• Adler, R. F., and D. D. Fenn, 1979: Thunderstorm vertical velocities estimated from satellite data. J. Atmos. Sci., 36, 17471754, doi:10.1175/1520-0469(1979)036<1747:TVVEFS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Adler, R. F., and D. D. Fenn, 1981: Satellite-observed cloud-top height changes in tornadic thunderstorms. J. Appl. Meteor., 20, 13691375, doi:10.1175/1520-0450(1981)020<1369:SOCTHC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Barnes, G. M., 1995: Updraft evolution: A perspective from cloud base. Mon. Wea. Rev., 123, 26932715, doi:10.1175/1520-0493(1995)123<2693:UEAPFC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Baum, B. A., P. F. Soulen, K. I. Strabala, M. D. King, S. A. Ackerman, W. P. Menzel, and P. Yang, 2000: Remote sensing of cloud properties using MODIS airborne simulator imagery during SUCCESS. 2. Cloud thermodynamic phase. J. Geophys. Res., 105, 11 78111 792, doi:10.1029/1999JD901090.

    • Search Google Scholar
    • Export Citation
  • Bedka, K., J. Brunner, R. Dworak, W. Feltz, J. Otkin, and T. Greenwald, 2010: Objective satellite-based detection of overshooting tops using infrared window channel brightness temperature gradients. J. Appl. Meteor. Climatol., 49, 181202, doi:10.1175/2009JAMC2286.1.

    • Search Google Scholar
    • Export Citation
  • Bedka, K., R. Dworak, J. Brunner, and W. Feltz, 2012: Validation of satellite-based objective overshooting cloud-top detection methods using CloudSat cloud profiling radar observations. J. Appl. Meteor. Climatol., 51, 18111822, doi:10.1175/JAMC-D-11-0131.1.

    • Search Google Scholar
    • Export Citation
  • Benjamin, S. G., and Coauthors, 2009: Rapid Refresh/Rapid Update Cycle (RR/RUC) technical review. NOAA/ESRL/GSD Internal Review, 168 pp. [Available online at http://ruc.noaa.gov/pdf/RR-RUC-TR_11_3_2009.pdf.]

  • Bonesteele, R. G., and Y. J. Lin, 1978: A study of updraft–downdraft interaction based on perturbation pressure and single-Doppler radar data. Mon. Wea. Rev., 106, 6268, doi:10.1175/1520-0493(1978)106<0062:ASOUDI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Buban, M. S., C. L. Ziegler, E. N. Rasmussen, and Y. P. Richardson, 2007: The dryline on 22 May 2002 during IHOP: Ground-radar and in situ data analyses of the dryline and boundary layer evolution. Mon. Wea. Rev., 135, 24732505, doi:10.1175/MWR3453.1.

    • Search Google Scholar
    • Export Citation
  • Byers, H. R., and R. R. Braham, 1949: The Thunderstorm. U.S. Dept. of Commerce, 287 pp.

  • Cho, H.-R., 1985: Rates of entrainment and detrainment of momentum of cumulus clouds. Mon. Wea. Rev., 113, 19201932, doi:10.1175/1520-0493(1985)113<1920:ROEADO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Cintineo, J. L., M. J. Pavolonis, J. M. Sieglaff, and A. K. Heidinger, 2013: Evolution of severe and nonsevere convection inferred from GOES-derived cloud properties. J. Appl. Meteor. Climatol., 52, 20092023, doi:10.1175/JAMC-D-12-0330.1.

    • Search Google Scholar
    • Export Citation
  • Cohen, J., P. Cohen, S. G. West, and L. S. Aiken, 2003: Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences. 3rd ed. Routledge, 736 pp.

  • Cotton, W. R., G. H. Bryan, and S. C. van den Heever, 2011: Storm and Cloud Dynamics—The Dynamics of Clouds and Precipitating Mesoscale Systems. 2nd ed. Academic Press, 809 pp.

  • Doswell, C. A., III, and P. M. Markowski, 2004: Is buoyancy a relative quantity? Mon. Wea. Rev., 132, 853863, doi:10.1175/1520-0493(2004)132<0853:IBARQ>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Emanuel, K. A., 1994: Atmospheric Convection. Oxford University Press, 580 pp.

  • Geerts, B., T. Andretta, S. J. Luberda, J. Vogt, Y. Wang, L. D. Oolman, J. Finch, and D. Bikos, 2009: A case study of a long-lived tornadic mesocyclone in a low-CAPE complex-terrain environment. Electron. J. Severe Storms Meteor, 4 (3), 129. [Available online at http://www.ejssm.org/ojs/index.php/ejssm/article/viewArticle/59.]

    • Search Google Scholar
    • Export Citation
  • Goodman, S. J., and Coauthors, 2012: The GOES-R Proving Ground: Accelerating user readiness for the next-generation geostationary environmental satellite system. Bull. Amer. Meteor. Soc., 93, 10291040, doi:10.1175/BAMS-D-11-00175.1.

    • Search Google Scholar
    • Export Citation
  • Hong, G., P. Yang, B.-C. Gao, B. A. Baum, Y. X. Hu, M. D. King, and S. Platnick, 2007: High cloud properties from three years of MODIS Terra and Aqua collection-4 data over the tropics. J. Appl. Meteor. Climatol., 46, 18401856, doi:10.1175/2007JAMC1583.1.

    • Search Google Scholar
    • Export Citation
  • Houston, A. L., and D. Niyogi, 2007: The sensitivity of convective initiation to the lapse rate of the active cloud-bearing layer. Mon. Wea. Rev., 135, 30133032, doi:10.1175/MWR3449.1.

    • Search Google Scholar
    • Export Citation
  • Houze, R. A., Jr., 1993: Cloud Dynamics. Academic Press, 573 pp.

  • James, R. P., and P. M. Markowski, 2010: A numerical investigation of the effects of dry air aloft on deep convection. Mon. Wea. Rev., 138, 140161, doi:10.1175/2009MWR3018.1.

    • Search Google Scholar
    • Export Citation
  • Johnson, R. H., and D. C. Kriete, 1982: Thermodynamic and circulation characteristics, of winter monsoon tropical mesoscale convection. Mon. Wea. Rev., 110, 18981911, doi:10.1175/1520-0493(1982)110<1898:TACCOW>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Johnson, R. H., T. M. Rickenbach, S. A. Rutledge, P. E. Ciesielski, and W. H. Schubert, 1999: Trimodal characteristics of tropical convection. J. Climate, 12, 23972418, doi:10.1175/1520-0442(1999)012<2397:TCOTC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Kirkpatrick, C., E. W. McCaul Jr., and C. Cohen, 2011: Sensitivities of simulated convective storms to environmental CAPE. Mon. Wea. Rev., 139, 35143532, doi:10.1175/2011MWR3631.1.

    • Search Google Scholar
    • Export Citation
  • Lensky, I. M., and D. Rosenfeld, 2006: The time-space exchangeability of satellite retrieved relations between cloud top temperature and particle effective radius. Atmos. Chem. Phys., 6, 28872894, doi:10.5194/acp-6-2887-2006.

    • Search Google Scholar
    • Export Citation
  • Lindell, M. K., and H. Brooks, 2013: Workshop on Weather Ready Nation: Science imperatives for severe thunderstorm research. Bull. Amer. Meteor. Soc., 94, ES171ES174, doi:10.1175/BAMS-D-12-00238.1.

    • Search Google Scholar
    • Export Citation
  • Lindsey, D. T., D. W. Hillger, L. Grasso, J. A. Knaff, and J. F. Dostalek, 2006: GOES climatology and analysis of thunderstorms with enhanced 3.9-μm reflectivity. Mon. Wea. Rev., 134, 23422353, doi:10.1175/MWR3211.1.

    • Search Google Scholar
    • Export Citation
  • Ludlam, F. H., and R. S. Scorer, 1953: Convection in the atmosphere. Quart. J. Roy. Meteor. Soc., 79, 317341, doi:10.1002/qj.49707934102.

    • Search Google Scholar
    • Export Citation
  • Manzato, A., S. Davolio, M. M. Miglietta, A. Pucillo, and M. Setvák, 2015: 12 September 2012: A supercell outbreak in NE Italy? Atmos. Res., 153, 98118, doi:10.1016/j.atmosres.2014.07.019.

    • Search Google Scholar
    • Export Citation
  • Marwitz, J. D., 1973: Trajectories within the weak echo regions of hailstorms. J. Appl. Meteor., 12, 11741182, doi:10.1175/1520-0450(1973)012<1174:TWTWER>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • McCaul, E. W., Jr., and M. L. Weisman, 2001: The sensitivity of simulated supercell structure and intensity to variations in the shapes of environmental buoyancy and shear profiles. Mon. Wea. Rev., 129, 664687, doi:10.1175/1520-0493(2001)129<0664:TSOSSS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Mecikalski, J. R., and K. M. Bedka, 2006: Forecasting convective initiation by monitoring the evolution of moving convection in daytime GOES imagery. Mon. Wea. Rev., 134, 4978, doi:10.1175/MWR3062.1.

    • Search Google Scholar
    • Export Citation
  • Mecikalski, J. R., K. M. Bedka, S. J. Paech, and L. A. Litten, 2008: A statistical evaluation of GOES cloud-top properties for predicting convective initiation. Mon. Wea. Rev., 136, 48994914, doi:10.1175/2008MWR2352.1.

    • Search Google Scholar
    • Export Citation
  • Mecikalski, J. R., P. Watts, and M. Koenig, 2011: Use of Meteosat Second Generation Optimal Cloud Analysis fields for understanding physical attributes of growing cumulus clouds. Atmos. Res., 102, 17519, doi:10.1016/j.atmosres.2011.06.023.

    • Search Google Scholar
    • Export Citation
  • Mecikalski, J. R., J. K. Williams, C. P. Jewett, D. Ahijevych, A. LeRoy, and J. R. Walker, 2015: Probabilistic 0–1-h convective initiation nowcasts that combine geostationary satellite observations and numerical weather prediction model data. J. Appl. Meteor. Climatol., 54, 10391059, doi:10.1175/JAMC-D-14-0129.1.

    • Search Google Scholar
    • Export Citation
  • Min, Q., and M. Duan, 2005: Simultaneously retrieving cloud optical depth and effective radius for optically thin clouds. J. Geophys. Res., 110, D21201, doi:10.1029/2005JD006136.

    • Search Google Scholar
    • Export Citation
  • Morrison, H., 2016: Impacts of updraft size and dimensionality on the perturbation pressure and vertical velocity in cumulus convection. Part II: Comparison of theoretical and numerical solutions and fully dynamical simulations. J. Atmos. Sci., doi:10.1175/JAS-D-15-0041.1, in press.

    • Search Google Scholar
    • Export Citation
  • Ooyama, K. V., 1990: A thermodynamic foundation for modeling the moist atmosphere. J. Atmos. Sci., 47, 25802593, doi:10.1175/1520-0469(1990)047<2580:ATFFMT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Parker, M. D., 2010: Relationship between system slope and updraft intensity in squall lines. Mon. Wea. Rev., 138, 35723578, doi:10.1175/2010MWR3441.1.

    • Search Google Scholar
    • Export Citation
  • Peckham, A. E., R. B. Wilhelmson, L. J. Wicker, and C. L. Ziegler, 2004: Numerical simulation of the interaction between the dryline and horizontal convective rolls. Mon. Wea. Rev., 132, 17921812, doi:10.1175/1520-0493(2004)132<1792:NSOTIB>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Reuter, G. W., and M. K. Yau, 1987: Mixing mechanisms in cumulus congestus clouds. Part I: Observations. J. Atmos. Sci., 44, 781797, doi:10.1175/1520-0469(1987)044<0781:MMICCC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Roberts, R. D., and S. Rutledge, 2003: Nowcasting storm initiation and growth using GOES-8 and WSR-88D data. Wea. Forecasting, 18, 562584, doi:10.1175/1520-0434(2003)018<0562:NSIAGU>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Romps, D. M., and A. B. Charn, 2015: Sticky thermals: Evidence for a dominant balance between buoyancy and drag in cloud updrafts. J. Atmos. Sci., 72, 28902901, doi:10.1175/JAS-D-15-0042.1.

    • Search Google Scholar
    • Export Citation
  • Rosenfeld, D., and W. L. Woodley, 2000: Deep convective clouds with sustained supercooled liquid water down to −37.5°C. Nature, 405, 440442, doi:10.1038/35013030.

    • Search Google Scholar
    • Export Citation
  • Rosenfeld, D., W. L. Woodley, A. Lerner, G. Kelman, and D. T. Lindsey, 2008: Satellite detection of severe convective storms by their retrieved vertical profiles of cloud particle effective radius and thermodynamic phase. J. Geophys. Res., 113, D04208, doi:10.1029/2007JD008600.

    • Search Google Scholar
    • Export Citation
  • Schmit, T. J., and Coauthors, 2015: Rapid refresh information of significant events: Preparing users for the next generation of geostationary operational satellites. Bull. Amer. Meteor. Soc., 96, 561576, doi:10.1175/BAMS-D-13-00210.1.

    • Search Google Scholar
    • Export Citation
  • Setvák, M., and J. Müller, 2013: MSG-3 Super Rapid Scan study. EUM/STG-SWG/34/13/DOC/06 (internal EUMETSAT document).

  • Setvák, M., K. Bedka, D. T. Lindsey, A. Sokol, Z. Charvát, J. Šťástka, and P. K. Wang, 2013: A-Train observations of deep convective storm tops. Atmos. Res., 123, 229248, doi:10.1016/j.atmosres.2012.06.020.

    • Search Google Scholar
    • Export Citation
  • Sherburn, K. D., and M. D. Parker, 2014: Climatology and ingredients of significant severe convection in high shear, low CAPE environments. Wea. Forecasting, 29, 854877, doi:10.1175/WAF-D-13-00041.1.

    • Search Google Scholar
    • Export Citation
  • Sieglaff, J. M., L. M. Cronce, W. F. Feltz, K. M. Bedka, M. J. Pavolonis, and A. K. Heidinger, 2011: Nowcasting convective storm initiation using satellite-based box-averaged cloud-top cooling and cloud-type trends. J. Appl. Meteor. Climatol., 50, 110126, doi:10.1175/2010JAMC2496.1.

    • Search Google Scholar
    • Export Citation
  • Sloss, P. W., 1967: An empirical examination of cumulus entrainment. J. Appl. Meteor., 6, 878881, doi:10.1175/1520-0450(1967)006<0878:AEEOCE>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Soper, D. S., 2015: p-value calculator for correlation coefficients. [Available online at http://www.danielsoper.com/statcalc.]

  • Stechmann, S. N., and B. Stevens, 2010: Multiscale models for cumulus cloud dynamics. J. Atmos. Sci., 67, 32693285, doi:10.1175/2010JAS3380.1.

    • Search Google Scholar
    • Export Citation
  • Stensrud, D. J., and Coauthors, 2009: Convective-scale warn-on-forecast system: A vision for 2020. Bull. Amer. Meteor. Soc., 90, 14871499, doi:10.1175/2009BAMS2795.1.

    • Search Google Scholar
    • Export Citation
  • Strabala, K. I., S. A. Ackerman, and W. P. Menzel, 1994: Cloud properties inferred from 8–12-μm data. J. Appl. Meteor., 33, 212229, doi:10.1175/1520-0450(1994)033<0212:CPIFD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Walker, J. R., W. M. MacKenzie, J. R. Mecikalski, and C. P. Jewett, 2012: An enhanced geostationary satellite-based convective initiation algorithm for 0–2-h nowcasting with object tracking. J. Appl. Meteor. Climatol., 51, 19311949, doi:10.1175/JAMC-D-11-0246.1.

    • Search Google Scholar
    • Export Citation
  • Weisman, M. L., and J. B. Klemp, 1982: The dependence of numerically simulated convective storms on vertical wind shear and buoyancy. Mon. Wea. Rev., 110, 504520, doi:10.1175/1520-0493(1982)110<0504:TDONSC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Young, A. H., J. J. Bates, and J. A. Curry, 2012: Complementary use of passive and active remote sensing for detection of penetrating convection from CloudSat, CALIPSO, and Aqua MODIS. J. Geophys. Res., 117, D13205, doi:10.1029/2011JD016749.

    • Search Google Scholar
    • Export Citation
  • Ziegler, C. L., and E. N. Rasmussen, 1998: The initiation of moist convection at the dryline: Forecasting issues from a case study perspective. Wea. Forecasting, 13, 11061131, doi:10.1175/1520-0434(1998)013<1106:TIOMCA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Zipser, E. J., 2003: Some views on “hot towers” after 50 years of tropical field programs and two years of TRMM data. Cloud Systems, Hurricanes, and the Tropical Rainfall Measuring Mission (TRMM)—A Tribute to Dr. Joanne Simpson, Meteor. Monogr., No. 51, Amer. Meteor. Soc., 49–58.

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 404 149 11
PDF Downloads 291 118 6

Analysis of Cumulus Cloud Updrafts as Observed with 1-Min Resolution Super Rapid Scan GOES Imagery

View More View Less
  • 1 Atmospheric Science Department, University of Alabama in Huntsville, Huntsville, Alabama
  • | 2 Earth Systems Science Center, University of Alabama in Huntsville, Huntsville, Alabama
  • | 3 Atmospheric Science Department, University of Alabama in Huntsville, Huntsville, Alabama
Restricted access

Abstract

A study was undertaken to examine growing cumulus clouds using 1-min time resolution Super Rapid Scan Operations for Geostationary Operational Environmental Satellite-R (GOES-R) (SRSOR) imagery to diagnose in-cloud processes from cloud-top information. SRSOR data were collected using GOES-14 for events in 2012–14. Use of 1-min resolution SRSOR observations of rapidly changing scenes provides far more insights into cloud processes as compared to when present-day 5–15-min time resolution GOES data are used. For midday times on five days, cloud-top temperatures were cataloged for 71 cumulus clouds as they grew to possess anvils and often overshooting cloud tops, which occurred over 33–152-min time periods. Characteristics of the SRSOR-observed updrafts were examined individually, on a per day basis, and collectively, to reveal unique aspects of updraft behavior, strength, and acceleration as related to the ambient stability profile and cloud-top glaciation. A conclusion is that the 1-min observations capture two specific cumulus cloud growth periods, less rapid cloud growth between the level of free convection and the 0°C isotherm level, followed by more rapid growth shortly after the time of cloud-top glaciation. High correlation is found between estimated vertical motion (w) and the amount of convective available potential energy (CAPE) realized to the cloud-top level as clouds grew, which suggests that updrafts were responding to the local buoyancy quite strongly. Influences of the environmental buoyancy profile shape and evidence of entrainment on cloud growth are also found through these SRSOR data analyses.

Corresponding author address: John R. Mecikalski, Atmospheric Science Department, University of Alabama in Huntsville, National Space Science and Technology Center, 320 Sparkman Dr., Huntsville, AL 35805-1912. E-mail: johnm@nsstc.uah.edu

Abstract

A study was undertaken to examine growing cumulus clouds using 1-min time resolution Super Rapid Scan Operations for Geostationary Operational Environmental Satellite-R (GOES-R) (SRSOR) imagery to diagnose in-cloud processes from cloud-top information. SRSOR data were collected using GOES-14 for events in 2012–14. Use of 1-min resolution SRSOR observations of rapidly changing scenes provides far more insights into cloud processes as compared to when present-day 5–15-min time resolution GOES data are used. For midday times on five days, cloud-top temperatures were cataloged for 71 cumulus clouds as they grew to possess anvils and often overshooting cloud tops, which occurred over 33–152-min time periods. Characteristics of the SRSOR-observed updrafts were examined individually, on a per day basis, and collectively, to reveal unique aspects of updraft behavior, strength, and acceleration as related to the ambient stability profile and cloud-top glaciation. A conclusion is that the 1-min observations capture two specific cumulus cloud growth periods, less rapid cloud growth between the level of free convection and the 0°C isotherm level, followed by more rapid growth shortly after the time of cloud-top glaciation. High correlation is found between estimated vertical motion (w) and the amount of convective available potential energy (CAPE) realized to the cloud-top level as clouds grew, which suggests that updrafts were responding to the local buoyancy quite strongly. Influences of the environmental buoyancy profile shape and evidence of entrainment on cloud growth are also found through these SRSOR data analyses.

Corresponding author address: John R. Mecikalski, Atmospheric Science Department, University of Alabama in Huntsville, National Space Science and Technology Center, 320 Sparkman Dr., Huntsville, AL 35805-1912. E-mail: johnm@nsstc.uah.edu
Save