Angevine, W. M., A. B. White, and S. K. Avery, 1994: Boundary-layer depth and entrainment zone characterization with a boundary-layer profiler. Bound.-Layer Meteor., 68, 375–385, https://doi.org/10.1007/BF00706797.
Bianco, L., J. M. Wilczak, and A. B. White, 2008: Convective boundary layer depth estimation from wind profilers: Statistical comparison between an automated algorithm and expert estimations. J. Atmos. Oceanic Technol., 25, 1397–1413, https://doi.org/10.1175/2008JTECHA981.1.
Bright, D. R., and S. L. Mullen, 2002: The sensitivity of the numerical simulation of the southwest monsoon boundary layer to the choice of PBL turbulence parameterization in MM5. Wea. Forecasting, 17, 99–114, https://doi.org/10.1175/1520-0434(2002)017<0099:TSOTNS>2.0.CO;2.
Clements, C. B., and Coauthors, 2007: Observing the dynamics of wildland grass fires: FireFlux–A field validation experiment. Bull. Amer. Meteor. Soc., 88, 1369–1382, https://doi.org/10.1175/BAMS-88-9-1369.
Coniglio, M. C., J. Correia Jr., P. T. Marsh, and F. Kong, 2013: Verification of convection-allowing WRF Model forecasts of the planetary boundary layer using sounding observations. Wea. Forecasting, 28, 842–862, https://doi.org/10.1175/WAF-D-12-00103.1.
Dabberdt, W. F., and Coauthors, 2004: Meteorological research needs for improved air quality forecasting: Report of the 11th Prospectus Development Team of the U.S. Weather Research Program. Bull. Amer. Meteor. Soc., 85, 563–586, https://doi.org/10.1175/BAMS-85-4-563.
Demoz, B., K. Vermeesch, M. Hicks, D. Atkinson, R. Delgado, and R. K. Sakai, 2017: Towards a ceilometer-lidar network in ASOS: Progress, problems, and prospects. Observation Symposium: Progress, Problems, and Prospects, Seattle, WA, Amer. Meteor. Soc., 1010, https://ams.confex.com/ams/97Annual/webprogram/Paper311707.html.
Doviak, R. J., and D. S. Zrnić, 1993: Doppler Radar and Weather Observations. 2nd ed. Academic Press, 562 pp.
Elmore, K. L., P. L. Heinselman, and D. J. Stensrud, 2012: Using WSR-88D data and insolation estimates to determine convective boundary layer depth. J. Atmos. Oceanic Technol., 29, 581–588, https://doi.org/10.1175/JTECH-D-11-00043.1.
Grimsdell, A. W., and W. M. Angevine, 1998: Convective boundary layer height measurement with wind profilers and comparison to cloud base. J. Atmos. Oceanic Technol., 15, 1331–1338, https://doi.org/10.1175/1520-0426(1998)015<1331:CBLHMW>2.0.CO;2.
Heinselman, P. L., P. L. Spencer, K. L. Elmore, D. J. Stensrud, R. M. Hluchan, and P. C. Burke, 2009: Radar reflectivity–based estimates of mixed layer depth. J. Atmos. Oceanic Technol., 26, 229–239, https://doi.org/10.1175/2008JTECHA1091.1.
Holzworth, G. C., 1964: Estimates of mean maximum mixing depths in the contiguous United States. Mon. Wea. Rev., 92, 235–242, https://doi.org/10.1175/1520-0493(1964)092<0235:EOMMMD>2.3.CO;2.
Kumjian, M. R., 2013: Principles and applications of dual-polarization weather radar. Part I: Description of the polarimetric radar variables. J. Oper. Meteor., 1, 226–242, https://doi.org/10.15191/nwajom.2013.0119.
Kumjian, M. R., A. V. Ryzhkov, H. D. Reeves, and T. J. Schuur, 2013: A dual-polarization radar signature of hydrometeor refreezing in winter storms. J. Appl. Meteor. Climatol., 52, 2549–2566, https://doi.org/10.1175/JAMC-D-12-0311.1.
Melnikov, V. M., R. J. Doviak, D. S. Zrnić, and D. J. Stensrud, 2011: Mapping Bragg scatter with a polarimetric WSR-88D. J. Atmos. Oceanic Technol., 28, 1273–1285, https://doi.org/10.1175/JTECH-D-10-05048.1.
Melnikov, V. M., R. J. Doviak, D. S. Zrnić, and D. J. Stensrud, 2013: Structures of Bragg scatter observed with the polarimetric WSR-88D. J. Atmos. Oceanic Technol., 30, 1253–1258, https://doi.org/10.1175/JTECH-D-12-00210.1.
NOAA, 2017: Operational modes and volume coverage patterns. Doppler radar meteorological observations; Part C: WSR-88D products and algorithms, Federal Meteorological Handbook 11, FCM-H11C-2017, Office of the Federal Coordinator for Meteorological Services and Supporting Research, 5-1–5-24, https://www.ofcm.gov/publications/fmh/FMH11/fmh11partC.pdf.
NRC, 2009: Observing Weather and Climate from the Ground Up: A Nationwide Network of Networks. The National Academies Press, 250 pp., https://doi.org/10.17226/12540.
Rabin, R. M., and R. J. Doviak, 1989: Meteorological and astronomical influences on radar reflectivity in the convective boundary layer. J. Appl. Meteor., 28, 1226–1235, https://doi.org/10.1175/1520-0450(1989)028<1226:MAAIOR>2.0.CO;2.
Richardson, L. M., J. G. Cunningham, W. D. Zittel, R. R. Lee, R. L. Ice, V. M. Melnikov, N. P. Hoban, and J. G. Gebauer, 2017a: Bragg scatter detection by the WSR-88D. Part I: Algorithm development. J. Atmos. Oceanic Technol., 34, 465–478, https://doi.org/10.1175/JTECH-D-16-0030.1.
Richardson, L. M., W. D. Zittel, R. R. Lee, V. M. Melnikov, R. L. Ice, and J. G. Cunningham, 2017b: Bragg scatter detection by the WSR-88D. Part II: Assessment of ZDR bias estimation. J. Atmos. Oceanic Technol., 34, 479–493, https://doi.org/10.1175/JTECH-D-16-0031.1.
Ryzhkov, A., P. Zhang, H. Reeves, M. Kumjian, T. Tschallener, S. Trömel, and C. Simmer, 2016: Quasi-vertical profiles—A new way to look at polarimetric radar data. J. Atmos. Oceanic Technol., 33, 551–562, https://doi.org/10.1175/JTECH-D-15-0020.1.
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, 1001–1027, https://doi.org/10.1016/S1352-2310(99)00349-0.
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.
Seliga, T. A., and V. Bringi, 1976: Potential use of radar differential reflectivity measurements at orthogonal polarizations for measuring precipitation. J. Appl. Meteor., 15, 69–76, https://doi.org/10.1175/1520-0450(1976)015<0069:PUORDR>2.0.CO;2.
Stensrud, D. J., and S. J. Weiss, 2002: Mesoscale model ensemble forecasts of the 3 May 1999 tornado outbreak. Wea. Forecasting, 17, 526–543, https://doi.org/10.1175/1520-0434(2002)017<0526:MMEFOT>2.0.CO;2.
Stull, R. B., 1988: An Introduction to Boundary Layer Meteorology. Atmospheric and Oceanographic Sciences Library, Vol. 13, Kluwer Academic Publishers, 670 pp., https://doi.org/10.1007/978-94-009-3027-8.
Weiss, G., 1961: Wave Propagation in a Turbulent Medium (by V. I. Tatarski). Science, 134, 324–325, https://doi.org/10.1126/science.134.3475.324-b.
White, A., 1993: Mixing depth detection using 915-MHz radar reflectivity data. Preprints, Eighth Symp. on Meteorological Observations and Instrumentation, Anaheim, CA, Amer. Meteor. Soc., 248–250.
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Convective Boundary Layer Depth Estimation from S-Band Dual-Polarization Radar
Displayed acceptance dates for articles published prior to 2023 are approximate to within a week. If needed, exact acceptance dates can be obtained by emailing amsjol@ametsoc.org.
This study investigates Bragg scatter signatures in dual-polarization radar observations, which are defined by low differential reflectivity 
© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).
This study investigates Bragg scatter signatures in dual-polarization radar observations, which are defined by low differential reflectivity
© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).
Angevine, W. M., A. B. White, and S. K. Avery, 1994: Boundary-layer depth and entrainment zone characterization with a boundary-layer profiler. Bound.-Layer Meteor., 68, 375–385, https://doi.org/10.1007/BF00706797.
Bianco, L., J. M. Wilczak, and A. B. White, 2008: Convective boundary layer depth estimation from wind profilers: Statistical comparison between an automated algorithm and expert estimations. J. Atmos. Oceanic Technol., 25, 1397–1413, https://doi.org/10.1175/2008JTECHA981.1.
Bright, D. R., and S. L. Mullen, 2002: The sensitivity of the numerical simulation of the southwest monsoon boundary layer to the choice of PBL turbulence parameterization in MM5. Wea. Forecasting, 17, 99–114, https://doi.org/10.1175/1520-0434(2002)017<0099:TSOTNS>2.0.CO;2.
Clements, C. B., and Coauthors, 2007: Observing the dynamics of wildland grass fires: FireFlux–A field validation experiment. Bull. Amer. Meteor. Soc., 88, 1369–1382, https://doi.org/10.1175/BAMS-88-9-1369.
Coniglio, M. C., J. Correia Jr., P. T. Marsh, and F. Kong, 2013: Verification of convection-allowing WRF Model forecasts of the planetary boundary layer using sounding observations. Wea. Forecasting, 28, 842–862, https://doi.org/10.1175/WAF-D-12-00103.1.
Dabberdt, W. F., and Coauthors, 2004: Meteorological research needs for improved air quality forecasting: Report of the 11th Prospectus Development Team of the U.S. Weather Research Program. Bull. Amer. Meteor. Soc., 85, 563–586, https://doi.org/10.1175/BAMS-85-4-563.
Demoz, B., K. Vermeesch, M. Hicks, D. Atkinson, R. Delgado, and R. K. Sakai, 2017: Towards a ceilometer-lidar network in ASOS: Progress, problems, and prospects. Observation Symposium: Progress, Problems, and Prospects, Seattle, WA, Amer. Meteor. Soc., 1010, https://ams.confex.com/ams/97Annual/webprogram/Paper311707.html.
Doviak, R. J., and D. S. Zrnić, 1993: Doppler Radar and Weather Observations. 2nd ed. Academic Press, 562 pp.
Elmore, K. L., P. L. Heinselman, and D. J. Stensrud, 2012: Using WSR-88D data and insolation estimates to determine convective boundary layer depth. J. Atmos. Oceanic Technol., 29, 581–588, https://doi.org/10.1175/JTECH-D-11-00043.1.
Grimsdell, A. W., and W. M. Angevine, 1998: Convective boundary layer height measurement with wind profilers and comparison to cloud base. J. Atmos. Oceanic Technol., 15, 1331–1338, https://doi.org/10.1175/1520-0426(1998)015<1331:CBLHMW>2.0.CO;2.
Heinselman, P. L., P. L. Spencer, K. L. Elmore, D. J. Stensrud, R. M. Hluchan, and P. C. Burke, 2009: Radar reflectivity–based estimates of mixed layer depth. J. Atmos. Oceanic Technol., 26, 229–239, https://doi.org/10.1175/2008JTECHA1091.1.
Holzworth, G. C., 1964: Estimates of mean maximum mixing depths in the contiguous United States. Mon. Wea. Rev., 92, 235–242, https://doi.org/10.1175/1520-0493(1964)092<0235:EOMMMD>2.3.CO;2.
Kumjian, M. R., 2013: Principles and applications of dual-polarization weather radar. Part I: Description of the polarimetric radar variables. J. Oper. Meteor., 1, 226–242, https://doi.org/10.15191/nwajom.2013.0119.
Kumjian, M. R., A. V. Ryzhkov, H. D. Reeves, and T. J. Schuur, 2013: A dual-polarization radar signature of hydrometeor refreezing in winter storms. J. Appl. Meteor. Climatol., 52, 2549–2566, https://doi.org/10.1175/JAMC-D-12-0311.1.
Melnikov, V. M., R. J. Doviak, D. S. Zrnić, and D. J. Stensrud, 2011: Mapping Bragg scatter with a polarimetric WSR-88D. J. Atmos. Oceanic Technol., 28, 1273–1285, https://doi.org/10.1175/JTECH-D-10-05048.1.
Melnikov, V. M., R. J. Doviak, D. S. Zrnić, and D. J. Stensrud, 2013: Structures of Bragg scatter observed with the polarimetric WSR-88D. J. Atmos. Oceanic Technol., 30, 1253–1258, https://doi.org/10.1175/JTECH-D-12-00210.1.
NOAA, 2017: Operational modes and volume coverage patterns. Doppler radar meteorological observations; Part C: WSR-88D products and algorithms, Federal Meteorological Handbook 11, FCM-H11C-2017, Office of the Federal Coordinator for Meteorological Services and Supporting Research, 5-1–5-24, https://www.ofcm.gov/publications/fmh/FMH11/fmh11partC.pdf.
NRC, 2009: Observing Weather and Climate from the Ground Up: A Nationwide Network of Networks. The National Academies Press, 250 pp., https://doi.org/10.17226/12540.
Rabin, R. M., and R. J. Doviak, 1989: Meteorological and astronomical influences on radar reflectivity in the convective boundary layer. J. Appl. Meteor., 28, 1226–1235, https://doi.org/10.1175/1520-0450(1989)028<1226:MAAIOR>2.0.CO;2.
Richardson, L. M., J. G. Cunningham, W. D. Zittel, R. R. Lee, R. L. Ice, V. M. Melnikov, N. P. Hoban, and J. G. Gebauer, 2017a: Bragg scatter detection by the WSR-88D. Part I: Algorithm development. J. Atmos. Oceanic Technol., 34, 465–478, https://doi.org/10.1175/JTECH-D-16-0030.1.
Richardson, L. M., W. D. Zittel, R. R. Lee, V. M. Melnikov, R. L. Ice, and J. G. Cunningham, 2017b: Bragg scatter detection by the WSR-88D. Part II: Assessment of ZDR bias estimation. J. Atmos. Oceanic Technol., 34, 479–493, https://doi.org/10.1175/JTECH-D-16-0031.1.
Ryzhkov, A., P. Zhang, H. Reeves, M. Kumjian, T. Tschallener, S. Trömel, and C. Simmer, 2016: Quasi-vertical profiles—A new way to look at polarimetric radar data. J. Atmos. Oceanic Technol., 33, 551–562, https://doi.org/10.1175/JTECH-D-15-0020.1.
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, 1001–1027, https://doi.org/10.1016/S1352-2310(99)00349-0.
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.
Seliga, T. A., and V. Bringi, 1976: Potential use of radar differential reflectivity measurements at orthogonal polarizations for measuring precipitation. J. Appl. Meteor., 15, 69–76, https://doi.org/10.1175/1520-0450(1976)015<0069:PUORDR>2.0.CO;2.
Stensrud, D. J., and S. J. Weiss, 2002: Mesoscale model ensemble forecasts of the 3 May 1999 tornado outbreak. Wea. Forecasting, 17, 526–543, https://doi.org/10.1175/1520-0434(2002)017<0526:MMEFOT>2.0.CO;2.
Stull, R. B., 1988: An Introduction to Boundary Layer Meteorology. Atmospheric and Oceanographic Sciences Library, Vol. 13, Kluwer Academic Publishers, 670 pp., https://doi.org/10.1007/978-94-009-3027-8.
Weiss, G., 1961: Wave Propagation in a Turbulent Medium (by V. I. Tatarski). Science, 134, 324–325, https://doi.org/10.1126/science.134.3475.324-b.
White, A., 1993: Mixing depth detection using 915-MHz radar reflectivity data. Preprints, Eighth Symp. on Meteorological Observations and Instrumentation, Anaheim, CA, Amer. Meteor. Soc., 248–250.
| All Time | Past Year | Past 30 Days | |
|---|---|---|---|
| Abstract Views | 0 | 0 | 0 |
| Full Text Views | 1052 | 260 | 12 |
| PDF Downloads | 894 | 189 | 14 |
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