Editorial Type:
Article
Article Type:
Research Article

Dynamic and Thermodynamic Environmental Modulation of Tropical Congestus and Cumulonimbus in Maritime Tropical Regions

Sean W. Freeman aDepartment of Atmospheric Science, Colorado State University, Fort Collins, Colorado

Search for other papers by Sean W. Freeman in
Current site
Google Scholar
PubMed Close
https://orcid.org/0000-0002-7398-1597
,
Derek J. Posselt bJet Propulsion Laboratory, California Institute of Technology, Pasadena, California

Search for other papers by Derek J. Posselt in
Current site
Google Scholar
PubMed Close
,
Jeffrey S. Reid cMarine Meteorology Division, U. S. Naval Research Laboratory, Monterey, California

Search for other papers by Jeffrey S. Reid in
Current site
Google Scholar
PubMed Close
, and
Susan C. van den Heever aDepartment of Atmospheric Science, Colorado State University, Fort Collins, Colorado

Search for other papers by Susan C. van den Heever in
Current site
Google Scholar
PubMed Close
Online Publication:
13 Nov 2024
Print Publication:
01 Nov 2024
Collections:
Air–Sea Interactions from the Diurnal to the Intraseasonal during the PISTON, MISOBOB, and CAMP2Ex Observational Campaigns in the Tropics
DOI:
https://doi.org/10.1175/JAS-D-24-0055.1
Page(s):
1921–1941
Restricted access

We are aware of a technical issue preventing figures and tables from showing in some newly published articles in the full-text HTML view.
While we are resolving the problem, please use the online PDF version of these articles to view figures and tables.

Abstract

We have quantified the impacts of varying thermodynamic environments on tropical congestus and cumulonimbus clouds (CCCs) within maritime tropical regions. To elucidate this relationship, we employed the Regional Atmospheric Modeling System (RAMS) to conduct high-resolution (1 km) simulations of convection over the Philippine Archipelago for a month-long period in 2019. We subsequently performed a cloud-object-based analysis, identifying and tracking hundreds of thousands of individual CCCs using the Tracking and Object-Based Analysis of Clouds (tobac) tracking library. Using this object-oriented dataset of tracked cells, we examined differences in individual storm strength, organization, and morphology due to the storm’s initial environment. We found that storm strength, defined here as maximum midlevel updraft velocity, was controlled primarily by convective available potential energy (CAPE) and precipitable water (PW); high CAPE (>2500 J kg−1) and high (approximately 63 mm) PW were both required for midlevel CCC updraft velocities to reach at least 10 m s−1. Of the CCCs with the most vigorous updrafts, 80.9% were also in the upper tercile of precipitation rates, with the strongest precipitation rates requiring even higher PW. Further, we found that vertical wind shear was the primary differentiator between organized and isolated convective storms. Within the set of organized storms, linearly oriented CCC systems have significantly weaker vertical wind shear than nonlinear CCCs in low- (0–1, 0–3 km) and midlevels (0–5, 2–7 km). Overall, these results provide new insights into the environmental conditions determining the CCC properties in maritime tropical regions.

Freeman’s current affiliation: Department of Atmospheric and Earth Science, The University of Alabama in Huntsville, Huntsville, Alabama.

© 2024 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Sean W. Freeman, sean.freeman@uah.edu

Abstract

We have quantified the impacts of varying thermodynamic environments on tropical congestus and cumulonimbus clouds (CCCs) within maritime tropical regions. To elucidate this relationship, we employed the Regional Atmospheric Modeling System (RAMS) to conduct high-resolution (1 km) simulations of convection over the Philippine Archipelago for a month-long period in 2019. We subsequently performed a cloud-object-based analysis, identifying and tracking hundreds of thousands of individual CCCs using the Tracking and Object-Based Analysis of Clouds (tobac) tracking library. Using this object-oriented dataset of tracked cells, we examined differences in individual storm strength, organization, and morphology due to the storm’s initial environment. We found that storm strength, defined here as maximum midlevel updraft velocity, was controlled primarily by convective available potential energy (CAPE) and precipitable water (PW); high CAPE (>2500 J kg−1) and high (approximately 63 mm) PW were both required for midlevel CCC updraft velocities to reach at least 10 m s−1. Of the CCCs with the most vigorous updrafts, 80.9% were also in the upper tercile of precipitation rates, with the strongest precipitation rates requiring even higher PW. Further, we found that vertical wind shear was the primary differentiator between organized and isolated convective storms. Within the set of organized storms, linearly oriented CCC systems have significantly weaker vertical wind shear than nonlinear CCCs in low- (0–1, 0–3 km) and midlevels (0–5, 2–7 km). Overall, these results provide new insights into the environmental conditions determining the CCC properties in maritime tropical regions.

Freeman’s current affiliation: Department of Atmospheric and Earth Science, The University of Alabama in Huntsville, Huntsville, Alabama.

© 2024 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Sean W. Freeman, sean.freeman@uah.edu
Save
Cover Journal of the Atmospheric Sciences
Journal of the Atmospheric Sciences

  • Albrecht, B. A., 1989: Aerosols, cloud microphysics, and fractional cloudiness. Science, 245, 1227–1230, https://doi.org/10.1126/science.245.4923.1227.

    • Search Google Scholar
    • Export Citation

  • Allan, D. B., T. Caswell, N. C. Keim, C. M. van der Wel, and R. W. Verweij, 2021: Soft-matter/trackpy: Trackpy v0.5.0. Zenodo, https://doi.org/10.5281/zenodo.4682814.

  • Atwood, S. A., and Coauthors, 2017: Size-resolved aerosol and Cloud Condensation Nuclei (CCN) properties in the remote marine South China sea – Part I: Observations and source classification. Atmos. Chem. Phys., 17, 1105–1123, https://doi.org/10.5194/acp-17-1105-2017.

    • Search Google Scholar
    • Export Citation

  • Austin, J. M., 1948: A note on cumulus growth in a nonsaturated environment. J. Atmos. Sci., 5, 103–107, https://doi.org/10.1175/1520-0469(1948)005<0103:ANOCGI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Barth, M. C., and Coauthors, 2015: The Deep Convective Clouds and Chemistry (DC3) field campaign. Bull. Amer. Meteor. Soc., 96, 1281–1309, https://doi.org/10.1175/BAMS-D-13-00290.1.

    • Search Google Scholar
    • Export Citation

  • Becker, T., C. S. Bretherton, C. Hohenegger, and B. Stevens, 2018: Estimating bulk entrainment with unaggregated and aggregated convection. Geophys. Res. Lett., 45, 455–462, https://doi.org/10.1002/2017GL076640.

    • Search Google Scholar
    • Export Citation

  • Bergemann, M., and C. Jakob, 2016: How important is tropospheric humidity for coastal rainfall in the tropics? Geophys. Res. Lett., 43, 5860–5868, https://doi.org/10.1002/2016GL069255.

    • Search Google Scholar
    • Export Citation

  • Bhat, G. S., J. Srinivasan, and S. Gadgil, 1996: Tropical deep convection, convective available potential energy and sea surface temperature. J. Meteor. Soc. Japan, 74, 155–166, https://doi.org/10.2151/jmsj1965.74.2_155.

    • Search Google Scholar
    • Export Citation

  • Cecil, D. J., S. J. Goodman, D. J. Boccippio, E. J. Zipser, and S. W. Nesbitt, 2005: Three years of TRMM precipitation features. Part I: Radar, radiometric, and lightning characteristics. Mon. Wea. Rev., 133, 543–566, https://doi.org/10.1175/MWR-2876.1.

    • Search Google Scholar
    • Export Citation

  • Chen, S., N. Z. Wong, D. Ma, P. W. Chan, and Z. Kuang, 2021: Dependence of precipitation on precipitable water vapor over the Maritime Continent and implications to the Madden-Julian oscillation. Geophys. Res. Lett., 48, e2021GL094648, https://doi.org/10.1029/2021GL094648.

    • Search Google Scholar
    • Export Citation

  • Coelho, L. P., 2017: Jug: Software for parallel reproducible computation in python. J. Open Res. Software, 5, 30, https://doi.org/10.5334/jors.161.

    • Search Google Scholar
    • Export Citation

  • Cotton, W. R., and Coauthors, 2003: RAMS 2001: Current status and future directions. Meteor. Atmos. Phys., 82, 5–29, https://doi.org/10.1007/s00703-001-0584-9.

    • Search Google Scholar
    • Export Citation

  • de Oliveira, F. P., and M. D. Oyama, 2015: Antecedent atmospheric conditions related to squall-line initiation over the northern coast of Brazil in July. Wea. Forecasting, 30, 1254–1264, https://doi.org/10.1175/WAF-D-14-00120.1.

    • Search Google Scholar
    • Export Citation

  • Dickerson, R. R., and Coauthors, 1987: Thunderstorms: An important mechanism in the transport of air pollutants. Science, 235, 460–465, https://doi.org/10.1126/science.235.4787.460.

    • Search Google Scholar
    • Export Citation

  • Fuchs, B. R., and Coauthors, 2015: Environmental controls on storm intensity and charge structure in multiple regions of the continental United States. J. Geophys. Res. Atmos., 120, 6575–6596, https://doi.org/10.1002/2015JD023271.

    • Search Google Scholar
    • Export Citation

  • Gallus, W. A., Jr., N. A. Snook, and E. V. Johnson, 2008: Spring and summer severe weather reports over the midwest as a function of convective mode: A preliminary study. Wea. Forecasting, 23, 101–113, https://doi.org/10.1175/2007WAF2006120.1.

    • Search Google Scholar
    • Export Citation

  • Grabowski, W. W., 2006: Indirect impact of atmospheric aerosols in idealized simulations of convective–radiative quasi equilibrium. J. Climate, 19, 4664–4682, https://doi.org/10.1175/JCLI3857.1.

    • Search Google Scholar
    • Export Citation

  • Grabowski, W. W., and M. W. Moncrieff, 2004: Moisture–convection feedback in the tropics. Quart. J. Roy. Meteor. Soc., 130, 3081–3104, https://doi.org/10.1256/qj.03.135.

    • Search Google Scholar
    • Export Citation

  • Grant, L. D., T. P. Lane, and S. C. van den Heever, 2018: The role of cold pools in tropical oceanic convective systems. J. Atmos. Sci., 75, 2615–2634, https://doi.org/10.1175/JAS-D-17-0352.1.

    • Search Google Scholar
    • Export Citation

  • Grant, L. D., M. W. Moncrieff, T. P. Lane, and S. C. van den Heever, 2020: Shear-parallel tropical convective systems: Importance of cold pools and wind shear. Geophys. Res. Lett., 47, e2020GL087720, https://doi.org/10.1029/2020GL087720.

    • Search Google Scholar
    • Export Citation

  • Hamada, A., Y. N. Takayabu, C. Liu, and E. J. Zipser, 2015: Weak linkage between the heaviest rainfall and tallest storms. Nat. Commun., 6, 6213, https://doi.org/10.1038/ncomms7213.

    • Search Google Scholar
    • Export Citation

  • Hannah, W. M., 2017: Entrainment versus dilution in tropical deep convection. J. Atmos. Sci., 74, 3725–3747, https://doi.org/10.1175/JAS-D-16-0169.1.

    • Search Google Scholar
    • Export Citation

  • Harrington, J. Y., 1997: The effects of radiative and microphysical processes on simulated warm and transition season Arctic stratus. Ph.D. dissertation, Colorado State University, 289 pp., https://ui.adsabs.harvard.edu/abs/1997PhDT........45H/abstract.

  • Hassim, M. E. E., T. P. Lane, and W. W. Grabowski, 2016: The diurnal cycle of rainfall over New Guinea in convection-permitting WRF simulations. Atmos. Chem. Phys., 16, 161–175, https://doi.org/10.5194/acp-16-161-2016.

    • Search Google Scholar
    • Export Citation

  • Heikenfeld, M., P. J. Marinescu, M. Christensen, D. Watson-Parris, F. Senf, S. C. van den Heever, and P. Stier, 2019: Tobac 1.2: Towards a flexible framework for tracking and analysis of clouds in diverse datasets. Geosci. Model Dev., 12, 4551–4570, https://doi.org/10.5194/gmd-12-4551-2019.

    • Search Google Scholar
    • Export Citation

  • Hersbach, H., and Coauthors, 2020: The ERA5 global reanalysis. Quart. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803.

    • Search Google Scholar
    • Export Citation

  • Hill, G. E., 1974: Factors controlling the size and spacing of cumulus clouds as revealed by numerical experiments. J. Atmos. Sci., 31, 646–673, https://doi.org/10.1175/1520-0469(1974)031<0646:FCTSAS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Holloway, C. E., and J. D. Neelin, 2009: Moisture vertical structure, column water vapor, and tropical deep convection. J. Atmos. Sci., 66, 1665–1683, https://doi.org/10.1175/2008JAS2806.1.

    • Search Google Scholar
    • Export Citation

  • Holloway, C. E., and J. D. Neelin, 2010: Temporal relations of column water vapor and tropical precipitation. J. Atmos. Sci., 67, 1091–1105, https://doi.org/10.1175/2009JAS3284.1.

    • Search Google Scholar
    • Export Citation

  • Houze, R. A., Jr., and C.-P. Cheng, 1977: Radar characteristics of tropical convection observed during GATE: Mean properties and trends over the summer season. Mon. Wea. Rev., 105, 964–980, https://doi.org/10.1175/1520-0493(1977)105<0964:RCOTCO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Inoue, T., M. Satoh, H. Miura, and B. Mapes, 2008: Characteristics of cloud size of deep convection simulated by a global cloud resolving model over the western tropical Pacific. J. Meteor. Soc. Japan, 86A, 1–15, https://doi.org/10.2151/jmsj.86A.1.

    • Search Google Scholar
    • Export Citation

  • Jensen, M. P., and A. D. Del Genio, 2006: Factors limiting convective cloud-top height at the ARM Nauru island climate research facility. J. Climate, 19, 2105–2117, https://doi.org/10.1175/JCLI3722.1.

    • 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, 2397–2418, https://doi.org/10.1175/1520-0442(1999)012<2397:TCOTC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Johnson, R. H., S. L. Aves, P. E. Ciesielski, and T. D. Keenan, 2005: Organization of oceanic convection during the onset of the 1998 east Asian summer monsoon. Mon. Wea. Rev., 133, 131–148, https://doi.org/10.1175/MWR-2843.1.

    • Search Google Scholar
    • Export Citation

  • Jourdain, N. C., A. S. Gupta, A. S. Taschetto, C. C. Ummenhofer, A. F. Moise, and K. Ashok, 2013: The Indo-Australian monsoon and its relationship to ENSO and IOD in reanalysis data and the CMIP3/CMIP5 simulations. Climate Dyn., 41, 3073–3102, https://doi.org/10.1007/s00382-013-1676-1.

    • 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, 3514–3532, https://doi.org/10.1175/2011MWR3631.1.

    • Search Google Scholar
    • Export Citation

  • Klemp, J. B., and R. B. Wilhelmson, 1978: The simulation of three-dimensional convective storm dynamics. J. Atmos. Sci., 35, 1070–1096, https://doi.org/10.1175/1520-0469(1978)035<1070:TSOTDC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Kumar, V. V., A. Protat, C. Jakob, and P. T. May, 2014: On the atmospheric regulation of the growth of moderate to deep cumulonimbus in a tropical environment. J. Atmos. Sci., 71, 1105–1120, https://doi.org/10.1175/JAS-D-13-0231.1.

    • Search Google Scholar
    • Export Citation

  • Lane, T. P., and M. W. Moncrieff, 2015: Long-lived mesoscale systems in a low–convective inhibition environment. Part I: Upshear propagation. J. Atmos. Sci., 72, 4297–4318, https://doi.org/10.1175/JAS-D-15-0073.1.

    • Search Google Scholar
    • Export Citation

  • Lee, T. J., 1992: The impact of vegetation on the atmospheric boundary layer and convective storms. Ph.D. dissertation, Colorado State University, 159 pp., https://mountainscholar.org/bitstreams/24ec52e6-9686-4b04-9dc1-9ad7c4b34ece/download.

  • LeMone, M. A., G. M. Barnes, and E. J. Zipser, 1984: Momentum flux by lines of cumulonimbus over the Tropical Oceans. J. Atmos. Sci., 41, 1914–1932, https://doi.org/10.1175/1520-0469(1984)041<1914:MFBLOC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • LeMone, M. A., E. J. Zipser, and S. B. Trier, 1998: The role of environmental shear and thermodynamic conditions in determining the structure and evolution of mesoscale convective systems during TOGA COARE. J. Atmos. Sci., 55, 3493–3518, https://doi.org/10.1175/1520-0469(1998)055<3493:TROESA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Louf, V., C. Jakob, A. Protat, M. Bergemann, and S. Narsey, 2019: The relationship of cloud number and size with their large-scale environment in deep tropical convection. Geophys. Res. Lett., 46, 9203–9212, https://doi.org/10.1029/2019GL083964.

    • Search Google Scholar
    • Export Citation

  • Luo, Z., G. Y. Liu, G. L. Stephens, and R. H. Johnson, 2009: Terminal versus transient cumulus congestus: A CloudSat perspective. Geophys. Res. Lett., 36, L05808, https://doi.org/10.1029/2008GL036927.

    • Search Google Scholar
    • Export Citation

  • Mapes, B. E., 1993: Gregarious tropical convection. J. Atmos. Sci., 50, 2026–2037, https://doi.org/10.1175/1520-0469(1993)050<2026:GTC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Markowski, P., and Y. Richardson, 2006: On the classification of vertical wind shear as directional shear versus speed shear. Wea. Forecasting, 21, 242–247, https://doi.org/10.1175/WAF897.1.

    • Search Google Scholar
    • Export Citation

  • Masunaga, H., 2013: A satellite study of tropical moist convection and environmental variability: A moisture and thermal budget analysis. J. Atmos. Sci., 70, 2443–2466, https://doi.org/10.1175/JAS-D-12-0273.1.

    • Search Google Scholar
    • Export Citation

  • May, R., S. Arms, P. Marsh, E. Bruning, J. Leeman, and Z. Bruick, 2020: MetPy: A python package for meteorological data. UCAR/NCAR – Unidata, https://www.unidata.ucar.edu/software/metpy/#:~:text=MetPy%20is%20a%20collection%20of,adding%20functionality%20specific%20to%20meteorology.

  • McGee, C. J., and S. C. van den Heever, 2014: Latent heating and mixing due to entrainment in tropical deep convection. J. Atmos. Sci., 71, 816–832, https://doi.org/10.1175/JAS-D-13-0140.1.

    • Search Google Scholar
    • Export Citation

  • Miller, D., and J. M. Fritsch, 1991: Mesoscale convective complexes in the western Pacific region. Mon. Wea. Rev., 119, 2978–2992, https://doi.org/10.1175/1520-0493(1991)119<2978:MCCITW>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Minamide, M., and D. J. Posselt, 2022: Using ensemble data assimilation to explore the environmental controls on the initiation and predictability of moist convection. J. Atmos. Sci., 79, 1151–1169, https://doi.org/10.1175/JAS-D-21-0140.1.

    • Search Google Scholar
    • Export Citation

  • Neale, R., and J. Slingo, 2003: The Maritime Continent and its role in the global climate: A GCM study. J. Climate, 16, 834–848, https://doi.org/10.1175/1520-0442(2003)016<0834:TMCAIR>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Park, J. M., S. C. van den Heever, A. L. Igel, L. D. Grant, J. S. Johnson, S. M. Saleeby, S. D. Miller, and J. S. Reid, 2020: Environmental controls on tropical sea breeze convection and resulting aerosol redistribution. J. Geophys. Res. Atmos., 125, e2019JD031699, https://doi.org/10.1029/2019JD031699.

    • Search Google Scholar
    • Export Citation

  • Parker, M. D., and R. H. Johnson, 2000: Organizational modes of midlatitude mesoscale convective systems. Mon. Wea. Rev., 128, 3413–3436, https://doi.org/10.1175/1520-0493(2001)129<3413:OMOMMC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Peters, J. M., H. Morrison, A. C. Varble, W. M. Hannah, and S. E. Giangrande, 2020: Thermal chains and entrainment in cumulus updrafts. Part II: Analysis of idealized simulations. J. Atmos. Sci., 77, 3661–3681, https://doi.org/10.1175/JAS-D-19-0244.1.

    • Search Google Scholar
    • Export Citation

  • Posselt, D. J., F. He, J. Bukowski, and J. S. Reid, 2019: On the relative sensitivity of a tropical deep convective storm to changes in environment and cloud microphysical parameters. J. Atmos. Sci., 76, 1163–1185, https://doi.org/10.1175/JAS-D-18-0181.1.

    • Search Google Scholar
    • Export Citation

  • Ramage, C. S., 1968: Role of a tropical “Maritime Continent” in the atmospheric circulation. Mon. Wea. Rev., 96, 365–370, https://doi.org/10.1175/1520-0493(1968)096<0365:ROATMC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Reid, J. S., and Coauthors, 2015: Observations of the temporal variability in aerosol properties and their relationships to meteorology in the summer monsoonal South China sea/east sea: The scale-dependent role of monsoonal flows, the Madden–Julian oscillation, tropical cyclones, squall lines and cold pools. Atmos. Chem. Phys., 15, 1745–1768, https://doi.org/10.5194/acp-15-1745-2015.

    • Search Google Scholar
    • Export Citation

  • Reid, J. S., and Coauthors, 2023: The coupling between tropical meteorology, aerosol lifecycle, convection, and radiation, during the Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex). Bull. Amer. Meteor. Soc., 104, E1179–E1205, https://doi.org/10.1175/BAMS-D-21-0285.1.

    • Search Google Scholar
    • Export Citation

  • Reynolds, R. W., T. M. Smith, C. Liu, D. B. Chelton, K. S. Casey, and M. G. Schlax, 2007: Daily high-resolution-blended analyses for sea surface temperature. J. Climate, 20, 5473–5496, https://doi.org/10.1175/2007JCLI1824.1.

    • Search Google Scholar
    • Export Citation

  • Riehl, H., and J. S. Malkus, 1958: On the heat balance in the equatorial trough zone. Geophysica, 6, 503–538.

  • Riley, E. M., B. E. Mapes, and S. N. Tulich, 2011: Clouds Associated with the Madden–Julian oscillation: A new perspective from CloudSat. J. Atmos. Sci., 68, 3032–3051, https://doi.org/10.1175/JAS-D-11-030.1.

    • Search Google Scholar
    • Export Citation

  • Riley Dellaripa, E. M., E. Maloney, and S. C. van den Heever, 2018: Wind–flux feedbacks and convective organization during the November 2011 MJO event in a high-resolution model. J. Atmos. Sci., 75, 57–84, https://doi.org/10.1175/JAS-D-16-0346.1.

    • Search Google Scholar
    • Export Citation

  • Rotunno, R., J. B. Klemp, and M. L. Weisman, 1988: A theory for strong, long-lived squall lines. J. Atmos. Sci., 45, 463–485, https://doi.org/10.1175/1520-0469(1988)045<0463:ATFSLL>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Saleeby, S. M., and S. C. van den Heever, 2013: Developments in the CSU-RAMS aerosol model: Emissions, nucleation, regeneration, deposition, and radiation. J. Appl. Meteor. Climatol., 52, 2601–2622, https://doi.org/10.1175/JAMC-D-12-0312.1.

    • Search Google Scholar
    • Export Citation

  • Schiro, K. A., J. David Neelin, D. K. Adams, and B. R. Lintner, 2016: Deep convection and column water vapor over tropical land versus Tropical Ocean: A comparison between the Amazon and the tropical western Pacific. J. Atmos. Sci., 73, 4043–4063, https://doi.org/10.1175/JAS-D-16-0119.1.

    • Search Google Scholar
    • Export Citation

  • Sheffield, A. M., S. M. Saleeby, and S. C. van den Heever, 2015: Aerosol-induced mechanisms for cumulus congestus growth. J. Geophys. Res. Atmos., 120, 8941–8952, https://doi.org/10.1002/2015JD023743.

    • Search Google Scholar
    • Export Citation

  • Shige, S., and T. Satomura, 2001: Westward generation of eastward-moving tropical convective bands in TOGA COARE. J. Atmos. Sci., 58, 3724–3740, https://doi.org/10.1175/1520-0469(2001)058<3724:WGOEMT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Silverman, B. W., 1986: Density Estimation for Statistics and Data Analysis. Springer, 175 pp.

  • Slingo, A., and J. M. Slingo, 1988: The response of a general circulation model to cloud longwave radiative forcing. I: Introduction and initial experiments. Quart. J. Roy. Meteor. Soc., 114, 1027–1062, https://doi.org/10.1002/qj.49711448209.

    • Search Google Scholar
    • Export Citation

  • Smagorinsky, J., 1963: General circulation experiments with the primitive equations: I. The basic experiment. Mon. Wea. Rev., 91, 99–164, https://doi.org/10.1175/1520-0493(1963)091<0099:GCEWTP>2.3.CO;2.

    • Search Google Scholar
    • Export Citation

  • Storer, R. L., and S. C. van den Heever, 2013: Microphysical processes evident in aerosol forcing of tropical deep convective clouds. J. Atmos. Sci., 70, 430–446, https://doi.org/10.1175/JAS-D-12-076.1.

    • Search Google Scholar
    • Export Citation

  • Storer, R. L., and D. J. Posselt, 2019: Environmental impacts on the flux of mass through deep convection. Quart. J. Roy. Meteor. Soc., 145, 3832–3845, https://doi.org/10.1002/qj.3669.

    • Search Google Scholar
    • Export Citation

  • Su, H., W. G. Read, J. H. Jiang, J. W. Waters, D. L. Wu, and E. J. Fetzer, 2006: Enhanced positive water vapor feedback associated with tropical deep convection: New evidence from Aura MLS. Geophys. Res. Lett., 33, L05709, https://doi.org/10.1029/2005GL025505.

    • Search Google Scholar
    • Export Citation

  • Takahashi, T., and T. D. Keenan, 2004: Hydrometeor mass, number, and space charge distribution in a “Hector” squall line. J. Geophys. Res., 109, D16208, https://doi.org/10.1029/2004JD004667.

    • Search Google Scholar
    • Export Citation

  • Takemi, T., 2007a: Environmental stability control of the intensity of squall lines under low-level shear conditions. J. Geophys. Res., 112, D24110, https://doi.org/10.1029/2007JD008793.

    • Search Google Scholar
    • Export Citation

  • Takemi, T., 2007b: A sensitivity of squall-line intensity to environmental static stability under various shear and moisture conditions. Atmos. Res., 84, 374–389, https://doi.org/10.1016/j.atmosres.2006.10.001.

    • Search Google Scholar
    • Export Citation

  • Takemi, T., 2010: Dependence of the precipitation intensity in mesoscale convective systems to temperature lapse rate. Atmos. Res., 96, 273–285, https://doi.org/10.1016/j.atmosres.2009.09.002.

    • Search Google Scholar
    • Export Citation

  • Takemi, T., 2014: Convection and precipitation under various stability and shear conditions: Squall lines in tropical versus midlatitude environment. Atmos. Res., 142, 111–123, https://doi.org/10.1016/j.atmosres.2013.07.010.

    • Search Google Scholar
    • Export Citation

  • Takemi, T., 2015: Relationship between cumulus activity and environmental moisture during the CINDY2011/DYNAMO field experiment as revealed from convection-resolving simulations. J. Meteor. Soc. Japan, 93A, 41–58, https://doi.org/10.2151/jmsj.2015-035.

    • Search Google Scholar
    • Export Citation

  • Tobin, I., S. Bony, and R. Roca, 2012: Observational evidence for relationships between the degree of aggregation of deep convection, water vapor, surface fluxes, and radiation. J. Climate, 25, 6885–6904, https://doi.org/10.1175/JCLI-D-11-00258.1.

    • Search Google Scholar
    • Export Citation

  • Toms, B. A., E. A. Barnes, E. D. Maloney, and S. C. van den Heever, 2020a: The global teleconnection signature of the Madden-Julian oscillation and its modulation by the quasi-biennial oscillation. J. Geophys. Res. Atmos., 125, e2020JD032653, https://doi.org/10.1029/2020JD032653.

    • Search Google Scholar
    • Export Citation

  • Toms, B. A., S. C. van den Heever, E. M. Riley Dellaripa, S. M. Saleeby, and E. D. Maloney, 2020b: The boreal summer Madden–Julian oscillation and moist convective morphology over the Maritime Continent. J. Atmos. Sci., 77, 647–667, https://doi.org/10.1175/JAS-D-19-0029.1.

    • Search Google Scholar
    • Export Citation

  • Twomey, S., 1977: The influence of pollution on the shortwave Albedo of clouds. J. Atmos. Sci., 34, 1149–1152, https://doi.org/10.1175/1520-0469(1977)034<1149:TIOPOT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • van den Heever, S. C., G. L. Stephens, and N. B. Wood, 2011: Aerosol indirect effects on tropical convection characteristics under conditions of radiative–convective equilibrium. J. Atmos. Sci., 68, 699–718, https://doi.org/10.1175/2010JAS3603.1.

    • Search Google Scholar
    • Export Citation

  • Vincent, C. L., and T. P. Lane, 2016: Evolution of the diurnal precipitation cycle with the passage of a Madden–Julian oscillation event through the Maritime Continent. Mon. Wea. Rev., 144, 1983–2005, https://doi.org/10.1175/MWR-D-15-0326.1.

    • Search Google Scholar
    • Export Citation

  • Walko, R. L., and Coauthors, 2000: Coupled atmosphere–biophysics–hydrology models for environmental modeling. J. Appl. Meteor., 39, 931–944, https://doi.org/10.1175/1520-0450(2000)039<0931:CABHMF>2.0.CO;2.

    • 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, 504–520, https://doi.org/10.1175/1520-0493(1982)110<0504:TDONSC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Weisman, M. L., and R. Rotunno, 2004: “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.

    • Search Google Scholar
    • Export Citation

  • White, B. A., A. M. Buchanan, C. E. Birch, P. Stier, and K. J. Pearson, 2018: Quantifying the effects of horizontal grid length and parameterized convection on the degree of convective organization using a metric of the potential for convective interaction. J. Atmos. Sci., 75, 425–450, https://doi.org/10.1175/JAS-D-16-0307.1.

    • Search Google Scholar
    • Export Citation

  • Yuter, S. E., and R. A. Houze Jr., 1995: Three-dimensional kinematic and microphysical evolution of Florida cumulonimbus. Part II: Frequency distributions of vertical velocity, reflectivity, and differential reflectivity. Mon. Wea. Rev., 123, 1941–1963, https://doi.org/10.1175/1520-0493(1995)123<1941:TDKAME>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Zipser, E. J., and M. A. LeMone, 1980: Cumulonimbus vertical velocity events in GATE. Part II: Synthesis and model core structure. J. Atmos. Sci., 37, 2458–2469, https://doi.org/10.1175/1520-0469(1980)037<2458:CVVEIG>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Zipser, E. J., and K. R. Lutz, 1994: The vertical profile of radar reflectivity of convective cells: A strong indicator of storm intensity and lightning probability? Mon. Wea. Rev., 122, 1751–1759, https://doi.org/10.1175/1520-0493(1994)122<1751:TVPORR>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Zipser, E. J., D. J. Cecil, C. Liu, S. W. Nesbitt, and D. P. Yorty, 2006: Where are the most intense thunderstorms on Earth? Bull. Amer. Meteor. Soc., 87, 1057–1072, https://doi.org/10.1175/BAMS-87-8-1057.

    • Search Google Scholar
    • Export Citation

  • Zuluaga, M. D., and R. A. Houze Jr., 2013: Evolution of the population of precipitating convective systems over the equatorial Indian Ocean in active phases of the Madden–Julian oscillation. J. Atmos. Sci., 70, 2713–2725, https://doi.org/10.1175/JAS-D-12-0311.1.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 7190 7190 1625
Full Text Views 204 204 23
PDF Downloads 152 152 11