doi.org/10.3402/tellusb.v53i4.16617, 2001. a
Nolan, D. S., Zhang, J. A., and Stern, D. P.: Evaluation of planetary boundary layer parameterizations in tropical cyclones by comparison of in situ observations and high-resolution simulations of Hurricane Isabel (2003). Part II: Inner-core boundary layer and eyewall structure, Mon. Weather Rev.,
137, 3675–3698, https://doi.org/10.1175/2009MWR2785.1, 2009. a
Otkin, J. A., Hartung, D. C., Turner, D. D., Petersen, R. A., Feltz, W. F., and Janzon, E.: Assimilation of surface-based boundary layer profiler observations during a cool-season weather event using an observing system simulation experiment. Part I: Analysis impact, Mon. Weather Rev., 139, 2309–2326, https://doi.org/10.1175/2011MWR3622.1, 2011. a
Pal, S., Lee, T., Phelps, S., and De Wekker, S.: Impact of atmospheric boundary layer depth variability and wind reversal on the diurnal variability of aerosol concentration at a valley site, Sci. Total Environ., 496, 424–434, https://doi.org/10.1016/j.scitotenv.2014.07.067, 2014. a
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 the CopterSonde 2 remotely piloted aircraft system in support of the LAPSE-RATE field campaign, Earth Syst. Sci. Data, 13, 269–280, https://doi.org/10.5194/essd-13-269-2021, 2021. a, b
Reen, B. P., Stauffer, D. R., and Davis, K. J.: Land-surface heterogeneity
effects in the planetary boundary layer, Bound.-Lay. Meteorol., 150,
1–31, https://doi.org/10.1007/s10546-013-9860-8, 2014. a
Reuder, J., Brisset, P., Jonassen, M., Müller, M., and Mayer, S.: The Small Unmanned Meteorological Observer SUMO: A new tool for atmospheric boundary layer research, Meteorol. Z., 18, 141–147,
https://doi.org/10.1127/0941-2948/2009/0363, 2009. a
Ruggiero, F. H., Sashegyi, K. D., Madala, R. V., and Raman, S.: The use of surface observations in four-dimensional data assimilation using a mesoscale model, Mon. Weather Rev., 124, 1018–1033, https://doi.org/10.1175/1520-0493(1996)124<1018:TUOSOI>2.0.CO;2, 1996. a
Segales, A. R., Greene, B. R., Bell, T. M., Doyle, W., Martin, J. J., Pillar-Little, E. A., and Chilson, P. B.: The CopterSonde: an insight into the development of a smart unmanned aircraft system for atmospheric boundary layer research, Atmos. Meas. Tech., 13, 2833–2848, https://doi.org/10.5194/amt-13-2833-2020, 2020. a, b
Seibert, P., Beyrich, F., Gryning, S.-E., Joffre, S., Rasmussen, A., and
Tercier, P.: Review and intercomparison of operational methods for the
determination of the mixing height, Atmos. Environ., 34, 1001–1027,
https://doi.org/10.1016/S1352-2310(99)00349-0, 2000. a
Shapiro, A. and Fedorovich, E.: Nocturnal low-level jet over a shallow slope,
Acta Geophys., 57, 950–980, https://doi.org/10.2478/s11600-009-0026-5, 2009. a
Shapiro, A., Fedorovich, E., and Rahimi, S.: A unified theory for the Great
Plains nocturnal low-level jet, J. Atmos. Sci., 73, 3037–3057, https://doi.org/10.1175/JAS-D-15-0307.1, 2016. a, b, c
Steeneveld, G., Mauritsen, T., de Bruijn, E., Vilà-Guerau de Arellano, J., Svensson, G., and Holtslag, A.: Evaluation of limited-area models for the representation of the diurnal cycle and contrasting nights in CASES-99, J. Appl. Meteorol. Clim., 47, 869–887, https://doi.org/10.1175/2007JAMC1702.1, 2008. a
Stull, R.: 1988: An Introduction to Boundary Layer Meteorology, Kluwer A cademic Publishers, ISBN 9789027727688, 1988. a
Teixeira, J., Stevens, B., Bretherton, C. S., Cederwall, R., Doyle, J. D., Golaz, J. C., Holtslag, A. a. M., Klein, S. A., Lundquist, J. K.,
Randall, D. A., Siebesma, A. P., and Soares, P. M. M.: Parameterization of the atmospheric boundary layer: a view from just above the inversion, B. Am. Meteorol. Soc., 89, 453–458, https://doi.org/10.1175/BAMS-89-4-453, 2008. a
Trier, S. B., Davis, C. A., Ahijevych, D. A., and Manning, K. W.: Use of the
parcel buoyancy minimum (B min) to diagnose simulated thermodynamic
destabilization. Part I: Methodology and case studies of MCS initiation
environments, Mon. Weather Rev., 142, 945–966,
https://doi.org/10.1175/MWR-D-13-00272.1, 2014. a, b
Villa, T. F., Gonzalez, F., Miljievic, B., Ristovski, Z. D., and Morawska, L.: An overview of small unmanned aerial vehicles for air quality measurements: Present applications and future prospectives, Sensors, 16, 1072, https://doi.org/10.3390/s16071072, 2016. a
Wagner, T. J., Klein, P. M., and Turner, D. D.: A new generation of ground-based mobile platforms for active and passive profiling of the boundary layer, B. Am. Meteorol. Soc., 100, 137–153, https://doi.org/10.1175/BAMS-D-17-0165.1, 2019.
a
Weckwerth, T. M., Horst, T. W., and Wilson, J. W.: An observational study of
the evolution of horizontal convective rolls, Mon. Weather Rev., 127,
2160–2179, https://doi.org/10.1175/1520-0493(1999)127<2160:AOSOTE>2.0.CO;2, 1999. a
Weisman, M. L. and Rotunno, R.: “A theory for strong long-lived squall lines” revisited, J. Atmos. Sci., 61, 361–382, https://doi.org/10.1175/1520-0469(2004)061<0361:ATFSLS>2.0.CO;2, 2004. a
Zhang, Y. and Klein, S. A.: Mechanisms affecting the transition from shallow to deep convection over land: Inferences from observations of the diurnal cycle collected at the ARM Southern Great Plains site, J. Atmos. Sci., 67, 2943–2959, https://doi.org/10.1175/2010JAS3366.1, 2010. a, b
Ziegler, C. L. and Rasmussen, E. N.: The initiation of moist convection at the dryline: forecasting issues from a case study perspective, Weather Forecast., 13, 1106–1131, https://doi.org/10.1175/1520-0434(1998)013<1106:TIOMCA>2.0.CO;2, 1998. a
Short summary
This study evaluates how a classically defined variable, air parcel buoyancy, can be used to interpret transitions in the atmospheric boundary layer (ABL). To capture the high-resolution variations, remotely piloted aircraft systems are used to collect data in two field campaigns. This paper finds that buoyancy has distinct evolutions prior to low-level jet and convective initiation cases. Additionally, buoyancy mixes well to act as an ABL height indicator comparable to other methods.
This study evaluates how a classically defined variable, air parcel buoyancy, can be used to...