Criticality in the Shallow-to-Deep Transition of Simulated Tropical Marine Convection

Scott W. Powell aDepartment of Meteorology, Naval Postgraduate School, Monterey, California

Search for other papers by Scott W. Powell in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

Idealized simulations of tropical, marine convection depict shallow, nonprecipitating cumuli located beneath the 0°C level transitioning into cumulonimbi that reach up to 12 km and higher. The timing of the transition was only weakly related to environmental stability, and 13 of the 15 simulations run with 5 different lapse-rate profiles had rain develop at nearly the same time after model start. The key quantity that apparently controlled deep convective formation was vertical acceleration inside cloudy updrafts between cloud base and the 0°C level. Below a critical value of updraft vertical acceleration, little rainfall occurred. Just as the domain-mean updraft acceleration reached the critical value, the first convection quickly grew to past 12 km altitude. Then, as acceleration increased above the critical value, rain rate averaged in the model domain increased quickly over about a 3-h-long period. The specific value of the critical updraft acceleration depended on how updrafts were defined and in what layer the acceleration was averaged; however, regardless of how criticality was defined, a robust relationship between domain-mean updraft vertical acceleration and rain rate occurred. Positive acceleration of updrafts below the 0°C level was present below 2.75 km and was largest in the 500 m above cloud base. However, the maximum difference between updraft and environmental temperatures occurred between 2 and 3 km. The domain-mean Archimedean buoyancy of updrafts relative to some reference state was a poor predictor for domain-mean rain rate. The exact value of the critical updraft acceleration likely depends on numerous other factors that were not investigated.

Significance Statement

A numerical model is utilized to investigate potential thermodynamic and dynamic quantities related to the growth of cumulus clouds into cumulonimbus clouds over tropical oceans when the atmosphere is sufficiently moist to support rainfall. Archimedean buoyancy alone cannot be used to predict rain rate reliably. Instead the total buoyancy not relative to an arbitrary reference state must be considered. The simulated relationship between total vertical acceleration in updrafts and rain rate was robust. While the processes that control the vertical acceleration remain unclear, our results highlight the importance of observing processes that occur on spatial scales of tens of meters and temporal scales of a few minutes.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Scott W. Powell, scott.powell@nps.edu

Abstract

Idealized simulations of tropical, marine convection depict shallow, nonprecipitating cumuli located beneath the 0°C level transitioning into cumulonimbi that reach up to 12 km and higher. The timing of the transition was only weakly related to environmental stability, and 13 of the 15 simulations run with 5 different lapse-rate profiles had rain develop at nearly the same time after model start. The key quantity that apparently controlled deep convective formation was vertical acceleration inside cloudy updrafts between cloud base and the 0°C level. Below a critical value of updraft vertical acceleration, little rainfall occurred. Just as the domain-mean updraft acceleration reached the critical value, the first convection quickly grew to past 12 km altitude. Then, as acceleration increased above the critical value, rain rate averaged in the model domain increased quickly over about a 3-h-long period. The specific value of the critical updraft acceleration depended on how updrafts were defined and in what layer the acceleration was averaged; however, regardless of how criticality was defined, a robust relationship between domain-mean updraft vertical acceleration and rain rate occurred. Positive acceleration of updrafts below the 0°C level was present below 2.75 km and was largest in the 500 m above cloud base. However, the maximum difference between updraft and environmental temperatures occurred between 2 and 3 km. The domain-mean Archimedean buoyancy of updrafts relative to some reference state was a poor predictor for domain-mean rain rate. The exact value of the critical updraft acceleration likely depends on numerous other factors that were not investigated.

Significance Statement

A numerical model is utilized to investigate potential thermodynamic and dynamic quantities related to the growth of cumulus clouds into cumulonimbus clouds over tropical oceans when the atmosphere is sufficiently moist to support rainfall. Archimedean buoyancy alone cannot be used to predict rain rate reliably. Instead the total buoyancy not relative to an arbitrary reference state must be considered. The simulated relationship between total vertical acceleration in updrafts and rain rate was robust. While the processes that control the vertical acceleration remain unclear, our results highlight the importance of observing processes that occur on spatial scales of tens of meters and temporal scales of a few minutes.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Scott W. Powell, scott.powell@nps.edu

Supplementary Materials

    • Supplemental Materials (PDF 72.3 KB)
Save
  • Adames, Á. F., S. W. Powell, F. Ahmed, V. C. Mayta, and J. D. Neelin, 2021: Tropical precipitation evolution in a buoyancy-budget framework. J. Atmos. Sci., 78, 509528, https://doi.org/10.1175/JAS-D-20-0074.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ahmed, F., and J. D. Neelin, 2018: Reverse engineering the tropical precipitation–buoyancy relationship. J. Atmos. Sci., 75, 15871608, https://doi.org/10.1175/JAS-D-17-0333.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ahmed, F., Á. F. Adames, and J. D. Neelin, 2020: Deep convective adjustment of temperature and moisture. J. Atmos. Sci., 77, 21632186, https://doi.org/10.1175/JAS-D-19-0227.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bosilovich, M. G., J. Chen, F. R. Robertson, and R. F. Adler, 2008: Evaluation of global precipitation in reanalyses. J. Appl. Meteor. Climatol., 47, 22792299, https://doi.org/10.1175/2008JAMC1921.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bretherton, C. S., M. E. Peters, and L. E. Back, 2004: Relationships between water vapor path and precipitation over the tropical oceans. J. Climate, 17, 15171528, https://doi.org/10.1175/1520-0442(2004)017<1517:RBWVPA>2.0.CO;2.

    • Crossref
    • Export Citation
  • Bryan, G. H., and J. M. Fritsch, 2002: A benchmark simulation for moist nonhydrostatic numerical models. Mon. Wea. Rev., 130, 29172928, https://doi.org/10.1175/1520-0493(2002)130<2917:ABSFMN>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bryan, G. H., J. C. Wyngaard, and J. M. Fritsch, 2003: Resolution requirements for the simulation of deep moist convection. Mon. Wea. Rev., 131, 23942416, https://doi.org/10.1175/1520-0493(2003)131<2394:RRFTSO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, B., and B. E. Mapes, 2018: Effects of a simple convective organization scheme in a two-plume GCM. J. Adv. Model. Earth Syst., 10, 867880, https://doi.org/10.1002/2017MS001106.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chou, M. D., M. J. Suarez, X. Z. Liang, and M. M. H. Yan, 2001: A thermal infrared radiation parameterization for atmospheric studies. NASA Tech. Memo., 68 pp., https://ntrs.nasa.gov/api/citations/20010072848/downloads/20010072848.pdf.

    • Crossref
    • Export Citation
  • Ciesielski, P. E., and Coauthors, 2014: Quality-controlled upper-air sounding dataset for DYNAMO/CINDY/AMIE: Development and corrections. J. Atmos. Oceanic Technol., 31, 741764, https://doi.org/10.1175/JTECH-D-13-00165.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Davies-Jones, R., 2003: An expression for effective buoyancy in surroundings with horizontal density gradients. J. Atmos. Sci., 60, 29222925, https://doi.org/10.1175/1520-0469(2003)060<2922:AEFEBI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Del Genio, A. D., Y. Chen, D. Kim, and M.-S. Yao, 2012: The MJO transition from shallow to deep convection in CloudSat/CALIPSO data and GISS GCM simulations. J. Climate, 25, 37553770, https://doi.org/10.1175/JCLI-D-11-00384.1.

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

    • Crossref
    • Export Citation
  • Gentemann, C. L., and Coauthors, 2020: Saildrone: Adaptively sampling the marine environment. Bull. Amer. Meteor. Soc., 101, E744E762, https://doi.org/10.1175/BAMS-D-19-0015.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hernandez-Deckers, D., and S. C. Sherwood, 2018: On the role of entrainment in the fate of cumulus thermals. J. Atmos. Sci., 75, 39113924, https://doi.org/10.1175/JAS-D-18-0077.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hersbach, H. , and Coauthors, 2020: The ERA5 global reanalysis. Quart. J. Roy. Meteor. Soc., 146, 19992049, https://doi.org/10.1002/qj.3803.

    • Crossref
    • Export Citation
  • Holloway, C. E., and J. D. Neelin, 2009: Moisture vertical structure, column water vapor, and tropical deep convection. J. Atmos. Sci., 66, 16651683, https://doi.org/10.1175/2008JAS2806.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jeevanjee, N., and D. M. Romps, 2015: Effective buoyancy, inertial pressure, and the mechanical generation of boundary layer mass flux by cold pools. J. Atmos. Sci., 72, 31993213, https://doi.org/10.1175/JAS-D-14-0349.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jeevanjee, N., and D. M. Romps, 2016: Effective buoyancy at the surface and aloft. Quart. J. Roy. Meteor. Soc., 142, 811820, https://doi.org/10.1002/qj.2683.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jiménez, P. A., J. Dudhia, J. F. González-Rouco, J. Navarro, J. P. Montávez, and E. García-Bustamante, 2012: A revised scheme for the WRF surface layer formulation. Mon. Wea. Rev., 140, 898918, https://doi.org/10.1175/MWR-D-11-00056.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kollias, P., and B. Albrecht, 2010: Vertical velocity statistics in fair-weather cumuli at the ARM TWP Nauru Climate Research Facility. J. Climate, 23, 65906604, https://doi.org/10.1175/2010JCLI3449.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kollias, P., N. Bharadwaj, K. Widener, I. Jo, and K. Johnson, 2014: Scanning ARM cloud radars. Part I: Operational sampling strategies. J. Atmos. Oceanic Technol., 31, 569582, https://doi.org/10.1175/JTECH-D-13-00044.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kuo, Y.-H., J. D. Neelin, and C. R. Mechoso, 2017: Tropical convective transition statistics and causality in the water vapor–precipitation relation. J. Atmos. Sci., 74, 915931, https://doi.org/10.1175/JAS-D-16-0182.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mapes, B., and R. Neale, 2011: Parameterizing convective organization to escape the entrainment dilemma. J. Adv. Model. Earth Syst., 3, M06004, https://doi.org/10.1029/2011MS000042.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mellado, J. P., C. S. Bretherton, B. Stevens, and M. C. Wyant, 2018: DNS and LES for simulating stratocumulus: Better together. J. Adv. Model. Earth Syst., 10, 14211438, https://doi.org/10.1029/2018MS001312.

    • Crossref
    • 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 I: Simple, generalized analytic solutions. J. Atmos. Sci., 73, 14411454, https://doi.org/10.1175/JAS-D-15-0040.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Morrison, H., G. Thompson, and V. Tatarskii, 2009: Impact of cloud microphysics on the development of trailing stratiform precipitation in a simulated squall line: Comparison of one- and two-moment schemes. Mon. Wea. Rev., 137, 9911007, https://doi.org/10.1175/2008MWR2556.1.

    • Crossref
    • Export Citation
  • Nugent, A. D., and R. B. Smith, 2014: Initiating moist convection in an inhomogeneous layer by uniform ascent. J. Atmos. Sci., 71, 45974610, https://doi.org/10.1175/JAS-D-14-0089.1.

    • Search Google Scholar
    • Export Citation
  • Peters, J. M., H. Morrison, G. J. Zhang, and S. W. Powell, 2021: Improving the physical basis for updraft dynamics in deep convection parameterizations. J. Adv. Model. Earth Syst., 13, e2020MS002282, https://doi.org/10.1029/2020MS002282.

    • Crossref
    • Export Citation
  • Peters, O., and J. D. Neelin, 2006: Critical phenomena in atmospheric precipitation. Nat. Phys., 2, 393396, https://doi.org/10.1038/nphys314.

  • Powell, S. W., 2019: Observing possible thermodynamic controls on tropical marine rainfall in moist environments. J. Atmos. Sci., 76, 37373751, https://doi.org/10.1175/JAS-D-19-0144.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Powell, S. W., and R. A. Houze Jr., 2013: The cloud population and onset of the Madden-Julian oscillation over the Indian Ocean during DYNAMO-AMIE. J. Geophys. Res. Atmos., 118, 1197911995, https://doi.org/10.1002/2013JD020421.

    • Crossref
    • Export Citation
  • Powell, S. W., and R. A. Houze, 2015: Effect of dry large-scale vertical motions on initial MJO convective onset. J. Geophys. Res. Atmos., 120, 47834805, https://doi.org/10.1002/2014JD022961.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Powell, S. W., R. A. Houze, and S. R. Brodzik, 2016: Rainfall-type categorization of radar echoes using polar coordinate reflectivity data. J. Atmos. Oceanic Technol., 33, 523538, https://doi.org/10.1175/JTECH-D-15-0135.1.

    • Search Google Scholar
    • Export Citation
  • Raymond, D. J., G. B. Raga, C. S. Bretherton, J. Molinari, and C. López-Carrillo, 2003: Convective forcing in the intertropical convergence zone of the eastern Pacific. J. Atmos. Sci., 60, 20642082, https://doi.org/10.1175/1520-0469(2003)060<2064:CFITIC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Rushley, S. S., D. Kim, C. S. Bretherton, and M.-S. Ahn, 2018: Reexamining the nonlinear moisture-precipitation relationship over the tropical oceans. Geophys. Res. Lett., 45, 11331140, https://doi.org/10.1002/2017GL076296.

    • Search Google Scholar
    • Export Citation
  • Schiro, K. A., F. Ahmed, S. E. Giangrande, and J. D. Neelin, 2018: GoAmazon2014/5 campaign points to deep-inflow approach to deep convection across scales. Proc. Natl. Acad. Sci. USA, 115, 45774582, https://doi.org/10.1073/pnas.1719842115.

    • Search Google Scholar
    • Export Citation
  • Schumacher, C., R. A. Houze Jr., and I. Kraucunas, 2004: The tropical dynamical response to latent heating estimates derived from the TRMM Precipitation Radar. J. Atmos. Sci., 61, 13411358, https://doi.org/10.1175/1520-0469(2004)061<1341:TTDRTL>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Stevens, B., C.-H. Moeng, and P. P. Sullivan, 1999: Large-eddy simulations of radiatively driven convection: Sensitivities to the representation of small scales. J. Atmos. Sci., 56, 39633984, https://doi.org/10.1175/1520-0469(1999)056<3963:LESORD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Tiedtke, M., 1989: A comprehensive mass flux scheme for cumulus parameterization in large-scale models. Mon. Wea. Rev., 117, 17791800, https://doi.org/10.1175/1520-0493(1989)117<1779:ACMFSF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • van den Heever, S. C., and Coauthors, 2021: The Colorado State University Convective Cloud Outflows and Updrafts Experiment (C3LOUD-Ex). Bull. Amer. Meteor. Soc., 102, E1283E1305, https://doi.org/10.1175/BAMS-D-19-0013.1.

    • Search Google Scholar
    • Export Citation
  • Wang, S., and A. H. Sobel, 2012: Impact of imposed drying on deep convection in a cloud-resolving model. J. Geophys. Res., 117, D02112, https://doi.org/10.1029/2011JD016847.

    • Search Google Scholar
    • Export Citation
  • Weckwerth, T. M., K. J. Weber, D. D. Turner, and S. M. Spuler, 2016: Validation of a water vapor micropulse differential absorption lidar (DIAL). J. Atmos. Oceanic Technol., 33, 23532372, https://doi.org/10.1175/JTECH-D-16-0119.1.

    • Search Google Scholar
    • Export Citation
  • Wolding, B., J. Dias, G. Kiladis, F. Ahmed, S. W. Powell, E. Maloney, and M. Branson, 2020: Interactions between moisture and tropical convection. Part I: The coevolution of moisture and convection. J. Atmos. Sci., 77, 17831799, https://doi.org/10.1175/JAS-D-19-0225.1.

    • Search Google Scholar
    • Export Citation
  • Wu, C.-M., B. Stevens, and A. Arakawa, 2009: What controls the transition from shallow to deep convection? J. Atmos. Sci., 66, 17931806, https://doi.org/10.1175/2008JAS2945.1.

    • Search Google Scholar
    • Export Citation
  • Yoneyama, K., C. Zhang, and C. N. Long, 2013: Tracking pulses of the Madden–Julian oscillation. Bull. Amer. Meteor. Soc., 94, 18711891, https://doi.org/10.1175/BAMS-D-12-00157.1.

    • Search Google Scholar
    • Export Citation
  • Zuidema, P., 1998: The 600–800-mb minimum in tropical cloudiness observed during TOGA COARE. J. Atmos. Sci., 55, 22202228, https://doi.org/10.1175/1520-0469(1998)055<2220:TMMITC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 423 133 0
Full Text Views 333 214 22
PDF Downloads 337 194 24